Claims:WE CLAIM:
1. A method for early diagnosis of ovarian cancer in a subject comprises of:
a. measuring the level of five biomarkers comprising of CA125, SPP1, IGFBP2, ADIPSIN and TSP1 in a sample from the said subject and;
b. correlating the measurements of the presence, absence, or level of the measured CA125, SPP1, IGFBP2, ADIPSIN and TSP1 biomarkers with ovarian cancer status.
2. The method as claimed in claim 1 further comprises of measuring and correlating atleast one or both biomarkers selected from the group consisting of CYSTATIN C and ICAM1.
3. The method as claimed in claim 1, wherein the said biomarkers CA125, SPP1, IGFBP2, ADIPSIN and TSP1are measured by any conventional methods including sandwich ELISA, ELISA, CHIP based detection, bead based fluorescent or non-fluorescent detection, LC-MS-MS, HPLC etc.
4. The method as claimed in claim 1 wherein the said sample is plasma or serum or whole blood.
5. The method as claimed in claim 1 wherein the said correlating is performed by a software classification algorithm.
6. The method as claimed in claim 1 wherein the said ovarian cancer status is selected from epithelial ovarian cancer, borderline cancers; mucinous, serous, endometroid carcinomas; germ cell tumors of the ovary; stromal tumors of the ovary; and other malignant conditions.
7. A novel cluster of biomarkers for use in early diagnosis of ovarian cancer in a subject comprises of characterized combination of CA125, SPP1, IGFBP2, ADIPSIN and TSP1.
8. The novel cluster of biomarkers as claimed in claim 7 further comprises of at least one or both biomarkers comprising of CYSTATIN C and ICAM1.
Dated this 31st day of March 2017 For CANCER INSTITUTE
By its Patent Agent

Dr.B.Deepa
, Description:Form 2

THE PATENT ACT, 1970
(39 of 1970)
&
THE PATENT RULES, 2003
COMPLETE SPECIFICATION
(See section 10 and rule 13)

“BIOMARKERS FOR EARLY DIAGNOSIS OF OVARIAN CANCER”

in the name of CANCER INSTITUTE an Indian National having address at CANCER INSTITUTE (WIA), ADYAR, CHENNAI – 600020, Tamil Nadu, India.

The following specification particularly describes the invention and the manner in which it is to be performed
FIELD OF THE INVENTION:
The present invention generally relates to detection of cancer. More specifically the present invention relates to a novel panel of biomarkers and their use in early diagnosis of ovarian cancer.
BACKGROUND OF THE INVENTION AND PRIOR ART:
Epithelial ovarian cancer is another silent killer disease, with no definitive markers or tests for early diagnosis. In ovarian cancers more than 75% are in stage IIIC at presentation, limiting the number of women who can be cured. While transvaginal ultrasound has been combined with CA-125 levels for early detection of ovarian cancer, most studies have failed to show a significant benefit with nearly 72% of cancers detected by multimodal screening being late stage (Partridge et al., 2009).
US 7670792 discloses a method of screening for ovarian neoplasia in a subject comprising: (a) measuring CA125 and ß-hemoglobin in a tissue sample of the subject, and (b) comparing the measured CA125 and ß-hemoglobin of the tissue sample to a measurement of CA125 and ß-hemoglobin in normal tissue, wherein a two-fold or greater increase in the measured CA125 and ß-hemoglobin of the tissue sample compared to the measurement of CA125 and ß-hemoglobin in normal tissue is indicative of ovarian neoplasia.
US 8465929 discloses a method for qualifying ovarian cancer status in a subject comprising: (a) measuring Calcyclin, Calgranulin C and Hepcidin in an ovarian cyst fluid, urine, or serum sample from the subject by mass spectrometry or immunoassay to determine the presence, absence, or level of the measured Calcyclin, Calgranulin C and Hepcidin biomarkers, and (b) correlating the measurements of the presence, absence, or level of the measured Calcyclin, Calgranulin C and Hepcidin biomarkers with ovarian cancer status.
US 8682591 discloses a method of qualifying ovarian cancer status in a subject comprising: (a) measuring using mass spectrometry or an immunoassay, biomarkers comprising modified ApoA1, and one or more modified transthyretin selected from the group consisting of cysteinylated transthyretin, sulfonated transthyretin, CysGly modified transthyretin, glutathionylated transthyretin, and combinations thereof, and (b) comparing the level of one or more of modified ApoA1 and modified transthyretin in said sample to a control level, wherein a decrease in said level of modified ApoA1 and modified transthyretin is indicative of ovarian cancer.
Further the OvaSure test using 6 biomarkers (leptin, prolactin, osteopontin, IGF-2, macrophage inhibitory factor, CA-125) which was introduced to screen high risk women, was subsequently withdrawn and has not been approved by FDA for routine clinical use. Other multiplex marker assays include
1. A four-biomarker panel comprised of CA 125, HE4, carcinoembryonic antigen (CEA), and vascular cell adhesion molecule-1 (VCAM-1) which could discriminate early-stage ovarian cancer (n=44) from the control group (n=929) with 86% SN at 98% SP 22 in the validation set using the Luminex platform [Yurkovetsky et al., 2010]
2. CA-125, transthyretin (TTR), and ApoA1 provided a SN of 93.9% at a SP of 95% in a group of 118 stage I-II ovarian cancer patients and 61 healthy controls, again using the Luminex platform [Kim et al., 2012].
3. SELDI-TOF-MS was used to identify a similar four-biomarker panel of CA 125, ApoA1, TTR and transferrin (TF) providing a SN/SP of 89%/92% for the discrimination of early stage ovarian cancer patients [Su et al., 2007].
4. A 11 analyte assay with CA 125, CA 19-9, EGFR, CRP, myoglobin, ApoA1, ApoCIII, MIP-1a, IL-6, IL-18, and tenascin C panel provided a SN of 91.3% at a SP of 88.5% in a validation set [Amonkar et al., 2009]
5. CA125 with HE4 has been evaluated and found to have a SN of 76.4% and SP of 95% in women with pelvic mass [Moore et al., 2008; 2009].
6. Risk of Ovarian Malignancy Algorithm (ROMA) which incorporates measurements of CA 125 and HE4 along with menopausal status has been approved by FDA for determining ovarian cancer risk in women with pelvic mass [Moore et al., 2011].
However the above said combination of biomarkers for early detection of ovarian cancer suffers various drawbacks which include inability to pick up mucinous carcinomas, germ cell and stromal tumor subtypes. Thus there exists a need in the state of art to develop a novel panel of biomarkers for early diagnosis of ovarian cancer.
OBJECT OF THE PRESENT INVENTION:
The main object of the present invention is to develop a novel cluster of biomarkers for use in early diagnosis of ovarian cancer.
Another object of the present invention is to develop a novel cluster of biomarkers for use in early diagnosis of ovarian cancer comprising of CA125, SPP1, IGFBP2, ADIPSIN and TSP1.
Yet another object of the present invention is to include atleast one or both biomarkers comprising of CYSTATIN C and ICAM1 along with CA125, SPP1, IGFBP2, ADIPSIN and TSP1 for use in early diagnosis of ovarian cancer.
Yet another object of the present invention is to develop methods for early diagnosis of ovarian cancer in a subject comprises of measuring the developed novel cluster of biomarkers in a sample by any conventional methods.
Further object of the present invention is to detect epithelial ovarian cancer particularly serous adenocarcinoma and mucinous carcinomas; borderline cancers; germ cell tumors of the ovary; stromal tumors of the ovary; and other malignant conditions of the ovary employing the developed novel cluster of biomarkers.
BRIEF DESCRIPTION OF DRAWINGS:
Figure 1 illustrates the study design for the identification of novel cluster of protein biomarkers for early detection of ovarian cancer.
Figure 2 illustrates the Schematic of the work flow of LC-MS analysis of the present invention
Figure 3 illustrates Sub-cellular localization of the proteins differentially expressed
Figure 4 illustrates Biological function of the proteins differentially expressed
SUMMARY OF THE INVENTION:
The present invention discloses a novel cluster of biomarkers for use in early diagnosis of ovarian cancer. The novel cluster of biomarkers comprises of characterized combination of CA125, SPP1, IGFBP2, ADIPSIN and TSP1. The novel cluster of biomarkers further comprises of atleast one or more biomarker comprising of CYSTATIN C and ICAM1. The present invention also discloses a method for early diagnosis of ovarian cancer by measuring the novel cluster of biomarkers of the present invention and correlating the measurements with ovarian cancer status.

DETAILED DESCRIPTION OF THE INVENTION:
The present invention discloses a novel panel of biomarkers and their use in early diagnosis of ovarian cancer.
New biomarkers have been identified that are capable early detection of ovarian cancer. LC-MS identification of protein biomarker was used. The samples used were plasma from healthy women who had clinical examination done and plasma from patients with benign conditions of the ovary by histopathological assessment [N=157] and plasma from patients with ovarian cancers [N=118] – serous adenocarcinoma [n=96]; mucinous carcinoma [8]; mucinous borderline tumor [N=3]; endometroid tumor [N=3]; Clear cell carcinoma [N=1]; Germ cell tumors [N=4]; Stromal tumors [N=3].
Immuno-depleted samples from 12 healthy volunteers and 12 serous ovarian adenocarcinoma patients were included in the LC-MS study (Figure 1). The pattern of detection is as follows
• Trypsin digestion
• TMT isobaric labelling
• C18 fractionation
• LC-MS/MS analysis
• Data Analysis
TMT-based quantitative proteomic approach was employed to identify differentially expressed proteins in plasma of patients with ovarian serous adenocarcinoma. Plasma samples from patients with ovarian serous adenocarcinoma and healthy volunteers were depleted of 14 high abundant proteins, labelled with TMT reagents and fractionated by C18 basic RPLC. LC-MS analysis mass spectrometry led to the acquisition of 2,15,587 MS/MS spectra from set1 and 1,93,656 spectra from set2. The schematic of the work flow is shown in Figure 2. MS/MS search against Human RefSeq 65 database using Mascot and SequestHT search algorithms led to the identification of 55,386 peptides in set1 and 92,492 peptides in set2 corresponding to total of 3,163 proteins. A total of 552 proteins were identified to be differentially regulated of which 483were up-regulated (TMT ratios of =1.7) and 69 were down-regulated (TMT ratios of =0.5) in minimum 4 samples out of 7. Sub-cellular localization and biological functions of all up-regulated proteins are given in figure 3 and 4, respectively, using Human Protein Reference Database (HPRD) (http://www.hprd.org).
Experiments were proceeded to validate the dysregulated proteins from LCMS analysis in the ovarian cancer plasma samples (n=82) and healthy control plasma samples (n=78). The Quantibody array, which is based on the principle of sandwich ELISA was used to determine the protein levels of 21 cytokines, chemokines and growth factors. The Median values and the Range of the levels are given in Table 1. CA125 median levels were found to be higher in tumours compared to the levels in normal. IGFBP2, SPP1/OPN, ICAM1, Cystatin C, and LYVE1 levels also were higher in patients with tumours compared to healthy normal individuals. CA125 (p=0), IGFBP2 (p=0.00022), SPP1/OPN (p=0.00988), ICAM1 (p=0.01552), Cystatin C (p=0.0088), and LYVE1 (p=0.01596) levels were significantly different (Mann Whitney U test) between patients with tumours versus healthy normal individuals.

Table 1: The expression levels of plasma biomarkers as determined by Quantibody array in patients with ovarian cancer and in healthy normal individuals.
Biomarkers Normal (ng/ml) Tumor (ng/ml) P-Value Median+
1MAD value ng/ml
Adipsin 41.08 (24.01-105.30) 39.89 (15.15-104.42) 0.14 46.24
B2M 11.49 (0.00-43.42) 12.18 (0.00-42.73) 0.82 15.72
CA125 53.00 (0.00-121.49) 403.31 (42.66-1094.66) 0.00** 87.04
Clusterin 42.13 (24.80-111.05) 41.57 (28.02-124.08) 0.46 47.51
CRP 121.59 (14.73-341.30) 118.65 (73.64-312.23) 0.96 137.29
Cystatin C 323.28 (108.54-2008.30) 359.23 (142.13-1114.54) 0.02* 420.62
Decorin 5.63 (0.59-14.27) 5.16 (0.40-14.07) 0.13 6.71
DKK-3 88.46 (14.65-229.98) 87.90 (39.05-219.75) 0.76 106.44
ICAM-1 201.58 (14.62-1710.25) 152.45 (26.09-1965.77) 0.03* 292.06
IGFBP-2 65.52 (6.13-243.61) 74.39 (41.11-229.00) 0.00** 80.50
IGFBP-3 43.11 (0.00-133.82) 47.50 (1.01-132.80) 0.05* 54.71
IGF-II 31.02 (0.00-143.71) 26.28 (0.00-89.94) 0.44 45.46
Lipocalin -2 5.71 (2.92-25.74) 5.57 (3.90-15.20) 0.27 6.46
LYVE-1 7.05 (4.50-21.06) 7.50 (4.59-21.52) 0.21 8.51
NAP-2 89.83 (53.43-191.83) 85.13 (55.77-165.26) 0.20 104.51
SPP1 213.06 (0.00-981.60) 246.03 (31.13-1120.15) 0.04* 369.14
SAA 55.88 (1.22-168.70) 50.76 (17.10-150.53) 0.06* 74.15
THBS1 651.48 (28.54-2084.38) 659.16 (323.75-2158.00) 0.83 783.01
TF 14.98 (0.00-71.95) 13.23 (0.08-73.21) 0.63 24.36
V-Cadherin 0.00 (0.00-2678.46) 2.46 (0.00-1592.83) 0.46 0.00
VEGFA 0.00 (0.00-7.78) 0.00 (0.00-4.89) 0.05* 0.00
* p-value <0.05; **p-value <0.001

Nine proteins were selected for validation using standard ELISA method. These proteins were selected based on the multivariate analysis of Quantibody array data. These proteins showed distinct expression change in serous epithelial ovarian cancer compared to healthy control.
Experiments were proceeded to validate the dysregulated proteins from Quantibody array analysis in the ovarian cancer plasma samples which included serous, mucinous, clear cell, germ cell tumor (n=36) and age matched healthy control plasma samples (n=79). This also included benign samples in this validation phase.
Using XLSTAT software data was analyzed using the Discriminant Analysis function. The summary of the results are given below. The Training samples included those that had been run on the Quantibody array initially. The Test [Predict] samples included new samples of plasma from healthy women, women who had undergone surgery and found to have a benign condition in the ovary; borderline cancers; mucinous, serous, endometroid carcinomas; germ cell tumors of the ovary; stromal tumors of the ovary; and one clear cell carcinoma.

TABLE 2.1: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125 ONLY

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 33 49 82 59.76%
Total 111 49 160 79.38%
AUC 0.909

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 34 48 82 58.54%
Total 112 48 160 78.75%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 78 1 79 98.73%
1 27 9 36 25.00%
Total 105 10 115 75.65%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 77 1 78 98.72%
1 6 9 15 60.00%
Total 83 10 93 92.47%

negative positive
Mucinous carcinoma/borderline 11 0
Endometroid 3 0
Dysgerminoma 3 0
Stromal tumors 3 0
Fibrothecoma [considered benign] 1 0
clear cell ca 1 0

Table 2.2: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125 AND IGFBP2

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 76 2 78 97.44%
1 13 69 82 84.15%
Total 89 71 160 90.63%
AUC 0.985

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 76 2 78 97.44%
1 13 69 82 84.15%
Total 89 71 160 90.63%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 67 12 79 84.81%
1 18 18 36 50.00%
Total 85 30 115 73.91%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 66 12 78 84.62%
1 4 11 15 73.33%
Total 67 26 93 82.80%

negative positive
Mucinous carcinoma/borderline 7 4
Endometroid 3 0
Dysgerminoma 2 1
Stromal tumors 1 2
Fibrothecoma [considered benign] 0 1
clear cell ca 1 0

Table 2.3: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125 AND SPP1/OPN

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 16 66 82 80.49%
Total 94 66 160 90.00%
AUC 0.967

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 17 65 82 79.27%
Total 95 65 160 89.38%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 72 7 79 91.14%
1 21 15 36 41.67%
Total 84 31 115 75.65%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 71 7 78 84.62%
1 4 11 15 73.33%
Total 67 26 93 82.80%

negative positive
Mucinous carcinoma/borderline 11 0
Endometroid 3 0
Dysgerminoma 1 2
Stromal tumors 1 2
Fibrothecoma [considered benign] 1 0
clear cell ca 1 0

Table 2.4: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125 + IGFBP2+SPP1/OPN

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 9 73 82 89.02%
Total 87 73 160 94.38%
AUC 0.987

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 9 73 82 89.02%
Total 87 73 160 94.38%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 66 13 79 83.54%
1 18 18 36 50.00%
Total 84 31 115 73.04%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 66 13 78 84.62%
1 4 11 15 73.33%
Total 67 26 93 82.80%

negative positive
Mucinous carcinoma/borderline 8 3
Endometroid 3 0
Dysgerminoma 1 2
Stromal tumors 1 2
Fibrothecoma [considered benign] 0 1
clear cell ca 1 0

Table 2.5 DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125+SPP1+IGFBP2+ADIPSIN

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 78 0 78 100.00%
1 8 74 82 90.24%
Total 86 74 160 95.00%
AUC 0.988

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 77 1 78 98.72%
1 9 73 82 89.02%
Total 86 74 160 93.75%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 66 13 79 83.54%
1 17 19 36 52.78%
Total 83 32 115 73.91%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 66 13 78 84.62%
1 4 11 15 73.33%
Total 67 26 93 82.80%

negative positive
Mucinous carcinoma/borderline 7 4
Endometroid 3 0
Dysgerminoma 1 2
Stromal tumors 1 2
Fibrothecoma [considered benign] 0 1
clear cell ca 1 0

Table 2.6: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125+SPP1+IGFBP2+ADIPSIN+TSP1


Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 77 1 78 98.72%
1 5 77 82 93.90%
Total 82 78 160 96.25%
AUC 0.987

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 75 3 78 96.15%
1 8 74 82 90.24%
Total 83 77 160 93.13%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 64 15 79 81.01%
1 15 21 36 58.33%
Total 79 36 115 73.91%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 64 14 78 82.05%
1 3 12 15 80.00%
Total 67 26 93 81.72%

negative positive
Mucinous carcinoma/borderline 6 5
Endometroid 3 0
Dysgerminoma 1 2
Stromal tumors 1 2
Fibrothecoma [considered benign] 0 1
clear cell ca 1 0

Table 2.7: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125+SPP1+IGFBP2+ADIPSIN+TSP1+CYSTATIN C

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 76 2 78 97.44%
1 5 77 82 93.90%
Total 81 79 160 95.63%
AUC 0.988

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 76 2 78 97.44%
1 7 75 82 91.46%
Total 83 77 160 94.38%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 66 13 79 83.54%
1 15 21 36 58.33%
Total 81 34 115 75.65%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 66 12 78 84.62%
1 3 12 15 80.00%
Total 69 24 93 83.87%

negative positive
Mucinous carcinoma/borderline 7 4
Endometroid 3 0
Dysgerminoma 1 2
Stromal tumors 1 2
Fibrothecoma [considered benign] 0 1
clear cell ca 1 0

Table 2.8: DISCRIMINANT ANALYSIS OF SANDWICH ELISA RESULTS FOR CA125+SPP1+IGFBP2+ADIPSIN+TSP1+CYSTATIN C+ICAM1

Confusion matrix for the training sample:
from \ to 0 1 Total % correct
0 76 2 78 97.44%
1 6 76 82 92.68%
Total 82 78 160 95.00%
AUC 0.988

Confusion matrix for the cross-validation results:
from \ to 0 1 Total % correct
0 76 2 78 97.44%
1 6 76 82 92.68%
Total 82 78 160 95.00%

Confusion matrix for the prediction results all cases:
from \ to 0 1 Total % correct
0 65 14 79 82.28%
1 15 21 36 58.33%
Total 81 34 115 74.78%

Confusion matrix for the prediction results only serous ca:
from \ to 0 1 Total % correct
0 65 13 78 83.33%
1 3 12 15 80.00%
Total 69 24 93 82.80%

negative positive
Mucinous carcinoma/borderline 7 4
Endometroid 3 0
Dysgerminoma 1 2
Stromal tumors 1 2
Fibrothecoma [considered benign] 0 1
clear cell ca 1 0

The first row in each Table 2.1 to 2.8 refers to Specificity, while the second row denotes the Sensitivity. The Overall picture is in favour of a 5 parameters assay which would have a better detection rate including the mucinous, borderline, GCT of the ovary.
Table 3.1: The biomarkers expression level determined using Sandwich ELISA in normal, benign and ovarian cancer plasma samples.

Samples
Normal Benign Ovarian cancer
Median (Range) Median (Range) P-value Median (Range) P-value
ADIPSIN (ng/ml) 9354.21
(3611.69-9186.71) 7454.82
(2573.07-20006.17) 0.03* 5787.67
(1764.09-23333.33) 0.00**
Cystatin C (ng/ml) 10758.89
(5837.47-19881.87) 10628.31
(6834.16-32822.42) 0.643 11197.40
(5885.03-22564.02) 0.172
ICAM1 (ng/ml) 281.37
(99.11-802.02) 391.85
(157.02-733.48) 0.009* 309.32
(129.92-897.18) 0.009*
IGFBP2 (ng/ml) 501.72
(149.74-2671.46) 946.45
(260.91-3301.20) 0.002* 1716.67
(354.56-3749.25) 0.00**
IGFBP3 (ng/ml) 748.50
(178.19-2562.50) 788.90
(452.47-2373.94) 0.45 689.72
(116.71-2775.61) 0.638
SPP1 (ng/ml) 22.94
(1.29-87.57) 24.21
(4.58-77.38) 0.132 52.82
(10.19-123.15) 0.00**
TSP1 (mg/ml) 105.77
(17.58-208.10) 104.71
(18.24-160.32) 0.228 89.17
(8.0-193.52) 0.003*
VEGFA (ng/ml) 0.0
(0.0-0.22) 0.0
(0.0-0.09) 0.593 0.00
(0.00-0.41) 0.37
CA125 (U/ml) 18.50
(0.0-437.00) 30.75
(2.50-93.00) 0.033 93.27
(0.00-710.0) 0.00**
*p-value <0.05; **p-value <0.001
The above Table provides the significant differentially expressed proteins in healthy normal women, women with benign ovarian conditions and women with ovarian cancer. Adipsin, ICAM1, IGFBP2, SPP1, TSP1 and CA125 were statistically significantly differentially expressed in cancers.
Table 3.2: Selected best predictive models for the prediction of ovarian cancer based on multiple marker analysis models using median+1MAD cut-off value.

S.No Model Sensitivity Specificity
1 CA125+IGFBP2+SPP1+TSP1+ADI 82.2% (74.09% to 88.63%) 91.24% (85.20% to 95.39%)
2 CA125+IGFBP2+SPP1+TSP1 84.75% (76.97% to 90.70%) 90.51% (84.32% to 94.85%)
3 CA125+IGFBP2 83.9% (76.00% to 90.02%) 88.32% (81.73% to 93.18%)
4 CA125+IGFBP2+SPP1+TSP1+ADI+IGFBP3+ICAM1 77.12% (68.48% to 84.35%) 91.97% (86.09% to 95.92%)
5 CA125+IGFBP2+SPP1+TSP1+ADI+CST 85.59% (77.94% to 91.38%) 84.67% (77.53% to 90.25%)
6 CA125+IGFBP2+SPP1+TSP1+ADI+CST+IGFBP3+ICAM1 78.81% (70.33% to 85.80%) 84.67% (77.53% to 90.25%)
7 CA125 63.56% (54.20% to 72.22%) 94.16% (88.82% to 97.45%)

Using a cut-off value of Median + 1 Median Absolute Deviation [MAD], the samples were scored. The Sensitivity and Specificity for classification as Normal & Benign versus cancers & borderline tumors are given in the Table above. CA125, IGFBP2, SPP1, TSP1, ADIPSIN when used as a group of markers, had a Sensitivity of 82.2% and Specificity of 91.24%. This compares far better than CA125 which has a Sensitivity of 63.56% and Specificity of 94.16%.

In one of the preferred embodiment the present invention shall disclose a method for early diagnosis of ovarian cancer in a subject comprises of measuring the level of five biomarkers comprising of CA125, SPP1, IGFBP2, ADIPSIN and TSP1 in a sample from the said subject and; correlating the measurements of the presence, absence, or level of the measured CA125, SPP1, IGFBP2, ADIPSIN and TSP1 biomarkers with ovarian cancer status.
As per the invention, the method of for early diagnosis of ovarian cancer further comprises of measuring and correlating at least one or both biomarker selected from the group consisting of CYSTATIN C and ICAM1.
According to the invention in the method of early diagnosis of ovarian cancer, the biomarkers CA125, SPP1, IGFBP2, ADIPSIN and TSP1are measured by any conventional methods including sandwich ELISA, CHIP based detection, bead based detection including Luminex platforms etc.
In accordance with the invention the sample obtained from the subject for diagnosis of ovarian cancer is plasma or serum or whole blood.
As per the invention, in the method of early diagnosis of ovarian cancer, the correlating the measurements of the presence, absence, or level of the measured biomarkers with ovarian cancer status is performed by a software classification algorithm.
According to the invention the said ovarian cancer status is selected from epithelial ovarian cancer, borderline cancers; mucinous, serous, endometroid carcinomas; germ cell tumors of the ovary; stromal tumors of the ovary; and other malignant conditions.
In another preferred embodiment the present invention shall disclose a novel cluster of biomarkers for use in early diagnosis of ovarian cancer in a subject comprises of characterized combination of CA125, SPP1, IGFBP2, ADIPSIN and TSP1.
As per the invention novel cluster of biomarkers further comprises of at least one or both biomarker comprising of CYSTATIN C and ICAM1.
Certain modifications and improvements will occur to those skilled in the art upon a reading of the foregoing description. The above-mentioned details are provided to serve the purpose of clarifying aspects of the invention and it will be apparent to one skilled in the art that they do not serve to limit the scope of the invention. All modifications and improvements have been deleted herein for the sake of conciseness and readability but are properly within the scope of the present invention. It is understood that the foregoing detailed description is given merely by way of illustration and that modification and variations may be made therein without departing from the spirit and scope of the invention.