<p>Two general types of genetic alterations drive cancer progression: mutations and copy number alterations (CNAs). With the exception of p53, single nucleotide variant mutations (here, simply "mutations") are not drivers of 80% of tumors within the most frequent and deadly histotype of ovarian cancer: serous ovarian cancer (SOC). Rather, CNAs are more prevalent in SOC than any other cancer type studied by <a href="https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000178">phs000178</a> The Cancer Genome Atlas (TCGA). Fully two-thirds of genes are altered by CNAs in the average SOC. Bioinformatic methods have shown that these CNAs modulate specific molecular pathways, such as autophagy, and this finding enabled effective pathway-targeted therapies1. Unfortunately, TCGA ovarian cancer data lacks racial diversity. Only 6% of SOC tumors (n=32) studied are from African origin. Black women diagnosed with ovarian cancer are more likely to die from their disease than white women. Five-year survival after diagnosis is 31% among blacks versus 42% among whites, and this disparity is seen in every age group and tumor stage distribution. Dr. Kelemen examined data from 365 white and 95 black ovarian cancer patients from the Hollings Cancer Center (HCC) Cancer Registry between 2000 and 2015 and found that black women had an 81% higher risk of death after diagnosis compared to white women (HR 1.81, 95% CI 1.35-2.43), independent of diagnosis center (98% were treated at HCC but half were diagnosed elsewhere), tumor stage, histology, extent of residual tumor remaining following surgery, insurance status, smoking, type of treatment for ovarian cancer, and age-adjusted Charlson comorbidity index. This disparity remained even when restricted to women who received the standard of care, surgery-chemotherapy sequence (HR 1.79, 95% CI 1.10-2.89). Despite receiving the same treatment, black race was still associated with inferior survival. A similar disparity has been reported by others, indicating that the HCC experience is representative of national data. Here, an additional set of high-grade serous ovarian cancer primary tumors were acquired from biorepositories with a focus on expanding data originating from African American women. Data were analyzed for copy-number alterations using exome sequencing and control-FREEC software.</p>

Copy-Number Analysis of Understudied Black Women Ovarian Cancers