Title: Dissecting FAK-regulated oncogenic signaling programs in ovarian cancer High-Grade Serous Ovarian Cancer (HGSOC) kills four of five women within sixty months. HGSOC is genetically complex, which has slowed past preclinical model development. To this end, we have molecularly characterized a new and in vivo evolved, aggressive, implantable, and syngeneic murine ovarian cancer model. These cells display many spontaneous acquired copy number changes, including K-Ras, Myc, and FAK/PTK2 genes (herein termed KMF cells) among other striking similarities to HGSOC. FAK (focal adhesion kinase) is a tyrosine kinase canonically supporting integrin signaling, motility and mechano-sensing. Our collective approaches in HGSOC and KMF cells, including pharmacological inhibition, FAK knockout, FAK re-expression, complementation, and bioinformatic analyses reveal that non-canonical adhesion-independent FAK signaling sustains intrinsic resistance to platinum chemotherapy in part via b-catenin activation and the elevation of transcription factors supporting stemness and DNA repair genes. FAK is activated in patient tumors surviving chemotherapy and acquired platinum resistance can facilitate ovarian tumorsphere dependence on FAK for growth. We identified a gene set associated with FAK expression and a subset linked to intrinsic FAK activity in 3D organoid cell culture. Exogenous activated b-catenin expression was sufficient to rescue FAK loss or inactivation phenotypes in 3D culture, but b-catenin did not promote FAK-null tumor growth in mice. Thus, FAK selectively promotes oncogenic signaling in vivo and FAK senses the tumor microenvironment. Our proposal will test the hypothesis that stress-induced FAK activation in tumorspheres surviving within a mouse peritoneal environment triggers specific cellular reprogramming, fostering stem-like state of heightened oncogenicity.
In Aim -1, our unique gene-edited human and murine ovarian tumor systems will be used together with an inducible FAK expression system to characterize FAK localization- and kinase-dependent signals driving malignancy.
In Aim -2, total and single cell RNA-seq will be performed on cells isolated from tumor-bearing mice to determine FAK regulated targets in vivo. Combined single cell RNA-seq and ATAC-seq will determine how subpopulations of cells are derived in response to time-dependent FAK activation and the interrelationship of gene markers in cell subpopulations.
In Aim -3, we will use molecular and immunohistochemical analyses of patient clinical trial samples to identify and biomarkers associated with FAK inhibition and patient outcome. Our proposal encompasses cell biology, advanced RNA sequencing, epigenome mapping as well as single cell sequencing with bioinformatic clustering analysis. These approaches, together with the evaluation of clinical trial patient samples, will identify a ?FAK-dependent? cell biomarker gene signature that can be re-tested for significance within KMF and HGSOOC tumor models. These studies will provide important insights into a targetable signaling pathway sustaining HGSOC malignancy.

Public Health Relevance

Ovarian cancer is a leading cause of cancer deaths among women with a five-year survival below 50% despite recent advances in therapy. These studies will determine the mechanisms by which a key signaling molecule (FAK) coordinately promotes tumor recurrence and acquired chemotherapy resistance. Knowledge gained from these studies will provide a blueprint for understanding FAK-driven disease, and will identify women whose disease will benefit from FAK-targeted drugs.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
1R01CA247562-01
Application #
9917335
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Xu, Wanping
Project Start
2020-05-01
Project End
2025-04-30
Budget Start
2020-05-01
Budget End
2021-04-30
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Obstetrics & Gynecology
Type
Schools of Medicine
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093