Abstract IA039: The breast cancer biomarkers as predictors of survival: Do they vary by race and ethnicity?

Abstract

Abstract Introduction: Racial/ethnic disparities in cancer survival in the United States are well documented, but the underlying biology is not well understood. Compared with European American (EA) counterparts, African American (AA) women are more likely to die from breast cancer in the United States. Our recent studies were aimed to evaluate trends in survival, by race-ethnicity, for women diagnosed with breast cancer. We uncovered some biological factors underlying this disparity by comparing functional expression and prognostic significance of several biomarkers including master transcriptional regulators of luminal differentiation. Materials & Methods: We used a ML approach to assess a cohort of racially diverse 555 primary BC patients who underwent surgery in Greenville, NC and develop proteomics-based genomics (PbG) signatures. We apply quantitative automated image processing and computational methods to profile the subcellular distribution of the multi-functional transcriptional regulator, Kaiso (ZBTB33), and GP78. The cross-validated models were developed on a BC pooled dataset of (N= 845) samples (primarily taxane and anthracycline based) and chemotherapy cohort (N=415) including racial disparities. Results: Multiplex multivariate analysis of the association of Kaiso’s subcellular distribution with other breast cancer biomarkers reveals novel functional and predictive linkages between Kaiso and the autophagy-related proteins, LC3A/B, that are associated with features of the tumor immune microenvironment, survival, and race. Univariate or multivariate HRs for overall survival, estimated from digital IHC scoring of nuclear antigen, show distinct differences in the magnitude and significance of these biomarkers to predict survival based on race: ESR1 [EA HR 0.47; 95% confidence interval (CI), 0.31–0.72 and AA HR 0.77; 95% CI, 0.48–1.18]; FOXA1 (EA HR 0.38; 95% CI, 0.23–0.63 and AA HR 0.53; 95% CI, 0.31–0.88), and GATA3 (EA HR 0.36; 95% CI, 0.23–0.56; AA HR 0.57; CI, 0.56–1.4). In addition, elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER+ and ER– tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. Conclusion: Understanding these biomarkers and their downstream regulons will elucidate the intrinsic mechanisms that drive racial disparities in breast cancer survival. These findings identify effective modalities of Kaiso biomarker assessment and uncover unanticipated insights into Kaiso’s role in breast cancer progression. Even within clinically homogeneous tumor groups, regulatory networks that drive mammary luminal differentiation reveal race-specific differences in their association with clinical out- come. Our findings implicate a prominent role for gp78 in tumor progression and offer insights into our understanding of racial differences in breast cancer outcomes. Citation Format: Sandeep K. Singhal, Kevin L. Gardner. The breast cancer biomarkers as predictors of survival: Do they vary by race and ethnicity? [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr IA039.