Grant Number:	5R01CA248288-03 Interpret this number
Primary Investigator:	Goode, Ellen
Organization:	Mayo Clinic Rochester
Project Title:	Relating Molecular Subgroups of Endometriosis-Associated Ovarian Cancers to Survival and Risk
Fiscal Year:	2023

PROJECT SUMMARY/ABSTRACT Ovarian cancer (OC) is the eleventh most common cancer and fifth deadliest among U.S. women. The low incidence, high fatality and molecularly broad range of tumor histotypes make OC challenging to study and to treat. Consequently, survival rates have scarcely changed over the past 35 years, largely because precision therapy lags behind most other cancers. Endometrioid (ENOC) and clear cell (CCOC) account for ~25% of all invasive OC. They are a heterogeneous and understudied group of tumors that are closely associated with endometriosis, but show few similarities to the more common high grade serous OC. ENOC or CCOC have variable or poor response to standard platinum-based chemotherapy. CCOC, in particular, is more likely to be platinum resistant at early stage and resistant to second line chemotherapy at advanced stage, resulting in worse survival than HGSOC. We hypothesize that molecular tumor subtypes exist for ENOC and CCOC that reflect differences in biological processes and risk factors and that might inform new treatment strategies. Our preliminary results using genomics analyses of 185 ENOC and 115 CCOC supports this hypothesis by showing that associations with survival and risk factors such as smoking and body mass index differ according to the tumor’s molecular profile, with some subgroups showing rapidly fatal outcome. In the current proposal, we intend to delve deeper into the genomic profile of ~1,100 ENOC and CCOC tumors to identify key molecular features of the tumor subtypes. Our approach uses a consortium effort that combines existing data from well-conducted epidemiologic studies of risk factors with corresponding clinical information among investigators with a strong history of collaboration. We will first characterize molecular subtypes, separately for ENOC and CCOC, by integrating sequencing and array data from gene expression, mutations and methylated regions from a training set (483 ENOC, 292 CCOC) using statistical clustering. Next, we will assess replication of the molecular subtypes in an independent test set (207 ENOC, 125 CCOC). To assess subtype-specific associations in the total sample (689 ENOC, 417 CCOC), we will relate molecular subtypes of ENOC and CCOC separately to risk factors and to survival. Impact: Less common OC such as ENOC or CCOC are often overshadowed by investigations of more common cancers, yet our data show that ENOC and CCOC can also be rapidly fatal in certain patient subsets or show more favorable outcome in others, directly impacting patients’ lives. Finding patterns with other cancers by using integrated analysis of ENOC and CCOC subtypes has high potential to inform new avenues for targeted therapy and to enhance understanding of ENOC and CCOC cancer biology. Future replication of our findings using an independent 1,400 ENOC/CCOC tumors from our unique consortia resources can lead to needed gains in biological, epidemiologic and therapeutic insights for these patients.





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