A Multistep Tumor Growth Model of High Grade Serous Ovarian Carcinoma Identifies Hypoxia Associated Signatures.

High-grade serous ovarian carcinoma (HGSC) is associated with late-stage disease presentation and poor prognosis, with limited understanding of early transformation events. Our study presents a comprehensive analysis of tumor progression and organ-specific metastatic dissemination to identify hypoxia-associated molecular, cellular, and histological alterations during HGSC tumor growth. H&E staining and subsequent histological assessment of tumor volume-based categories revealed recapitulation of numerous clinical features, including the prevalence of >0.0625≤0.5cm3 volume tumors and metastatic spread by orthotopic xenografts. The constant evolution of the tissue architecture concerning increased hyaluronic acid deposition, tumor vasculature, necrosis, altered proliferative potential, and gland forming ability of the tumor cells was identified. Flow cytometry and label chase-based molecular profiling across the tumor regenerative hierarchy identified the hypoxia-vasculogenic niche and the hybrid epithelial-mesenchymal tumor-cell state as determinants of self-renewal capabilities of progenitors and cancer stem cells (CSCs). A regulatory network and mathematical model based on tumor histology and molecular signatures predicted hypoxia-inducible factor 1-alpha (HIF1A) as a central node connecting epithelial-mesenchymal transition, metabolic and necrotic pathways in HGSC tumors. Thus, our findings provide a temporal resolution of hypoxia-associated events that sculpt HGSC tumor growth, and an in-depth understanding of it may aid in the early detection and treatment of HGSC.

A monoclonal antibody against annexin A2 targets stem and progenitor cell fractions in tumors.

The involvement of cancer stem cells (CSCs) in driving tumor dormancy and drug resistance is well established. Most therapeutic regimens however are ineffective in targeting these regenerative populations. We report the development and evaluation of a monoclonal antibody, mAb150, which targets the metastasis associated antigen, Annexin A2 (AnxA2) through recognition of a N-terminal epitope. Treatment with mAb150 potentiated re-entry of CSCs into the cell cycle that perturbed tumor dormancy and facilitated targeting of CSCs as was validated by in vitro and in vivo assays. Epigenetic potentiation further improved mAb150 efficacy in achieving total tumor regression by targeting regenerative populations to achieve tumor regression, specifically in high-grade serous ovarian adenocarcinoma.

Tumor deconstruction as a tool for advanced drug screening and repositioning.

A major focus of contemporary drug screening strategies is the identification of novel anticancer compounds, which often results in underutilization of resources. Current drug evaluation involves in vivo tumor (xenograft) regression as proof-of-principle for cytotoxicity (POC). However, this end-point lacks any assessment of drug resistance of the residual tumor and its capability to establish refractory and/or recurrent disease, which would represent more appropriate indicators of therapeutic failure. We have recently developed a flow cytometry-based approach for the analyses of intra-tumor cellular heterogeneity across stem cell hierarchies, genetic instability and differential cell cycling fractions, which can potentially be predictive of refractory disease and tumor relapse. Iterating this approach after initial POC screening in the drug discovery pipeline would have a great impact in terms of precision of drug evaluation, design of optimal drug combinations and/or drug repositioning. In this perspective, we highlight how through embracing of a comprehensive, informative and analytical assessment of the cellular content of residual tumors, the fidelity and statistical robustness of preclinical drug discovery can be greatly improved.

Elucidation of molecular and functional heterogeneity through differential expression network analyses of discrete tumor subsets.

Intratumor heterogeneity presents a major hurdle in cancer therapy. Most current research studies consider tumors as single entities and overlook molecular diversity between heterogeneous state(s) of different cells assumed to be homogenous. The present approach was designed for fluorescence-activated cell sorting-based resolution of heterogeneity arising from cancer stem cell (CSC) hierarchies and genetic instability in ovarian tumors, followed by microarray-based expression profiling of sorted fractions. Through weighted gene correlation network analyses, we could assign enriched modules of co-regulated genes to each fraction. Such gene modules often correlate with biological functions; one such specific association was the enrichment of CD53 expression in CSCs, functional validation indicated CD53 to be a tumor-initiating cell- rather than quiescent CSC-marker. Another association defined a state of poise for stress-induced metastases in aneuploid cells. Our results thus emphasize the need for studying cell-specific functionalities relevant to regeneration, drug resistance and disease progression in discrete tumor cell fractions.