DESC:FIELD OF THE INVENTION

The present invention relates to an in vitro method and system for detecting and predicting neurotoxicity of a chemotherapeutic agent in a subject suffering from cancerous disease. The method and system also determine safe dosage range of a chemotherapeutic agent for the subject. In particular, the present invention relates to the use of induced pluripotent stem cell (iPSC) and neural progenitor cells (NPCs) for the determination of toxicity and safe dosage range of a chemotherapeutic agent.

BACKGROUND OF THE INVENTION

The use of chemotherapeutic agents and drugs has improved the survival of cancer patients over the decades, but these agents are notorious for causing many severe side effects that significantly reduce the efficacy of anti-cancer treatment and patients’ quality of life. There is accumulating clinical evidence that chemotherapeutic agents induce neurological side effects, including memory deficits and mood disorders, in cancer patients who have undergone chemotherapeutic treatments (Yang M. et. al., Neural Regen Res. 2013 Jun 15; 8(17): 1606–1614). Many widely used chemotherapy drugs, including platinum-based agents (oxaliplatin, cisplatin, carboplatin), taxanes (paclitaxel, docetaxel), vinca alkaloids (vincristine, vinblastine), proteasome inhibitors, and thalidomide analogues may cause direct and indirect neurotoxicity.

Taxane is a family of antineoplastic agents discovered in the 1960s as a result of a National Cancer Institute screening program in which extracts from thousands of plants were tested for anticancer activity (Velasco R et. al. Toxics 2015; 3, 152-169). Taxane-derived agents are chemotherapy drugs widely employed in cancer treatment, among them, paclitaxel and docetaxel are most commonly administered. Paclitaxel and docetaxel were the initial prototypic taxane agents introduced into clinical practice, and they are two of the antineoplastic drugs currently in widest use. Taxane diterpenoids were isolated from the bark of the Pacific yew tree (Taxus brevifolia and Taxus baccata for paclitaxel and docetaxel, respectively) (Saloustros et al., 2008; Wani and Horwitz; 2014). Taxanes have been approved by the US Food and Drug Administration (FDA) since the mid-1990s for the treatment of several cancers: breast, ovarian, non-small cell lung, prostate, gastric, and head/neck (Qin et. al.; 2012). Currently, taxane-based chemotherapy schedules are a first-line treatment in both early-stage and metastatic breast cancer, the most common malignant tumor in women, occurring in one out of every eight women in her lifetime. Taxanes are microtubule-stabilizing drugs, thus preventing their depolymerization [Amos and Löwe, 1999; Zhang J et. al. Oncol Rep. 2014; Sep;32(3):1312-8]. This stabilization promotes the formation of abnormal bundles of microtubules in the cytoplasm, leading to mitotic spindle disruption. Thus, cells arrest their cell cycle in the G0/G1 and G2/M phases, leading to apoptosis in dividing cells (mainly tumor cells) [Hornick et. al.; 2008].

Paclitaxel Docetaxel

[Source: BMC Clinical Pharmacology 6(1):2, DOI:10.1186/1472-6904-6-2]

As observed in Molassiotis et. al. (BMC Cancer 2019; 19:132), Chemotherapy-induced peripheral neuropathy (CIPN) is one of the major dose-limiting side effects of chemotherapeutic agents including platinum analogues, vinca alkaloids, and taxanes [Hausheer FH et. al. Semin Oncol. 2006; 33:15–49]. The structure and function of peripheral motor, sensory and autonomic neurons are affected, causing peripheral neuropathic signs and symptoms [Postma TJ et. al. Ann Oncol. 2000; 11:509–13]. In a systematic review of 31 studies (N = 4179), CIPN prevalence was found to be 68.1% at the first month of chemotherapy to 30% six-months after chemotherapy, with wide variance in prevalence from 12.1–96.2%, depending on different timings of assessment and type of chemotherapy, and many assessing CIPN as part of a drug trial or with studies being cross-sectional [Seretny M. et. al. Pain. 2014;155(12):2461–70]. Neuropathic symptoms tend to progress during chemotherapy and generally regress once treatment stops. Symptoms can consist of a mixture of motor, sensory, and autonomic signs; and the pain associated with CIPN can be prolonged and severe, and its treatment is usually difficult [Mols F et. al. Support Care Cancer. 2014; 22(8):2261–9; Miaskowski C et. al. J Pain Symptom Manag. 2017;54(2):204–18].

TABLE 1: Summarized characteristics of Neurotoxicity-inducing drugs routinely used in cancer treatment (based on the most frequently treated cancers assigned to a given drug or a group of drugs):

The most commonly used commercial preparation of paclitaxel is Taxol® (Bristol-Myers Squibb; New York, NY, USA). This is a semisynthetic agent derived from the precursor 10-deacetylbaccatin III produced from the needles of European yew tree Taxus baccata. Docetaxel is a semisynthetic paclitaxel derivate commercialized under the trade name Taxotere® (Sanofi-Aventis; Paris, France). Both paclitaxel and docetaxel consist of a complex taxane ring linked to an ester at the C-13 position. Both share hydrophobic properties, requiring solvents for their administration: Cremophor® EL (polyethoxylated castor oil, CrEL) for paclitaxel and polysorbate-80 for docetaxel. These solvents have also been related with frequently observed allergic reactions. There is extensive research striving to find new analogs and new formulations with better therapeutic and toxicity profiles, and higher solubility. The second-generation of taxane includes nanoparticle albumin-bound paclitaxel (nab-paclitaxel, ABI-007, Abraxane®) and cabazitaxel (Jevtana®), a semi-synthetic derivative of docetaxel, which have recently been incorporated in the antineoplastic armamentarium. Liposomal paclitaxel formulations (i.e., Genexol®-PM) and other drug delivery systems are also being investigated.

Taxane Induced Toxicity

Paclitaxel and docetaxel are both associated with two main types of toxicity: peripheral neurotoxicity (NTX) and myelosuppression. Whilst hematological toxicity can become lesser with the concurrent use of granulocyte colony-stimulating factors during chemotherapy, the occurrence of peripheral nerve toxicity represents one of the Achilles’ heels of taxane treatment. In one study including adjuvant or neoadjuvant breast cancer patients, dose-modification of taxane planned schedule was performed due to peripheral NTX in 17% of patients.

As observed and recorded in Kerckhove N. et. al. (Front Pharmacol. 2017; 8:86), among patients treated with adjuvant paclitaxel chemotherapy, between 80 to 97% experienced symptoms of neuropathy with a time range to CIPN onset of 1–101 weeks [Chaudhry et. al. Ann. Neurol. 1994; 35, 304–311; Hershman et. al. Breast Cancer Res. Treat. 2011; 125, 767–774; Tanabe et. al. Clin. Oncol. 2013; 18, 132–138]. These symptoms remained during a median follow-up time of 57 months for 212 neuropathic patients (minimum: 5.3, maximum: 95.5) [Tanabe et. al., 2013]. Few studies have reported the increased incidence of acute and chronic toxicities with taxanes that could potentially lead to dose reductions and treatment withdrawal [Tanabe et al., 2013; Ho and Mackey, 2014]. More recently, breast cancer survivors with CIPN developed more severe insomnia, anxiety, and depression than those without neuropathy [Bao et. al. Breast Cancer Res Treat. 2016; 159(2):327–33; Thornton et al., 2008], which also demonstrated that in the years following chemotherapy, the taxane group had significantly worse emotional distress and mental Health-related quality of life (HRQOL) throughout adjuvant treatment. These outcomes were also associated with rates of probable clinical depression during the first year. Interestingly, it was observed that the taxane cohort had a significantly slower psychological recovery and required 2 years on average for emotional recovery compared with 6–12 months for patients in the no taxane comparison group [Thornton et. al., 2008].

Taxane-induced peripheral neuropathy (TIPN) has been increasingly problematic for several reasons. First, nowadays more cancer patients live longer or are cured due to the greater effectiveness of new drugs and therapeutic regimes. Due to improved long-term cancer survival of patients in general, the peripheral neuropathy, which effects post-treatment and recovery phase, is a growing issue. Second, receiving a complete taxane regimen is probably a critical factor in determining the outcome of a given cancer patient. TIPN is a dose-limiting side effect that must be considered while treating cancer patients with these agents, decreasing total cumulative dose administered, which may impair cancer outcome. Third, TIPN negatively impacts on routine activities, functions, and behaviors in the domestic, work, and social/leisure lives of cancer patients, adversely compromising the quality of the survivorship. Finally, the development of TIPN is associated with an increase in the overall cost of cancer care for healthcare systems.

The incidence of all grades of TIPN among those patients treated with paclitaxel is high, often ranging from 57%–83% overall and with severity in 2%–33% of patients, while incidence reported with docetaxel is highly variable: 11%–64% and 3%–14% overall and severe, respectively. Classically, Paclitaxel is considered more neurotoxic than docetaxel and is reported to be the most neurotoxic Taxane drug approved for gynecological cancers. Pace et al. (Clin. Breast Cancer 2007, 7, 550–554) reported an incidence of 71% and 96% at 12 and 24 weeks of weekly-paclitaxel, respectively, assessed with neurologic and neurophysiological evaluation. Neuropathy incidence and severity also seem greater when patient-reported outcome measures are considered in TIPN assessment. Regarding the second generation of taxane, phase III clinical trials comparing standard paclitaxel with nab-paclitaxel in breast cancer showed higher incidence of grade 3 neuropathy in nab-paclitaxel than in the standard treatment (10% vs. 2%). Finally, NTX rates up to 35% with liposomal paclitaxel formulation have been reported.
Patients undergoing taxane treatment may present two types of peripheral NTX: acute transient and subacute long-lasting TIPN. Paclitaxel and docetaxel are associated with an acute pain syndrome in up to 70% of patients, consisting of diffuse muscle aching, most often in the legs, hips, and lower back, although it can be widespread, regarded as myalgia or arthralgia. Long-lasting TIPN is characterized by symmetrical onset of sensory symptoms usually first in the tips of the toes and afterwards in the fingers, although simultaneous development in both the fingers and toes is not infrequent. Sensory disturbance extends to soles and palms. Facial involvement is less common, although anecdotally reported. In order of frequency, paclitaxel and docetaxel display a similar pattern of induced sensory symptoms including numbness (100%), tingling (80%), sensitivity to cold (60%) and neuropathic pain (50%). Loss of balance is also a complaint made by over 50% of patients. Neurological examination consistently shows a loss of reflexes. Although initially only ankle reflexes are lost, global arreflexia is also common in patients.

While the overall incidence of TIPN in cancer patients receiving taxane treatment is quite high but not all patients will develop TIPN. Moreover, among those patients affected, there is considerable difference in the severity of NTX. Reasons underlying this variability are only partially known, and there are no established, validated predictive biomarkers to determine which patients are at greater risk for TIPN. Furthermore, diagnosing and assessing symptoms related to TIPN in daily practice is complex and typically the physician goes after clinical syndrome. In particular, NTX in metastatic breast cancer patients receiving paclitaxel can be problematic because treatment is frequently administered until progression or toxicity, as a common approach.

Total cumulative dose and dose intensity are considered important determinants of incidence and severity of NTX, as in other chemotherapy-induced peripheral neuropathies. Onset doses for neuropathy of any grade range from 100–300 mg/m2 and 75–100 mg/m2 with paclitaxel and docetaxel, respectively. In a randomized phase III study of metastatic breast cancer, the mean cumulative dose leading to onset of grade 2 peripheral NTX was 371 mg/m2 for docetaxel and 715 mg/m2 for paclitaxel. Generally, severe TIPN occurs in patients receiving cumulative doses around 1000 mg/m2 for paclitaxel and 400 mg/m2 for docetaxel. Notwithstanding, the administration of multiple neurotoxic agents concurrently is not uncommon in oncology practice. Co-administration of paclitaxel with cisplatin, which is a common schedule in a variety of cancers, showed that nearly the totality (95%) of patients developed peripheral NTX. Concurrent treatment of taxane with other neurotoxic agents seems to induce a synergistic effect on neurotoxicity more than an additive one.

While demographic characteristics of patients receiving taxane have also been investigated to search for risk factors associated with TIPN development, but such studies are not conclusive and have not been able to significantly reduce TIPN in any set demographics. Whereas it has been suggested that elderly people were more prone to developing TIPN, many studies have failed to observe such association including the largest epidemiologic retrospective study published of breast, lung and ovarian cancer. Regarding severity, more severe TIPN also seems not to be related with age of patients. Nevertheless, one retrospective study evaluating duration of NTX induced by paclitaxel reported longer persistence of neuropathy in older patients (>60 years). In regard to race differences in TIPN, several paclitaxel studies show a higher associated risk of NTX in the African-American population, and found that non-Europeans were at significantly higher neuropathy risk than Europeans of similar genotype.

The putatively higher associated risk of TIPN in patients with pre-existing neuropathy is difficult to evaluate since the majority of clinical trials routinely exclude these patients. Whilst a statistically significant association was observed for early peripheral NTX induced by docetaxel and preexisting neuropathy, other studies failed to find this association. More agreement exists regarding patients with the hereditary neuropathy Charcot-Marie-Tooth (CMT) being poorly tolerant of paclitaxel. Furthermore, there is conflicting evidence in literature regarding the potential higher-risk of TIPN in patients suffering from diabetes mellitus. Importantly, a lack of information concerning concurrent peripheral neuropathy secondary to diabetes is common and critical in these studies.

In addition, the role of tumor-related characteristics molecular profiles associated with TIPN has also been investigated. In one study including more than 1700 breast cancer patients, those who developed early docetaxel peripheral NTX more frequently had tumors less than 2 cm and node-negative disease. However, most studies (all retrospective) including patients treated with paclitaxel and docetaxel did not find any significant association of variables related with tumor type, extension and time to or duration of TIPN. Finally, there is growing evidence that chemotherapy-related toxicity is an inheritable trait, and the genetic signature of a predisposition to TIPN is increasingly being investigated. Several studies have identified genetic polymorphisms associated with TIPN, most of them with inconclusive results, and only few accompanied with replication or validation studies. Overall, polymorphisms in genes involved in the drug metabolism, distribution, and elimination properties of taxanes have been shown to be relevant for TIPN. More recently, the role of genes involved in regulation of axon outgrowth and genes associated with congenital neuropathies (Charcot-Marie-Tooth disease) have been also reported in large prospective studies. However, the available data need to be read and interpreted with caution because of several limitations and aberrations in the available studies, including the implementation of post-hoc analysis of oncology-based databases of different, not pre-planned size and inappropriate outcome measures for neurological impairment. This is one of the primary reasons, it is not recommendable to adopt decisions on treatment on the basis of the current evidence on genomics.

While multiple strategies to prevent TIPN have been investigated, no therapy has been found to be definite or proven in randomized controlled trials for preventing the paclitaxel-associated acute pain syndrome or long-lasting TIPN. Among the strategies studied are acetyl-L-Carnitine, amifostine, amitriptyline, glutamate, glutathione, leukemia inhibitory factor, omega 3, corticosteroids, retinoid acid and Vitamin E. Up to now, evidence concerning their effectiveness is scarce or negative. TIPN is of major concern for physicians and patients due to the negative consequences in terms of cancer outcome and quality of life. New taxane formulations are being developed to improve antineoplastic properties and minimize toxicities, but NTX remains an unsolved problem. There are limited data available describing risk factors of NTX, mainly epidemiologic and obtained from retrospective studies. Increased knowledge from pharmacogenomics studies is being investigated regarding inherited risk associated with TIPN development. However, knowledge of these risk markers is still far from being considered in clinical practice, and multiple considerations must be made before denying taxane treatment to candidate cancer patients based on the potential NTX savings.

The historical variation reported in CIPN incidence and prevalence is mostly confounded by disagreement between assessment modalities. Clinical practices do not consider assessment of motor neuropathy for neurotoxic chemotherapy. Current methodologies are not appropriate to measure or predict CIPN in a valid way, since a combination of scales are needed, by way of reliable preclinical strategies and platforms that can predict such adverse events. Conventional technologies for drug screening and disease modeling make use of animal models that often fail to recapitulate human pathophysiology and underlying molecular profile. Also, lack of physiologically relevant human drug screening and disease modeling platforms result in an almost 90% failure rate for drugs entering clinical trials. High failure rate in clinical trials, despite significant (and ever growing) expense of time and cost in pharmaceutical R&D, along with adverse reactions leading to debilitation or loss of human life (due to extreme toxicity and side-effects) has been a major hurdle for many decades. Further, the toxic effects of these drugs coupled with inherited susceptibility of individuals make the toxicology prediction even more difficult. Conventional animal-based toxicity and safety tests have high costs, use large numbers of animals and in many cases, they do not provide clearly translatable results for humans. Most neurotoxicity studies are carried out in rodents or rodent derived primary cells, resulting in relatively high cost and lower translational value of the results due to the species differences.

Major international initiatives have started to convert the traditional animal-based neurotoxicity tests to in vitro assays using both mammalian brain cells and human cells to detect and predict chemical hazards. In vitro pharmacology profiling of new chemical entities during early phases of drug discovery has recently become an essential tool to predict clinical adverse effects. The development of in vitro platforms for neuro-toxicology screenings is driven by the urgent needs of the pharma industries that are constantly thriving to get more efficient and economically-viable drugs to the general public. However, there are only a limited number of human neuronal cell lines (e.g., carcinoma cell lines such as SH-SY5Y; BE2-M17 or immortalized cell lines like LUHMES) available and it is hard to obtain primary human CNS tissue suitable for neurotoxicity studies. Overall, the highly complex structure of the human brain makes in vitro modeling very difficult.

Further, while technology platforms for safety testing or more general liability testing are available, no specific in vitro neurotoxic panels exist for predictive toxicology screening in cancer patients to aid in clinical decision-making. In most of the cases, in fact, in-vivo animal models are still used for preclinical assessments, for drug discovery and testing. However, correlations between animal and human data might be weak in some cases and animal studies are quite expensive, ethically questionable and require large amount of chemical compounds. Moreover, after market authorizations, the drugs often show differential response and cytotoxic profiles on individualized basis, presumably driven by the patient’s genetic profile and environmental exposure. These responses, peculiar to patients are not fully captured by generic platforms made from a healthy donor’s cells/ genetic information.

The advent of induced pluripotent stem cell (iPSC) technology in 2007 has led to a new human in vitro/ex vivo drug testing platform, with the capability to provide additional ways for screening drugs for efficacy and safety in a high-throughput as well as a personalized and precision testing format. iPSCs technology has opened a new avenue for scientists which allows unlimited access to human hepatocytes [Zhang et. al. Aging. 2021; 13 (4):5621–37; cardiomyocytes (Gintant et. al., 2019), endothelial cells (Jang et. al., 2019), neurons (McKinney et. al., 2017)] and other cell types involved in drug toxicity research and testing. Research on a variety of diseases, including rare diseases and those with multifactorial origins, as well as to simulate drug effects on difficult-to-obtain tissues like the brain and cardiac muscles, has been made possible by the growing number of human disease models created with iPSCs. Before advancing to clinical trials, toxicity and teratogenicity studies performed with iPSC-derived cells can add an extra level of assurance. Recently, iPSC-derived cortical neurons and astrocytes were co-cultured in 3D to detect calcium oscillations upon a chemical compound treatment, analyzing multiple parameters, highlighting the potential of such readouts in neurotoxicity assessment. Another study has presented a novel 3D heterotypic glioblastoma-brain sphere (gBS) model applied for screening new anti-glioblastoma agents.

Recently, an increasing number of studies use primary cell cultures, and induced pluripotent stem cells (iPSCs) are used to create in vitro systems for Neurotoxicity (NT) and Developmental Neurotoxicity (DNT) screenings. 3D cell cultures are known to mimic the original tissue environment including tissue-specific architecture, mechanical and biochemical features, cell-to-cell communication and signalling, and differentiation capability, while 2D cell culture systems are less complex and thus in existing assays provide meaningful readouts for specific neurodevelopmental processes. Only one in vitro assay is not able to cover the complexity of the in vivo development, therefore a battery of assays and fit-for-purpose applications are used to cover the relevant processes. Human induced pluripotent stem cell-derived (iPSC) neural progenitor cells (NPCs), grown on 3D scaffolds or self-forming can establish cell–cell interactions and model certain neurodevelopmental processes, therefore, demonstrating the use as an in vitro screening platform not only for NT but in DNT screenings. In neuronal disease modelling, a major step that opened new perspectives was the development of cortical layer-organized 3D brain micro-tissues, providing a complex system forming under in vitro conditions from human iPSCs. However, for toxicological studies the very low throughput potential of such complete systems is a significantly limiting factor at the moment.

Despite the developments mentioned above, still, a limited number of human iPSC derived 3D neuronal culture-based studies are available focusing on the development of NT or DNT models. A limiting factor for the further development of such test methods is the lack of high-throughput screening (HTS) read-outs on 3D cell cultures. Furthermore, none of these studies have tested cancer patient-based iPSC-derived cells to test the effect of drugs (taking into account predisposing genetic profile which may be individual patient specific).
Generally, in neurotoxicity screening, the usage of human iPSC derived neuronal cultures, especially the commercially available QC controlled neuron and astrocyte cultures, where the differentiation of iPSCs is not required for the “users”, is dynamically increasing. In recent years, numerous in vitro models have been created in order to study the human CNS in a more physiological way, but the field of neurotoxicity and developmental neurotoxicity using neuronal tissues did not develop as fast as disease or developmental modelling. It is due to the difficulty to find a compromise between biological complexity and technical reproducibility which are necessary for drug or toxicity screening.

Consequently, there is an increasing need to develop alternative testing methods which could handle numerous drugs or chemicals with affordable time and cost and with human-relevant neurotoxicology (NT) outcome. Development of new approach methods is critical both for NT and developmental neurotoxicology (DNT) tests, providing data on the effect of drugs and the potential adverse outcomes.

The present invention aims to overcome the problems associated with the prior art by providing a system and method which is effective in early and precise prediction and detection of clinical neurotoxicity of chemotherapeutic drugs for individual patients. To this end, the present invention has developed integrated system and method using 2D and 3D cell cultures derived from patients diagnosed of Breast and Ovarian Cancer to develop iPSCs, primary cancer cells and their respective derivatives, that Inventors show, have the potential to detect drug-induced toxicity (as a patient surrogate) in the iPSC-based platforms and drug-efficacy and dose ranging can be performed in isogenic cancer organoids, to enable predictive and personalized medicine applications.

OBJECTS OF THE PRESENT INVENTION

The main objects of the present invention is to provide an in vitro method and system for detecting and predicting neurotoxicity of a chemotherapeutic agent in a subject suffering from cancerous disease.

Another object of the present invention is to provide an in vitro method and system wherein it is possible to predict the toxicity of a particular chemotherapeutic agent on an individual human suffering from a cancerous disease (such as breast cancer or ovarian cancer) without administering the chemotherapeutic agent into the subject.

Yet another object of the present invention is to provide an in vitro method and system for predicting the toxicity of a particular chemotherapeutic agent on an individual human suffering from a cancerous disease (such as breast cancer or ovarian cancer) wherein the method and system takes into account the impact of genetic profile and predisposing conditions of the subject, which is likely to contribute in the subject’s response and sensitivity to the chemotherapeutic agent.

Still another object of the present invention is to provide an in vitro method and system for predicting the toxicity of a particular chemotherapeutic agent on an individual human suffering from a cancerous disease (such as breast cancer or ovarian cancer) wherein the method and system can be used to determine the dosage range of the chemotherapeutic agent in which it is effective and not toxic to the particular subject.

Another object of the present invention is to provide an in vitro method and system which is able to identify the inherent neurological defects in an individual human suffering from a cancerous disease (such as breast cancer or ovarian cancer) prior to commencing any treatment of chemotherapeutic agent.

Still another object of the present invention is to provide an in vitro method and system which is able to provide post treatment readout to assess the drug-induced neurotoxicity in an individual human suffering from a cancerous disease (such as breast cancer or ovarian cancer).

Still another object of the present invention is to provide an in vitro method and system which enables creation of large banks and databases of patient derived neurotoxicity testing platforms – for identifying and implicating common gene signatures and predictive biomarkers for prognosis of neurotoxicity upon drug treatment.
The other objects, preferred embodiments and advantages of the present invention will become more apparent from the following detailed description of the present invention when read in conjunction with the accompanying claims, examples, figures and tables, which are not intended to limit scope of the present invention in any manner.

SUMMARY OF THE PRESENT INVENTION

The present invention relates to an in-vitro method for determining toxicity of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, wherein the method comprises: (a) Isolating peripheral blood mononuclear cells (PBMCs) from the subject; (b) Re-programming isolated PBMCs into induced pluripotent stem cells (iPSCs); (c) Developing neural progenitor cells (NPCs) from the iPSCs; (d) Conducting at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs; and (e) Determining the concentrations of the chemotherapeutic agent at which it is toxic to the NPCs.

The present invention also discloses a system for determining neurotoxicity of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, wherein the system comprises: (a) Means to isolate peripheral blood mononuclear cells (PBMCs) from the subject; (b) Means to re-program isolated PBMCs into induced pluripotent stem cells (iPSCs); (c) Means to develop neural progenitor cells (NPCs) from the iPSCs; (d) Means to conduct at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs; and (e) Means for determining the concentrations of the chemotherapeutic agent at which it is toxic to the NPCs.

The present invention also relates to an in-vitro method for determining safe dosage range of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, wherein the method comprises: (a) Isolating peripheral blood mononuclear cells (PBMCs) and cancer biopsy sample from the subject; (b) Re-programming isolated PBMCs into induced pluripotent stem cells (iPSCs); (c) Developing neural progenitor cells (NPCs) from the iPSCs; (d) Conducting at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs; (e) Determining the concentrations of the chemotherapeutic agent at which it is neurotoxic to the NPCs; (f) Developing organoids from the cancer biopsy sample of the subject wherein the organoids depict histological features and key biomarker profile of primary tumor; (g) Determining the dosage range of chemotherapeutic agent which is effective against the cancer organoids; and (h) Identifying the part of the effective dosage range of chemotherapeutic agent in (g) which is lower than the concentration in (e) at which the chemotherapeutic agent is toxic to the NPCs.

The present invention also discloses a system for determining safe dosage range of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, wherein the system comprises: (a) Means for isolating peripheral blood mononuclear cells (PBMCs) and cancer biopsy sample from the subject; (b) Means for re-programming isolated PBMCs into induced pluripotent stem cells (iPSCs); (c) Means for developing neural progenitor cells (NPCs) from the iPSCs; (d) Means for conducting at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs; (e) Means for determining the concentrations of the chemotherapeutic agent at which it is neurotoxic to the NPCs; (f) Means for developing organoids from the cancer biopsy sample of the subject wherein the organoids depict histological features and key biomarker profile of primary tumor; (g) Means for determining the dosage range of chemotherapeutic agent which is effective against the cancer organoids; and (h) Means for identifying the part of the effective dosage range of chemotherapeutic agent in (g) which is lower than the concentration in in (e) at which the chemotherapeutic agent is toxic to the NPCs.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1: A. Time course of reprogramming of Peripheral Blood Mononuclear Cells (PBMCs) for iPSC development from human donors – Healthy Volunteer 1; Breast Cancer Patient (SH62) and Ovarian Cancer Patient (SH50); B. Time course of reprogramming of Peripheral Blood Mononuclear Cells (PBMCs) for iPSC development from human donors – Healthy Volunteer 1; Breast Cancer Patient (SH67) and Ovarian Cancer Patient (OS196).

Figure 2: Immunocytochemistry analyses for Pluripotency markers SSEA4, OCT4, NANOG in human iPSCs developed from reprogramming of PBMCs from healthy volunteers.

Figure 3: Alkaline Phosphatase staining as well as quantitative flowcytometry analyses for OCT4 and SSEA4 in human iPSCs developed from reprogramming of PBMCs from healthy volunteers, to establish pluripotency.

Figure 4: Karyotyping analyses to establish that there were no chromosomal aberrations introduced during the process of reprogramming in human iPSCs developed from reprogramming of PBMCs from healthy volunteers.

Figure 5: STR analyses in human iPSCs developed from healthy volunteers to confirm purity of cell-line and a match with the source PBMCs.

Figure 6: Immunocytochemistry analyses for Pluripotency markers SSEA4, OCT4, NANOG in human iPSCs developed from reprogramming of PBMCs from Breast Cancer patients.

Figure 7: Alkaline Phosphatase staining as well as quantitative flowcytometry analyses for SSEA4 and Tra1-60 in human iPSCs developed from reprogramming of PBMCs from breast cancer patient, to establish pluripotency. Karyotyping analyses to establish that there were no chromosomal aberrations introduced during the process of reprogramming in human iPSCs developed from reprogramming of PBMCs from breast cancer patients. STR analyses in human iPSCs developed from breast cancer patient to confirm purity of cell-line and a match with the source PBMCs

Figure 8: In vivo Teratoma (Differentiation) assay to establish pluripotency by differentiation into cells of 3-germ layers, in human iPSCs developed from reprogramming of PBMCs from breast cancer patient.

Figure 9: Immunocytochemistry analyses for Pluripotency markers SSEA4, OCT4, NANOG in human iPSCs developed from reprogramming of PBMCs from Ovarian Cancer patients.

Figure 10: Alkaline Phosphatase staining as well as quantitative flowcytometry analyses for SSEA4 and Tra1-60 in human iPSCs developed from reprogramming of PBMCs from ovarian cancer patient, to establish pluripotency. Karyotyping analyses to establish that there were no chromosomal aberrations introduced during the process of reprogramming in human iPSCs developed from reprogramming of PBMCs from ovarian cancer patients. STR analyses in human iPSCs developed from ovarian cancer patient to confirm purity of cell-line and a match with the source PBMCs.

Figure 11: In vivo Teratoma (Differentiation) assay to establish pluripotency by differentiation into cells of 3-germ layers, in human iPSCs developed from reprogramming of PBMCs from ovarian cancer patient.

Figure 12: Overview of Next-generation RNA and DNA sequencing analyses in cancer tissues and iPSCs from Breast and Ovarian cancer patients.

Figure 13: Functional gene variant analyses in next-generation sequencing data from cancer tissues and iPSCs of Breast and Ovarian cancer patients, reveal conserved Germline mutations in key genes and pathways.

Figure 14: List of annotated genes across Breast Cancer samples showing germline variations (as per the Human Reference Consortium GRCh38.p14, a non-coordinate changing update to the human reference assembly incorporated in May 2022), confirmed to be conserved between patient tumors and PBMC-derived iPSCs.

Figure 15: List of annotated genes across Ovarian Cancer samples showing germline variations (as per the Human Reference Consortium GRCh38.p14, a non-coordinate changing update to the human reference assembly incorporated in May 2022), confirmed to be conserved between patient tumors and PBMC-derived iPSCs.

Figure 16: Time course revealing different stages during the process of development of Neural Progenitor Cell-based platform from human iPSCs.

Figure 17A and B: A. Immunocytochemistry analyses for markers of Neural Progenitor Cells (NPCs), Pax 6 and Nestin, post differentiation from human iPSCs derived from healthy volunteers; B. Quantitative Flowcytometry analyses for Pax6 in iPSC-derived NPCs from healthy volunteers.

Figure 18: Immunocytochemistry analyses for markers of Neural Progenitor Cells (NPCs), Pax 6, Nestin and NCad post differentiation from human iPSCs derived from Breast and Ovarian cancer patients.

Figure 19A-E: Immunocytochemistry analyses for Pax 6 and Nestin along with Quantitative Flowcytometry analyses in iPSC-derived NPCs from Breast cancer patient.

Figure 20A-C: Immunocytochemistry analyses for Pax 6 and Nestin along with Quantitative Flowcytometry analyses for Pax6 in iPSC-derived NPCs from Ovarian cancer patient.

Figure 21A-E: Immunocytochemistry analyses for GFAP and Tuj1 in Mature Astrocytes developed from the differentiation of NPCs from healthy volunteers. Quantitative Flowcytometry analyses for S100beta and Tuj1 in healthy volunteers NPC-derived Mature Astrocytes.

Figure 22A and B: Immunocytochemistry analyses for GFAP and Tuj1 in Mature Astrocytes developed from the differentiation of NPCs from Breast Cancer patients. Quantitative Flowcytometry analyses for Tuj1 in Breast Cancer patient NPC-derived Mature Astrocytes.

Figure 23A and B: Immunocytochemistry analyses for GFAP and Tuj1 in Mature Astrocytes developed from the differentiation of NPCs from Ovarian Cancer patients. Quantitative Flowcytometry analyses for Tuj1 in Ovarian Cancer patient NPC-derived Mature Astrocytes.

Figure 24A and B: Immunocytochemistry analyses and Quantitative Flowcytometry for Tuj1/ beta-Tubulin in Mature Forebrain Neurons developed from the differentiation of NPCs from healthy volunteers.

Figure 25A and B: Immunocytochemistry analyses and Quantitative Flowcytometry for Tuj1/ beta-Tubulin in Mature Forebrain Neurons developed from the differentiation of NPCs from Breast Cancer patients.

Figure 26A and B: Immunocytochemistry analyses and Quantitative Flowcytometry for Tuj1/ beta-Tubulin in Mature Forebrain Neurons developed from the differentiation of NPCs from Ovarian Cancer patients.

Figure 27: Immunocytochemistry analyses for Tyroxine Hydroxylase and Tuj1 in Mature Midbrain Dopaminergic Neurons developed from the differentiation of NPCs from healthy volunteers.

Figure 28A and B: Quantitative Flowcytometry analyses for Tyroxine Hydroxylase and Tuj1 in Mature Midbrain Dopaminergic Neurons developed from the differentiation of NPCs from healthy volunteers.

Figure 29: Immunocytochemistry analyses for Tyroxine Hydroxylase and Tuj1 in Mature Midbrain Dopaminergic Neurons developed from the differentiation of NPCs from Breast Cancer patients.

Figure 30A and B: Quantitative Flowcytometry analyses for Tyroxine Hydroxylase and Tuj1 in Mature Midbrain Dopaminergic Neurons developed from the differentiation of NPCs from Breast Cancer patients.

Figure 31: Immunocytochemistry analyses for Tyroxine Hydroxylase and Tuj1 in Mature Midbrain Dopaminergic Neurons developed from the differentiation of NPCs from Ovarian Cancer patients.

Figure 32A and B: Quantitative Flowcytometry analyses for Tyroxine Hydroxylase and Tuj1 in Mature Midbrain Dopaminergic Neurons developed from the differentiation of NPCs from Ovarian Cancer patients.

Figure 33: Phase contrast imaging of iPSC-derived NPCs from Breast Cancer patients in response to drug treatment with Paclitaxel and 5-fluorouracil (5-FU).

Figure 34: Phase contrast imaging of iPSC-derived NPCs from Ovarian Cancer patients in response to drug treatment with Paclitaxel and 5-fluorouracil (5-FU).

Figure 35A and B: Phase contrast imaging and quantitative cell viability determination for iPSC-derived NPCs from Breast and Ovarian Cancer patients in response to drug treatment with Paclitaxel and 5-fluorouracil (5-FU).

Figure 36A and B: Phase contrast imaging and quantitative growth and size patterns for iPSC-derived NPC spheroids from Healthy Volunteers, Breast and Ovarian Cancer patients over a course of 7 and 14 days in culture.

Figure 37A and B: Conditions used in the Cell Lysis, Immunocytochemistry (ICC) and Antibody details used in the ICC of iPSC-derived NPCs. Tuj1 and Nestin staining detected by ICC in iPSC-derived Neural Spheroids.

Figure 38: RT-PCR based gene expression analyses in iPSC-derived NPC spheroids from Healthy Volunteers, Breast Cancer patients and Ovarian Cancer patients.

Figure 39: RT-PCR based gene expression analyses in iPSC-derived NPC spheroids from Healthy Volunteers, Breast Cancer patients and Ovarian Cancer patients, over the course of 7,14 and 21 days in culture.

Figure 40: Neurotoxicity screening and CTG assay based cell viability and proliferation analyses in NPCs derived from Healthy volunteers, Breast Cancer patient and Ovarian Cancer patients in response to Drug treatment with Paclitaxel and 5-FU.

Figure 41: High clinical correlation of established Neurotoxicity Platform for Breast and Ovarian Cancer patients.

Figure 42: Quantitative Flow-cytometry of NPC Spheroids in Response to Drug Treatment – show constant baseline i.e. Pax6 Expression.

Figure 43: Neurite growth assay in response to Paclitaxel/ Taxol treatment in NPC spheroids from Healthy Volunteers, Breast Cancer patients and Ovarian Cancer patients, over the course of 7, 14 and 21 days in culture.

Figure 44: Quantitative comparisons from Neurite Outgrowth Assay in response to Paclitaxel/ Taxol treatment in NPC spheroids from Healthy volunteers and Ovarian Cancer patients, over the course of 7, 14 and 21 days in culture.

Figure 45: Comparison of Neurite Outgrowth in iPSC-derived Neural Derivatives in response to Paclitaxel and 5FU. Mean neurite length and number of neurite intersections for NPC spheroids from healthy volunteer and ovarian cancer patient analyzed in ImageJ using Neurite-J plugin. All data is represented as the mean, and all error bars represent SEM. Individual data points are shown for all bar graphs. ns = not significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001.

Figure 46: Toxicological Profiling in Response to Paclitaxel (Drug) Treatment of iPSC-derived Neural Derivatives.

Figure 47: Profiling of Apoptotic Cell Death in Response to Paclitaxel (Drug) Treatment of iPSC-derived Neural Derivatives, presumably by Microtubule Stabilization Mimics Latrunculin A Targeted Actin Disruption and Consequentially, Microtubule Stabilization.

Figure 48: A. Phase contrast imaging of Primary Breast Cancer Organoids (Primary Cancer Organoid and isogenic Adjacent Normal Organoid) from Breast Cancer patients; B. Immunocytochemistry analyses of Primary Breast Cancer organoids for epithelial markers, EpCAM and CK8/18.

Figure 49: Immunocytochemistry analyses of Primary Breast Cancer organoids (or adjacent normal organoids) for cancer specific markers (ER and Her2) and comparison with Immunohistochemistry staining analyses in the cancer tissue from the same donor i.e. Breast Cancer patient. epithelial markers.

Figure 50 – 52: Drug sensitivity and resistance assay in vitro, in 3 different Breast Cancer patients in response to Doxorubicin and Paclitaxel treatments.

Figure 53: Comparisons of drug responsiveness/ sensitivity and IC50 for Doxorubicin and Paclitaxel, between different Breast Cancer patients, using Primary Cancer Organoid platform, for personalized drug screening.

Figure 54: Immunocytochemistry analyses of Primary Ovarian Cancer organoids for epithelial marker, CK8/18 and proliferation marker, Ki67.

Figure 55: A. Phase contrast imaging of Primary Ovarian Cancer Organoids (Primary Cancer Organoid and isogenic Adjacent Normal Organoid) from Ovarian Cancer patients; B. Immunocytochemistry analyses of Primary Ovarian Cancer organoids for cancer specific markers (HE4).

Figure 56 - 58: Drug sensitivity and resistance assay in vitro, in 3 different Ovarian Cancer patients in response to Doxorubicin and Paclitaxel treatments.

Figure 59: Comparisons of drug responsiveness/ sensitivity and IC50 for Doxorubicin and Paclitaxel, between different Ovarian Cancer patients, using Primary Cancer Organoid platform, for personalized drug screening.

Figure 60 – 62: Immunocytochemistry based expression profiling of key neural and proliferation markers in iPSC-neural derivatives from Breast Cancer patients, in response to 7 days Paclitaxel and 5FU exposures.

Figure 63 – 65: Immunocytochemistry based expression profiling of key neural and proliferation markers in iPSC-neural derivatives from Ovarian Cancer patients, in response to 7 days Paclitaxel and 5FU exposures.

DETAILED DESCRIPTION OF THE INVENTION

A general understanding of the invention with its foregoing and other objects will be apparent upon consideration of the following detailed description read in conjunction with the accompanying drawings. It must be understood that the disclosed embodiments are merely exemplary and for better illustration of the invention, which can be embodied in various forms. Descriptions of specific techniques, protocols, devices, and applications are provided only as illustration for greater understanding of the invention. Further, the terms and phrases used herein are not intended to be limiting but rather to provide a detailed and easy description of the invention. It must be noted that various modifications to the examples described herein will be readily apparent to any person having ordinary skill in the art, and the general principles defined herein may be applied to other examples and applications without departing from the spirit and scope of the various embodiments. Thus, the various embodiments are not intended to be limited to the examples described herein and shown, but are to be accorded the scope consistent with the claims.

Accordingly, one of the most general embodiments of the present invention discloses a method and system for development of human somatic cell-derived induced pluripotent stem cell (iPSC) and differentiated lineages (isogenic neural progenitors and mature neural derivatives) for preclinical drug screening and toxicology. According to another general embodiments of the invention, clinical samples are sourced, and the system is developed for healthy volunteers as well as diseased individuals (Breast and Ovarian cancer patients). The present invention further discloses development of iPSC-derived neurotoxicity method and system in both 2-dimensional (2D) and 3-dimensional (3D) culture systems. The presently disclosed method and system are found by the inventors to be physiologically relevant for humans through functional screens, e.g. drug profiling (using standard-of-care chemotherapy drugs) in response to both acute and chronic/systemic exposure to drugs. The neurotoxicity method and system as disclosed here predicts clinical toxicity and adverse event(s) in humans, at the preclinical stage, including the clinical IC50 values with accuracy up to 85-90% and a confidence interval of greater than 95%.

According to another embodiment of the present invention is disclosed a method and system utilizing iPSC-derived neural progenitor cells (NPCs) from breast cancer patient and ovarian cancer patient in adherent 2D cultures as well as 3D suspension cultures in 96-well plate format for use in neurotoxicity assessment of chemotherapeutic drugs. Over a period of three weeks, three time points are characterized, and spheroids are exposed to known chemotherapeutic drugs for short term and long term exposure to investigate their cytotoxic effect. Using the said approach, Inventors have been able to successfully demonstrate the potential of iPSC-derived patient NPCs to detect and predict drug-induced neurotoxicity upon Paclitaxel treatment for the individual patients. The generated neuronal spheroids used for NT measurements at different time-points, resembling various in vivo differentiation stages, therefore, provide a unique and efficient platform for further DNT test system developments.

In accordance with another general embodiment of the present invention, the inventors developed an integrated and high throughput system and method for cancer-drug induced neurotoxicity assessment, based on in vitro assays using human induced pluripotent stem cells (iPSCs) and derivatives from cancer patients. The system is developed by integrating information from whole genome profiling of patient tumors and iPSCs along with the in vitro drug screening and profiling using isogenic iPSC derivatives (such as iPSC-derived neural cells). These analyses, alongside the downstream assays provide a combined readout to predict the likelihood of a patient experiencing drug-induced neurotoxicity upon treatment, at doses that may show clinical efficacy against the cancer, in the isogenic cancer organoid system. It is observed and established by the inventors of the present invention that the use of human induced pluripotent stem cell (iPSC) technology-based platforms with the samples of diseased patients in accordance with the method and system of the present invention is able to overcome the drawbacks of the existing technology by offering the advantage and unconstrained availability of cells and tissue types (e.g., neuronal, liver, cardiac, kidney, intestinal etc.) sharing the same genetic background as the human donor or patient, to develop disease-specific models for in vitro drug evaluation in a replicable and scalable manner. It is also found and established by the inventors of the present invention that patient-derived testing platforms that carry germline mutations and gene signatures specific to that patient are likely to have an impact on drug response and rendered cytotoxicity. Accordingly, in the present invention, the inventors leveraged human cancer patient (Breast Cancer and Ovarian Cancer) derived in vitro models for evaluating (pre)-clinical neurotoxicity of cancer drugs, including the most commonly used cancer drug Paclitaxel and found up to 85-90% clinical correlation with the clinical setting (previously reported) with more than 95% confidence interval.

As per some preferred embodiments of the present invention, the disclosed method and system includes fabrication of uniform, 3D, free-floating iPSC-derived NPC spheroids from healthy volunteer, breast cancer and ovarian cancer donors. According to some other embodiments, healthy volunteer and cancer NPCs depict baseline differences in spheroid size and growth rates; however, they maintain critical marker expression of progenitor cells (notably, the inventors used PAX6 expression, by quantitative flow-cytometry to show comparable baseline expression in the healthy volunteer versus cancer patients) and also depicts differentiation of a sub-population to mature neurons, astrocytes and oligodendrocytes thus recapitulating the neurodevelopment process in the fetal brain. Accordingly, as per one of the general embodiments, the present invention has provided an integrated system and method developed using 2D and 3D cell cultures derived from patients diagnosed of Breast and Ovarian Cancer to develop iPSCs and its derivatives, which are found to have the potential to detect drug-induced toxicity (as a patient surrogate) and thus can be used for predictive and personalized medicine applications. The present invention thus provides a highly accurate and effective in vitro system and method for toxicologists for capturing the individual variability in the human population.

The iPSC-based method and system of the present invention enables phenotypic testing, as patient iPSCs can exhibit cellular and molecular phenotypes found in patients. Using these benefits, efficacy and toxicity of a drug candidate can be evaluated in vitro before instigating expensive human clinical trials. For example, one critical constraint in clinical trials is the selection of the right target population [Ko et al, Neuropeptides 2014; 48, 109–117]. Due to variability in genetic milieu and predisposition, patients with the same disease and pathology may differ significantly in their response to drugs and a variety of adverse events. The production of specific cell types derived from patients’ iPSCs provides an opportunity for ex vivo “clinical trials” i.e. “human trials in a dish”, in which drugs are tested for their toxicity and efficacy against the specific gene profile of the patient. Accordingly, the system and method of the present invention provides a more accurate identification of effective and personalized drugs, which can be tested and linked in vivo for patient stratification, leading to lower drug attrition rate and identification of safer drugs.

Ethical statements for Studies Involving Human samples and Patient Informed Consent:
All the studies conducted by the inventors were approved by the Institutional Committee for Stem Cell Research (IC-SCR) duly registered with National Apex Committee for Stem Cell Research and Therapy (NAC-SCRT) of ICMR registration ID: NAC-SCRT/134/20200209 and The Institutional Ethics Committee (IEC) duly registered with Drug Controller General of India (DCGI) registration ID: ECR/305/Indt/MH/2018. Signed voluntary informed consent was obtained from the patients. The animal experiments were conducted after approval from Institutional Animal Ethics Committees (IAEC) and approvals of Institutional Biosafety Committee (IBSC) were obtained for genetic engineering and cellular reprogramming. Biospecimens are traceable and are uniquely identifiable by a coding system that protects the donors’ identity, thereby blindfolding the experimenters who perform research (to avoid bias). The informed patient consent document allows the use of the biological material for research, development and manufacturing. Details of the clinical samples from human volunteers (Breast and Ovarian Cancer Patients) that were used in different aspects of the present invention are provided in TABLE 2 (below).

TABLE 2. Details of the clinical samples from human volunteers
Sr. No. Sample ID Donor’s Gender
/Age Donor’s Race Morbidity Cancer Stage
1 YBL0001 F/44 Asian Ca. Breast Invasive duct carcinoma, grade III with metastatic regional nodes, pTNM - T2 N2
2 YBL002 F/69 Asian Ca. Ovary Moderately differentiated papillary serous adenocarcinoma I involving right ovary infiltrating into myometrium and sigmoid colonic wall
3 YBL003 F/45 Asian Ca. Ovary (Serous cystadenoma) Metastatic poorly differentiated carcinoma
4 YBL004 F/54 Asian Ca. Breast Invasive duct carcinoma, grade III with metastatic regional nodes; pTNM - T2 N2
5 YBL005 F/36 Asian Ca. Breast Invasive duct carcinoma, grade III with reactive regional nodes
6 YBL006 F/68 Asian Ca. Breast Infiltrating duct carcinoma, grade III with left axillary nodal metastasis
7 YBL007 F/61 Asian Ca. Breast Invasive duct carcinoma; grade III with reactive regional nodes; pTNM - T2 N0
8 YBL008 F/63 Asian Ca. Breast Invasive ductal carcinoma, Grade II with metastatic regional nodes
9 YBL009 F/65 Asian Ca. Ovary Metastatic adenocarcinoma
10 YBL010 F/51 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes, pTNM - T2N1
11 YBL011 F/65 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes, pTNM - T2N1
12 YBL012 F/41 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes; pTNM - T3 N3
13 YBL013 F/25 Asian Ca. Breast Fibroadenoma,- benign breast lesion - suggestive of fibrocystic change
14 YBL014 F/62 Asian Ca. Breast Invasive ductal carcinoma; grade II with reactive regional nodes; pTNM - T1 N0
15 YBL015 F/43 Asian Ca. Ovary Submucousal Polypoid Leiomyoma
16 YBL016 F/33 Asian Ca. Ovary Mild Chronic Inflammation
17 YBL017 F/55 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes; pTNM - T3 N3
18 YBL018 F/62 Asian Ca. Breast Invasive ductal carcinoma; grade II with reactive regional nodes; pTNM - T2 N0
19 YBL019 F/72 Asian Ca. Ovary High grade sero-mucinous adenocarcinoma involving both ovaries with metastatic deposit in omentum & reactive regional nodes
20 YBL020 F/44 Asian Ca. Breast Invasive ductal carcinoma; grade III with reactive regional nodes; pTNM - T2 N3
21 YBL021 F/55 Asian Ca. Breast Invasive ductal carcinoma; grade III with reactive regional nodes
22 YBL022 F/52 Asian Ca. Ovary Moderately differentiated papillary serous adenocarcinoma involving both ovaries infiltrating into colonic wall with metastatic deposit in right & left abdominal pelvic wall peritoneum; pTNM - T4 N2
23 YBL023 F/60 Asian Ca. Breast Invasive ductal carcinoma grade III with reactive regional nodes pTNM-T2 N2
24 YBL024 F/45 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes; pTNM - T2 N3
25 YBL025 F/51 Asian Ca. Ovary Both ovaries - corpus albicans and follicular cysts
26 YBL026 F/46 Asian Ca. Breast Invasive ductal carcinoma, grade III with reactive regional nodes
27 YBL027 F/69 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes; pTNM - T3 N3
28 YBL028 F/45 Asian Ca. Breast Malignant phyllodes tumor with reactive nodes
29 YBL029 F/32 Asian Ca. Breast Benign phyllodes tumor
30 YBL030 F/38 Asian Ca. Breast Invasive ductal carcinoma grade III with reactive regional nodes
31 YBL031 F/38 Asian Ca. breast Invasive ductal carcinoma grade III with reactive regional nodes
32 YBL032 F/71 Asian Ca. Breast Invasive ductal carcinoma
33 YBL033 F/18 Asian Ca. Ovary Right ovarian mass - suggestive of gangrenous change
34 YBL034 F/63 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes, pTNM - T2 N3
35 YBL035 F/45 Asian Ca. Ovary Left Ovarian Mass - Mature Teratoma
36 YBL036 F/60 Asian Ca. Breast Invasive Ductal Carcinoma Grade III
37 YBL037 F/42 Asian Ca. Breast Invasive ductal carcinoma grade III with metastatic unilateral regional nodes pTNM - T2 N1
38 YBL038 F/70 Asian Ca. Ovary (Adenoid) Metastatic deposits in both ovaries with metastatic regional nodes
39 YBL039 F/21 Asian Ca. Ovary Metastatic poorly differentiated adenocarcinoma
40 YBL040 F/70 Asian Ca. Ovary (Adenoid) Moderately differentiated adenocarcinoma with regional nodes
41 YBL041 F/65 Asian Ca. Breast Invasive ductal carcinoma grade II
42 YBL042 F/43 Asian Ca. Breast Invasive duct carcinoma, grade III with metastatic regional nodes
43 YBL043 F/66 Asian Ca. Breast Invasive ductal carcinoma, grade III with reactive regional nodes
44 YBL044 F/65 Asian Ca. Breast Metastatic bilateral regional nodes
45 YBL045 F/51 Asian Ca. Ovary (Adenoid) Invasive ductal carcinoma, grade III with reactive regional nodes
46 YBL046 F/37 Asian Ca. Ovary Moderately differentiated papillary adenocarcinoma with reactive regional nodes pTNM-pT1N0
47 YBL047 F/58 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes, pTNM - pT2 N2
48 YBL048 F/75 Asian Ca. Ovary (Adenoid) Invasive ductal carcinoma, grade III with reactive regional nodes
49 YBL049 F/74 Asian Ca. Breast Invasive ductal carcinoma, grade III
50 YBL050 F/65 Asian Ca. Breast invasive ductal carcinoma, grade III
51 YBL051 F/55 Asian Ca. Breast Poorly differentiated adenocarcinoma
52 YBL052 F/75 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional node
53 YBL053 F/58 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional node
54 YBL054 F/69 Asian Ca. Breast Invasive ductal carcinoma; grade III with metastatic regional nodes
55 YBL055 F/42 Asian Ca. Ovary (Adenoid) Moderately differentiated papillary serous adenocarcinoma involving ovary with metastatic deposits in omentum & reactive regional nodes
56 YBL056 F/36 Asian Ca. Breast invasive carcinoma grade II
57 YBL057 F/56 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional node
58 YBL058 F/35 Asian Ca. Ovary Moderately differentiated mucinous adenocarcinoma involving right ovary with reactive regional nodes
59 YBL059 F/60 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional node
60 YBL060 F/77 Asian Ca. Breast Invasive ductal carcinoma Grade III (T2N3)
61 YBL061 F/49 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes
62 YBL062 F/65 Asian Ca. Breast No residual tumor with reactive regional nodes. pTNM - pT2 N2
63 YBL063 F/45 Asian Ca. Breast Grade II with reactive regional nodes. pTNM - pT2 N2
64 YBL064 F/53 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes
65 YBL065 F/58 Asian Ca. Ovary Moderately differentiated mucinous adenocarcinoma involving left ovary with reactive lymph nodes
66 YBL066 F/45 Asian Ca. Breast Invasive ductal carcinoma, grade III
67 YBL067 F/49 Asian Ca. Breast Mixed mucinous carcinoma, grade III with metastatic regional nodes
68 YBL068 F/60 Asian Ca. Ovary (Adenoid) Well differentiated mucinous adenocarcinoma involving one ovary with reactive regional nodes
69 YBL069 F/45 Asian Ca. Ovary Both ovaries corpus albicans
70 YBL070 F/47 Asian Ca. Breast Invasive ductal carcinoma - grade III with metastatic regional nodes, pTNM - pT2 N1
71 YBL071 F/62 Asian Ca. Breast Invasive duct carcinoma, grade III
72 YBL072 F/61 Asian Ca. Ovary Low grade serous adenocarcinoma involving right ovary with reactive regional nodes
73 YBL073 F/52 Asian Ca. Breast Invasive ductal carcinoma, grade III, ER - positive, PR - positive, HER2 - negative
74 YBL074 F/23 Asian Ca. Ovary (Adenoid) level 1a - single reactive node
75 YBL075 F/59 Asian Ca. Ovary Moderately differentiated serous adenocarcinoma
76 YBL076 F/55 Asian Ca. Ovary Invasive lobular carcinoma, grade III with metastatic regional nodes, pTNM - pT2 N2
77 YBL077 F/38 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes, pTNM - pT2 N2
78 YBL078 F/63 Asian Ca. Ovary Acute inflammation with reactive cellular changes
79 YBL079 F/70 Asian Ca. Breast Invasive ductal carcinoma, Grade III
80 YBL080 F/74 Asian Ca. breast Invasive tubular carcinoma with reactive unilateral regional nodes
81 YBL081 F/68 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes, pTNM - pT3 N1
82 YBL082 F/47 Asian Ca. Breast Invasive ductal carcinoma, grade III with reactive regional nodes
83 YBL083 F/57 Asian Ca. Breast Invasive ductal carcinoma, grade II
84 YBL084 F/67 Asian Ca. Breast Metastatic adenocarcinoma without perinodal extension
85 YBL085 F/71 Asian Ca. Breast Invasive ductal carcinoma, Grade II with metastatic regional nodes
86 YBL086 F/85 Asian Ca. Breast Mucinous carcinoma, Grade II with reactive regional nodes
87 YBL087 F/71 Asian Ca. Breast Invasive ductal carcinoma, grade III with reactive regional nodes
88 YBL088 F/61 Asian Ca. Ovary spindle cell carcinoma
89 YBL089 F/65 Asian Ca. Breast Invasive lobular carcinoma, grade III with reactive regional nodes
90 YBL090 F/47 Asian Ca. Ovary Squamous metaplasia & mild chronic cervicitis
91 YBL091 F/47 Asian Ca. Ovary Moderately differentiated papillary serous adenocarcinoma involving ovary with reactive regional nodes
92 YBL092 F/73 Asian Ca. Breast Ductal carcinoma in situ (DCIS)
93 YBL093 F/63 Asian Ca. Breast Invasive ductal carcinoma, grade III with metastatic regional nodes
94 YBL094 F/72 Asian Ca. Breast Invasive ductal carcinoma, grade II
95 YBL095 F/79 Asian Ca. Ovary (Adenoid) Right ovarian mass granulosa cell tumer pTNM-pT1N0
96 YBL096 F/38 Asian Ca. Breast Invasive ductal carcinoma grade III with reactive regional nodes pTNM-pT4N0
97 YBL097 F/51 Asian Ca. Ovary Mass Well differentiated mucinous adenocarcinoma
98 YBL098 F/46 Asian Ca. Ovary (Adenoid) Well two moderately differentiated papillary serous adenocarcinoma involving both ovaries with metastatic deposits
99 YBL099 F/61 Asian Ca. Breast Metaplastic carcinoma grade III with metastatic regional node pTNM - pT4 N1
100 YBL100 F/54 Asian Ca. Breast Invasive duct carcinoma grade III with metastatic region node pTNM - pT4 N2
101 YBL101 F/75 Asian Ca. Breast Invasive duct carcinoma grade III
102 YBL102 F/34 Asian Ca. Ovary Granulosa cell tumour pTNM - pT4 N2
103 YBL103 F/55 Asian Ca. Breast Invasive duct carcinoma grade III
104 YBL104 F/57 Asian Ca. Ovary Moderately differentiated papillary serous adeno carcinoma involving ovary with reactive regional nodes.
105 YBL105 F/48 Asian Ca. Breast Invasive duct carcinoma grade III with reactive regional nodes pTNM-pT3N0.
106 YBL106 F/44 Asian Ca. Ovary Moderately differentiated papillary serous adeno carcinoma involving ovary with reactive regional nodes.
107 YBL107 F/56 Asian Ca. Breast Metaplastic carcinoma grade III with reactive regional nodes.pTNM-pT3N0
108 YBL108 F/55 Asian Ca. Breast Invasive duct carcinoma grade III with reactive regional nodes.pTNM-pT3N0
109 YBL109 F/52 Asian Ca. Ovary (Adenoid) Low grade papillary serous adeno carcinoma involving both ovary with reactive regional nodes. pTNM-pT1C2pN0
110 YBL110 F/56 Asian Ca. Breast Invasive breast carcinoma grade III with metastatic regional nodes, pTNM-pT2N3
111 YBL111 F/47 Asian Ca. Breast Invasive breast carcinoma grade III with metastatic regional nodes pTNM- pT2N3
112 YBL112 F/41 Asian Ca. Breast Invasive duct carcinoma grade III with metastatic regional nodes pTNM-PT4N3
113 YBL113 F/72 Asian Ca. Ovary (Adenoid) Low grade adenocarcinoma involving left ovary
114 YBL114 F/46 Asian Ca. Ovary Moderately differentiated adenocarcinoma involving both ovaries
115 YBL115 F/69 Asian Ca. Ovary (Adenoid) Left ovarian mass: high grade adenocarcinoma involving left ovary.
116 YBL116 F/74 Asian Ca. Breast Invasive breast carcinoma grade III with metastatic regional nodes. pTNM- pT2N1
117 YBL117 F/59 Asian Ca. Ovary Moderately differentiated papillary serous adenocarcinoma involving ovary with reactive regional nodes
118 YBL118 F/56 Asian Ca. Breast Invasive breast carcinoma grade III with metastatic regional nodes pTNM-pT2N1
119 YBL119 F/55 Asian Ca. Ovary Moderately differentiated adenocarcinoma involving both ovaries
120 YBL120 F/56 Asian Ca. Breast Invasive breast carcinoma grade III with metastatic regional nodes pTNM-pT3N1
121 YBL121 F/69 Asian Ca. Breast Invasive ductal carcinoma grade III with reactive regional nodes pTNM-pT3N0

The inventors demonstrated a process for the development of fully pluripotent and functionally mature iPSCs from PBMCs of healthy volunteers and Breast and Ovarian Cancer patients (Figure 1 to 12). The inventors have also demonstrated processes for the differentiation of these iPSCs into Neural Progenitor Cells (NPCs) that have been shown to be functionally active and capable of further development and maturation into functionally mature neural derivatives that together control the functioning of the central and peripheral nervous system i.e. Forebrain Motor Neurons, Midbrain Dopaminergic Neurons as well as Astrocytes (Figure 16 to 32).

Isolation of PBMCs and Development of iPSCs

Healthy volunteer and Patient-derived PBMCs developed iPSC clones that express key pluripotency markers: To generate human iPSCs from healthy volunteers, breast and ovarian cancer patients minimizing the risk of genomic abnormalities, the inventors introduced the OSKM factors using the non-integrating sendai virus based interim gene modification technology. Colonies with a typical human ESC-like appearance began to emerge in culture 22 days after reprogramming, in Healthy volunteers as well as Breast Cancer and Ovarian Cancer patients (Figure 1A and B). The inventors observed that iPSCs maintained undifferentiated morphology with round and clear edges in control conditions. The iPSC clones stained strongly positive for Alkaline Phosphatase activity as a test for pluripotency, and this positivity was maintained after passaging in healthy volunteers (Figure 3) as well as Breast Cancer (Figure 7) and Ovarian Cancer patients (Figure 10). The clones expressed pluripotent markers NANOG, OCT-4 and SSEA4 in healthy volunteers (Figure 2) as well as Breast Cancer (Figure 6) and Ovarian Cancer patients (Figure 9). These reprogrammed iPSC clones also expressed >80% SSEA-4, TRA-1-81 and OCT4 in flow cytometry analysis (Figure 3, 7 and 10).

Determination of Pluripotency and genomic stability of iPSCs

Healthy volunteer and Patient derived iPSCs formed teratoma i.e. differentiated in vivo into Cells of all Three Germ-Layers: Teratoma formation is considered a hallmark property of iPSCs when they are transplanted into immunodeficient mice. In order to check the in vivo pluripotency of the iPSC lines, teratoma assay was performed. In all transplanted animals, tumors were observed 4-6 weeks after transplantation with 1×106 healthy volunteer (https://authors.elsevier.com/sd/article/S187350612300048X), breast cancer (Figure 8) and ovarian cancer patients’ iPSCs (Figure 11). By 8–10 weeks the tumors were larger than 1 cm3 (average tumor volume of 2.2±0.4 cm3) and the animals were sacrificed as per international animal ethics and regulatory norms. The tissues of the sacrificed animals' peritoneum, liver, spleen, and lungs were examined, no additional sites of tumor. The three germ layer structures were randomly arranged within the teratomas (Figure 8 and 11). In contrast, none of the control animals (n?=?10) transplanted with 1×106 healthy volunteer, breast cancer and ovarian cancer patients’ PBMCs either in the presence or absence of ROCK inhibitor, developed tumors or teratoma. These results demonstrated that subcutaneous transplantation of 5×105 or 1×106 undifferentiated human iPSCs, combined with matrigel, into NOD/SCID mice was highly efficient, leading to teratoma formation in 100% of the transplanted mice, suggesting confirmation of pluripotency of the iPSC lines.

Karyotypic studies indicate genomic stability in healthy and patient iPSCs: Karyotyping was performed by GTG-banding analysis performed by MedGenome Laboratory, Mumbai. Cells were treated with KaryoMAX® Colcemid™ Solution (ThermoFisher Scientific, 15212-012) overnight at 37 °C and thereafter processed following standard procedures in routine diagnostics. Karyotypic analysis revealed no genomic abnormalities in healthy volunteer or patients’ iPSCs suggesting that during reprogramming with non-integrating sendaivirus method, no genomic instability was introduced in patients’ iPSCs. Both source PBMC and iPSCs had normal diploid 46 karyotype, without acquired detectable abnormalities (Figure 4, 7 and 10).

Short Tandem Repeat (STR) Analyses: STR analyses was performed using standard procedures, by MedGenome Laboratory, Mumbai. 100% match between donor PBMCs and derived iPSC lines confirmed iPSC identity and purity (indicating no contamination from any other cells). Across all iPSC lines developed for Healthy volunteers, Breast Cancer patients and Ovarian Cancer patients, 100% match of STR was observed (Figure 5, 7 and 10).

Differentiation of iPSCs and Development of NPCs

Neural progenitor differentiation under defined conditions: The inventors differentiated hiPSCs from healthy volunteer, breast and ovarian cancer patients towards neural progenitor cells (NPCs) under defined, xeno-free conditions. This method yielded homogeneous and proliferative NPCs (Figure 16). Neural induction was assessed by expression of PAX6, an early marker of neuroectodermal development. Combined treatment with Noggin and SB431542 greatly increased the efficiency of neural induction where more than 80% of total cells were found PAX6+. Results demonstrate that SB431542 and Noggin worked synergistically at several phases of differentiation to effectively transform hiPSC cells to neurons (Figures 17, 18 and 19). Immunocytochemical analysis showed that, PAX6+ neuroectodermal cells express general neural stem cell markers, such as Nestin (Figures 20). More than 80% NPCs expressed PAX6 and Nestin (Figure 17, 18 and 19).

Forebrain motor neurons generated efficiently under xeno-free conditions: The inventors first investigated whether hiPSCs had the functional capability to differentiate to forebrain motor neurons under xeno-free conditions. More than 90% of cells expressed neuronal marker ß III-tubulin or Tuj1 at day 28, demonstrating that the differentiated neurons have a neuronal characteristic phenotype (Figure 24, 25 and 26). iPSCs-derived neurons from healthy volunteer, breast cancer and ovarian cancer patient were treated with 0.1 µM Paclitaxel and neurite outgrowth was analyzed. Ovarian cancer patient’s neurons were found more sensitive to paclitaxel followed by breast cancer patient and healthy volunteer in addition to the baseline differences seen between clinical groups in terms of neurite function (Figure 42, 43, 44 and 45).

Astrocytes were developed in a xeno-free environment: Astrocytes are critical components of the central nervous system. A number of mental and neurodegenerative disorders are linked to astrocyte dysfunction. To explore whether hiPSCs in xeno-free condition could differentiate to astrocytes, neural progenitors were treated with 20 ng/ml BDNF, 10 ng/ml GDNF, 10?ng/ml EGF, 250?g/ml Dibutyryl cyclic-AMP, 10 ng/ml LIF, and 10?ng/ml FGF2 starting at d21. With two months of continuous treatment, more than 60 % of cells were GFAP & S100ß positive and ~ 30 % were ßIII-tubulin positive (Figure 21, 22 and 23).

Midbrain Dopaminergic Neurons were generated under xeno-free condition: Neural patterning was initiated by a dual SMAD inhibition strategy (Chambers et al, 2009) and specification towards a ventral midbrain dopaminergic neural fate was performed using the morphogens sonic hedgehog (SHH) and fibroblast growth factor-8a (FGF8a) (Cooper et al, 2010). It was observed that ascorbic acid, BDNF, GDNF and cAMP induced neural maturation. Extensive immunocytochemical analysis was performed on differentiated neurons from all clinical sub-groups and large populations (> 80%) of tyrosine hydroxylase- (TH) expressing cells were found suggestive of a robust process for the differentiation of iPSC-derived NPCs into Midbrain Dopaminergic Neurons (Figure 27 to 32).

Genetic Profiling of NPCs

Further investigations into the genetic profiling of the tumors and isogenic iPSCs from human participants/ volunteers in this study, through next generation sequencing analyses (Figure 12), revealed preservation of the genetic signature of the donor and the various germline mutations/ variations profiled in the patient’s tumor biopsies, in the iPSC derivatives developed from the reprogramming of the donor’s PBMCs. Gene annotation details provided in Figure 13, 14, 15 present the key genetic anomalies by way of germline mutations that were found to be conserved between isogenic tumors and iPSCs from the same donor. Many of these genetic mutations are known to be associated with disease (cancer, etc.) predisposition, cancer progression, drug responsiveness, drug-induced cytotoxicity, cancer invasiveness, metastasis as well as propensity for neurodegeneration/ neurotoxicity as per Gene Ontology, Genome-wide Association Studies (GWAS) as well as KEGG and Clin Var databases.

Notably, upon gene profiling the inventors identified genetic signatures unique to an individual that are expected to not only predispose an individual to disease and related pathology but also that are determining of possible propensity or likelihood of acquired, drug induced toxicity. In this context the inventors hypothesized the necessity to develop a donor-specific neurological testing platform, in vitro, that is able to capture the genetic signature and functional/ biological characteristics of the donor, while showing output in drug exposure studies (in vitro drug sensitivity, resistance and drug induced toxicity assays) which is reflective of the patient’s clinical response. This approach circumvents the limitations of current models that are developed out of neurological cells sourced from healthy individual, that are not optimal for such preclinical screens as they lack the genetic profile/ signature of the patients (which has been shown in previous studies as a contributing factor towards, drug induced toxicity). To this end, the inventors developed a novel neurotoxicity assessment method and system for preclinical screening to predict “Drug-induced Neurotoxicity” in Breast and Ovarian Cancer patients.

Detection and Prediction of Neural Toxicity of Chemotherapeutic Agents

The neurite outgrowth assay perform by the inventors was also able to capture the intrinsic effects of cancer types on neurite extension lengths showcasing the effect of malignancy and predisposing gene signatures on neurological and neurodevelopmental process as well as drug responsiveness (Figure 43, 44 and 45). Thus, the method and system as per one of the preferred embodiment of the present invention built using cells sourced from individual cancer patients can also be used to test outcomes and impacts of genetic signatures and imprint of individual patients on both the baseline of neuronal response (DNT screening) as well as effects of drug treatment based on genetic profile of the patient and impact of treatment (NT screening), through read-outs like gene and protein expression/ localization, as well as functions such as neurite outgrowth. This enables discovery of biomarkers for predicting neurotoxicity and drug responsiveness under pathological state. Furthermore, the disclosed method and system can also be utilized in the in vitro drug screening of novel compounds for short- and long-term (i.e. acute versus chronic) exposure up to 14 days. The resultant data can be used to model and predict the unknown neurotoxic effects of chemotherapy drugs to be administered for breast cancer and ovarian cancer treatment for Neurotoxicity (NT) screening, patient stratification based on drug response as well as for investigating Developmental Neurotoxicity (DNT) and its underlying mechanisms.

According to another preferred embodiment of the present invention, a novel, scaffold-free 3D model of neural progenitor cells derived from healthy, breast cancer and ovarian cancer patient-derived iPSCs is developed. PBMCs isolated from patients are reprogrammed to iPSCs and further differentiated to NPCs. These NPCs are well characterized and used to fabricate uniform 3D models that are cultured for up to 21 days (Figure 37, 38, 39 and 40). The NPC spheroids demonstrated critical neural progenitor marker as well as mature neuronal, astrocytes and oligodendrocyte expression at gene and protein levels. In the present system, there is no need to use any specialized growth factors, thereby making the process simple to scale and cost effective; a neural progenitor medium and 3D micro environmental cue are sufficient to promote the differentiation into complex cell population spheroids within 3 weeks of culture. Low variability among samples and high homogeneity is crucial when the aim is to develop a reliable HTS for developmental neurotoxicity studies. Although the spheroids show a continuous growth and development/ maturation, the homogeneity of the plates is not compromised, the diameter of the spheroids within the 96-well plate, gene and protein expression levels shows very low variation at a given time point, represented by the low SEM values.

Similar initial cell seeding density for all three donor groups resulted in significantly different sizes in spheroids at Day 7 and Day 21 that could be attributed to intrinsic genetic differences between the cell sources, presumably due to their genetic profile. Differentiating NPC population did not show any significant change in neuronal gene expression for Tuj1 and Engrailed-1. Interestingly, GFAP expression was significantly upregulated at Day 14 and Day 21 in breast cancer NPC spheroids. However, some previous studies have shown that increased expression of GFAP, is not a result of astrocyte differentiation nor is it a reflection of non-specific up-regulation of astrocyte gene expression but during metastatic progression from primary breast tumor to brain metastasis.

Neurite outgrowth is a process wherein developing neurons produce new projections as they grow in response to guidance cues. Dynamic neurite outgrowth during development results in the formation of a complex neuronal architecture that results in the establishment of the functional nervous system and brain. Understanding the biology of neurite outgrowth can shed light on mechanisms underlying certain neurodegenerative diseases. Immunostaining in neurite outgrowth assay shows expression for beta III tubulin after plating on matrigel-coated plates at Day 7, Day 14 and Day 21. However, the length of the neurites showed donor specific profiles that could possibly be attributed to the genetic variants reported for the donor lines, which as per previous reports have a potential impact on neural function. Moreover, Taxol treatment appeared to show further reduction in neurite length in Ovarian cancer patients demonstrating its likely impact on neuronal function, but no significant differences in neurite length in response to Paclitaxel treatment were observed in Breast cancer patients. Notably, Paclitaxel increased the average number of neurite intersections in some breast and ovarian cancer patients (Figure 45). Higher concentrations and longer exposures of Taxol can be assessed in future studies in order to see the dose dependent effect on neurite outgrowth of NPC spheroids.

Notably, a case study of one of the Breast Cancer patients (with invasive ductal carcinoma having a germline mutation in ARID1A gene, a known tumor suppressor, reported in literature to have an impact on cell cycle, cell proliferation, chromatin dynamics, DNA repair pathways as well as drug responsiveness and resistance) showed remarkable growth phenotype in NPC cultures compared to healthy volunteers and ovarian cancer patients. The findings again, pointed to the importance of profiling individual diseased patients for assessing their drug response in the backdrop of their genetic profile, as a practically more accurate measure for predicting drug-induced cytotoxicity and/or resistance. The method and system disclosed in the present invention is the first instance where a neurotoxicity platform (using NPCs) from Breast and Ovarian Cancer patients is able to capture and demonstrate the phenomenon and extent of drug-induced cytotoxicity for well-known cancer drugs (such as Paclitaxel), correlating well with the patient genetic profile and drug treatment regime.

As per Cheng X et. al, Front. Oncol. 2021, 11:759577, Breast cancer has become the most frequently occurring malignancy worldwide, with 2.3 million women diagnosed with breast cancer in 2020 (World Cancer Day 2021: Spotlight on IARC Research Related to Breast Cancer. Available at: https://www.iarc.who.int/featured-news/world-cancer-day-2021/). Despite advances in early diagnosis and comprehensive therapeutic regimens, 20–30% of breast cancer patients who are diagnosed with new or recurrent advanced-stage or metastatic breast cancers contribute to 90% of cancer-related deaths (Nature (2012) 490(7418):61–70; Cochrane Database Syst Rev (2018) 3:CD011276). Owing to their high heterogeneity, aggressive metastatic breast cancers have variable responses to treatment and different patient prognoses. The common distant metastatic organs are bone, lung, liver, and brain, with 5-year overall survival rates of 22.8, 16.8, and 8.5%, that are nearly 80% lower than the survival rates of breast cancer patients without metastasis.

In breast cancer, ARID1A is regarded as a tumor suppressor (Genes Chromosomes Cancer (2007) 46(8):745–50) and cooperates with CEBPa to suppress cell proliferation and migration (Oncogene (2018) 37(45):5939–51). Previous studies support ARID1A deletion as an independent prognostic factor for invasive breast cancer (Oncogene (2012) 31(16):2090–100; Aging (2021) 13 (4):5621–37; Nat Genet (2020) 52(2):198–207). The low mRNA expression of ARID1A is related to shorter overall survival in luminal A and human epidermal growth factor receptor 2 (HER2)-rich breast cancer (Aging (2021) 13 (4):5621–37). Takao et al. analyzed the immunohistochemical staining to evaluate the relationship between the downregulation of ARID1A and poor disease-free survival (J Cancer (2017) 8(1):1–8). Moreover, ARID1A may have a high prognostic value for drug sensitivity. Xu et al. verified a vital function of ARID1A in breast luminal lineage maintenance, which further revealed that the expression of ARID1A in the luminal type was higher than that in the nonluminal type (Aging (2021) 13 (4):5621–37; Nat Genet (2020) 52(2):198–207). The loss of ARID1A was more general in post-endocrine therapy metastatic cancer and regarded as the top candidate whose loss indicated fulvestrant resistance (Nat Genet (2020) 52(2):198–207; Breast Cancer Res BCR (2021) 23(1):1). In addition, ARID1A loss or downregulation drives paclitaxel resistance and HER2/PI3K/mTOR-targeting drug resistance in breast cancer (J Cell Mol Med (2018) 22(4):2458–68; Clin Cancer Res Off J Am Assoc Cancer Res (2016) 22(21):5238). Therefore, ARIDIA is closely related to tumor metastasis or drug resistance-mediated tumor recurrence. Notably, ARID1A germline mutation, p.A2237V (missense mutation), found in the Invasive Ductal Carcinoma in the Breast sample, that is part of our cohort, is also a mutation found in Zehir A et. al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017 Jun;23(6):703-713. This is one of the highest cited Breast Cancer studies that has been cited > 2400 times since publication in 2017. It discusses the association of ARID1A mutation [p.A2237V (Substitution - Missense, position 2237, A?V)] in metastatic cancers (https://cancer.sanger.ac.uk/cosmic/mutation/overview?id=103322030). ARID1A mutation gives rise to specific signalling pathways and cellular functions that can potentially be targeted for treatment(s) of ARID1A-mutated metastatic breast cancer (Cheng X et. al, Front. Oncol. 2021, 11:759577).

Additionally, several other studies support the involvement of genes such as TCF3, XRCC1, NRG1, PLXNA3, ATP7A, IRS4, implicated in the neurodevelopment and/or regulation of drug-induced neurotoxicity mechanisms. Germline mutations, presumably critical for their function, were found in the patient samples that could explain their sensitivity to Paclitaxel (references 260, 295, 296, 303, 368, 309, 377).

Since iPSCs are known to retain the genetic profile of the source, inventors observed a concurrent high degree of proliferation in this Breast Cancer iPSC-derived NPCs, that also showed abrogated neurite outgrowth which remained dampened post Paclitaxel exposure. This also highlighted and validated the importance of having cancer patient specific platforms for testing the possibilities of drug-induced neurotoxicity (which is likely to be impacted, as shown in our work, by the genetic profile, and particularly the predisposing germline mutations in the patients), which is specifically disclosed and established in the present invention.

Additionally, as per Tiane A. et al., 2019, Cells, 8(10), 1236, Oligodendrocytes (OLs) are myelinating glial cells within the central nervous system (CNS) that
insulate neuronal axons to provide them with trophic, metabolic and functional support. OLs are generated from oligodendrocyte precursor cells (OPCs) via a consecutive process of cell cycle exit, maturation, and differentiation. OPCs arise during early development, persist throughout a lifetime and occupy around 5%–10% of the total number of cells in the brain. In response to both intrinsic molecular cues and extracellular signals, OPCs are able to withdraw from their proliferative stage and differentiate into myelin-producing OLs.

OPCs arise from the ventricular zone during early development, proliferate and migrate their way into the different developing areas of the brain, where they differentiate into myelin-forming OLs. Unlike most progenitor cells, OPCs persist throughout life as adult, self-renewing OPCs that can differentiate into newly formed myelinating OLs to maintain myelin plasticity or in response to damaging signals. The differentiation of OPC into mature and myelin-producing OLs is a gradual and well-defined process that can be divided into four successive stages: proliferative OPCs, pre-OLs, differentiated OLs and myelinating OLs. This process of OL differentiation, both during early development and in adult stages, is controlled by the combination of OL-specific transcription factors, extracellular signals, epigenetic modifications and signalling pathways. It is necessary to maintain a homeostatic balance between these molecular cues to allow for proper differentiation.

Oligodendrocytes provide metabolic and functional support to neuronal cells, rendering them key players in the functioning of the central nervous system. Oligodendrocytes (OL) need to be newly formed from a pool of oligodendrocyte precursor cells (OPCs). The differentiation of OPCs into mature and myelinating cells is a multistep process, tightly controlled by spatiotemporal activation and repression of specific growth and transcription factors. Consequently, alterations in these extrinsic stimuli, such as an increase in inhibitory ECM molecules (LINGO, glycosaminoglycans, fibronectin) or secreted factors (BMP, FGF), hamper differentiation, possibly via an upstream effect on transcriptional and epigenetic processes that regulate OL differentiation. Indeed, current evidence indicates that epigenetic mechanisms, comprising DNA methylation, histone modifications and microRNAs (miRNAs), play an essential role in the regulation of OL lineage development.

While oligodendrocyte turnover is rather slow under physiological conditions, a disruption in this balanced differentiation process, for example in case of a differentiation block, could have devastating consequences during ageing and in pathological conditions. Over the recent years, increasing evidence has shown that epigenetic mechanisms, such as DNA methylation, histone modifications, and microRNAs, are major contributors to OPC differentiation. Olig2, a transcription factor that is a key regulator of this process, plays decisive roles in the OPC to OL transition to facilitate primary myelination as well as remyelination of damaged neurons.

Intriguingly, in the Breast Cancer case study discussed above, inventors observed where the iPSC-derived NPCs show increased proliferation, possibly due to missense mutations in ARID1A tumor suppressor gene, the inventors also observed a complete lack of neurite extension. Since these samples also showed a significantly reduced expression of Olig2 gene, which is responsible for the renewal of OPC pool and its differentiation into Oligodendrocytes (OLs) that facilitate myelination of axons to support neurite extension and function, the same could be a potential underlying mechanism. Interestingly, the levels of Olig2 gene were normal in iPSC-derived NPCs from Healthy volunteers and Ovarian Cancer patients that did show neurite extensions and outgrowth. Notably, there was striking impairment in NPC proliferation observed in Ovarian Cancer patient derived NPCs compared to Healthy volunteers and Breast Cancer. Additionally, there was an additive impact and impairment of these neurite outgrowth seen, in response to Paclitaxel treatment, specifically in the Ovarian cancer patient derived NPCs which again could be implicated to the genetic profile of the said patient. Further investigations, by performing next-generation sequencing based RNAseq in NPCs (with and without Paclitaxel or 5FU treatments), corroborated our findings and implications of key genes involved in the neurodevelopmental pathways, known for predisposing to drug-induced cytotoxicity, involved in cell cycle/ cell proliferation as well as cytoskeletal signalling pathways, for their potential role in Paclitaxel-induced neurotoxicity in Breast and Ovarian Cancer patients (data not shown).

These findings highlight the underlying observation of our invention, and proves that it is critical to develop the neurotoxicity platform not just from the healthy volunteers (as has been the case thus far, which has not yielded desired outcomes in several decades), but specifically from the patients of the targeted cancer/ disease, develop the 2D and 3D model systems for different drug exposure studies and downstream testing for molecular expression and function (e.g. Neurite Outgrowth, Proliferation etc.), integrate the genomic information and profile of the patient for predictive modelling and Neurotoxicity assessment. Doing so, has provided us with up to >85% accuracy in predicting drug-induced neurotoxicity in patients.

To this end, 96-well plate assay was performed on 3D neurospheres to detect the cytotoxic effect of the selected compounds, based on ATP-release measurements. Well-known chemicals for acute and systemic neurotoxicity – Taxol, 5-fluorouracil, doxorubicin and amiodarone were used (Taxol being reported as one of the most neurotoxic Taxane drugs). Initial number of cells seeded in 2D and 3D culture is kept same across all donor groups for the sake of consistency. The results highlighted a compound-specific toxicity-profile of the tested chemicals, thereby allowing calculation of IC50 values for the compounds for H- NPCs, BC-NPCs and OC-NPCs, all of which showed significant alignment with clinical Cmax values reported for different drugs (Figure 40 and 41).

In the experiment, Doxorubicin is found to be highly toxic for all iPSC-derived neural progenitor cells irrespective of healthy volunteer or cancer patient source, culture conditions (2D vs 3D) & drug exposure (acute and systemic). Taxol (paclitaxel) is also found to be highly toxic to all NPCs albeit long term exposure in 3D culture showed higher resistance (i.e. higher IC50 value), contrary to previously reported studies. Interestingly, in the method and system disclosed as per the present invention, paclitaxel-induced cell death was found to be much more drastic compared to 5-flurouracil (5FU), as previously reported in clinical studies (Figure 33, 34 and 35) while intrinsic differences were also observed between clinical sub-groups (Figure 36). However, the NPCs showed common baseline in terms of Pax6 expression (Figure 37, 38 and 42). Intriguingly, and upon further investigation it was observed that the paclitaxel driven neurotoxicity was presumably due to microtubule stabilization (as is known from published work) leading ultimately to apoptotic cell death. These mechanisms are also replicated in the iPSC-neural derivatives exposed to Latrunculin A, a known actin disruptor that specifically targets F-actin filaments, leads to microtubule stabilization as a result of cross-talk with the actin signaling pathway, ultimately leading to apoptotic cell death through mechanisms similar to Paclitaxel (Figure 46 and 47). 5-fluorouracil, which is only mildly neurotoxic (in line with previous reports), shows stark differences between 2D and 3D systems for all three groups (Figure 40). As opposed to in vivo preclinical testing results (that show little clinical correlation), amiodarone shows mild neurotoxicity with reported IC50 values greater than the highest dose tested in 3D short term and long-term exposure. Amiodarone is a class III antiarrhythmic drug prescribed commonly for atrial fibrillation and ventricular arrhythmias. The initial experience with this drug also suggested potential for significant neurologic toxic effects mostly at high dosages.

Determination of safe dosage range using Organoids

As per one of the preferred embodiments of the present invention, the method and system for neurotoxicity testing was also integrated with the in vitro testing of chemotherapeutic drug efficacy on isogenic primary cancer organoids derived from cancer patients, who voluntarily consented for their cancer biopsies and other bio-specimens, made available during planned surgeries, to be used for determination of appropriate dosage range and sensitivity of the chemotherapeutic drugs. Intriguingly, in few case studies shown, the chemotherapeutic drug (e.g. Paclitaxel) resulted in drug-induced neurotoxicity and damage at concentrations much lower than those required for the drug to be efficacious against the primary cancer (Figure 40, 41, 50 to 53 and 56 to 59). The present innovation thus also presents an integrated method and system with ability to test the drugs for their efficacy against primary cancer and their likelihood of causing drug-induced neurotoxicity, along with the dose-ranging studies that can assist in identifying the most effective treatment dose, for a given individual, that is likely to be effective against the cancer while minimizing the cytotoxic side-effects. Next-generation sequencing studies and database build-up using such deterministic studies can eventually fill the current gap (that has existed for several decades) in the understanding of underlying gene signatures that drive or at least can help predict drug-induced neurotoxicity upon Paclitaxel treatment in Breast and Ovarian cancer patients.

Establishment of primary ovarian cancer organoids: The inventors developed a protocol to culture and expand organoids from tissue biopsies collected from ovarian cancer patients. Primary ovarian cancer organoids were developed from various histologic subtypes (High grade serous carcinoma, moderately differentiated endometrial adenocarcinoma, and mucinous carcinoma) of stage I–III ovarian cancer patients in 2-3 weeks with matching adjacent normal tissue. The overall success of the primary organoid culture was ~80% (8 out of 10). The created organoids replicated the histological features of primary tumor. In less than three weeks, inventors created expandable ovarian cancer organoids that accurately reflected the traits of many histological cancer subtypes. In terms of the expression of key molecular and cancer markers as well as therapeutic response, histological analysis of Patient Derived Organoids (PDOs) and the patient biopsies from which they were initially produced revealed striking morphological parallels (Figure 54 and 55).

The inventors performed drug sensitivity and resistance test (DSRT) using 2 FDA-approved commonly used therapeutic drugs paclitaxel and doxorubicin. Depending on the properties of the individual drugs, the concentrations ranged from 0.001 µM to 1000 µM (Figure 56 to 59).

Establishment of primary breast cancer organoids: Inventors produced matched organoid cultures using the normal and tumor tissues with a success rate of ~80% (12 out of 15) from human mammary tissues removed during mastectomies. Pathologists in each case validated the histology of the originating tissue. Viable BC organoids were obtained from luminal A, luminal B, human epidermal growth factor receptor 2 (HER2)-enriched and triple negative BC (TNBC; estrogen and progesterone receptors negative, HER2 negative). Organoids were produced from both invasive ductal carcinomas and invasive lobular carcinomas based on the histological characterization. Different samples of BC organoid cultures produced solid, cystic, cribriform, and "grape-like" structures that varied widely in size and morphology. PDO’s long term maintenance was higher for more aggressive tumor subtypes, TNBC and HER2-enriched PDOs having the highest proliferative potential and luminal A-derived PDOs having the lowest (data not shown).

Organoids were also developed from normal adjacent tissue (NAT) biopsies with glandular structures and mimicking mammary ducts. However, NAT-derived organoids propagated slowly, and lost proliferation after few passages (Figure 48 and 49). Inventors investigated BC organoids in response to standard medications in order to assess their potential as in vitro disease models. Towards this, PDOs were treated with doxorubicin and paclitaxel (commonly used chemotherapeutic drugs). Inventors found that few breast cancer PDOs were resistant to doxorubicin but were sensitive to treatment with paclitaxel. Notably, in some of these cases, the effective concentration of Paclitaxel was higher than the minimum concentration that was shown to be neurotoxic on our Neurotoxicity Testing Platform” (Figure 50 to 53).
Organoids retained the Genomic and Histological Features of the Original Tumor biopsy: Histological evaluation revealed significant morphological similarities between PDOs and the patient biopsies from which they were originally-derived (Figure 48, 49, 54, 55). To compare the genomic characteristics of the parental tumor tissues and derived organoids, Inventors did genomic DNA and cDNA analysis for selected ovarian cancer and breast cancer markers. Tumor tissue derived organoids and snap frozen tissues were analyzed for BRCA1, BRCA2, ER, PR and HER2 in breast cancer, Tal2, EGF, ILF3, UBI2I, BRCA1, and BRCA2 in ovarian cancer. Pluripotency markers OCT4, SOX2 with cancer markers BRCA1, BRCA2, ER, PR and HER2 in breast cancer iPSCs; Tal2, EGF, ILF3, UBI2I, BRCA1, and BRCA2 in ovarian cancer iPSCs were analyzed.

Organoid usability for personalized Drug sensitivity and resistance testing (DSRT): Following seven days’ incubation, organoid cultures were manually inspected using a phase-contrast microscope to check cell health and morphology prior to the addition of drugs. CellTiter-Glo® 2.0 determines the number of viable cells in a well, based on the quantification of ATP present, an indicator of metabolically viable cells. Total cell count was measured by CellTiter-Glo® 2.0, which causes cell lysis and produces a luminescence signal proportional to the amount of ATP present (Francies et al, 2019). Following completion of the above quality metrics, the data was normalized or the raw intensity data was used for curve-fitting (Figure 50 to 53 and 56 to 59).

(a) Data normalization: Normalization was completed using the following calculation: (Raw intensity signal- Mean of positive control/ Mean of negative control-Mean positive control)
For drugs where the concentrations selected have generated a dose–response curve, measurements such as the IC50 (half-maximal inhibitory concentrations) and AUC (area under the curve) were calculated to assess and compare sensitivity.

b) Curve-fitting: Commercial software packages such as GraphPad Prism and Microsoft Office Excel were used to analyze the data generated from the drug screen assay. Curve-fitting algorithms for modeling drug response were also applied.

Finally, inventors performed DSRT using 2 FDA-approved drugs paclitaxel and doxorubicin. Ovarian cancer and breast cancer patient samples displayed heterogeneity in drug sensitivity pattern, on expected lines. Comparative studies were carried out across different patient samples and treatment groups. Notably, PDOs displayed simultaneous sensitivity or resistance to paclitaxel and doxorubicin. Organoids produced from metastatic cancers have a higher frequency of resistance to the microtubule- and nucleic acid synthesis-targeting drugs compared to primary malignancies.

Doxorubicin or paclitaxel were administered to the resistant and sensitive organoid lines, to confirm the specific drug responses. Inventors found apoptotic vesicles around the organoids in the sensitive lines after 24-72 hours of treatment; these vesicles became more distinct after 72 hours. Resistant organoids, however, retained distinct morphology until day 21 of drug treatment, as assessed by histological analysis.

Taken together, it is found and established in the present invention that it is possible to identify neurotoxic compounds by applying the disclosed method and system that utilizes information from both 2D and 3D short term and long-term cytotoxicity screens. The disclosed method and system based on clinical specimens sourced from both healthy volunteers and breast and ovarian cancer patients provides remarkable insights into predicting clinical neurotoxicity of several gold-standard chemotherapeutic drugs as well as safe dosage ranges for individual patients. It shows immense promise as a tool for successful use in a quantitative high throughput (unbiased) screen (qHTS), with ability to generate concentration–response curves for a library of test compounds in a single experiment providing high throughput for rapid screening of novel compounds.

The system and method as per the present invention provides a high-throughput, fast and cost-effective way to predict clinical neurotoxicity in breast and ovarian cancer patients. Further, it also provides for the discovery of clinical biomarkers for predicting drug-induced neurotoxicity as well as to screen for compounds for combinatorial therapy to circumvent the neurotoxicity in response to cancer or other drugs. In addition to the personalized drug screening, for precision medicine, the human in-vitro system and method for neurotoxicity analysis according to the disclosure in the present invention is of particular relevance for pharmaceutical industries, since it can provide a powerful, fast and cost-effective tool for neurotoxicity assessment, applicable to the early phases of drug discovery. The present system and method can also help in flagging and potentially avoiding late, high attrition rates, making finally drug development more cost-effective.

EXAMPLES

Example 1. Isolation of Characterization of Samples from Patients

Blood samples are collected from healthy volunteers or Breast Cancer patients (ductal carcinoma in situ) or Ovarian Cancer patients (adenocarcinoma) by following informed consenting procedures. All the donors are Indian in origin. The study has been approved by the Institutional Committee for Stem Cell Research (ISSCR) and the Institutional Ethics Committee (IEC). Written informed consent is obtained from the patients for procuring and processing their clinical samples, made available through planned surgeries, for research and development activities. The animal tests are conducted according to the Guidelines for using Experimental Animals and approved by Institutional Animal Ethics Committee (IAEC).

Sample processing and establishment of patient-derived cells:
A total of 41 ovarian cancer and 80 breast cancer patients’ biospecimens (i.e. blood-with anticoagulant, blood-without anticoagulant, urine, tumor biopsies, normal adjacent biopsies and adipose tissues) were collected from patients (Inclusion criteria: Age = 18) at Om Sai Onco Surgery Hospital, Maharashtra, India and Sushrut Hospital, Maharashtra, India between January 2019 to April 2022. All samples were transported from the hospital to research and development laboratories of Yashraj Biotechnology Ltd. at Maharashtra, India via validated cold chain logistics for downstream processing and R&D (sample details provided in TABLE 2).
a) Serum: Blood without anticoagulant was allowed to clot for 30 minutes and clot was removed by centrifuge at 1,000–2,000 x g for 10 minutes in a refrigerated centrifuge. Extracted serum was aliquoted and stored. Serum is suitably used for biomarker (genomics, proteomics) studies.
b) Urine: Urine sample was centrifuged in a refrigerated centrifuge (40 C) at 1500 g for 10 min to remove sediments. Urine supernatant and pellet were aliquoted and stored. Urine is a major repository of biometabolites, some proteins, and DNA. Urine is suitably used for biomarker studies.
c) Peripheral Blood Mononuclear Cells (PBMCs): Blood with anti-coagulant was diluted 1:1 (vol:vol) in DPBS and layered over Histopaque (sigma). PBMCs were isolated by Histopaque density gradient centrifugation method and cryopreserved (post viability determination by Trypan Blue dye exclusion method). PBMCs are suitably used for reprogramming for iPSC development, T-cell engineering, immune cells research, cell-line development, immunophenotyping assays, etc.
d) Tissue snap-freezing: Tumor and normal adjacent tissue biopsies (from isogenic donor) were cut into small pieces and tissues no thicker than 0.4 cm longitudinal section were aliquoted in vials and snap frozen in liquid nitrogen (for 2 minutes or less depending on the size of the tissue) and stored in -80deg freezer for long-term storage. Snap-frozen tissues are suitably used for downstream analysis of DNA, RNA and protein. 2 mm3 tissue biopsies were also cryopreserved in 10% DMSO and 90% FBS which is suitable for developing patient derived xenograft (PDX) models for in vivo pharmacology studies.
e) Formalin-Fixed Paraffin Embedded (FFPE) Tissue Block preparation: Tumor and normal adjacent tissue biopsies were cut into small pieces and tissues no thicker than 0.4 cm longitudinal section were fixed in 10% Neutral Buffered Formalin (NBF), followed by serial dehydration in ethanol, tissue clearing in xylene and embedding in paraffin. Formalin-Fixed Paraffin Embedded (FFPE) blocks were stored long-term for histopathology, biomarker testing.
f) Establishing a Collection of Patient-Derived Breast Cancer and Ovarian Cancer Organoids (Primary Cancer Organoids): At the time of each patient’s surgical debulking (i.e. “surgical waste”), Tumor and Normal-appearing Adjacent-to-Tumor (NAT) tissue biopsies were collected and mechanically dissected followed by enzymatic treatment. Minced tissues were incubated in enzymatic degradation solution containing Advanced DMEM: F12 (Gibco), collagenase I (Sigma), dispase II (Sigma), Rock Inhibitor- Y-27632 (Sigma), and DNase I (Stem Cell Technologies). The mixture was incubated in shaking water-bath at 370C, shaken at 180–200 rpm for 30 - 90 min. After incubation mixture was passed through 70µm cell strainer (Corning). Cell suspension was centrifuged at 300g for 10 minutes. Cells were counted and seeded in 96 well plate(s) at cell density of 1x104 cells per well in matrigel. Cells were overlaid with an optimized culture medium containing critical compounds and growth factors that allow the generation of breast and ovarian organoids. Breast organoid medium consists of Advanced DMEM: F12 (Gibco) supplemented with 1X Glutamax, 1X B27 supplement, 5% FBS, 100 ng/mL Noggin, 20 ng/mL EGF, 50 ng/ml cholera toxin, 0.5 µg/ml hydrocortisone and 10 µg/ml insulin. Ovarian organoid medium consists of MCDB 105 Medium (Sigma), Medium 199 Earle's Salts (Thermo Fisher Scientific), 1×GlutaMAX-I (Thermo Fisher Scientific), 1X B27 supplement minus vitamin A (Thermo Fisher Scientific), 100 ng/mL Noggin (PeproTech), 10 % FBS, 50 ng/mL EGF and 10 µg/ml insulin. Moreover, 10 µM Y-27632 was added to culture media for the first three days of culture. Medium was changed every 4 days and organoids were passaged every 1-4 weeks. These patient-derived organoids are suitably used for drug efficacy and safety studies.

Example 2. Development, detection, and isolation of induced pluripotent stem cells (iPSCs)

Generation of Human iPSCs by Sendai viral Reprogramming of PBMCs:
Generation, expansion, and characterization of human iPSCs from peripheral blood mononuclear cell (PBMC) of healthy volunteer, breast and ovarian cancer patients was performed, and reprogramming of Human PBMC by Sendai virus transduction was undertaken wherein PBMCs were reprogrammed using non-integrating Sendai viruses containing the reprogramming factors POU5F1 (OCT4), SOX2, KLF4 and MYC. PBMCs were cultured in StemPro-34 serum-free medium (Stem Cell Technologies) supplemented with 100 ng/mL SCF (Stem Cell Technologies), 100 ng/mL FLT-3 (Stem Cell Technologies), 20 ng/mL IL-3 (Stem Cell Technologies), 20 ng/mL IL-6 (Stem Cell Technologies) prior to reprogramming with Cytotune™-iPS 2.0 Sendai virus (ThermoFisher Scientific) expressing OCT4, SOX2, KLF4 and cMYC (Bhatt S. et. al, Cell Metab. 2015 Aug 4;22(2):239-52; Chitrangi S. and Bhatt S. et. al. Stem Cell Research, Volume 69, June 2023, 103062), in the presence of 4 µg/ml Polybrene (EMD Millipore). Transduced cells were plated on vitronectin (Stem Cell Technologies) coated plates. Reprogrammed clusters emerged on day 14 post transduction, that formed reprogrammed iPSC colonies by day 22 and mature iPSCs at passage 2 by day 45, as illustrated in Figure 1A and B. iPSC colonies were mechanically cut and further expanded in mTeSR™ (Stem Cell Technologies). Human iPSCs were characterized by expression of Oct4, Nanog, Sox2, SSEA4 using flowcytometry and immunocytochemistry and other downstream assays including but not limited to Karyotyping, STR analyses, Next-generation Sequencing to ascertain their quality and prototyping identity. The iPSC lines exhibited a normal karyotype, expressed pluripotency markers and differentiated into cells representative of the three embryonic germ layers. The critical qualities attributed for induced pluripotent stem cells along with detection methods and acceptance criteria are provided in the TABLE 3 below.

TABLE 3. Attributes for detection and isolation of induced pluripotent stem cells (iPSCs)

Product Source of Isolation Quality parameters evaluated Detection methods Acceptance criteria Inventor data
Human
iPSCs • Control healthy volunteer
• Breast cancer patients
• Ovary cancer patients Morphology Microscopy • Tightly packed colony
• Well defined colony border • Tightly packed colony
• Well defined colony border
Pluripotency Immuno- cytochemistry:
OCT4, SSEA4, NANOG, TRA-160,
Alkaline phosphatase Positive Positive
Flow cytome try: TRA 181, SSEA4 = 70% ~ 80-90%
Genetic stability Karyotyping Normal (diploid) Normal (diploid)
=20
metaphase
Endotoxin Limulus Am ebocyte Lysate (LAL)
assay. Negative 0.01 EU/mL =0.001
EU/mL
Mycoplasma PCR
Method Negative Negative
Post-thaw Plating Thawing 20+ colonies
/ vial ~ 25-30
Colonies
/vial
Cell Count & Viability Typan exclusion
staining viability > 60% ~ 70-80 %
Differentiation potential Trilineage Differentiation Detection of minimum one marker per germ layer Detection of one marker per germ layer Ectoderm: N-
cadherin- positive Mesoderm: BMP 4-
positive Endoderm: Gata 4- positive

These human iPSCs are found suitable for directed differentiation, disease modelling, CRISPR-Cas9 mediated gene editing, developmental biology research, drug discovery applications, organoid development and precision drug screening, etc.

Example 3. Pluripotency and genomic stability testing of iPSCs

Karyotype analysis:
Karyotypes were analyzed by outsource partner (MedGenome Labs Private Ltd.). No differences were detected between the original PBMC sample and its corresponding iPSC line, suggesting that no chromosomal aberrations are introduced and normal karyotype was retained post reprogramming of somatic cells to generate iPSCs.

Trilineage Differentiation:
iPSCs are differentiated into endoderm, ectoderm and mesoderm as monolayer cultures using STEMdiff™ Trilineage Differentiation Kit (Stem Cell Technologies, Vancouver, Canada) and analyzed by IF after 5?days (mesoderm and endoderm) and 7 days (ectoderm). Inventor data (Figure 8 and 11) shows iPSCs differentiated into three germ layers and readily expressed the markers for ectoderm (N-cadherin), endoderm (GATA4) and mesoderm (BMP4). DAPI shows the nuclei stain in blue.

Teratoma (in vivo differentiation) Assay:
Teratoma assay was performed as per Bhatt et. al. (2015). 8-12 weeks’ old animals were fed regular chow diet and kept in 12h/12h light and dark cycle, as per IAEC and IACUC guidelines. Briefly, approximately 2 × 106 cells harvested as cell clumps, in a 5:1 mixture with Matrigel (BD Biosciences) were injected intramuscularly in NOD SCID male mice 12-18 weeks old. Animals were monitored for cellular engraftment and in vivo growth and differentiation over the next 4–8 weeks while the teratomas started to emerge/grow, and the size measurements were recorded every week using Vernier calipers. Animals were procured from Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Maharashtra, India and sacrificed using CO2 asphyxiation. (Figure 8 and 11)

Next-generation (Genome) Sequencing Analyses:
Next-generation sequencing analyses was performed for comparison of genomic profiles of the source patient (tumor biopsy) and the derived isogenic iPSC from the same donor. These studies and downstream analyses were used to analyze and correlate the genomic variants/ germline mutations conserved between the donor tissue and iPSCs with the specific response of the donor’s primary cancer organoid and neurotoxicity platforms to the respective treatment exposure.

Alignment summary
The overall alignment is around 99.99 % and the average passed alignment (percent of reads aligning to hg19) is around 87.89 percent for all the samples.

Coverage analysis
The average coverage of the samples on the panel is around 99.05 %

Analysis Overview
The following bioinformatics steps are performed for the analysis:

SCHEMATIC REPRESENTATION OF BIOINFORMATICS ANALYSIS PIPELINE

The workflow contains major components of the bioinformatics analysis pipeline and the tools used in each component.

Adapter Trimming
The Adapter trimming phase involves processing of raw FASTQ files from the upstream analysis to remove adapters and generating QC metrics on raw and trimmed read data. The open-source fastq- mcf command line tool is being used for detecting and removing the sequencing adapters, primers, poor quality nucleotides at the ends of reads.

Alignment
The Alignment phase involves aligning of trimmed FASTQ reads to a human genome reference sequence (hg19/GRCh37) and obtaining variants from the alignments. Inventorsfollow GATK good- practice workflow steps for secondary analysis. Alignment of adapter trimmed FASTQ reads is performed using Sention’s version of BWA. The adapter trimmed FASTQ files are used as input for aligning with human reference genome (hg19). The reference genome can be accessed at:
http://hgdownload.soe.ucsc.edu/goldenPath/hg19/bigZips/chromFa.tar.gz. Sorting and conversion of the alignment SAM file to binary compressed BAM file format is done using samtools.

PCR Duplicates Removal
The BAM files from the alignment step is further sorted in coordinate order to perform PCR duplicates removal using Sentieon’s version of Picard tools and chromosome wise alignment metrics are generated.

Indel Realignment
Sentieon’s version of Genome Analysis Toolkit (GATK – IndelRealigner) is used to perform local realignment in regions containing potential indels.

Base Quality Score Recalibration
The raw Phred-scaled quality scores do not always accurately reflect the true base-calling error rate. To recalibrate the quality scores of all the reads in the BAM file, Inventors use Sentieon’s version of GATK Toolkit - BaseRecalibrator. During this analysis step, the set of mapped reads at a locus is locally re-aligned to the primary human reference sequence.

Variant Calling
The variant calling is a process of obtaining variants such as indels and SNPs by scanning through the aligned reads to reference sequence. The results are generated in VCF format using Sentieon’s GATK Haplotypecaller and UnfiedGenotyper. At a minimum, these files record information and annotations about the sequence variants identified, such as their type (e.g., SNP, Indel). Both haplotype caller and genotype caller variants files are merged into a single variant VCF file. Both the callers are used to avoid missing of any variant. If the variant is common in both the callers, then the variant is picked from Haplotype Caller file. These variants are further processed for normalization using bcftools. Real time genomics tools (rtg vcfstats) was used to calculate the TS/Tv ratio from the VCF files.

Variant Annotation
The in-house variant annotation pipeline (VariMAT - Variation and Mutation Annotation Toolkit) is being used for variant annotation. It integrates multiple clinical grade databases, variant class prediction and variants pathogenicity prediction tools for annotating the variants and mutation which rely on VEP. VariMAT contains more than 70 entities for every transcript to annotate in depth to understand their cause/effect on associated disease or phenotype. Some of the annotated information available in VariMAT are the population frequency, computational pathogenicity prediction, variant type and predicted impact of the variant on the protein (missense, loss of function, etc).

TABLE 4. Versions of Software used for Sequencing.

DNA Extraction
DNA was extracted from the Cell pellet and Frozen tissue by using QIAmp DNA Mini kit (Cat No# 51306).

DNA Sample QC
The Extracted DNA samples were quantified using Qubit DNA HS Assay (Invitrogen, Cat# Q32854). DNA purity was checked using QIAxpert and DNA integrity was checked on 1% Agarose gel. After confirmation, QC passed samples were taken for the library preparation and sequencing.

Library Prep Protocol for DNA

QIAseq® Targeted DNA prep for Illumina, (Cat# 333525) was used to prepare libraries for Comprehensive tumor panel. First, 100ng Genomic DNA samples were fragmented, end repaired and A tailed within a single, controlled multienzyme reaction. The prepared DNA fragments were then ligated at their 5' ends with a sequencing platform-specific adapter containing UMIs and sample index (Figure 12). Adapter ligated products were then purified and enriched with Qiaseq TMB panel probes using the following thermal conditions: Initial denaturation 95°C for 13mins, 98°C for 2mins, 6 cycles of 98°C for 15sec, 65°C for 30mins, Final extension of 72°C for 5min, 4°C for 5min. Target enriched products were then purified and processed for Universal PCR using the following thermal conditions: Initial denaturation 95°C for 13mins, 98°C for 2mins, 22 cycles of 98°C for 15sec, 60°C for 2mins, Final extension of 72°C for 5min, 4°C for 5min. PCR products were then purified and the final libraries were checked for fragment size distribution using High Sensitivity NGS Fragment Analysis Kit 1-6000bp (Cat #DNF4741000).

RNA Extraction
RNA was extracted from Cell pellet samples by using RNeasy mini kit (Cat No# 74104) and from Snap Frozen tissues by using Trizol method.

Sample QC
The RNA samples were quantified using Qubit RNA BR Assay (Invitrogen, Cat# Q10211). RNA purity was checked using QIAxpert and RNA integrity was checked using RNA Screen Tapes (Agilent, Cat# 5067-5576). After confirmation, QC passed samples were taken for the library preparation and sequencing.

Library Prep Protocol for STMP RNA
RNA was fragmented using divalent cations under elevated temperature. Next, the cDNA was synthesized using Reverse transcriptase and random hexamers in a first strand synthesis reaction. Subsequently, the cDNA was converted to double stranded cDNA in a DNA polymerase based reaction. Converted cDNA was enzymatically fragmented to ~250bp, end repaired, A-tailed and adapter ligated in a series of enzymatic steps. The adapter-ligated products were then purified by Agencourt®AMPure®XP beads (Beckman Coulter, Cat# A63882) and PCR enriched using the following thermal conditions: initial denaturation 98°C for 45sec, 12 cycles of 98°C for 15sec, 60°C for 30sec, 72°C for 30sec, final extension of 72°C for 1min. The prepared whole genome libraries were then subjected to Twist Solid Tumor panel (STMP_RNA) capture using Twist kit (Twistbio, Cat# 102033). The targeted regions were captured by hybridizing the library fragments to the biotinylated probes which were then captured on streptavidin bead, isolated by magnetic pulldown, and enriched using following PCR conditions: initial denaturation 98°C for 45sec, 12 cycles of 98°C for 15sec, 60°C for 30sec, 72°C for 30sec, final extension of 72°C for 1min. The final captured libraries were checked for fragment size distribution on Tape Station using D1000 DNA Screen Tapes (Agilent, Cat# 5067-5582) / High Sensitivity NGS Fragment Analysis Kit 1-6000bp (Cat #DNF4741000).

Sequencing Protocol
Prepared libraries were quantified using Qubit HS Assay (Invitrogen, Cat# Q32854). The obtained libraries were pooled and diluted to final optimal loading concentration. The pooled libraries were then loaded on to Illumina Novaseq 6000 to generate 150bp Paired end reads.

Example 4. Differentiation of iPSCs into Neural Progenitor Cells (NPCs)

In vitro Neural Progenitor Cells (NPCs) differentiation of human iPSCs:
When human iPSCs cultured in mTeSR™1 media reached a confluency level of approximately 80%, they were passaged with StemPro® Accutase® Cell Dissociation Reagent (Thermo Fisher Scientific, Waltham, MA, USA) and resuspended as single cells in mTeSR™1 medium. Approximately 3 × 105 cells/cm2 were seeded in six-well plates pre-coated with laminin and polyornithine diluted in DMEM/F12 (Thermo Fisher Scientific) for at least 1 h at 37 °C in a CO2 incubator. For initial differentiation, DMEM/F12 medium supplemented with 0.5% N2 supplement (GIBCO), 1 mM l-glutamine, 1% nonessential amino acids, noggin (500 ng/ml), SB431542 (10 m?) and laminin (1 µg/ml) was used. For generation of neural precursor cells (NPCs), media was changed to neural induction medium (d7–14), containing DMEM/F12, 1% N2 supplement, 2% B27 supplement (Thermo Fisher Scientific), 1?µg/ml laminin, 20?ng/?ml basic fibroblast growth factor (stem cell technologies, USA). Once the cells are confluent (~80%), they were passaged with StemPro® Accutase® Cell Dissociation Reagent (Thermo Fisher Scientific, Waltham, MA, USA) and reseeded on six-well plates pre-coated with laminin and polyornithine diluted in DMEM/F12 (Thermo Fisher Scientific). Further NPCs were expanded in Neural progenitor expansion media containing DMEM/F12, 1% N2 supplement, 2% B27 supplement (Thermo Fisher Scientific), 1?µg/?ml laminin, 20?ng/ml basic fibroblast growth factor, 20 ng/ml epidermal Growth Factor (stem cell technologies, USA).

On Day15, cells were considered pre-NPCs (passage 1) and able to be passaged (1:4) and cryopreserved when confluent. From passage 5, cells were considered NPCs and further used for neural differentiation studies. These Neural Progenitor Cells were characterized by expression of Pax6, N-Cad and Nestin using flowcytometry and immunocytochemistry and utilized further for differentiation into mature neural derivatives (e.g. Midbrain, Forebrain Neurons, Astrocytes etc.), gene expression analysis, subjected to drug screening, growth and metabolic analysis, and other downstream assays.

In vitro Forebrain Motor Neuron differentiation of human NPCs:
NPCs were differentiated towards forebrain motor neurons by seeding dissociated single cells at 80 - 125,000 cells/cm2 density on polyornithine-laminin coated plates in Advanced DMEM/F-12, 2% B27 supplement, 200 µM Ascorbic acid (Sigma), 0.65?µM Purmorphamine (Stem Cell Technologies) and 200 µM Dibutyryl cyclic-AMP (Sigma)) with 20 µM DAPT (?-secretase inhibitor; Sigma) for 5-6 days. On day 7, cells were passaged with accutase (Stem cell technologies) and seeded at a density of 1.5 x 104 - 3 x 104 cells/cm2 in Advanced DMEM/F-12, 2% B27 supplement, 200 µM Ascorbic acid (Sigma), 0.65?µM Purmorphamine (Stem Cell Technologies) and 200 µM Dibutyryl cyclic-AMP (Sigma), DAPT was removed for next 5-6 days. The medium was changed every 3 days. These Forebrain motor neurons were characterized for the expression of Tuj1 using flowcytometry and immunocytochemistry and were utilized further for gene expression analysis, studying neurogenesis, neurodegenerative diseases, neuroinflammation and CNS function, subjected to neurotoxicity tests, drug screening, disease modeling, growth and metabolic analysis and other downstream assays. Neurite outgrowth assay was performed to determine neurotoxicity. This assay offers a practical in vitro method for evaluating substances that inhibit or promote neurons' normal neurite development. Inventors tested neurotoxic chemotherapeutic drug on iPSC-derived neurons- control (healthy volunteer), breast cancer and ovarian cancer (Filous and Silver, 2016; Spijkers et al, 2021, Linvi et al, 2018) using ImageXpress® Nano Automated Imaging System (Molecular Devices).

In vitro Midbrain Dopaminergic Neuron differentiation of human NPCs:
NPCs were differentiated to midbrain dopaminergic neurons by seeding dissociated single cells at 80 - 125,000 cells/cm2 density on polyornithine-laminin coated plates in DMEM/F12 medium supplemented with N2/B27/Glutamax (Invitrogen) containing retinoic acid (RA), ascorbic acid (AA), Sonic hedgehog (SHH), and FGF8 for 5-6 days. When cells reached 80 - 90% confluence, they were passaged with accutase (Stem cell technologies) and seeded at a density of 4 x 104 - 6 x 104 cells/cm2 in DMEM/F12 medium supplemented with N2/B27/Glutamax (Invitrogen) containing retinoic acid (RA), ascorbic acid (AA), and FGF8 for next 5-6 days. These Midbrain Dopaminergic Neurons were characterized for the expression of Tuj1 and Tyrosine Hydroxylase (TH) using flowcytometry and immunocytochemistry and further utilized for gene expression analysis, studying neurogenesis, neurodegenerative diseases, neuroinflammation and CNS function, subjected to neurotoxicity tests, drug screening, disease modeling, growth and metabolic analysis, and other downstream assays.

In vitro Astrocyte differentiation of human NPCs:
NPCs were differentiated to astrocytes by seeding dissociated single cells at 4x104 - 6x104 cells/cm2 density on matrigel-coated plates in DMEM/F12 medium supplemented with N2 supplement/B27/Glutamax (Invitrogen) containing BDNF (20ng/ml, Peprotech), GDNF (10ng/ml, PeproTech), Dibutyryl cyclic-AMP (250?g/ml, Sigma), and L-ascorbic acid (200nM Sigma); Ara-C (2?g/l, Sigma), EGF (10?ng/ml, Sigma), LIF (10?ng/ml, Sigma), and FGF2 (10?ng/ml, Sigma) for 5-6 days. When cells reached 80 - 90% confluence, they were passaged with accutase (Stem cell technologies) and seeded at a density of 4 x 104 - 6 x 104 cells/cm2 in DMEM/F12 medium supplemented with N2 supplement/B27/Glutamax (Invitrogen) containing BDNF (20ng/ml, Peprotech), GDNF (10ng/ml, PeproTech), Dibutyryl cyclic-AMP (250?g/ml, Sigma), and L-ascorbic acid (200nM Sigma); Ara-C (2?g/l, Sigma), EGF (10?ng/ml, Sigma), LIF (10?ng/ml, Sigma), and FGF2 (10?ng/ml, Sigma) + CNTF (20 ng/mL) for next 5-6 days. From D29 to D42, medium was changed every other day and cells were passaged once confluent. These Astrocytes were characterized by expression of Tuj1 and GFAP or S100ß using flowcytometry and immunocytochemistry and utilized further for gene expression analysis, studying neurogenesis, neurodegenerative diseases, neuroinflammation and CNS function, subjected to neurotoxicity tests, drug screening, disease modelling, growth and metabolic analysis, and other downstream assays.

TABLE 5.

Antibodies
(For Characterization of Differentiated iPSC-derivatives) Make Catalog Number
Tuj1 Cell Signaling 5568S
Nestin Invitrogen MA1-110
Sox1 Thermofisher Scientific MA5-32447
GFAP Cell Signaling 3670T
TH Abcam Ab112
Olig-2 Abcam Ab109186
MAP-2 Abcam Ab32454
GAPDH Merck G9545

Example 5. Genetic Profiling of Neural Progenitor Cells (NPCs)

DNA and RNA extraction for RT-PCR:
gDNA and RNA was extracted from cells and organoids using the QIAamp® DNA Mini Kit (Qiagen, Venlo, Netherlands) and RNeasy Kit (Qiagen, Hilden, Germany) respectively as per manufacturer’s instruction. cDNA was synthesized using iScript cDNA synthesis kit (Biorad, California, United States). PCR was performed by using PCR Master Mix (2X) (ThermoFisher Scientific, Massachusetts, United States). The primer sequences used in PCR are provided (TABLE 6).

Cell viability assays. Cells were seeded at a density of 2500–5000 per well in 96-well clear bottom microplates. Cells were incubated overnight and treated with drugs for 3 days. Cell viability was analyzed using CellTiter-Glo (Promega, Wisconsin, USA) in SpectraMax ID5 Multimode Plate reader (Molecular devices, USA). IC50 values were calculated using GraphPad Prism version 5. Drugs used in the assays were purchased from Selleckchem (Texas, USA).

Cell proliferation assay: The growth rate of organoids was measured. Briefly, the organoids were dissociated into single cells and 100,000 cells as initial setting were seeded into a 48-well plate, in triplicate. Cells were encapsulated in the Matrigel were cultured in respective culture media for 8 days, then newly grown organoids were digested into single cells again, and the number of cells was counted with a haemocytometer and trypan blue exclusion. The growth rate was calculated from the mean of three replicates using the following equation:

where y(t) is the number of cells at the final time point, y0 is the number of cells at the initial time point, and t is the time.

RNA Isolation, RT-PCR Analysis of iPSCs and Derivatives:
The isolation of RNA and RT-PCR were performed as per manufacturer’s instructions [RNeasy Kit, Qiagen, Hilden, Germany; iScript cDNA synthesis kit, Biorad, California, United States; PCR Master Mix (2X), Thermo Fisher Scientific, Massachusetts, United States]. The primer sequences used in RT-PCR are given in TABLE 6.

TABLE 6. Primer Sequences used in RT-PCR
GENE Forward Primer (5’-3’)
Reverse Primer (5’-3’)
Product size (bp)
Nestin F: 5'-TCCAGAAACTCAAGCACCA-3'
R: 5'-AAATTCTCCAGGTTCCATGC-3' 183
PAX6 F-5’GATAACATACCAAGCGTGTCATCAATA-3’
R-5’TGCGCCCATCTGTTGCT-3’ 75
N-CAD F 5’- TCCTGATATATGCCCAAGACAA-3’
R 5’-TGACCCAGTCTCTCTTCTGC-3’ 183

GAD67/GAD1 F 5’- AAGCTACACAAGGTGGCTCC-3’
R 5’- CATCCGGAAGAAGTTGGCCT-3’ 105
MAP2 F 5’- GCGCCAATGGATTCCCATAC-3’
R 5’- CAGACACCTCCTCTGCTGTT-3’ 114
Olig2 F 5’- GGTGCGCAAGCTTTCCAAGA-3’
R 5’- GATCTCGCTCACCAGTCGCT-3’ 103
PSD95/DLG4 F 5’-GAGAGTCAGAAATACCGCTACC-3’
R 5’-CCCGTTCACCTGCAACTCAT-3’ 147
TUBB3 F 5’-ATCTTTGGTCAGAGTGGGGC-3’
R 5’-CTGCAGGCAGTCGCAGTTTT-3’ 123
GFAP F: 5'-GCAGAGATGATGGAGCTCAATGACC-3'
R: 5'-GTTTCATCCTGGAGCTTCTGCCTCA-3' 266
Engrailed1 (En1) F: 5'-CTAGCCAAACCGCTTACGAC-3'
R: 5'-GCAGAACAGACAGACCGACA-3' 358
18s rRNA F 5’-GGAGAGGGAGCCTGAGAAAC-3’
R 5’-CCTCCAATGGATCCTCGTTA-3’ 171

Example 6. Preparation of NPCs for neural toxicity of chemotherapeutic agents in 2D and 3D models

Immunofluorescence (IF):
iPSCs and derivatives were cultured on glass chamber slides (Thermo Scientific™ Nunc™ Lab-Tek™ II Chamber Slide™) for IF analysis. Cells were fixed with 4% Paraformaldehyde for 10?min at room temperature, permeabilized in 0.2%Triton™-X-100 (Sigma) for 10?min, blocked in 10% Bovine Serum Albumin (Life Technologies Inc.) for 60?min. Cells were then incubated with primary antibodies overnight (TABLE 7), followed by secondary antibodies for 2?h at room temperature (TABLE 8). Subsequently, nuclei were stained with DAPI (Life Technologies Inc.) and images were captured with Evos FL Microscope (ThermoFisher).

TABLE 7. Details of Primary Antibodies for characterizing iPSCs and Primary Derivatives

Sr. No. Name of antibody Host Make Catalog No. Dilution
For Characterizing iPSCs
1 Anti-Alkaline Phosphatase Mouse

R & D system

SC008 1:100
2 Anti-Nanog Goat 1:100
3 Anti-Oct-4 Goat 1:100
4 Anti-SSEA-1 Mouse 1:100
5 Anti-SSEA-4 Mouse 1:100
6 N-Cadherin Mouse Sigma C3865 1:100
7 GATA-4 Rabbit Sigma HPA073899 1:100
8 BMP4 Rabbit Atlas Antibodies HPA066235 1:100
9 Tuj1 Rabbit Cell Signaling 5568T 1:100
10 GFAP Rabbit Cell Signaling 3670T 1:100
11 Tyrosine hydroxylase Mouse Abcam Ab112
1:100

TABLE 8. Details of Secondary Antibodies for characterizing iPSCs and Primary Derivatives

Sr.
No. Secondary Antibodies Host Make Catalog No. Dilution
1 Goat Anti-Mouse IgG H&L (Alexa Fluor 594) Pre- adsorbed Goat Abcam ab150120 1:200
2 Goat Anti-Rabbit IgG H&L (Alexa Fluor 488) Pre- adsorbed Goat Abcam ab150081 1:200

Immunohistochemistry (IHC) of Tissues/ Organoids:
FFPE blocks were prepared, and sections were cut to a thickness of 3 µm. Deparaffinized, rehydrated, and antigen retrieved with citrate buffer (pH 6.0). The slides were blocked in 0.1% bovine serum albumin (BSA), 0.2% Triton X-100, and 0.05% Tween 20 in PBS for 1 h at room temperature (RT). The slides were then incubated overnight with primary antibodies against targets of interest (TABLE 7) in blocking buffer at 40C. After washing, slides were incubated with secondary antibody (TABLE 8) for 45 min at 370 C. Nuclei were counterstained with DAPI (Sigma). Images were acquired on the ImageXpress® Nano Automated Imaging System (Molecular devices, USA).

Flow cytometry:
Harvested iPSCs were incubated with antibodies for 30?min on ice. Samples are analyzed using BD accuri FACS analyzer (BD Bioscience). Samples were prepared for flow cytometery analysis and 10000 events were acquired using BD Accuri™ C6 Plus Flow Cytometer, (BD Biosciences, California, USA) and analyzed with FlowJo (FlowJo, RRID: SCR_008520) software.

Mycoplasma and Endotoxin Detection:
Absence of mycoplasma contamination was confirmed by PCR by Universal Mycoplasma Detection Kit (ATCC, Virginia, United States). Bioburden testing performed routinely by plating spent media on Nutrient Agar Plate- for bacterial count (Merck) and on Sabouraud Agar Plate- for fungal count (Merck). Endotoxin was detected by Pierce™ LAL Chromogenic Endotoxin Quantitation Kit (Thermo Fisher Scientific, Massachusetts, United States). All developed cell-based platforms met the quality standards of sterility and were found negative for mycoplasma and other microbial contamination.

Neural Progenitor Cells (NPCs) Spheroid Formation:
Healthy Individual-Neural Progenitor Cells (H-NPCs), Breast Cancer Patient-Neural Progenitor Cells (BC-NPCs) and Ovarian Cancer Patient -Neural Progenitor Cells (OC-NPCs) cultured at passage 6 on poly-ornithine (Sigma Aldrich, Cat: A-004-M)/ laminin (Sigma Aldrich, Cat: L2020)-coated plates were allowed to reach 70-80% confluency. NPCs were treated with Accutase (Stem Cell Technologies, Cat: 07920) for 3-5 mins till the cells were loosely attached and lifted by repeated pipetting. The cell suspension was neutralized by adding equal volume of Dulbecco's Modified Eagle's Medium/Nutrient Ham's Mixture F-12 (DMEM/F-12) with 15 mM HEPES buffer (Stem Cell Technologies, Cat: 36254) and collected in a centrifuge tube. The cells were pelleted down by centrifuging at 300g for 5 mins and resuspended in Neural Progenitor Cells medium (Stem Cell Technologies, Cat: 05883). Cells were counted in a hemocytometer and further diluted with NPC medium to seed 1200 cells and 200 µL medium per well in a 96-well plate. The plate was centrifuged at 300 g for 5 mins and transferred to a 37oC, 5% CO2 incubator. Post three days after seeding, 100 µL of the medium was carefully exchanged from each spheroid well every 2-3 days during the culture period.
Neural Progenitor Cells (NPCs) were analyzed for their expression of the neural progenitor markers, Nestin and Pax6 via flow cytometry analyses. The images of cytometry analysis are shown in Figure 17, 19 and 20. iPSCs-derived forebrain motor neurons are analyzed for their expression of the neural markers Tuj1 (ß tubulin) via flow cytometry analyses. Expression of neural cell markers Tuj1 (ß tubulin) in iPSCs-derived forebrain motor neurons is illustrated in Figure 24, 25 and 26. It is noted that long neurites were visible with nuclei stained with DAPI.
iPSCs-derived astrocytes were also analyzed for their expression of the neural markers Tuj1 (ß tubulin) and astrocytes marker GFAP via flow cytometry analyses, whose images are captured and shown in Figure 21, 22 and 23. Figure 27 to 32 show expression of neural cell marker Tuj1 (ß tubulin) and midbrain dopaminergic neural marker Tyrosine Hydroxylase (TH) in iPSCs-derived midbrain dopaminergic neurons.

NPC Spheroid Characterization:
NPC spheroids were observed by naked eyes and under the microscope during each medium exchange for growth and morphological changes in the spheroid size and shape. For characterization, healthy volunteer-derived NPCs (H-NPCs), breast cancer patient-derived NPCs (BC-NPCs) and ovarian cancer-derived NPCs (OC-NPCs) spheroids were collected at Day 3, Day 7, Day 14 and Day 21 post-cell seeding, for gene expression analysis by PCR and biomarker analysis by western blotting and/or immunostaining, FACS. The spheroids were transferred to a µ-centrifuge tube and washed with 1X-PBS. The PBS was aspirated and the spheroids were frozen at -80oC. For RNA extraction, the samples were crushed with a clean pestle and further processed using RNA extraction kit. RNA concentration was measured using a nanodrop and converted to cDNA using a cDNA synthesis kit. cDNA was further used to run PCR for neural progenitor markers Pax6 and NESTIN, mature neuron marker Tuj1 and Engrailed-1 and astrocyte marker GFAP. For Western blotting, the frozen spheroids were crushed and lysed with RIPA lysis buffer. DNA concentration was measured using Picogreen assay and consistent amount of DNA was used to load samples (normalization) for western blotting. For immunostaining, the spheroids were fixed in 4% paraformaldehyde overnight at 4oC and replaced with PBS. The spheroids were either stained as whole spheroids or sectioned after embedding in paraffin blocks with appropriate primary and fluorescent secondary antibodies (as listed in TABLE 9) and imaged at suitable magnification in Image Xpress Nano (Molecular Devices).

TABLE 9. Details of Primary and Secondary Antibodies for characterizing iPSC Derivatives

FACs Antibodies
Primary Antibodies Dilution CAT No. MAKE Host
Nestin 1:100 60091 Stem cell technology Mouse
Pax 6 1:50 ab 5790 ABCAM Rabbit
Tuj 1 1:200 5568S Cell signalling Rabbit
GFAP 1:200 3670T Cell signalling Mouse
Secondary Antibodies
Rabbit secondary 1:500 ab150081 ABCAM
Mouse secondary 1:500 ab150120 ABCAM

ICC Antibodies
Primary Antibodies Dilution CAT No. MAKE Host
Ki67 250 MA5/14520 Thermo Fisher scientific Rabbit
MAP2 250 ab32454 ABCAM Rabbit
PAX6 50 ab 5790 ABCAM Rabbit
GFAP 200 3670T Cell signalling Mouse
Secondary Antibodies
Rabbit secondary 500 ab150081 ABCAM
Mouse secondary 500 ab150120 ABCAM

Figure 36 illustrates (A) Representative phase contrast images of NPC spheroids at Day 7 and day 14; and (B) Phase contrast images of spheroids fabricated from H-NPCs, BC-NPCs and OC- NPCs imaged and measured for spheroid size. The sizes were further normalized w.r.t Day 7 healthy volunteer-derived NPC spheroid. Data represents mean ± SEM for n = 3 technical replicates wherein ‘*’ represents significant difference for p < 0.05; ‘**’ represents significant difference for p < 0.01; and ‘***’ represents significant difference for p < 0.001 and ‘****’ represents significant difference for p < 0.0001.

H-NPCs, BC-NPCs and OC-NPCs are seeded at the same starting cell number of 1200 cells per well of a 96-well plate for spheroid formation. However, significant differences were observed in the sizes of spheroids measured after 7 and 14 days of culture (refer Figure 15). While spheroids from H-NPCs and OC-NPCs demonstrated a fold increase from Day 7 to Day 14, BC-NPCs showed a fold stark increase that was statistically significant. Furthermore, significant differences are observed for size change between spheroids at Day 7 and Day 14 between donor groups. Overall, the size of spheroids at Day 7 and Day 14 were in the order: Breast cancer patient > Healthy volunteer > Ovarian cancer patient.

Gene Expression:
Figure 39 illustrates relative gene expression data for neural progenitor markers Pax6 (A) and Nestin (B), mature neuron marker Tuj1 (C) and Engrailed-1(D) and Astrocyte Marker GFAP (E) for 3D NPC spheroids collected after 7, 14 and 21 days in culture. 18s RNA was used as the housekeeping gene. The expression levels were further normalized w.r.t Day 7 samples for each group i.e., H-NPC, BC-NPC and OC-NPC samples. Data represents mean ± SEM for n = 1-3 wherein ‘*’ represents significant difference for p < 0.05 and ‘**’ represents significant difference for p < 0.01.

NPCs are typically characterized by neural progenitor markers Nestin and Pax6 in 2D monolayer culture. In the present invention, scaffold-free long-term 3D culture of NPCs in neural progenitor medium is reported. In order to track the effect of spheroid culture on NPC phenotype, it is decided to measure the relative expression levels of Nestin and/or Pax6. Compared to Day 7, H-NPC and BC-NPC spheroids shows an increasing trend while gene expression shows decrease for OC-NPCs albeit; no significant differences are observed between Day 7, 14 and 21 levels. Nestin and Pax6 gene levels indicate that 3D scaffold-free culture appeared to maintain the neural progenitor phenotype at the mRNA and protein expression levels in all three donor groups (Figure 37, 38, 39 and 42). The findings could also be validated at the protein level by monitoring expression of key neural factors (Pax6, MAP2) and proliferation markers (ki67) in Breast and Ovarian Cancer-patient derived, iPSC-derived 3D neural derivatives, exposed to Paclitaxel (Taxol) and 5FU. With 7-day exposure of drugs, Taxol demonstrated shrinking at 0.1nM concentration while 5FU was much more tolerated and relatively less cytotoxic, if at all, even at 100nM concentration (Figure 60 to 65).

NPCs are known to differentiate in 3D culture in the presence of growth factors that drive signaling pathways towards specific lineages. However, the effects of 3D culture alone on the differentiation of NPCs towards mature neural lineages like neurons and astrocytes. Towards this goal, the relative levels of Tuj1, a mature neuron marker and Engrailed-1, dopaminergic neuron marker and astrocyte marker GFAP (refer Figure 16C, 16D and 16E). While Tuj1 and Engrailed-1 showed similar expression profiles as the neural progenitor markers, no significant differences were observed in the three groups from Day 7 to Day 21. In contrast, glial fibrillary acidic protein (GFAP), a mature astrocyte marker, was found to be significantly upregulated at Day 14 and Day 21 relative to Day 7 levels.

Neurite Outgrowth:
Figure 43, 44, 45 shows (A) Representative immunostaining images for 3D NPC spheroids seeded on Matrigel and cultured for 72 hours in NPC medium and fixed with 4% PFA. The fixed spheroids were stained for Beta-III-tubulin (green) and nucleus (blue). Scale Bar – 500 µm; (B) Representative actual image and output image from neurite-J plugin in ImageJ software and representative image of neurite outgrowth from a NPC spheroid seeded on a Matrigel-coated surface; and (C) Mean neurite length and number of neurite intersections for NPC spheroids from healthy volunteer and ovarian cancer patient analyzed in ImageJ using Neurite-J plugin. Data represents mean ± SEM for n = 1-3 technical replicates. ‘***’ significant difference for p < 0.001.

It is found that matrigel-coated surface sufficiently supports the rapid and strong attachment of free-floating Day 7, Day 14 and Day 21 H-NPC and OC-NPC spheroids. BC-NPC spheroids appeared to have attached but didn’t show neurite extensions as typically observed in 2D monolayer culture (Figure 43). Surprisingly, Taxol treatment didn’t appear to show significant differences in mean neurite length and number of neurite extensions for H- NPC and OC-NPC spheroids at all three time points. Furthermore, although the number of neurites did not differ significantly, the mean neurite length appeared to be higher in case of H-NPC spheroids compared to O-NPCs (Figure 43). This is contradictory to the results obtained by Park SH et. al. 2021 who observed an increase in neurite growth when exposed to cancer- derived conditioned medium. However, this could also be attributed to increased astrocyte differentiation in the cancer-derived NPCs that has been shown to inhibit neurite outgrowth.

Example 7. Neural toxicity testing and response of chemotherapeutic agents

For drug toxicity, H-NPCs, BC-NPCs and OC-NPCs spheroids were added with different concentration of drugs paclitaxel and 5-flurouracil, doxorubicin and amiodarone in 0.1% DMSO as the vehicle. Spheroids were cultured in NPC medium and 0.1% DMSO as medium control and vehicle control, respectively. For measuring acute toxicity, viability was assessed at 72 hours post-drug addition, using CTG 3D assay. NPCs seeded with initial cell seeding density of 1200 cells per well were also tested for acute drug toxicity. For assessing systemic toxicity, NPC spheroids were added with fresh drug dosage every 2-3 days during medium exchange. The spheroids were analyzed 14 days after administering first dosage with CTG 3D assay (Promega). Figure 40 shows drug response curve for Taxol (A) and 5-Fluorouracil (B) prepared in GraphPad Prism for acute toxicity measured in 2D NPC monolayer and NPC spheroids and systemic toxicity measured in NPC spheroids only. Data points represent mean ± stdev for n = 1-6. Figure 40-A and 40-B shows the drug response curve for Taxol (paclitaxel) and 5-Fluorouracil. The drug response curve for paclitaxel and 5-fluorouracil appeared to show distinct differences between the IC50 values for 2D and 3D culture in acute exposure for all donor groups. Furthermore, the IC50 values also differed between acute and systemic exposure. Drug response curves for Amiodarone (not shown) resulted in higher IC50 values thus indicating mild toxicity, which was on expected lines and aligned to clinically known phenomenon. IC50 values calculated using these curves are tabulated in TABLE 10 as shown below.

TABLE 10.

The four drugs as per their toxicity in ascending order have been ranked based on the said IC50 values in different culture conditions for H-NPCs, BC-NPCs and OC-NPCs in TABLE 11. It is observed that doxorubicin ranked the highest as the IC50 values in all the systems was lower than the lowest concentration tested.

TABLE 11.
Ranking of compounds based on IC50 values
Healthy Volunteer Breast Cancer Patient Ovarian Cancer Patient
Rank 72h
2D 72h
3D 14 days
3D 72h
2D 72h
3D 14 days
3D 72h
2D 72h
3D 14 days
3D
1 DOX DOX DOX DOX DOX DOX DOX DOX DOX
2 TAX TAX TAX TAX TAX TAX TAX TAX TAX
3 AMR 5-FU 5-FU 5-FU AMR 5-FU AMR AMR 5-FU
4 5-FU AMR AMR AMR 5-FU AMR 5-FU 5-FU AMR

The 3D spheroid-based model was tested by inventors in cytotoxicity assay, monitoring the viability of the cells within the spheroids. Four compounds with well-known effects are selected and applied on 2D monolayer culture and spheroids in 8 different concentrations, (compounds and concentrations range of which are as detailed in TABLE 12) at Day 3 by acute (72 h) exposure and systemic (14 days – only for 3D culture) exposure. Concentration-response curves were generated and evaluated. Figure 41 shows in vitro IC50 values and mean cumulative dosage used in clinical trials that have shown neurotoxicity for the four drugs tested plotted on X and Y-axis, respectively.

TABLE 12.
Drug Concentration Range (µM)
Taxol 0.00001 - 50
5-Fluorouracil 0.01 - 100
Doxorubicin 0.005 - 50
Amiodarone 0.001 - 10

From the above results, Paclitaxel appears to be highly neurotoxic even at the lowest doses used for treatment amongst the entire drug panel. This significantly impairs its use in cancer treatment thus making it all the more important to develop platforms from predictive neurotoxicity to make its use effective for patients not vulnerable or predisposed for taxane-induced neurotoxicity.

Literature survey of clinical trials for paclitaxel (Taxol), 5-fluorouracil, amiodarone and pegylated liposomal doxorubicin was used to calculate the mean cumulative dose of the drugs that reported neurotoxicity symptoms for peripheral neuropathy and encephalopathy. Log (IC50 values for acute toxicity for 3D NPC spheroids) and Log (mean cumulative dose) values were plotted and the regression value was calculated for each donor group. For doxorubicin, the lowest drug concentration tested was chosen as the IC50 value to calculate the regression value. The in vitro model as illustrated in the present invention shows good correlation with the clinical trial data with regression values of up to R2 = 0.85 and higher for healthy volunteer, breast and ovarian cancer patients. Better correlation and further improvement in understanding can be obtained, going forward, with a screening study consisting of a larger drug library and patient samples.

Neurite Outgrowth Assay:
For neurite outgrowth measurement, the 3D spheroids were treated with 0.01 µM Taxol. After 72h of treatment, the spheroids were transferred to Matrigel-coated wells of a 96-well plate and allowed to extend neurites in a 37oC and 5% CO2 incubator. 72-hour after seeding, the NPC spheroids were fixed with 4% PFA for 15 mins at RT and stained with Tuj1 antibody and green fluorescent secondary antibody. Images were captured at suitable magnification in Image Xpress Nano (Molecular Devices). The images were analyzed using neurite-j plugin in Image J software to calculate mean neurite length and number of intersections (average number of neurites/spheroid) for different radii of distances from the spheroid boundary.

Paclitaxel Treatment Response in iPSC-based Neural Derivatives: iPSC-based neural derivatives (as shown in the embodiment) differentiated from Neural Progenitor Cells-passage 6 were seeded at a density of 1000 cells/cm2; neurites were allowed to grow for 96 hours. iPSC-neural derivatives- passage 2 were maintained in STEMdiff™ Forebrain Neuron Maturation media (Stem Cell Technologies, Cat: 08605) for 4 days in 5% CO2 incubator. After 96 hours, cells were treated with Paclitaxel (Tocris, cat: 1097) - 50 nM. Cells were stained with green-fluorescent calcein-AM to indicate intracellular esterase activity and red-fluorescent ethidium homodimer-1 as per manufacturer’s instruction to indicate loss of plasma membrane integrity at different time points i.e. 24, 48 and 96 hours. Control cells were incubated in the same conditions with the toxin vehicle, dimethylsulfoxide (DMSO).

The inventors demonstrate time-dependent effects of Paclitaxel on iPSC-based neural derivatives (Figure 40, 41, 45, 46, and 47). The majority of paclitaxel eventually accumulates in the microtubule-bound compartment after a long time of exposure (96 hour), as reported previously, leading to significant intracellular drug accumulation and arguably causing increased apoptosis (as observed in our investigations).

Latrunculin A Treatment of iPSC-based Neural Derivatives: iPSC-based neural derivatives-passage 6 were seeded at a density of 3000 cells/cm2. and maintained in STEMdiff™ Astrocyte Maturation media (Stem Cell Technologies, Cat: 100-0016) for 2 days in 5% CO2 incubator. After 48 hours, cells were treated with Latrunculin A (Tocris, Cat: 3973)-1.5 µg/ml for 72 hours and post 72 hours of drug treatment, cells were stained with Alexa Fluor™ 488 Phalloidin with DAPI as per manufacturer’s instruction. Control cells were incubated in the same conditions with the toxin vehicle, dimethylsulfoxide (DMSO). We monitored the effects of Latrunculin A, a toxin isolated from marine sponges that promotes actin depolymerization by sequestering actin monomers (Spector et al. 1999). Notably, iPSC-neural derivatives were found to be sensitive to actin disruption by Latrunculin, demonstrated shortening of F-actin cytoskeleton (F-actin being a preferential target of Latrunculin A) (Figure 46), which mimicked Paclitaxel mediated microtubule stabilization (as a result of Actin filament shortening/ disruption), arguably leading to apoptotic cell death (as reported previously) (Figure 47).

Statistical Analysis:
Descriptive statistics including mean, SD and SEM were conducted with GraphPad Prism version 9.3.0 (GraphPad Prism, RRID: SCR_002798). Means were compared among different time points and donor groups using ANOVA and post hoc Tukey’s test and p < 0.05 are considered statistically significant. Significance is represented by: *p<0.5, **P<0.01, ***p<0.001, ****p<0. 0001.The significance level for 95% confidence interval was set to = 0.05. The Pearson correlation test was applied to evaluate the correlation between replicate experiments. Curve-fitting algorithms for modelling drug response was also used for analysis and multivariate data was subjected to Bonferonni correction.

Although the present invention has been described in considerable detail with reference to certain preferred embodiments and examples thereof, other embodiments and equivalents are very much possible. Even though numerous characteristics and advantages of the present invention have been set forth in the foregoing description, together with efficacy, functional and other details, the disclosure is illustrative only, and changes may be made in detail, especially in terms of reagents used, non-essential ingredients to the method and system within the principles of the invention to the full extent indicated by the broad general meaning of the terms in which the appended claims are expressed. Thus various modifications are possible of the presently disclosed system and method without deviating from the intended scope and spirit of the present invention. More particularly, the system and method as depicted in the present invention, is simplified and generalized one and there are several variations possible. Accordingly, in one embodiment, such modifications of the presently disclosed system and method are included in the scope of the present invention. Also, unless the context clearly dictates otherwise, it is understood that when a range of value is provided, the tenth of the unit of the lower limit as well as other stated or intervening values in that range shall be deemed to be encompassed within the disclosure. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the disclosure. ,CLAIMS:1. An in-vitro method for determining toxicity of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, the method comprising:

a. Isolating peripheral blood mononuclear cells (PBMCs) from the subject;
b. Re-programming isolated PBMCs into induced pluripotent stem cells (iPSCs);
c. Developing neural progenitor cells (NPCs) from the iPSCs;
d. Conducting at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs; and
e. Determining the concentrations of the chemotherapeutic agent at which it is toxic to the NPCs.

2. The method as claimed in claim 1, wherein the said toxicity is neurotoxicity of the chemotherapeutic agent in the subject.

3. The method as claimed in claim 1, wherein the chemotherapeutic agent is a taxane-derived agent selected from the group consisting of paclitaxel and docetaxel and derivatives thereof.

4. The method as claimed in claim 1, wherein the said cancerous disease is selected from the group consisting of breast cancer and ovarian cancer.

5. The method as claimed in claim 1, wherein the said re-programming of PBMCs into iPSCs is carried out without integration of any external genetic material into the genome.

6. The method as claimed in claim 1, wherein the said iPSCs exhibit the same karyotypes as PBMCs thereby suggesting no chromosomal aberrations are introduced during the re-programming.

7. The method as claimed in claim 1, wherein the variations and germline mutations in the genome of the said subject are conserved in the iPSCs and derivatives, which is determined by the gnomic sequencing.

8. The method as claimed in claim 1, wherein the said iPSCs are identified and characterized by the expression of pluripotency markers such as Oct4, Nanog, Sox2, and SSEA4.

9. The method as claimed in claim 1, wherein the said iPSCs are capable of differentiating into cells representative of all three embryonic germ layers.

10. The method as claimed in claim 1, wherein the said NPCs are characterized by the expression of PAX6 gene and/or neural stem cell marker Nestin.

11. The method as claimed in claim 1, wherein the said NPCs are capable of differentiating into neural derivative cells such as forebrain motor neurons, astrocytes, and midbrain dopaminergic neurons.

12. The method as claimed in claim 1, wherein the said assay to detect toxicity of the chemotherapeutic agent involve qualitative and quantitative read out of NPCs upon drug exposure using cell viability or proliferation, gene expression, biomarker expression, immunocytochemistry, flowcytometry, neurite outgrowth, drug response studies, etc.

13. The method as claimed in claim 1, wherein the said assay to detect toxicity of the chemotherapeutic agent is a cytotoxicity assay on NPC spheroids in a 3D micro-environment.

14. The method as claimed in claim 1, wherein the said toxicity of the chemotherapeutic agent is detected and recorded in the form of IC50 values for 2D and 3D cultures of NPCs with acute and systemic exposure for different donor groups.

15. A system for determining neurotoxicity of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, the system comprising:

a. Means to isolate peripheral blood mononuclear cells (PBMCs) from the subject;
b. Means to re-program isolated PBMCs into induced pluripotent stem cells (iPSCs);
c. Means to develop neural progenitor cells (NPCs) from the iPSCs;
d. Means to conduct at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs; and
e. Means for determining the concentrations of the chemotherapeutic agent at which it is toxic to the NPCs.

16. An in-vitro method for determining safe dosage range of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, the method comprising:

a. Isolating peripheral blood mononuclear cells (PBMCs) and cancer biopsy sample from the subject;
b. Re-programming isolated PBMCs into induced pluripotent stem cells (iPSCs);
c. Developing neural progenitor cells (NPCs) from the iPSCs;
d. Conducting at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs;
e. Determining the concentrations of the chemotherapeutic agent at which it is neurotoxic to the NPCs;
f. Developing organoids from the cancer biopsy sample of the subject wherein the organoids depict histological features and key biomarker profile of primary tumor;
g. Determining the dosage range of chemotherapeutic agent which is effective against the cancer organoids; and
h. Identifying the part of the effective dosage range of chemotherapeutic agent in (g) which is lower than the concentration in in (e) at which the chemotherapeutic agent is toxic to the NPCs.

17. The method as claimed in claim 16, wherein the chemotherapeutic agent is a taxane-derived agent selected from the group consisting of paclitaxel and docetaxel and derivatives thereof.

18. The method as claimed in claim 16, wherein the said cancerous disease is selected from the group consisting of breast cancer and ovarian cancer.

19. The method as claimed in claim 16, wherein the said re-programming of PBMCs into iPSCs is carried out without integration of any external genetic material into the genome.

20. The method as claimed in claim 16, wherein the said iPSCs exhibit the same karyotypes as PBMCs thereby suggesting no chromosomal aberrations are introduced during the re-programming.

21. The method as claimed in claim 16, wherein the variations and germline mutations in the genome of the said subject are conserved in the iPSCs and derivatives, which is determined by the gnomic sequencing.

22. The method as claimed in claim 16, wherein the said iPSCs are identified and characterized by the expression of pluripotency markers such as Oct4, Nanog, Sox2, and SSEA4.

23. The method as claimed in claim 16, wherein the said iPSCs are capable of differentiating into cells representative of all three embryonic germ layers.

24. The method as claimed in claim 16, wherein the said NPCs are characterized by the expression of PAX6 gene and/or neural stem cell marker Nestin.

25. The method as claimed in claim 16, wherein the said NPCs are capable of differentiating into neural derivative cells such as forebrain motor neurons, astrocytes, and midbrain dopaminergic neurons.

26. The method as claimed in claim 16, wherein the said assay to detect toxicity of the chemotherapeutic agent involve qualitative and quantitative read out of NPCs upon drug exposure using cell viability or proliferation, gene expression, biomarker expression, immunocytochemistry, flowcytometry, neurite outgrowth, drug response studies, etc.

27. The method as claimed in claim 16, wherein the said assay to detect toxicity of the chemotherapeutic agent is a cytotoxicity assay on NPC spheroids in a 3D micro-environment.

28. The method as claimed in claim 16, wherein the said toxicity of the chemotherapeutic agent is detected and recorded in the form of IC50 values for 2D and 3D cultures of NPCs with acute and systemic exposure for different donor groups.

29. A system for determining safe dosage range of a chemotherapeutic agent in a subject suffering from at least one cancerous disease, the system comprising:

a. Means for isolating peripheral blood mononuclear cells (PBMCs) and cancer biopsy sample from the subject;
b. Means for re-programming isolated PBMCs into induced pluripotent stem cells (iPSCs);
c. Means for developing neural progenitor cells (NPCs) from the iPSCs;
d. Means for conducting at least one assay to detect toxicity of the chemotherapeutic agent on the NPCs;
e. Means for determining the concentrations of the chemotherapeutic agent at which it is neurotoxic to the NPCs;
f. Means for developing organoids from the cancer biopsy sample of the subject wherein the organoids depict histological features and key biomarker profile of primary tumor;
g. Means for determining the dosage range of chemotherapeutic agent which is effective against the cancer organoids; and
h. Means for identifying the part of the effective dosage range of chemotherapeutic agent in (g) which is lower than the concentration in in (e) at which the chemotherapeutic agent is toxic to the NPCs.