Abstract
Cancer disparities research has a sample number problem, especially in serous ovarian cancer (SOC). Driver genes for SOC are mutated in <10% of patients, with the sole exception of p53. Even with hundreds of patients, this limits the ability to perform gene-oriented statistics between racial groups, even in the relatively diverse population in the United States. Yet research is needed; the CONCORD-2 study and researchers at the Hollings Cancer Center have consistently found worse prognosis for black patients with SOC, despite correcting for socioeconomic factors. Biologic tumor-intrinsic factors may explain some aspects of the worse prognosis. The Cancer Genome Atlas (TCGA) well mapped the US population for Caucasians and African Americans (77% white, 12% black), but with only 12% of samples within the second most prevalent racial group, driver genes are missed. For example, while BRCA1 mutation was found in tumors from white patients, it was not found in tumors from black patients. However, research need not be limited to amino-acid level mutations and indels; copy-number alterations (CNAs) likely drive the biology of SOC, with the average number of genes affected per TCGA tumor around 16,000. Pathway-level analyses of these widely disrupted genes can find significant differences between racial/ethnic groups. Here, we present evidence that significant differences are present in somatic CNA data for the pathways: xenobiotic metabolism, cAMP kinase signaling, and adaptive immune response. An expansion of research into somatic CNAs is warranted in underrepresented minority groups to better understand how treatment options and prognostic markers may differ.
Citation Format: Joe R. Delaney. Copy-number analysis of understudied black women ovarian cancers [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A11.
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