Abstract P1-06-02: Characterization of gene- and sample-level APOBEC mutagenesis enrichment with respect to intrinsic subtypes, tumor mutational burden, and immune composition in breast cancer

Introduction: APOlipoprotein B mRNA Editing enzyme Catalytic peptide-like, APOBEC, is a family of innate immune enzymes that catalyze cytosine to uracil deamination in single-stranded DNA, which lead to mutations in preferred trinucleotide contexts. APOBEC mutagenesis portends a worse prognosis in several breast cancer subtypes and associates with increased tumor mutational burden (TMB). Specific mutations enriched with APOBEC mutation signatures and immune phenotypes are not well described. The purpose of our study was to identify genes enriched for APOBEC mutagenesis and determine their relationship to intrinsic subtypes, TMB, and the immune composition of the transcriptome in breast cancers.Methods: We queried TCGA breast cancer database involving 980 breast cancer samples. We used consensus mutation calls from four somatic mutation callers (MuTect2, VarScan2, MuSE, and SomaticSniper). APOBEC mutagenesis scores were calculated for each tumor using a published method (Nik-Zainal et al. 2012) and a modified version thereof. The score was calculated at the gene-level, to identify genes enriched for APOBEC mutagenesis, and the cancer sample-level to investigate the relationship of APOBEC mutagenesis scores with intrinsic subtypes (using PAM50), APOBEC3A and 3B expression levels, and TMB. We also undertook differential expression analysis of CIBERSORT gene signatures and individual genes from the innate immune system, IFN, TGFB, WNT, and immune checkpoints with respect to common somatic mutations in APOBEC enriched genes.Results: The genes with the strongest statistical evidence for enrichment of APOBEC mutagenesis were PIK3CA, TP53, MUC16, and TTN. Among three common somatic mutations in PIK3CA (E542K, E545K, H1047R), the APOBEC score was only observed to be associated with E542K (q=2.47 × 10−2) and E545K (q=9.81 × 10−6) mutations. APOBEC mutagenesis revealed a high degree of enrichment across all breast cancer intrinsic subtypes, 75% in luminal A, 68% in luminal B, 91% in HER2 enriched, 73% in basal, and 89% in normal-like phenotypes. APOBEC mutagenesis scores were observed to significantly associate with APOBEC3A expression (q=1.1 × 10−9) and as a trend of association with APOBEC3B expression (q=1.62 × 10−1). A strong association was observed between APOBEC mutagenesis score and elevated TMB (p<2 × 10−16). No checkpoint genes (i.e. CTLA-4, PD-1, and PD-L1) were observed to be significantly overexpressed among those tumors with E542K and E545K PIK3CA mutations. The CIBERSORT mast cell gene signature (q=1.32 × 10−2) and the individual genes TGFB3 (q=5 × 10−3), ROR (q=7.91 × 10−3), and WNT5A (q=1.92 × 10-2) were overexpressed in breast tumors with E542K PIK3CA mutations.Conclusion: APOBEC mutagenesis patterns are seemingly prevalent across all breast cancer intrinsic subtypes and associate with elevated TMB and mutations in the PIK3CA helical loop domain and TP53 gene in TCGA breast cancer samples. Cancers with PIK3CA mutations in the helical loop domain did not demonstrate checkpoint gene overexpression, but were associated with other immunosuppressive features (e.g. TGFB3 and WNT5A overexpression). Investigation into innate immune cell signaling, mast cell immune signaling, and immunosuppressive expression profiles in APOBEC mutated breast cancers with and without PIK3CA mutations may help to identify novel immune targets to combine with PI3K inhibitors in breast cancer.Citation Format: Jeremy Force, Xiaodi Qin, Dadong Zhang, P. Kelly Marcom, Jeffrey Marks, Mary Love Taylor, Carey Anders, Kouros Owzar, Jichun Xie. Characterization of gene- and sample-level APOBEC mutagenesis enrichment with respect to intrinsic subtypes, tumor mutational burden, and immune composition in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-06-02.

Duke Scholars

Author Jichun Xie Biostatistics & Bioinformatics, Division of Integrative Geno ...