Abstract B123: Using eHealth and data science to dissect breast cancer heterogeneity in the Chicago Multi-Ethnic (ChiMEC) Breast Cancer Cohort

Abstract

Abstract Background: Differences in tumor biology, genomics and health care delivery patterns contribute to breast cancer mortality gap between white women of European ancestry (EA) and black women of African ancestry (AA) in the US. Accumulating evidence suggest that the genetic architecture of breast cancer is different across race and ethnicity but individuals of African ancestry, with the oldest and most diverse genome, remain under represented in clinical trials. Beyond interventions to improve quality of guideline directed cancer care, there is an urgent need to implement and disseminate innovative interventions that promote health equity and inform evidence based interventions. Method: We established a breast cancer patient cohort by collecting clinical and epidemiological data via electronic medical records and interview as well as biospecimen banking at the University of Chicago Comprehensive Cancer Center. We compared overall survival and relapse-free survival between EA and AA patients using Cox models. We also examined racial difference in pathologic complete response (pCR) in patients receiving neoadjuvant therapy. Using the xT 595-gene panel (Tempus Labs, Inc.) with matched tumor-normal samples in a subset of the cohort (n=127), we evaluated genomic heterogeneity. Results: 2773 stage I-III breast cancer patients were enrolled in the cohort, including 54% white, 39% black and 7% Asian and Hispanic patients. Over a median follow-up of 5.8 years, 456 patients died and 301 patients had recurrent breast cancers. After adjusting for stage, age, and comorbidities, AA patients had higher mortality rate than EA patients, and the racial difference varied across molecular subtypes: the hazard ratios comparing AA vs. EA patients were 3.92 (95% CI 1.58-9.73) in the hormone receptor (HR)-/HER2+ group, 1.55 (1.20-2.01) in the HR+/HER2- group, 1.51 (0.81-2.80) in the HR+/HER2+ group, and 1.21 (0.82-1.80) in the triple negative group. Of the 560 patients undergoing neoadjuvant chemotherapy, 166 (30%) had pCR. AA patients had lower pCR rate than EA patients (26% vs. 34%, p=0.053). Of note, molecular subtype was a strong predictor for pCR (p<0.001), highest in HR-/HER2+ group (59%), followed by triple negative (32%), HR+/HER2- (26%), and HR+/HER2- (16%) groups. In patients with pCR, 4 died, compared to 78 deaths in patients with residual diseases after neoadjuvant therapy (hazard ratio 9.70, 95% CI 3.51-26.8; p<0.001). Genomic mutations for therapy resistance and relapse will be integrated before the meeting presentation. Conclusion: Racial differences in pCR in part explain the mortality disparity between AAs and EAs in the ChiMEC cohort. This underscores the need for broader access to adaptive biomarker based clinical trials in communities that serve predominantly AA breast cancer patients. Citation Format: Dezheng Huo, Nike Beaubier, Nora Jaskowiak, Rita Nanda, Gini Fleming, Masaya Hattori, Padma Sheila Rajagopal, Abiola Ibraheem, Brenda Copley, Qun Niu, Fang Liu, Elisabeth Sveen, Toshio Yoshimatsu, Galina Khramtsova, Yonglan Zheng, Taylor Abboushi, Kevin White, Olufunmilayo Olopade. Using eHealth and data science to dissect breast cancer heterogeneity in the Chicago Multi-Ethnic (ChiMEC) Breast Cancer Cohort [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr B123.