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Abstract
Molecular stratification of high-grade serous ovarian carcinoma (HGSC) for targeted therapy is a pertinent approach in improving prognosis of this highly heterogeneous disease. Enabling the same necessitates identification of class-specific biomarkers and their robust detection in the clinic. We have earlier resolved three discrete molecular HGSC classes associated with distinct functional behavior based on their gene expression patterns, biological networks, and pathways. An important difference revealed was that Class 1 is likely to exhibit cooperative cell migration (CCM), Class 2 undergoes epithelial to mesenchymal transition (EMT), while Class 3 is possibly capable of both modes of migration. In the present study, we define clinical stratification of HGSC tumors through the establishment of standard operating procedures for immunohistochemistry and histochemistry based detection of a panel of biomarkers including TCF21, E-cadherin, PARP1, Slug, AnnexinA2, and hyaluronan. Further development and application of scoring guidelines based on expression of this panel in cell line-derived xenografts, commercial tissue microarrays, and patient tumors led to definitive stratification of samples. Biomarker expression was observed to vary significantly between primary and metastatic tumors suggesting class switching during disease progression. Another interesting feature in the study was of enhanced CCM-marker expression in tumors following disease progression and chemotherapy. These stratification principles and the new information thus generated is the first step towards class-specific personalized therapies in the disease.
Highlights
Personalized therapeutic decisions in cancer necessitate the development of accurate stratification schemes based on mutations and/or association of tumor sub-groups with specific biomarkers and biological functions, besides well-elucidated principles for their detection [1]
Sections were washed and incubated with anti-rabbit HRP-conjugate (Jackson ImmunoResearch Laboratories, Inc., PA, USA) or anti-mouse HRP-conjugate (Jackson ImmunoResearch Laboratories, Inc., PA, USA) for 1 h, and color developed with DAB (Thermo Pierce, MA, USA); hematoxylin used as a counterstain
Computation of these scores led to the derivation of biomarker and class indices, which compared between groups by Pearson correlation using SPSS for Windows to delineate classes
Summary
Personalized therapeutic decisions in cancer necessitate the development of accurate stratification schemes based on mutations and/or association of tumor sub-groups with specific biomarkers and biological functions, besides well-elucidated principles for their detection [1]. Multiplexed IHC for the concurrent detection of a number of biomarkers in lung cancer is increasingly becoming point-of care in treatment [15] Such translation of molecular information implies the feasibility of similar applications in other tumor types. Further evaluation and application were performed in xenografts and commercial tissue microarrays (TMAs), along with the determination of thresholds for clinical classification in resected primary tumors and secondary metastases and/or cell blocks prepared from ascitic fluid of chemo-naïve and chemo-treated patients were achieved (Supplementary Figure S1). These efforts define the establishment of diagnostic principles for application in clinical practice
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