Abstract TMIM-067: EXPRESSION OF LNCRNAS IN OVARIAN CANCER-ASSOCIATED FIBROBLASTS IS ASSOCIATED WITH PATIENT SURVIVAL

Abstract

BACKGROUND: Ovarian cancer is the most lethal gynecological malignancy in women, with high-grade serous ovarian cancer (HGSOC) the most common and aggressive subtype. The tumor microenvironment is acknowledged to play a vital role in the growth and metastasis of many solid tumors, including ovarian cancer, and as such represents an attractive new therapeutic target. In ovarian cancer, patients with a higher proportion of desmoplasia have a poorer survival. Cancer-associated fibroblasts (CAFs) represent the most abundant cell type in the tumor stroma and are responsible for producing the desmoplastic reaction that is a poor prognostic factor in HGSOC. Genetic aberrations in ovarian CAFs are extremely rare, raising the possibility of alternative mechanisms that regulate gene expression in CAFs, such as regulation by long non-coding RNAs (lncRNAs). LncRNAs are transcripts that do not encode for protein, but have been shown to play important roles in several diseases, including cancer. However, very little is known about the role of lncRNAs in the tumor microenvironment. OBJECTIVES: To identify lncRNAs whose expression levels in CAFs are associated with patient survival and use computational approaches to predict their function. METHODS: CAFs were laser capture microdissected from 67 advanced stage HGSOCs. RNA was extracted from the microdissected samples and expression analyzed using Affymetrix U133 Plus 2.0 Arrays. Probes identified as lncRNAs were used in this analysis. Samples were normalized and background corrected using the robust multiarray average (RMA) method and expression values were log2 transformed. Expression levels of each lncRNA were clustered into low and high expression groups. Kaplan Meier /log-rank analysis was used to assess the association between expression levels of each lncRNA and the patients9 overall survival. Multivariate cox regression analysis was used to determine if differential expression of lncRNAs were independent predictors of survival. A network based ‘guilt-by-association9 approach was used to predict the function of lncRNAs associated with patient survival. RESULTS: Increased expression of 9 lncRNAs including DANCR, MALAT1 and NEAT1 and decreased expression of 1 lncRNA in ovarian CAFs were found to be associated with poorer overall survival by the log-rank test. Expression profiles of 5 lncRNAs as well as response to chemotherapy and debulking status were significant predictors of survival by univariate cox proportional hazards analysis. To adjust for existing collinearity of the 10 lncRNAs, the first principal component of these lncRNAs (capturing 98% of variations), as well as response to chemotherapy and debulking status were incorporated into a multivariate model. The first principal component (HR=0.74, P=0.0001163) and response to chemotherapy (HR=0.22, P=0.000168) were found to be independent predictors of survival. Functional enrichment analysis revealed these lncRNAs are likely to play a role in metabolism, autophagy or immune response. CONCLUSIONS: We have identified several lncRNAs whose expression levels in CAFs are associated with survival of HGSOC patients, raising the likelihood that they play an important role in the tumor-promoting functions of CAFs. A further understanding of the role of lncRNAs in CAFs may be useful when designing novel therapies that target the tumor microenvironment. Citation Format: Emily K. Colvin, Viive M. Howell, Samuel C. Mok, Goli Samimi and Fatemeh Vafaee. EXPRESSION OF LNCRNAS IN OVARIAN CANCER-ASSOCIATED FIBROBLASTS IS ASSOCIATED WITH PATIENT SURVIVAL [abstract]. In: Proceedings of the 12th Biennial Ovarian Cancer Research Symposium; Sep 13-15, 2018; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2019;25(22 Suppl):Abstract nr TMIM-067.