Abstract PO1-08-12: Genomic Characterization of the Carolina Breast Cancer Study
Authors: Sarah Van Alsten, Ebonee Butler, Benjamin Calhoun, Michael Love, Charles Perou, Katherine A Hoadley, Melissa Troester
Journal: Cancer Research (2024)

Abstract Background: Breast cancer is a heterogeneous disease defined by distinct subtypes, mutational profiles, and genomic characteristics. Previous analyses in The Cancer Genome Atlas (TCGA) have been instrumental in understanding the genomic landscape of breast cancer, including identification of key driver mutations, mutational signatures, and distinguishing features of breast cancer subtypes. However, TCGA may not be representative of other population-based breast cancer cohorts, particularly those of earlier stage and including a more diverse set of patients. Our aim was to characterize the genomic landscape of breast cancer in the Carolina Breast Cancer Study (CBCS), a cohort which oversamples Black and young women. Methods: We used targeted sequencing to profile somatic alterations in 1,175 genes from 275 formalin fixed paraffin embedded primary breast tumors in CBCS, 52% of which came from Black women, 41% from women under age 50, and 29% of which were Basal-like based on bulk RNA profiling. We also evaluated TP53 mutation as a source of breast cancer heterogeneity, comparing the type and location of TP53 mutations in each cohort. We assessed chromosome arm-level gains and losses using GISTIC and defined genomic instability as the total number of aneuploid chromosome arms. Intratumoral heterogeneity was assessed with PyClone-VI and defined as the total number and Shannon’s Diversity Index of tumor-specific subclones. For genes mutated in more than 5% of samples and chromosomal aberrations significantly enriched in GISTIC, we estimated the prevalence of alterations and compared to previous distributions in 981 TCGA tumors. Results: Seven genes [TP53 (N=101, 37%), PIK3CA (N=76, 28%), GATA3 (N=32, 12%), CDH1 (N=31, 11%), MAP3K1 (N=22, 8%), KMT2C (N=20, 7%), and CBFB (N =19, 7%)] were mutated in more than 5% of CBCS tumors; all but CBFB which were also highly prevalent in TCGA. While most TP53 hotspot mutations observed in CBCS were previously reported in TCGA, CBCS had twice as many Y220C mutations, one-third fewer R175H mutations, and a non-significantly higher proportion of nonsense mutations than TCGA (20% vs 12%, p = 0.05). Hotspot mutation prevalence in other Luminal-associated driver genes (e.g. PIK3CA, GATA3, CDH1) did not differ by dataset. CBCS tumors showed a higher degree of genomic instability (8 arms vs. 5 arms, p &amp;lt; 0.001) and subclonal diversity than TCGA (48% vs 12% comprised of two or more subclones, p &amp;lt; 0.05). Both datasets showed significant amplifications of 1q and 8q, and deletions of 13q and 17p (where BRCA2 and TP53, respectively, are located), with CBCS having non-significantly higher prevalence of each of these changes. Conclusions: While comparisons should be interpreted in light of technical and population differences between TCGA and CBCS, the overall results show that the suite of commonly altered genes and chromosome arms were highly consistent between TCGA and the diverse CBCS cohort. CBCS tumors tended to display higher genomic instability, intratumoral heterogeneity, and number and diversity of TP53 mutations. This may reflect distinctions in tumor evolutionary state between CBCS and TCGA tumors, and/or could reflect differences in the study populations. Results underscore the importance of considering population characteristics – particularly stage and race – in large-scale genomic contexts, and highlight the importance of diverse cohorts in genomic research. Citation Format: Sarah Van Alsten, Ebonee Butler, Benjamin Calhoun, Michael Love, Charles Perou, Katherine A Hoadley, Melissa Troester. Genomic Characterization of the Carolina Breast Cancer Study [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-08-12.