TECHNICAL FIELD
[001] Embodiments disclosed herein relate to metastatic potential of a primary
carcinoma, and more particularly to systems and methods for determining the ability
of one or more cancer cells to metastasize and for screening of drugs for their potential
use in inhibiting cancer metastasis.
10 BACKGROUND
[002] Cancer metastasis is a major cause of cancer mortality that accounts for about
90% of cancer deaths. Metastasis involves spread of cancer cells from primary tumor
site to surrounding and distant organs.
[003] Cancer survival rates have increased significantly over the years, which can be
15 basically credited to early diagnosis and cancer growth inhibition. However, limited
progress has been made in the field of cancer metastasis.
[004] Current treatments for cancer metastasis predominantly include surgery,
followed by chemotherapy and radiotherapy. The biggest challenge for clinicians is
their inability to understand which primary tumor patients will develop metastasis,
20 even after successful surgical intervention and chemotherapy. Adding to that, the lack
of understanding of the timeline, as to when the patient will develop metastasis,
exponentially increases this challenge.
[005] The three major myths that have contributed to the lack of understanding of the
metastatic process are as follows:
25 i) Dissemination of cancerous cells is directly proportional to tumor size. PET
SCANs can detect tumors having more than 109 cells. The most sensitive liquid biopsy
can detect greater than 105 cells present in the blood. Hence, even if there are hundreds
3
or thousands of tumor cells already metastasized in the blood, on their way to a
secondary tissue, clinically they may go undetected. Some of these cells survive the
body’s immune system and successfully hide in other tissues, remaining dormant and
staying undetected, only to grow to a secondary tumor at some point of time. Such
5 patients are clinically declared to be cancer free, till the time the tumor recurs in a
different area (metastasis, 0.01% efficient process) or the same area (recurrence) and
are visible by liquid biopsy or PET SCAN, which is probably too late.
ii) Metastasis is heterogenous for different cancers, as a result of different late-stage
mutations.
10 iii) Cellular plasticity is not relevant. Unfortunately, no tumor agnostic prediction or
diagnostic tests are available till date for all epithelial carcinomas that can predict the
probability of the primary tumor to metastasize. Further, in the last 25 years, only one
anti metastatic drug has been approved by FDA, from the 220+ drugs that were
approved for cancer. This can be attributed to the limited understanding of the complex
15 metastatic process. Current research has only unveiled a part of this complexity and
hence as a result, all drug discovery efforts till date have been primarily focused on
targeting of the cancer cell’s ability to move away from the primary tumor site, adhere
and invade the epithelial cell layer.
OBJECTS
20 [006] The principal object of embodiments herein is to disclose methods and systems
for determining the ability of at least one cancer cell to metastasize and for screening
of drugs for their potential use in inhibiting cancer metastasis.
[007] These and other aspects of the embodiments herein will be better appreciated
and understood when considered in conjunction with the following description and the
25 accompanying drawings. It should be understood, however, that the following
descriptions, while indicating at least one embodiment and numerous specific details
thereof, are given by way of illustration and not of limitation. Many changes and
modifications may be made within the scope of the embodiments herein without
4
departing from the spirit thereof, and the embodiments herein include all such
modifications.
BRIEF DESCRIPTION OF FIGURES
[008] Embodiments herein are illustrated in the accompanying drawings, throughout
5 which like reference letters indicate corresponding parts in the various figures. The
embodiments herein will be better understood from the following description with
reference to the drawings, in which:
[009] FIG. 1 depicts a method for determining the ability of at least one cancer cell
to metastasize and for screening of drugs for their potential use in inhibiting cancer
10 metastasis, according to embodiments as disclosed herein;
[0010] FIG. 2 depict results of an assay, chemosensitivity (A1), for chemotherapeutic
drugs Dxorubicin, Paclitaxel, Cytochalasin D, and Nocodazole, respectively, according
to embodiments as disclosed herein;
[0011] FIGs. 3A and 3B and 3C depict results of an assay, epithelial to mesenchymal
15 ratio (A2), for Epithelial marker E-Cadherin (AF 594) and Mesenchymal marker
Vimentin (AF 488) in a tumor, according to embodiments as disclosed herein;
[0012] FIG. 4 depict results of an assay, stemness of the cell (A3), for stemness markers
CD 133 (AF 647) & CD 44 (AF 488), according to embodiments as disclosed herein;
[0013] FIGs. 5A and 5B depict results of an assay, doubling time of tumor (A4), for
20 CRC cell lines and HT 29 spheroids, respectively, according to embodiments as
disclosed herein;
[0014] FIGs. 6A and 6B depict results of an assay, adhesion (B5) of tumor, showing
adhesion percentages in colon cancer cells and effect of heparin on adhesion,
respectively, according to embodiments as disclosed herein;
25 [0015] FIGs. 7A and 7B depict results of an assay, migration (B6) of tumor cells, using
FBS as chemoattractant and in presence of different doses of Cytochalasin D, according
to embodiments as disclosed herein;
5
[0016] FIGs. 8A, 8B and 8C depict results of an assay, invasion (B7) of tumor cells,
using Basement membrane matrix and FBS and in presence of different doses of
Paclitaxel, according to embodiments as disclosed herein;
[0017] FIGs. 9A, 9B, 9C and 9D depict an assay, intravasation (C8), showing trans5 endothelial migration (TEM) images of tumor cells with and without FBS and/or
Cytochalasin D; percentage inhibition of TEM; TEM with platelet rich plasma (PRP)
and platelet poor plasma; and fold change in intravasation ability of colon cancer cell,
respectively, according to embodiments as disclosed herein;
[0018] FIGs. 10A, 10B and 10C depict results of an assay, Tumor Cell Induced Platelet
10 Aggregation (TCIPA) (C9), at various concentrations of PRP and cancer cells; with
colon cancer cells at 0.25M and 0.5 M concentrations; and with HT 29 wildtype and
its clones, viz. 8C5 and 12BC6, according to embodiments as disclosed herein;
[0019] FIGs. 11A and 11B depict an assay, extravasation (C10) in tumor, showing
TEM images of tumor cells with and without platelets; and of HT 29 wildtype versus
15 HT 29, 8C5 and 12BC6, respectively, according to embodiments as disclosed herein;
[0020] FIGs. 12A and 12B depict an assay, Mesenchymal to Epithelial transition
(MET) (D11), at various concentrations of Retinoic acid (RA) assessing markers ECadherin and Vimentin; and RA effect on expression of E-Cadherin and Vimentin in
SW480 clone 1C3, respectively, according to embodiments as disclosed herein;
20 [0021] FIG. 13 depict the results of an assay, Apoptosis (D12), showing fold increase
in Caspase-3 in HT 29 wildtype, HT 29 clone 8C5 and HT 29 clone 12BC6 cells,
according to embodiments as disclosed herein;
[0022] FIG. 14 depict results of an assay, Metabolism (D13), showing 72 hour
metabolic profile of HT 29 wildtype, HT 29 clone 8C5 and HT 29 clone 12BC6 cells,
25 according to embodiments as disclosed herein;
[0023] FIGs. 15A, 15B and 15C depict results of an assay, Exosome vesicles secretion
and uptake (D14), showing standard curve of exosome quantification; exosome
6
secretion in colon cancer cells; and exosome uptake in cell lines, according to
embodiments as disclosed herein;
[0024] FIG. 16 depict results of an assay, cytotoxicity (E15) in tumor, by LDH release
in cell lines treated with Montelukast, Metformin, and Propanol, according to
5 embodiments as disclosed herein;
[0025] FIG. 17 depicts an assay, Angiogenesis (E16), showing the formation of
HUVEC cell mediated tubes, according to embodiments as disclosed herein;
[0026] FIGs. 18A, 18B and 18C depict an assay, immune profiling (E17), showing PDL1 across epithelial and mesenchymal forms (percent population change) of cell lines
10 and primary tumor; % expression in HT 29 wildtype, engineered HT29#12BC6, and
engineered HT29#8C5; and CD-73 across epithelial and mesenchymal forms (percent
population change) of cell lines and primary tumor cells, respectively, according to
embodiments as disclosed herein;
[0027] FIGs. 19A and 19B depict results of an assay, autophagy analysis (E18),
15 showing survival of dormant cells in a nutrient deficient environment, according to
embodiments as disclosed herein;
[0028] FIGs. 20A and 20B depict an assay, effect of hypoxia, by incubation with Cobalt
chloride and percentage of HIF-1alpha positive cells in colon cancer cells, according
to embodiments as disclosed herein;
20 [0029] FIGs. 21A, 21B and 21C depict an assay, cell cycle analysis by Ki67 (E20),
according to embodiments as disclosed herein;
[0030] FIG. 22A shows spontaneous spheroid formation in a gradient of fetal bovine
serum (FBS) and using different number of cell density for wild type HT29 and
engineered HT29#8C5.
25 [0031] FIG 22B is a confocal microscopy characterization of spheroid showing the
inner necrotic and hypoxic core, along with the peripheral live cells;
[0032] FIG 23A is a representation of EMT assay in the 3D form;
7
[0033] FIG. 23B is a representation of invasion assay in the 3D form.
[0034] FIG. 24A is a representation depicting overexpression strategy to convert nonmetastatic (non-met) cells to metastatic(met) cell, showing vectors construction for
genetically engineered cell lines, to increase PR and metastatic properties, the cell lines
5 were engineered by both constitutive and inducible transfection;
[0035] FIG 24B is a representation of CRISPR CAS9 based strategy to convert metcells into non-met cells;
[0036] FIG. 25A is a radial chart representation depicting values and correlation of
parameter of the assays for wild type cell lines, viz. HT 29, HCT 116, SW480 and
10 COLO 205;
[0037] FIG. 25B is a radial representation depicting values and correlation of parameter
of the assays for engineered constitutive and inducible clones of HT29;
[0038] FIG. 26A is a radial chart representation depicting values and correlation of
parameter of the assays for engineered (by CRISPR CAS9) cell lines;
15 [0039] FIG. 26B is a radial chart representation depicting values and correlation of
parameter of the assays for five representative patient samples;
[0040] FIG. 27 depicts a system for determining the ability of at least one cancer cell
to metastasize and for screening of drugs for their potential use in inhibiting cancer
metastasis, according to embodiments as disclosed herein; and
20 [0041] FIG. 28 depicts an example correlation matrix with a heatmap (positive and
inverse), according to embodiments as disclosed herein.
DETAILED DESCRIPTION
[0042] The embodiments herein and the various features and advantageous details
thereof are explained more fully with reference to the non-limiting embodiments that
25 are illustrated in the accompanying drawings and detailed in the following description.
Descriptions of well-known components and processing techniques are omitted so as
to not unnecessarily obscure the embodiments herein. The examples used herein are
8
intended merely to facilitate an understanding of ways in which the embodiments
herein may be practiced and to further enable those of skill in the art to practice the
embodiments herein. Accordingly, the examples should not be construed as limiting
the scope of the embodiments herein.
5 [0043] The embodiments herein achieve methods and systems for determining the
ability of at least one cancer cell to metastasize and for screening of drugs for their
potential use in inhibiting cancer metastasis. Referring now to the drawings, and more
particularly to FIGS. 1 through 23, where similar reference characters denote
corresponding features consistently throughout the figures, there are shown
10 embodiments.
The following terms have been used herein:
[0044] Primary Carcinoma: The term “primary carcinoma” refers to the original site in
the body where cancer initially began.
[0045] Cancer Metastasis: The term “cancer metastasis” refers to spread of cancer cells
15 from a primary carcinoma site to a secondary site.
[0046] Cancer stem cell: The term “cancer stem cell” refers to subpopulation of cells
within a tumor capable of displaying dormancy, self- renewal, differentiation,
proliferation, and tumorigenicity.
[0047] Growing cell type: The term “growing cell type” refers to the cells having
20 predominant characteristics of an epithelial cell. The growing cell type is highly
proliferating, chemosensitive and do not have any significant cancer stem cell like
properties.
[0048] Moving cell type: The term “moving cell type” refers to the cells having
predominant characteristics of a mesenchymal cell. The moving cell type is less
25 proliferating, chemo-resistant and have significant cancer stem cell like properties.
9
[0049] Normalization: The term “normalization” refers to a scaling technique in which
numeric values of a dataset are shifted and brought to a common scale, without
distorting the differences in the ranges of values.
[0050] Screening of drugs: The term “screening of drugs” can be interchangeably used
5 with the term “screening of compounds” and refers to identifying compound(s)
having inhibitory potency towards cancer metastasis.
[0051] Inhibitory potency: The term “inhibitory potency” refers to potency of
compound(s) to inhibit cancer metastasis.
[0052] Embodiments herein disclose methods and systems for determining the ability
10 of at least one cancer cell to metastasize and for screening of drugs for their potential
use in inhibiting cancer metastasis. Embodiments herein disclose a computer
implemented tool for predicting the metastatic potential of a primary carcinoma.
Embodiments herein disclose a method for predicting the metastatic potential of a
primary carcinoma. Embodiments herein disclose a tool for screening drugs for their
15 potential use in inhibiting cancer metastasis.
[0053] FIG. 1 is a flowchart depicting the process of determining the ability of at least
one cancer cell to metastasize and for screening of drugs for their potential use in
inhibiting cancer metastasis. In step 101, cell-based assays are conducted in wild type
tumor cell lines, genetically engineered tumor cell lines and patient derived tumor cells
20 or tissues samples. Each of these assays can be considered as an in-vitro biological
mimicry for studying key cellular characteristic and studying of the physiological
process of metastasis, wherein the physiological process that includes multiple steps,
which are collectively responsible for metastasis. The assays can be broken into five
major groups namely group A, group B, group C, group D, and group E.
25 [0054] Group A includes characterization of cells. For characterization of cells (Group
A), the following parameters are evaluated; chemosensitivity (A1) (as depicted in FIG.
2), the epithelial to mesenchymal ratio in a tumor (A2) (as depicted in FIGs. 3A, 3B
10
and 3C), stemness of the cell (A3) (as depicted in FIGs. 4) and doubling time of tumor
(A4) (as depicted in FIGs. 5A and 5B).
[0055] FIG. 2 is representation depicting chemosensitivity assay (A1), for
chemotherapeutic drugs Dxorubicin, Paclitaxel, Cytochalasin D, and Nocodazole,
5 respectively. FIGs. 3A, 3B and 3C are representations depicting epithelial to
mesenchymal ratio assay (A2), for Epithelial marker E-Cadherin (AF 594) and
Mesenchymal marker Vimentin (AF 488) in a tumor. FIG. 4 is representation depicting
assay for stemness of the cell (A3), for stemness markers CD 133 (AF 647) & CD 44
(AF 488). FIGs. 5A and 5B are representations depicting assay for doubling time of
10 tumor (A4), for CRC cell lines and HT 29 spheroids, respectively.
[0056] Chemosensitivity (A1) is evaluated by checking the tumor cell’s ability to
survive upon treatment with multiple chemotherapeutic drugs. Chemo resistance is
proportional to stemness and invasiveness. Chemosensitivity is measured by treating
the cells with a compound and measuring the number of live cells remaining after 96
15 hours, as compared to untreated cells. In an embodiment herein, WST-8 (water soluble
tetrazolium salt) forms formazan dye, which can be used as a measure of
dehydrogenase activity of live cells). In an embodiment herein, fluorescent DNA
binding dye can be used to measure the cellular DNA content. In an embodiment
herein, ATP content can be used as a measure of viable cells.
20 [0057] The epithelial to mesenchymal ratio in a tumor (A2) of the tumor cells is
measured by comparing the total percentage of mesenchymal markers to the total
percentage of epithelial markers to generate a Plasticity Ratio (PR). PR can help in
characterizing cells vis-a-vis invasiveness & growth properties, (PR ∝ invasiveness).
The mesenchymal markers that are analyzed, include Vimentin and/or N cadherin. The
25 epithelial markers that are analyzed, include E-cadherin and/or EpCam. A ratio < 0.7
indicates epithelial characteristics of the cells and a ratio >1 indicates mesenchymal
properties of the cells. An increase in this ratio suggests increasing invasiveness of the
tumor cell. Embodiments herein can evaluate the transition from the epithelial form to
11
the mesenchymal form by measuring the same epithelial markers and mesenchymal
markers to determine the plasticity ratio (PR) ratio. Embodiments herein can measure
the epithelial to mesenchymal ratio and PR ratio using flow cytometry and
immunofluorescence. In the experimental data depicted in FIG. 3A, 3B and 3C, the
5 reagent used is a cocktail of proteins promoting epithelial to mesenchymal transition,
the Epithelial marker is E-Cadherin (AF 594), and the Mesenchymal marker is
Vimentin (AF 488). Table 1 provides the plasticity ratios determined for Epithelial
marker E- Cadherin (AF 594) and Mesenchymal marker Vimentin (AF 488).
[0058] Table 1 showing plasticity ratios (PR) for E-Cadherin (AF 594) and Vimentin
10 (AF 488).
Cell line E-Cadherin Vimentin PR
HT 29 95.6 50.9 0.532
HCT 116 42.2 70.8 1.678
Colo 205 95.1 98.2 1.033
SW 480 30.5 99.2 3.252
[0059] Metastatic cells are stem like, analysis of patient samples in conjunction with
PR gives a tighter correlation of plasticity. Cancer stem cells (CSCs) are defined by
their ability for self-renewal and multipotency. The CSC hypothesis states that,
15 although CSCs represent a rare population of cells within a tumor, their high
tumorigenic capacity drives tumorigenesis. Due to their intrinsic stem cell-like
properties, CSC proliferation generates more CSCs, and all the differentiated cell types
that compose the bulk of the tumor. Non-CSCs in the tumor have been shown to
proliferate at a faster rate than CSCs, but have low tumor- initiating potential. A key
20 therapeutic intervention for metastasis will be to prevent cells from being plastic, i.e.,
change from the epithelial form to the moving mesenchymal form. The amount of
stemness (A3) in tumor cells can be measured by analyzing stem cell markers,
12
including, but not limited to, CD133, CD 44, CD24, CD166, CD44+, EpCAM,
ABCG2, and ALDH1A1, by flow cytometry and immunofluorescence.
[0060] The Doubling time of tumor (A4) is the total time taken by the tumor to double
the number of cells. A higher doubling time would indicate the presence of higher
5 stemness resulting in increased invasive behavior. Metastatic or moving cells, have
comparatively lower proliferation rate. The doubling time is measured by adding a
labelled dye into cells and monitoring the incorporation of the labelled dye into the
DNA of the growing cells. In an embodiment herein, WST-8 (water soluble tetrazolium
salt) forms formazan dye, which can be used as a measure of dehydrogenase activity
10 of live cells). In an embodiment herein, fluorescent DNA binding dye can be used to
measure the cellular DNA content. In an embodiment herein, ATP content can be used
as a measure of viable cells.
[0061] Group B includes evaluating the ability of the cells to move out of epithelial
layer. For evaluating the ability of the cells to move out of epithelial layer (group B),
15 the following parameters are evaluated, adhesion (B5) (as depicted in FIGs. 6A and
6B), migration (B6) (as depicted in FIGs. 7A and 7B), and invasion (B7) (as depicted
in FIGs. 8A, 8B and 8C).
[0062] Adhesion properties of the cells is the ability to dissociate from tumor mass and
adhere to the epithelial membrane and is one of the first criteria of metastasis, that is
20 evaluated by measuring the ability of tumor cells to bind to epithelial membranes. This
is achieved by using synthetic proteins that mimic epithelial membrane proteins,
thereby creating an epithelial like environment. This is important for the initial success
of metastasis as without successful anchoring, cells would not be able to penetrate
inside and through the epithelial membrane. Basement membrane matrix (major
25 components: laminin, collagen IV, entactin, and heparin sulfate proteoglycan) - Final
Concentration 2ug/ml. Readout: Counting of adhered cells after wash, by measurement
of ATP content. FIG. 6A depicts the adhesion percentage of colon cancer cells. FIG.
6B depicts the effect of Heparin on adhesion.
13
[0063] The ability to move towards a chemoattractant is one of the first criteria of
metastasis. Migration properties of the cells are evaluated by measuring the ability of
tumor cells to move away from the solid tumor towards a chemoattractant signature.
Chemoattractants are chemical or biochemical agents that attract an organism or a cell
5 towards itself. They are the reason for cell motility. In tumors, growth factors,
cytokines and chemokines and several proteins in the blood act as a chemoattractant,
drawing the tumor out from its natural habitat. For measuring the migration property
of the cell, the assay uses a two chamber system, divided by a transwell insert, that are
laid over a chemoattractant, with the cells being plated on top of the insert. Transwell
10 inserts are permeable tissue culture plate insert (Transwell®, Corning, Inc., Lowell,
Mass). Alternatively, any permeable growth support that capable of being inserted into
a well of a tissue culture plate may be used. The permeable insert generally provides a
means to partition the well into a two or more portions, for e.g.: basolateral portion and
apical portion, etc. The results depicted in FIGs. 7A-7B use Transwell Inserts
15 (Polyester membrane, 8um pore size, 6.5 mm diameter), 24 well plate format, FBS as
chemoattractant, and ATP measurement and/or 0.1% crystal violet staining. FIGs. 7A
and 7B are representations depicting migration (B6) of tumor cells, using FBS
as chemoattractant and in presence of different doses of Cytochalasin D.
[0064] The ability to cleave through the epithelial membrane is one of the first criteria
20 of metastasis. Invasion properties of the cells are evaluated by measuring the ability of
tumor cells to tear through the epithelial membrane and move towards the
chemoattractant. This is a summative characterization of the adhesion and migration,
along with the cells ability to penetrate the epithelial membrane. The assay is a mixture
of both the migration and adhesion assay, using transwell inserts and artificial epithelial
25 protein membrane. FIGs. 8A, 8B and 8C are representations depicting invasion assay
(B7) of tumor cells. The results depicted in FIGs. 8A and 8B use Transwell Inserts
(Polyester membrane, 8um pore size, 6.5 mm diameter), 24 well plate format, FBS as
chemoattractant , Basement membrane matrix (major components: laminin, collagen
14
IV, entactin, and heparin sulfate proteoglycan) - Final Concentration 2ug/ml, 0.1%
crystal violet staining (FIG. 8A) and / or ATP measurement (FIG. 8B). Dissemination
can be of two types; single cell vs. cluster (as depicted in FIG. 8C).
[0065] Group C includes evaluating the ability of the cell to enter the endothelial
5 system (blood), survive in the endothelial system and migrate from the endothelial
system to a secondary site. For evaluating the ability of the cells to enter the endothelial
system (blood), survive in the endothelial system and migrate from the endothelial
system into the secondary site (group C), the following parameters are evaluated;
intravasation (C8) (as depicted in FIGs. 9A, 9B, 9C and 9D), Tumor Cell Induced
10 Platelet Aggregation (TCIPA) (C9) (as depicted in FIGs. 10A, 10B and 10C), and
extravasation (C10) (as depicted in FIGs. 11A and 11B).
[0066] FIGs. 9A, 9B, 9C and 9D are representations depicting assay for intravasation
(C8), showing TEM images of tumor cells with and without FBS and/or Cytochalasin
D; percentage inhibition of TEM; platelet rich plasm (PRP) and platelet poor plasma;
15 and fold change in intravasation ability of colon cancer cell, respectively. FIGs. 10A,
10B and 10C are representations depicting assay for Tumor Cell Induced Platelet
Aggregation (TCIPA) (C9), at various concentrations of PRP and cancer cells; with
colon cancer cells at 0.25M and 0.5 M concentrations; and with HT 29 wildtype and
its clones, viz. 8C5 and 12BC6. FIGs. 11A and 11B are representations depicting
20 extravasation (C10) in tumor, showing TEM images of tumor cells with and without
platelets; and of HT 29 wildtype versus HT 29, 8C5 and 12BC6.
[0067] Intravasation is defined as the ability of tumor cells to invade through the
endothelial layer in the presence of stimuli (i.e., it measures the ability of cells to
penetrate through endothelial cell layers (FIGs. 9A and 9B) and the ability to cleave
25 through the endothelial membrane, moving towards enriched blood (FIGs. 9C and
9D)). For measuring the intravasation ability of tumor, monolayer formation of the
endothelial layer and its integrity is studied followed by measuring the amount of tumor
cells that successfully invade through the endothelial layer. The assay uses both
15
synthetic protein cocktail as a chemoattractant and also whole human blood in an
enriched form, to mimic the physiology. Transwell inserts are used with tumor cells,
primary endothelial cells being on the top and enriched whole blood or protein cocktail
on the bottom. In the experimental results depicted in FIGs. 9A and 9B (which
5 depicts the Trans-endothelial migration), Transwell Inserts, 24 well plate format,
FBS or platelet rich plasma (PRP) as chemoattractant, Human umbilical vein
endothelial cells (HUVEC), integrity confirmed by FITC – Dextran after 72 h of
seeding, and Readout EmGFP engineered cells. In the experimental results depicted in
FIGs. 9C and 9D (which depicts the measure of intravasation), Transwell Inserts, 24
10 well plate format, FBS or PRP as chemoattractant, Human umbilical vein endothelial
cells (HUVEC), integrity confirmed by FITC – Dextran after 72 h of seeding, and
Readout EmGFP engineered cells.
[0068] Surviving in blood is a prerequisite for successful metastasis and is done by
binding with platelets. TCIPA is defined as the ability of tumor cells to bind with
15 platelets and subsequently activate them. This not only helps them to evade immune
surveillance, but also activated platelets release chemicals that helps cells to
extravasate out. Platelet rich plasma (PRP) isolated form healthy volunteers and
platelet activation is standardized with ADP. It is measured by measuring the change
in the optical density of the tumor cell binding with platelets and subsequent platelet
20 aggregation, using a co-culture of PRP and tumor cells. FIG. 10A depicts platelet
aggregation by colon cancer cells. FIG. 10B depicts platelet aggregation with ADP.
FIG. 10C depicts platelet aggregation with non-metastatic HT29 wild type and its
metastatic clones; 8C5 and 12BC6.
[0069] Extravasation is defined as the ability of tumor cells to break out of the
25 endothelial layer to an external tissue. This assay is very similar to the intravasation
assay and uses transwell inserts, and enriched whole blood. In this case, the enriched
blood and tumor cells are co-incubated together on the transwell insert, coated with a
primary endothelial cell monolayer and checked for the integrity of the endothelial
16
layer. FIGs. 11A and 11B are representations depicting assay for extravasation (C10)
in tumor, showing TEM images of tumor cells with and without FBS; and of HT 29
wildtype versus HT 29, 8C5 and 12BC6, respectively. In the experimental results
depicted in FIGs. 11A and 11B, Transwell Inserts, 24 well plate format, Human
5 umbilical vein endothelial cells (HUVEC), PRP co incubation, and Readout EmGFP
engineered cells.
[0070] Group D includes evaluating the ability of the cells to survive in the secondary
site, cross talk with the tissue in the secondary site and successfully grow back to a
tumor in the secondary site. For evaluating the ability of the cells to survive in the
10 secondary site, cross talk with the tissue in the secondary site and successfully grow
back to a tumor in the secondary site (group D), the following parameters are evaluated;
Mesenchymal to Epithelial transition (MET) (D11) (as depicted in FIGs. 12A and
12B), Apoptosis (D12) (as depicted in FIG. 13), Metabolism (D13) (as depicted in FIG.
14), and Exosome vesicles secretion and uptake (D14) (as depicted in FIGs. 15A, 15B
15 and 15C).
[0071] FIGs. 12A and 12B are representations depicting assay for Mesenchymal to
Epithelial transition (MET) (D11), at various concentrations of Retinoic acid (RA)
measuring markers E-Cadherin and Vimentin; and RA effect on expression of ECadherin and Vimentin in SW480 clone 1C3, respectively. FIG. 13 is representations
20 depicting assay for Apoptosis (D12), showing fold increase in Caspase-3 in HT 29
wildtype, HT 29 clone 8C5 and HT 29 clone 12BC6 cells. FIG. 14 is representation
depicting assay for Metabolism (D13), showing 72 hour metabolic profile of HT 29
wildtype, HT 29 clone 8C5 and HT 29 clone 12BC6 cells. FIGs. 15A, 15B and 15C
are representations depicting assay for Exosome vesicles secretion and uptake (D14),
25 showing standard curve of exosome quantification; exosome secretion in colon cancer
cells; and exosome uptake in cell lines.
[0072] Mesenchymal to Epithelial transition (MET) is the ability of the tumor cells to
change from the moving cellular form, back to the growing cellular form. This is
17
measured by detecting the change in the epithelial and mesenchymal cell markers, once
cells are treated with agents promoting MET. Mesenchymal to Epithelial transition is
characterized by measuring the PR ratio, where a decrease in PR ratio from 1 or > 1 to
< 1 would decrease invasiveness and stem like properties. Flow cytometry is used,
5 along with imaging techniques like fluorescence markers using multiple proteins as
markers, including but not limited to E cadherin, Vimentin, N Cadherin, Epcam, CD
133, CD 44, to measure MET. For the experimental results depicted in FIGs. 12A and
12B, Epithelial marker: E- Cadherin (AF 647), and Mesenchymal marker: Vimentin
(AF 488), inducible engineered cell. In FIG. 12A, the PR changes from 1.3 (no RA) to
10 0.56 (10 mM RA).
[0073] Apoptosis tests the ability of the tumor cells to succumb or resist the efforts of
the microenvironments to destroy the tumor cells (measurement of caspase 3/7
activity). This is measured by checking the amount of caspase 3 released by cells. FIG.
13 depict the results of an assay, Apoptosis (D12), showing fold increase in Caspase-3
15 in HT 29 wildtype, HT 29 clone 8C5 and HT 29 clone 12BC6 cells.
[0074] The energy metabolism of tumor cells can be studied by measuring the
parameters including, but not limited to, lactate consumption, glutamate production,
NADH/NADPH and Reactive Oxygen Species (ROS) production. Exploitation of
differential metabolism in cells with different PR ratios is disclosed herein. FIG. 14
20 depict a comparison of aerobic glycolysis versus mitochondrial respiration comparison
(with a focus on glycolysis – production of lactate). It depicts a comparison of aerobic
glycolysis versus mitochondrial respiration comparison (with a focus on
glutaminolysis – production of glutamate). It further depicts a comparison of aerobic
glycolysis versus mitochondrial respiration comparison (with a focus on mitochondrial
25 respiration - ROS). It helps in understanding the metabolic profile of epithelial and
mesenchymal cells.
[0075] Exosome vesicles secretion and uptake measures the ability of the tumor cells
to grow in a foreign secondary environment. This is the direct result of the ability of
18
the tumor cells to secrete and absorb exosome vesicles that allows it to cross talk with
the microenvironment. Exosomes are isolated and quantitated from cell cultures, of
both moving and growing cells, and from genetically modified cells. FIG. 15A depicts
a standard curve of exosome quantification. FIG. 15B depicts an exosome secreted/mL
5 culture of colon cancer cells. The isolated and quantitated exosomes are labeled. The
labeled exosomes are then used to evaluate uptake of exosomes in the cells. Survival
of tumor cells in secondary tissue depends on successful cross talk, carried out by
uptake of exosomes. Embodiments herein label cells, isolate exosomes, purify and
quantify the exosomes. Embodiments herein incubate the cell of choice with labeled
10 exosomes and analyze by flow cytometry with DNA counterstaining.
[0076] Group E are extrinsic assays. These assays include analysis of certain typical
characteristics of the tumor cells that define their ability to survive in a hostile
environment, e.g., response to oxidative stress (hypoxia), response to starvation,
response to host immune microenvironment, and so on. For group E, the following
15 parameters are evaluated, cytotoxicity (E15) (as depicted in FIG. 16), Angiogenesis
(E16) (as depicted in FIG. 17), immune profiling (E17) (as depicted in FIGs. 18A, 18B
and 18C), autophagy analysis (E18) (as depicted in FIGs. 19A and 19B), effect of
hypoxia (E19) (as depicted in FIGs. 20A and 20B), and cell cycle analysis by Ki67
(E20) (as depicted in FIGs. 21A, 21B and 21C).
20 [0077] FIG. 16 is a representation depicting assay for cytotoxicity (E15) in tumor, by
LDH release in cell lines treated with Montelukast, Metformin, and Propanol. FIG. 17
is a representation depicting assay for Angiogenesis (E16), showing the formation of
HUVEC cell mediated tubes. FIGs. 18A, 18B and 18C are representations depicting
results of immune profiling (E17), showing PD-L1 across epithelial and mesenchymal
25 forms (Percent population change) of cell lines and primary tumor; and CD-73 across
epithelial and mesenchymal forms (percent population change) of cell lines and
primary tumor cells. FIGs. 19A and 19B is a representation depicting autophagy
analysis (E18), showing survival of dormant cells in a nutrient deficient environment.
19
FIGs. 20A and 20B are representations depicting assay for effect of hypoxia, by
incubation with cobalt chloride and percentage of HIF-1alpha positive cells in colon
cancer cells. FIGs. 21A, 21B and 21C are representations depicting assay for cell cycle
analysis by Ki67 (E20).
5 [0078] Cytotoxicity (E15) detect low level/early cellular damage by measuring LDH
activity (as depicted in FIG. 16)
[0079] Angiogenesis (E16) is used to test the ability of compounds to inhibit
angiogenesis, which is a key step for secondary tumor formation, after MET. FIG. 17
depicts the formation of HUVEC cell mediated tubes.
10 [0080] Immune profiling (E17) comprises of measuring PD-L1 across epithelial and
mesenchymal forms (Percent population change) of cell lines and primary tumor cells
(as depicted in FIG. 18A) and measuring CD-73 across epithelial and mesenchymal
forms (percent population change) of cell lines and primary tumor cells (as depicted in
Fig. 18B).
15 [0081] Autophagy analysis (E18) comprises of determining how dormant cells survive
in a nutrient deficient environment, till the soil becomes conducive. Autophagy can be
measured using flow cytometry.
[0082] E19 comprises of understanding the effect of hypoxia on different cell types, by
induction with cobalt chloride and measured using flow cytometry.
20 [0083] Cell cycle analysis (E20) comprises of understanding the effect of PR on cell
cycles using Ki67. Cells accumulate in G0 and decrease in M with an increase in PR.
This can eventually be directly correlated with cancer stemness properties and can also
act as a marker for dormancy.
[0084] Each of the above assays, A1 to E20 are carried out with the wild type cancer
25 cell line. The wild type cancer cell line is characteristic of a growing type of a cancer
cell. A set of second input data set is generated by conducting the assays A1 to E20 in
the genetically altered form of the same cancer cells lines. The genetically engineered
20
cancer cell line is characteristics of a moving type of a cancer cell. The wild type cancer
cell line and the genetically engineered cancer cells lines of the present disclosure are
selected from, including but not limited to, epithelial carcinoma of head and neck
cancers, oesophageal cancer, skin cancer, lung cancer, triple negative breast cancer,
5 gastric cancer, pancreatic cancer, colorectal cancer, liver cancer, bladder cancer, kidney
cancer, ovarian cancer, cervical cancer, endometrial cancer, vulvar cancer, uterine
cancer, thyroid cancer, and so on. Conducting the assays A1 to E20 for the wild type
cancer cell line and genetically engineered cancer cell lines, independently, helps in
analyzing the key differences of cellular characteristics, and functional readouts of the
10 wild type cancer cell line (growing cell type) and the engineered cancer cell lines
(moving cell type).
[0085] The assays are evaluated in at least one of a two-dimensional (2D) or a three
dimensional (3D) space. In an embodiment herein, a 2D assay can be converted to a
3D assay using at least one suitable 3D model, with some examples given below.
15 [0086] FIG. 22A shows spontaneous spheroid formation in a gradient of fetal bovine
serum (FBS) and using different number of cell density for wild type HT29 and
engineered HT29#8C5. FIG. 22B is a confocal microscopy characterization of spheroid
showing the inner necrotic and hypoxic core, along with the peripheral live cells.
[0087] FIG. 23A is a representation of EMT assay in the 3D form and FIG. 23B is a
20 representation of invasion assay in the 3D form.
[0088] In step 102, the conducted cell-based assays are used to obtain data sets. Each
of the above assays, A1 to E20 is carried out with the wild type cancer cell line, which
provides a first input data set. The assays, wild type cancer cell line and the genetically
engineered cell line are used to generate the first input data set and a second input data
25 set. The first and second data sets constitute initial data sets. The data sets comprise
data corresponding to the parameters/assays A1 to E20 for each of the cell lines,
thereby creating two baselines, one for growing cells and the other for moving cells.
21
[0089] A patient data set is further generated by conducting the assays A1 to E20 on
patient derived tumor cells or tumor tissue samples. For this, tissue from cancer patients
is collected as per Standard Operating Procedures (SOP), minimizing the ischemia time
into standardized buffer, transported to laboratory in cold boxes. A section or small
5 tissue is then submitted for H&E (hematoxylin and eosin) processing and the rest of
the tumor is treated to isolate a single cell population as per SOP. This gives P0 of the
patient tumor, which is then sub- cultured till P4 or P5, and cells from these subcultures are used in the assay platform A1 to E20 to generate a patient dataset, which
comprises data corresponding to the parameters A1 to E20.
10 [0090] FIG. 24A and 24B are a representation depicting overexpression strategy to
convert non-metastatic (non-met) cells to metastatic (met) cell and CRISPR CAS 9
mediated conversion of met to non-met cells respectively, showing vectors
construction for genetically engineered cell lines, to increase or decrease PR and
metastatic properties, the cell lines were engineered by both constitutive and inducible
15 transfection for overexpression and CRISPR CAS 9 mediated under expression. In an
example, genetically engineered cell lines of HT 29: 5 inducible clone, 1 constitutive
clone; SW 480: 2 constitutive clones; HCT 116: 2 constitutive clones were used in
conducting assays as disclosed herein. FIGs. 25A, 25B, 26A and 26B are radial chart
representations depicting values and correlation of parameter of the assays for wild
20 type and engineered cell line, and also representative patient data samples; wherein
FIG. 25A depicts values and correlation of parameter of the assays for wild type cell
lines, viz. HT 29, HCT 116, SW480 and COLO 205; FIG. 25B depicts values and
correlation of parameter of the assays for engineered constitutive and inducible clones
of HT29; FIG. 26A depicts values and correlation of parameter of the assays for
25 engineered (by CRISPR CAS9) cell lines; and FIG. 26B depicts values and correlation
of parameter of the assays for five representative patient samples.
[0091] In addition to generating the initial data sets obtained from the cell lines and
patient data set obtained from patient tumor sample, an in vitro inhibitory potency data
22
of multiple compounds can be obtained by screening multiple compounds, can be either
approved drugs (repurposing) or novel compound libraries (new drug discovery), on
the cancer cell lines to generate a compound dataset. The compound data set is
generated by studying the effect of multiple compound(s) on both wild type and
5 genetically engineered tumor cell lines, through A1 to E20, to obtain metastasis
inhibitory potency data of compounds. The plasticity ratio (PR) in the epithelial to
mesenchymal transition and mesenchymal to epithelial transition is an essential part of
the compound data set. The compounds/drugs used for initial proof-of-concept (POC)
are all approved drugs, with literature curated information on their efficacy, safety and
10 toxicity along with all pharmacological data.
[0092] In step 103, the data sets (comprising of the initial datasets, the patient dataset,
and the compound dataset) are used to generate a predictive model. The initial dataset
is normalized in accordance with the respective patient dataset (which can be
associated with each tumor type). Correlations between the initial dataset and a first
15 output can be generated by assigning a weightage to each of the parameters of the initial
dataset for various outputs. The first output gives an indication of whether the tumor is
a metastatic tumor (step 104). The metastasis inhibitory potency data of
compounds/drugs in the compound dataset is normalized with respect to assigned
weightages of parameters of the initial data set and correlations are generated between
20 the initial dataset and a second output. The second output gives an indication of the
inhibitory potency of the compounds/drugs (step 105). The compound data set is
normalized with respect to the weightages that are assigned/imparted to each parameter
during the first normalization of the initial data set, where the patient data sets are used.
However, for certain validation cases, the patient sample data set may be used for
25 compounds, but it will be only for validation purposes. The generated correlations are
mapped to generate the predictive model, wherein the predictive model defines
association(s) between the parameters of the initial dataset and the first and second
outputs.
23
[0093] The various actions in method 100 may be performed in the order presented, in
a different order or simultaneously. Further, in some embodiments, some actions listed
in FIG. 1 may be omitted.
[0094] FIG. 27 depicts a system for determining the ability of at least one cancer cell
5 to metastasize and for screening of drugs for their potential use in inhibiting cancer
metastasis. The system 2200 can identify the metastatic potential of a tumor and
identifying compound(s) that have the maximum potency against parameters of the
assays with maximum weightages, thereby identifying a combination that would help
delay or prevent metastasis in animal models. This would help filter compounds for
10 drug discovery and expedite the discovery screening procedure for candidate drugs.
The system 2200, as depicted, comprises a processing module 2201, a memory 2202,
an output module 2203, and a communication interface 2204.
[0095] The memory 2202 stores at least one of, the initial data set, the patient dataset
for each tumor type, the compound dataset, data used by the assays, data generated
15 from the assays, data generated by the processing module 2201, and so on. Examples
of the memory 2202 may be, but are not limited to, NAND, embedded Multimedia
Card (eMMC), Secure Digital (SD) cards, Universal Serial Bus (USB), Serial
Advanced Technology Attachment (SATA), solid-state drive (SSD), and so on.
Further, the memory 2202 may include one or more computer- readable storage media.
20 The memory 2202 may include one or more non-volatile storage elements. Examples
of such non-volatile storage elements may include magnetic hard discs, optical discs,
floppy discs, flash memories, or forms of electrically programmable memories
(EPROM) or electrically erasable and programmable (EEPROM) memories. In
addition, the memory 2202 may, in some examples, be considered a non-transitory
25 storage medium. The term "non- transitory" may indicate that the storage medium is
not embodied in a carrier wave or a propagated signal. However, the term "nontransitory" should not be interpreted to mean that the memory is non-movable. In
24
certain examples, a non- transitory storage medium may store data that can, over time,
change (e.g., in Random Access Memory (RAM) or cache).
[0096] The memory 2202 may be present remotely. Examples of the memory 2202 can
be, but not limited to, a data server, a file server, the Cloud, and so on.
5 [0097] The processing module 2201 may include one or a plurality of processors. The
one or a plurality of processors may be a general-purpose processor, such as a central
processing unit (CPU), an application processor (AP), or the like, a graphics-only
processing unit such as a graphics processing unit (GPU), a visual processing unit
(VPU), and/or an Artificial Intelligence (AI)-dedicated processor such as a neural
10 processing unit (NPU).
[0098] The processing module 2201 can fetch the initial dataset, the patient dataset
associated with each tumor type and the compound dataset from the memory 2202.
The processing module 2201 maps the generated correlations to generate a predictive
model. Mapping can be done using at least one of a classified supervised model and/or
15 an unsupervised learning, using neuronal networks. The predictive model defines an
association between the parameters of the initial dataset and the first and second
outputs. The processing module 2201 can receive at least one input value
corresponding to at least one parameter of the assay from a user (either directly via the
communication interface 2204 or from the memory 2202). The input value is derived
20 from an unknown patient tumor sample. The processing module 2201 can map the
received input values into the predictive model and generate a predictive/prescriptive
solution. The predictive/prescriptive solution includes probability of a tumor to
metastasize and/or inhibitory potency of compound(s)/drug(s).
[0099] The processing module 2201 can normalize the initial dataset, in accordance
25 with the respective patient dataset. The processing module 2201 can generate
correlations between the initial dataset and a first output, using classified supervised
learning, by assigning a weightage to each of the parameters of the initial dataset for
various outputs. The processing module 2201 can generate the correlations between
25
initial dataset and the output by dividing the initial and patient datasets corresponding
to each tumor type into the following three sets; a training set; a validation set; and a
test set. The training set is a dataset that is used for training the predictive model based
on the initial dataset and the patient dataset. The validation set is a dataset which is
5 used to evaluate and improve the trained model.
Once the model is completely trained, the test set provides the unbiased evaluation of
the model. The predictive model receives the inputs of test data and predicts output
without seeing the actual output. After prediction, the model is evaluated by comparing
its output with the actual output present in the test set. Thus, validation and test sets are
10 used for minimizing any overfits or underfits in the trained model.
FIG. 28 depicts an example correlation matrix with a heatmap (positive and inverse).
The first output gives an indication of whether the tumor is a metastatic tumor.
[00100] The processing module 2201 can normalize the metastasis inhibitory potency
data of compounds in the compound dataset with respect to the assigned weightages of
15 parameters of the initial data set and generate correlations between the initial dataset
and a second output via non supervised learning using neuronal networks. The second
output gives an indication of the inhibitory potency of the compounds. The processing
module 2201 normalizes the compound data set with respect to the weightages that are
assigned/imparted to each parameter during the first normalization of the initial data
20 set, where the patient data sets are used. Similarly, for screening of drugs, the
processing module normalizes initial dataset relating to each tumor type with respective
compound dataset and generates the correlations between initial dataset and the output
by dividing the initial and compound datasets corresponding to each tumor type into
the following three sets; a training set; a validation set; and a test set. The training set
25 is a dataset that is used for training the predictive model based on the initial and the
compound dataset. The validation set is a dataset which is used to evaluate and improve
the trained model. Once the model is completely trained, the test set provides the
unbiased evaluation of the model. The model receives the inputs of test data and
26
predicts output without seeing the actual output. After prediction, the model is
evaluated by comparing its output with the actual output present in the test set. Thus,
validation and test sets are used for minimizing any overfits or underfits in the trained
model. However, for certain validation cases, the patient sample data set may be used
5 for compounds/drugs, but it will be only for validation purposes.
[00101] The communication interface 2204 can enable the system 2200 to
communicate with at least one external device, such as the memory 2202. The
communication interface 2204 may include at least one of, but is not limited to, a wired
network, a value-added network, a wireless network, a satellite network, or a
10 combination thereof. Examples of the wired network may be, but are not limited to, a
Local Area Network (LAN), a Wide Area Network (WAN), an Ethernet, and so on.
Examples of the wireless network may be, but are not limited to, a cellular network, a
wireless LAN (Wi-Fi), Bluetooth, Bluetooth low energy, Zigbee, Wi-Fi Direct (WFD),
Ultra-wideband (UWB), infrared data association (IrDA), near field communication
15 (NFC), and so on.
[00102] The output module 2203 can enable data generated by the processing module
2201 to be presented to at least one external entity. Examples of the external entity can
be, but not limited to, a user, an administrator, and so on. The output module 2203 can
store the data generated by the system 2200 in the memory 2202 or any other suitable
20 location. Examples of the output module 2203 can be, but not limited to, a display, a
printer, and so on.
[00103] The model generated by the processing module 2201 is cancer agnostic; i.e.,
independent of the tumor type. The correlations used for generating the model are
drawn from the individual tumor based models. Thus, the final cancer agnostic model
25 will be able to predict metastasis probability and compound potential with higher
sensitivity, as it would be a culmination of iterative cycles of normalization and
validation with thousands and thousands of data sets.
27
[00104] It is not practically feasible to correlate all the individual facets of metastasis
directly to each other. Some facets are totally independent of each other; for example,
angiogenesis and platelet activation, whereas some others can be interconnected, e.g.
EMT and MET. Therefore, the processing module 2201 is designed to bin the assays
5 in such way that each bin will have assays whose biology are connected. Any dual
inhibitory activity within a bin would be more representative of additive nature,
whereas dual inhibition across bins would be more synergistic in nature.
[00105] The processing module 2201 generates a sub-model for fitting the dataset
contained in each of the bins. The processing module 2201 subsequently analyses these
10 sub-models for specific patterns within the same bins and then creates further patterns
connecting different bins. Based on inter-bin pattern interactions, the processing
module 2201 generates the cancer agnostic module to make decisions and predictions.
[00106] The processing module 2201 may employ Support vector machines, Neural
networks, or Deep neural network techniques for assessing the probability of
15 multivariate pattern interactions, to identify the best fit.
[00107] The processing module 2201 comprises a self-learning editor. The editor can
receive and store dataset relating to unknown tumor samples and corresponding
predictions in the repository. The processing module 2201 uses this data to re-train the
predictive model for improving its accuracy of predicting the output. The output
20 module 2203 is configured to display the collective score assigned to at least one of the
above features indicating the likelihood of cancer metastasis of the patient tumor
sample and/or inhibitory potency of compound(s).
[00108] FIG. 27 shows exemplary blocks of the system 2200, but it is to be understood
that other embodiments are not limited thereon. In other embodiments, the system 2200
25 may include less or more number of blocks. Further, the labels or names of the blocks
are used only for illustrative purpose and does not limit the scope of the embodiments
herein. One or more blocks can be combined to perform same or substantially similar
function in the system 2200.
28
[00109] Embodiments herein further disclose a method for treatment of metastatic
cancer at various stages of metastasis.
[00110] The embodiments disclosed herein can be implemented through at least one
software program running on at least one hardware device and performing network
5 management functions to control the network elements. The elements include blocks
which can be at least one of a hardware devices, or a combination of hardware device
and software module.
[00111] The embodiment disclosed herein describes methods and systems for
determining the ability of at least one cancer cell to metastasize and for screening of
10 compounds/drugs for their potential use in inhibiting cancer metastasis. Therefore, it is
understood that the scope of the protection is extended to such a program and in
addition to a computer readable means having a message therein, such computer
readable storage means contain program code means for implementation of one or
more steps of the method, when the program runs on a server or mobile device or any
15 suitable programmable device. The method is implemented in at least one embodiment
through or together with a software program written in e.g. Very high speed integrated
circuit Hardware Description Language (VHDL) another programming language, or
implemented by one or more VHDL or several software modules being executed on at
least one hardware device. The hardware device can be any kind of portable device that
20 can be programmed. The device may also include means which could be e.g. hardware
means like e.g. an ASIC, or a combination of hardware and software means, e.g. an
ASIC and an FPGA, or at least one microprocessor and at least one memory with
software modules located therein. The method embodiments described herein could be
implemented partly in hardware and partly in software. Alternatively, the invention
25 may be implemented on different hardware devices, e.g. using a plurality of CPUs.
[00112] The foregoing description of the specific embodiments will so fully reveal the
general nature of the embodiments herein that others can, by applying current
knowledge, readily modify and/or adapt for various applications such specific
29
embodiments without departing from the generic concept, and, therefore, such
adaptations and modifications should and are intended to be comprehended within the
meaning and range of equivalents of the disclosed embodiments. It is to be understood
that the phraseology or terminology employed herein is for the purpose of description
5 and not of limitation. Therefore, while the embodiments herein have been described in
terms of embodiments and examples, those skilled in the art will recognize that the
embodiments and examples disclosed herein can be practiced with modification within
the scope of the embodiments as described herein.

We claim,
1. A method for determining the ability of at least one cancer cell to metastasize,
the method comprising
conducting (101) cell-based assays in at least one of wild type tumor cell
5 lines, genetically engineered tumor cell lines and patient derived tumor cells;
obtaining (102), by the system (2200), initial datasets, and a patient dataset
from the conducted cell based assays;
generating (103), by the system (2200), a predictive model using the
datasets; and
10 determining (104), by the system (2200), ability of at least one cancer cell to
metastasize using the predictive model.
2. The method, as claimed in claim 1, wherein the cell assays comprise
group A assays for characterizing cells;
15 group B assays for evaluating the ability of the cells to move out of an
epithelial layer;
group C assays for evaluating ability of the tumor cell to enter endothelial
system (blood), survive in the endothelial system and migrate from the
endothelial system to a secondary site;
20 group D assays for evaluating ability of tumor cells to survive in the
secondary site, cross talk with the tissue in the secondary site and successfully
grow to a tumor in the secondary site; and
group E extrinsic assays for evaluating the ability of tumor cells to survive
oxidative and nutrient stress and remain dormant;
25
3. The method, as claimed in claim 2, wherein group A assays comprise of evaluating
31
epithelial to mesenchymal ratio in a tumor (A2) by comparing a total
percentage of mesenchymal markers to a total percentage of epithelial markers
to generate a Plasticity Ratio (PR), wherein PR is directly proportional to
invasiveness;
5 stemness of the cell (A3) by analyzing stem cell markers using flow
cytometry and immunofluorescence; and
doubling time of tumor (A4), which is total time taken by the tumor to
double number of cells of the tumor and the doubling time is measured by adding
a labeled dye into the cells of the tumor and monitoring incorporation of the
10 labeled dye into DNA of the cells.
4. The method, as claimed in claim 2, wherein group B assays comprise of evaluating
adhesion (B5) by measuring ability of tumor cells to bind to epithelial
membranes using synthetic proteins that mimic epithelial membrane proteins;
15 migration (B6) by measuring ability of tumor cells to move away from
the tumor towards a chemoattractant signature using a two-chamber system,
divided by a permeable tissue culture plate insert, that are laid over a
chemoattractant, with the tumor cells being plated on top of the insert; and
invasion (B7) by measuring the ability of tumor cells to tear through
20 the epithelial membrane and move towards the chemoattractant.
5. The method, as claimed in claim 2, wherein group C assays comprise of evaluating
intravasation (C8), which comprises of determining ability of tumor cells to
invade through the endothelial layer in the presence of stimuli and ability to cleave
25 through the endothelial membrane, moving towards enriched blood by studying the
monolayer formation of the endothelial layer, the integrity of the endothelial layer
and measuring the amount of tumor cells that successfully invade through the
endothelial layer;
32
tumor Cell Induced Platelet Aggregation (TCIPA) (C9), wherein TCIPA is
ability of tumor cells to bind with platelets and subsequently activate them and
TCIPA is evaluated by measuring change in an optical density of the tumor cell
binding with platelets and subsequent platelet aggregation, using a co-culture of
5 platelet rich plasma (PRP) and tumor cells; and
extravasation (C10), which is ability of tumor cells to break out of the
endothelial layer to an external tissue and is measured by co-incubating the
enriched blood and tumor cells together on a permeable tissue culture plate insert,
wherein a primary endothelial cell layer is coated on the insert and checking for
10 integrity of the endothelial cell layer.
6. The method, as claimed in claim 2, wherein group D assays comprise of evaluating
mesenchymal to epithelial transition (MET) (D11), which is ability of the
tumor cells to change from a moving cellular form back to a growing cellular form
15 by detecting a change in epithelial and mesenchymal cell markers, on treating the
cells with agents promoting MET, wherein MET is characterized by measuring the
PR ratio using flow cytometry and at least one imaging technique, wherein the
imaging technique uses fluorescence markers using multiple proteins as markers;
apoptosis (D12) by checking amount of caspase 3 released by tumor
20 cells;
energy metabolism of tumor cells (D13) by measuring parameters
including, but not limited to, lactate consumption, glutamate production,
NADH/NADPH and Reactive Oxygen Species (ROS) production; and
25 7. The method, as claimed in claim 2, wherein group E assays comprise of
evaluating
cytotoxicity (E15) comprises of detecting low level/early cellular damage by
measuring Lactate Dehydrogenase (LDH) activity;
33
angiogenesis (E16), which is ability of tumors to form new blood vessels in
the secondary site or compounds to inhibit angiogenesis;
immune profiling (E17), which comprises of measuring PD-L1 across
epithelial and mesenchymal forms (percent population change) of the cell lines and
5 the primary cells, and measuring CD-73 across epithelial and mesenchymal forms
of the cell lines and the primary cells;
autophagy analysis (E18), which comprises of determining how dormant cells
survive in a nutrient deficient environment;
effect of hypoxia (E19) on different cell types, by induction with cobalt
10 chloride; and
cell cycle analysis by Ki67 (E20) distinguishing between the G0 and M phases,
determining dormancy
8. The method, as claimed in claim 1, wherein the patient data set is generated by
15 conducting the assays on patient derived tumor tissue samples, which comprises
obtaining tissue from cancer patients;
submitting a section of the collected tissue for hematoxylin and eosin
processing;
treating at least a portion of the tumor to isolate a single cell population of
20 the tumor to obtain P0 of the patient tumor, wherein the single cell population of the
tumor is isolated using enzymatic degradation and negative selection;
subculturing the obtained P0 of the patient tumor till P4 or P5; and
generating the patient dataset using cells from the sub-cultures in the assays.
25 9. The method, as claimed in claim 1, wherein generating the predictive model
comprises
normalizing the initial dataset in accordance with the patient dataset;
34
generating correlations between the initial dataset and a first output by
assigning a weightage to each of the parameters of the initial dataset for various
outputs, wherein the first output gives an indication of whether the tumor is a
metastatic tumor; and
5 mapping the generated correlations to generate the predictive model.
10. The method, as claimed in claim 9 , wherein determining ability of at least one
cancer cell to metastasize using the predictive model comprises
mapping at least one received input value into the predictive model;
10 and
generating a predictive/prescriptive solution, wherein the generated
solution indicates ability of at least one cancer cell to metastasize.
11. A method for screening of compounds/drugs for their potential use in inhibiting
15 cancer metastasis, the method comprising
conducting (101) cell-based assays in at least one of wild type tumor cell
lines, genetically engineered tumor cell lines and patient derived tumor cells;
obtaining, by the system (2200), initial datasets, a patient dataset and a
compound dataset from the conducted cell based assays;
20 generating (103), by the system (2200), a predictive model using the datasets;
and
determining (105), by the system (2200), at least one compound/drug for
their potential use in inhibiting cancer metastasis using the predictive model.
25 12. The method, as claimed in claim 11, wherein the cell assays comprise
group A assays for characterizing cells;
group B assays for evaluating the ability of the cells to move out of an
epithelial layer;
35
group C assays for evaluating ability of the tumor cell to enter
endothelial system (blood), survive in the endothelial system and migrate from
the endothelial system to a secondary site;
group D assays for evaluating ability of tumor cells to survive in the
5 secondary site, cross talk with the tissue in the secondary site and successfully
grow to a tumor in the secondary site; and
group E extrinsic assays for evaluating the ability of tumor cells to
survive oxidative and nutrient stress and remain dormant;
10 13. The method, as claimed in claim 12, wherein group A assays comprise of
evaluating
chemosensitivity (A1) by checking ability of a tumor cell to survive
upon treatment with multiple chemotherapeutic drugs;
epithelial to mesenchymal ratio in a tumor (A2) by comparing a total
15 percentage of mesenchymal markers to a total percentage of epithelial markers
to generate a Plasticity Ratio (PR), wherein PR is directly proportional to
invasiveness;
stemness of the cell (A3) by analyzing stem cell markers using flow
cytometry and immunofluorescence; and
20 doubling time of tumor (A4), which is total time taken by the tumor to
double number of cells of the tumor and the doubling time is measured by
adding a labelled dye into the cells of the tumor and monitoring incorporation
of the labelled dye into DNA of the cells.
25 14. The method, as claimed in claim12 , wherein group B assays comprise of
evaluating
adhesion (B5) by measuring ability of tumor cells to bind to epithelial
membranes using synthetic proteins that mimic epithelial membrane
36
proteins;
migration (B6) by measuring ability of tumor cells to move away from
the tumor towards a chemoattractant signature using a two chamber system,
divided by a permeable tissue culture plate insert, that are laid over a
5 chemoattractant, with the tumor cells being plated on top of the insert; and
invasion (B7) by measuring the ability of tumor cells to tear through
the epithelial membrane and move towards the chemoattractant.
15. The method, as claimed in claim 12, wherein group C assays comprise of
10 evaluating
intravasation (C8), which comprises of determining ability of tumor cells
to invade through the endothelial layer in the presence of stimuli and ability to
cleave through the endothelial membrane, moving towards enriched blood by
studying the monolayer formation of the endothelial layer, the integrity of the
15 endothelial layer and measuring the amount of tumor cells that successfully
invade through the endothelial layer;
Tumor Cell Induced Platelet Aggregation (TCIPA) (C9), wherein TCIPA
is ability of tumor cells to bind with platelets and subsequently activate them and
TCIPA is evaluated by measuring change in an optical density of the tumor cell
20 binding with platelets and subsequent platelet aggregation, using a co-culture of
Platelet rich plasma (PRP) and tumor cells;
and
extravasation (C10), which is ability of tumor cells to break out of the
endothelial layer to an external tissue and is measured by co-incubating the
25 enriched blood and tumor cells together on a permeable tissue culture plate insert,
wherein a primary endothelial cell layer is coated on the permeable tissue culture
plate insert and checking for integrity of the endothelial cell layer.
37
16. The method, as claimed in claim 12, wherein group D assays comprise of
evaluating
mesenchymal to epithelial transition (MET) (D11), which is ability of
the tumor cells to change from a moving cellular form back to a growing cellular
5 form by detecting a change in epithelial and mesenchymal cell markers, on
treating the cells with agents promoting MET, wherein MET is characterized by
measuring the PR ratio using flow cytometry and at least one imaging technique,
wherein the imaging technique uses fluorescence markers using multiple
proteins as markers;
10 apoptosis (D12) by checking amount of caspase 3 released by tumor
cells;
energy metabolism of tumor cells (D13) by measuring parameters
including, but not limited to, lactate consumption, glutamate production,
NADH/NADPH and Reactive Oxygen Species (ROS) production; and
15 exosome vesicles secretion and uptake (D14), which comprises of
measuring ability of the tumor cells to grow in a foreign secondary environment
by isolating exosomes and quantitating from cell cultures, of moving and
growing cells, and from genetically modified cells, labelling the isolated and
quantitated exosomes, and evaluating uptake of exosomes in the cells using the
20 labelled exosomes.
17. The method, as claimed in claim12 , wherein group E assays comprise of
evaluating
cytotoxicity (E15) comprises of detecting low level/early cellular
25 damage by measuring Lactate Dehydrogenase (LDH) activity;
angiogenesis (E16), which is ability of compounds to inhibit
angiogenesis;
38
immune profiling (E17), which comprises of measuring PD-L1 across
epithelial and mesenchymal forms of the cell lines and the primary cells (Percent
population change) and measuring CD-73 across epithelial and mesenchymal
forms of the cell lines and the primary cells;
5 autophagy analysis (E18), which comprises of determining how
dormant cells survive in a nutrient deficient environment;
effect of hypoxia (E19) on different cell types, by induction with cobalt
chloride; and
cell cycle analysis by Ki67 (E20) distinguishing between the G0 and M
10 phases.
18. The method, as claimed in claim11 , wherein the patient data set is generated by
conducting the assays on patient derived tumor tissue samples, which
comprises
15 obtaining tissue from cancer patients;
submitting a section of the collected tissue for H&E processing;
treating at least a portion of the tumor to isolate a single cell
population of the tumor as to obtain P0 of the patient tumor, wherein the single
cell population of the tumor is isolated using enzymatic degradation and
20 negative selection;
subculturing the obtained P0 of the patient tumor till P4 or P5; and
generating the patient dataset using cells from the sub-cultures in the
assays.
25 19. The method, as claimed in claim 11 , wherein the compound dataset is obtained
by studying effect of multiple compound(s) on wild type and genetically
engineered tumor cell lines, through the assays, to obtain metastasis inhibitory
potency data of compounds, wherein the compound dataset comprises of a
39
plasticity ratio (PR) in the epithelial to mesenchymal transition and
mesenchymal to epithelial transition.
20. The method, as claimed in claim 11, wherein generating the predictive model
5 comprises
normalizing the initial dataset in accordance with assigned weightages
of parameters of the initial data set;
generating correlations between the initial dataset and a second
output, wherein the second output gives an indication of the inhibitory potency
10 of the compounds; and
mapping the generated correlations to generate the predictive model.
21. The method, as claimed in claim 20 , wherein at least one compound/drug for
their potential use in inhibiting cancer metastasis using the predictive model
15 comprises
mapping at least one received input value into the predictive model;
and
generating a predictive/prescriptive solution, wherein the generated
solution indicates at least one compound/drug which may be used in
20 inhibiting cancer metastasis.
22. A system (2202) comprising:
a memory (2203); and
a processing module (2201) coupled to the memory (2203) configured
25 to:
obtain initial datasets, a patient dataset, and a compound dataset from a
plurality of cell based assays;
generate a predictive model using the datasets;
40
determine ability of at least one cancer cell to metastasize using the
predictive model; and
determine at least one compound/drug for their potential use in
inhibiting cancer metastasis using the predictive model.
5
23. The system, as claimed in claim 22, wherein the cell assays are conducted in
at least one of wild type tumor cell lines, genetically engineered tumor cell lines
and patient derived tumor cells and the cell assays comprise
group A assays for characterizing cells;
10 group B assays for evaluating the ability of the cells to move out of an
epithelial layer;
group C assays for evaluating ability of the tumor cell to enter
endothelial system (blood), survive in the endothelial system and migrate from
the endothelial system to a secondary site;
15 group D assays for evaluating ability of tumor cells to survive in the
secondary site, cross talk with the tissue in the secondary site and successfully
grow to a tumor in the secondary site; and
group E extrinsic assays.
20 24. The system, as claimed in claim 23, wherein group A assays comprise of
evaluating
chemosensitivity (A1) by checking ability of a tumor cell to survive
upon treatment with multiple chemotherapeutic drugs;
epithelial to mesenchymal ratio in a tumor (A2) by comparing a total
25 percentage of mesenchymal markers to a total percentage of epithelial markers
to generate a Plasticity Ratio (PR), wherein PR is directly
proportional to invasiveness;
stemness of the cell (A3) by analyzing stem cell markers using flow
cytometry and immunofluorescence; and
41
doubling time of tumor (A4), which is total time taken by the tumor
to double number of cells of the tumor and the doubling time is measured by
adding a labelled dye into the cells of the tumor and monitoring incorporation
of the labelled dye into DNA of the cells.
5
25. The system, as claimed in claim 23, wherein group B assays comprise of
evaluating
adhesion (B5) by measuring ability of tumor cells to bind to epithelial
membranes using synthetic proteins that mimic epithelial membrane proteins;
10 migration (B6) by measuring ability of tumor cells to move away from
the tumor towards a chemoattractant signature using a two chamber system,
divided by a permeable tissue culture plate insert, that are laid over a
chemoattractant, with the tumor cells being plated on top of the insert; and
invasion (B7) by measuring the ability of tumor cells to tear through
15 the epithelial membrane and move towards the chemoattractant.
26.The system, as claimed in claim 23, wherein group C assays comprise of
evaluating
intravasation (C8), which comprises of determining ability of tumor
20 cells to invade through the endothelial layer in the presence of stimuli and
ability to cleave through the endothelial membrane, moving towards enriched
blood by studying the monolayer formation of the endothelial layer, the
integrity of the endothelial layer and measuring the amount of tumor cells that
successfully invade through the endothelial layer;
25 Tumor Cell Induced Platelet Aggregation (TCIPA) (C9), wherein
TCIPA is ability of tumor cells to bind with platelets and subsequently activate
them and TCIPA is evaluated by measuring change in an optical density of the
tumor cell binding with platelets and subsequent platelet aggregation, using a
co-culture of Platelet rich plasma (PRP) and tumor cells;
42
and
extravasation (C10), which is ability of tumor cells to break out of the
endothelial layer to an external tissue and is measured by co-incubating the
enriched blood and tumor cells together on a permeable tissue culture plate
5 insert, wherein a primary endothelial cell layer is coated on the insert
andchecking for integrity of the endothelial cell layer.
27.The system, as claimed in claim 23, wherein group D assays comprise of
evaluating
10 mesenchymal to epithelial transition (MET) (D11), which is ability of
the tumor cells to change from a moving cellular form back to a growing cellular
form by detecting a change in epithelial and mesenchymal cell markers, on
treating the cells with agents promoting MET, wherein MET is characterized by
measuring the PR ratio using flow cytometry and at least one imaging technique,
15 wherein the imaging technique uses fluorescence markers using multiple
proteins as markers;
apoptosis (D12) by checking amount of caspase 3 released by tumor
cells;
energy metabolism of tumor cells (D13) by measuring parameters
20 including, but not limited to, lactate consumption, glutamate production,
NADH/NADPH and Reactive Oxygen Species (ROS) production; and
Exosome vesicles secretion and uptake (D14), which comprises of
measuring ability of the tumor cells to grow in a foreign secondary environment
by isolating exosomes and quantitating from cell cultures, of moving and
25 growing cells, and from genetically modified cells, labelling the isolated and
quantitated exosomes, and evaluating uptake of exosomes in the cells using the
labelled exosomes.
43
28. The system, as claimed in claim 23, wherein group E assays comprise of
evaluating
cytotoxicity (E15) comprises of detecting low level/early cellular
damage by measuring Lactate Dehydrogenase (LDH) activity;
5 Angiogenesis (E16), which is ability of compounds to inhibit
angiogenesis;
immune profiling (E17), which comprises of measuring PD-L1
across epithelial and mesenchymal forms of the cell lines and the primary cells
(Percent population change) and measuring CD-73 across epithelial and
10 mesenchymal forms of the cell lines and the primary cells;
autophagy analysis (E18), which comprises of determining how
dormant cells survive in a nutrient deficient environment;
effect of hypoxia (E19) on different cell types, by induction with
cobalt chloride; and
15 cell cycle analysis by Ki67 (E20) distinguishing between the G0 and
M phases.
29. The system, as claimed in claim 23, wherein the initial data sets comprise data
corresponding to the assays for each of growing cell lines, and moving cell
20 lines.
30. The system, as claimed in claim 23, wherein the patient data set is generated
by conducting the assays on patient derived tumor tissue samples, which
comprises
25 obtaining tissue from cancer patients;
submitting a section of the collected tissue for H&E processing;
treating at least a portion of the tumor to isolate a single cell population
of the tumor to obtain P0 of the patient tumor, wherein the single cell
44
population of the tumor is isolated using enzymatic degradation and negative
selection;
subculturing the obtained P0 of the patient tumor till P4 or P5; and
generating the patient dataset using cells from the sub-cultures in the assays.
5
31. The system, as claimed in claim 23, wherein generating the predictive model
comprises
normalizing the initial dataset in accordance with the patient dataset;
generating correlations between the initial dataset and a first output
10 by assigning a weightage to each of the parameters of the initial dataset for
various outputs, wherein the first output gives an indication of whether or not
the tumor is a metastatic tumor; and
mapping the generated correlations to generate the predictive model.
15 32. The system, as claimed in claim 23, wherein generating the predictive model
comprises
normalizing the initial dataset in accordance with assigned weightages
of parameters of the initial data set;
generating correlations between the initial dataset and a second
20 output, wherein the second output gives an indication of the inhibitory potency
of the compounds; and
mapping the generated correlations to generate the predictive model.
33.The method, as claimed in claim 9, wherein determining ability of at least one
25 cancer cell to metastasize using the predictive model comprises
mapping at least one received input value into the predictive model;
and
generating a predictive/prescriptive solution, wherein the generated
solution indicates ability of at least one cancer cell to metastasize.
45
34. The method, as claimed in claim 20, wherein at least one compound/drug for
their potential use in inhibiting cancer metastasis using the predictive model
comprises
5 mapping at least one received input value into the predictive model;
and
generating a predictive/prescriptive solution, wherein the generated solution
indicates at least one compound/drug which may be used in inhibiting cancer
metastasis.