Abstract 4428: Characterizing the tumor-infiltrating T-cell repertoire of breast cancer in indigenous African patients from Southwest Nigeria

Abstract

Abstract Background: Women of African ancestry have a higher risk of young onset breast cancer than their European ancestry counterparts, with often more aggressive molecular tumor subtypes: these patients have fewer treatment options available to them, leading to higher mortality rates. Immunotherapy has recently garnered significant interest as a possible treatment for aggressive tumor subtypes (such as triple-negative breast cancer), but our lack of understanding of the tumor immune micro-environment has made it difficult to find more adaptive treatments for such cancers. Methods: We studied 96 invasive breast cancers collected from Nigerian women (mean age at diagnosis, 51.6±12.4 years), of which 62 (64.6%) were hormone receptor negative (HR-) by IHC, and 31 (32.3%) were basal-like subtype by PAM50 classification. Paired-end reads from bulk transcriptome sequencing were aligned to the human reference genome hg19 using STAR, and two algorithms (TRUST and MiXCR) were used to characterize the T-cell diversity in the tumors. To overcome the difficulty of extracting T-cell receptor (TCR) sequence information due to V(D)J recombination during T-cell maturation, we built a pipeline that incorporated data from public TCR databases (VDJdb and McPAS-TCR) to ensure a more accurate characterization of TCR diversity. Each potential TCR was first truncated to the appropriate start and end amino acids. Fragments of TCRs were discarded, and pairwise alignment of each output sequence was used to remove any duplicates. Results: Despite the many differences between TRUST and MiXCR, there was a 48.5% overlap in TCR sequences between the two methods, providing confirmation of the validity of these two algorithms. The intersection of the results from the two algorithms was then used for downstream analysis, which allowed for an expansive characterization of the tumor immune micro-environment, with 3,127 TCR sequences extracted over all 96 samples. We observed higher TCR diversity in basal-like tumors as compared to luminal-A/B tumors (p=0.011), whereas we saw no significance between HER2-enriched vs. luminal-A/B tumors (p=0.23). This is in accordance with other studies, which have shown that the most inflamed tumors are triple-negative/basal-like. Conclusion: Overall, this novel pipeline harnesses the power of two algorithms to effectively study the diversity of T-cells in the tumor, which, combined with further analyses of the tumor micro-environment, would allow for a more detailed understanding of the tumor immune infiltrates as potential therapeutic targets. Citation Format: Jean-Baptiste Reynier, Toshio F. Yoshimatsu, WABCS Working Group, Yonglan Zheng, Olufunmilayo I. Olopade. Characterizing the tumor-infiltrating T-cell repertoire of breast cancer in indigenous African patients from Southwest Nigeria [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 4428.