Characterization of the tumor immune microenvironment of triple-negative breast cancer (TNBC) patients who self-identify as African American (AA) or non-African American (NonAA).
Authors: Blenman Kim , Marczyk Michal , Qing Tao , O'Meara Tess , Yaghoobi Vesal , Pelekanou Vasiliki , Bai Yalai , Reisenbichler Emily , Li Xiaotong , Gunasekharan Vignesh , Ibrahim Eiman Y , Rimm David L. , Pusztai Lajos , Cole Kimberly 
Published: June 2021

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Background: What tumor biological differences, if any, contribute to the higher incidence and worse prognosis of triple negative breast cancer (TNBC) in African American (AA) compared to NonAA patients are unknown. We hypothesized that differences in the tumor immune microenvironment may contribute to the outcome disparities. The purpose of this study was to characterize and compare the immune microenvironment of TNBC between patients self-identified as NonAA or AA. Methods: Formalin fixed paraffin embedded surgically resected cancer and paired normal tissues collected before any systemic therapy and the corresponding clinical data were collected for NonAA (n = 56) and AA (n = 54) stage I-III TNBC treated at Yale Cancer Center between 2000-2017. The two cohorts were matched for clinical stage, age of diagnosis, and year of diagnosis. We performed somatic and germline whole exome sequencing (WES), bulk RNA sequencing, and immunohistochemistry to assess PD-L1 expression (SP142). Stromal tumor infiltrating lymphocytes (sTILs) were assessed on H&E slides. Mutation load, mutation frequencies, and gene expression differences were compared at gene and pathway level. Immune cell composition was estimated through gene expression deconvolution analyses (TIDE). Results: Tumor mutational burden was similar between the two cohorts. At gene level, few genes had significantly different somatic mutation frequencies, or differential mRNA expression between AA and NonAA samples. Pathway level alterations showed inflammation, immunity (adaptive; innate), antigen presentation, and allograft rejection pathways were more affected by somatic mutations in AA samples. The affected genes differed from cancer to cancer and were not recurrent and therefore were missed at gene level analysis. Gene set enrichment and co-expression analysis also showed higher immune related pathway expression in AA samples. Unsupervised co-expression cluster analysis confirmed coordinated overexpression of genes involved in immunity, inflammation, and cytokine/chemokine signaling in AA patients. Two immunotherapy response predictive signatures, immune inflamed and the IFNG as well as sTILs score and PD-L1 positivity were also higher in AA samples. These findings raise the possibility that immune checkpoint inhibitors might be particularly effective in AA patients. In NonAA samples, the EMT transition, angiogenesis, adipogenesis, myogenesis, fatty acid metabolism, TGFβ signaling, UV-response, and hypoxia pathways were overexpressed. TIDE analysis suggested higher levels of TAM M2, overall TIDE score, and the Immune Exclusion score in NonAA samples. Conclusions: TNBC in AA patients more frequently harbor somatic mutations in genes involved with immune functions and overexpress immune and inflammatory genes compared to NonAA patients.