Age-related mutational signature negatively associated with immune activity and survival outcome in triple-negative breast cancer

Abstract

Triple-negative breast cancer (TNBC) is characterized by broad genomic and transcriptional heterogeneity and results in a worse prognosis than other breast cancer types. Here, we integrated genomic and transcriptomic data combined with clinicopathologic information from 538 patients with TNBC and identified four novel significantly mutated genes (SMGs), namely, KDM6A, CD86, RBM47, and IFNGR1. A mutational signature (known as age-related signature 1) featured by enrichment of C > T mutations at NpCpG trinucleotides was associated with worse survival in TNBC (HR, 1.76 [95% CI, 1.07-2.90]; P = .025). We also analyzed gene transcriptomic profiles of TNBC samples and identified immune regulation-related gene pathways (e.g., antigen processing presentation and interferon signaling), and the cell cycle was significantly altered in samples with different signature 1 activity groups. The analysis further revealed that signature 1 was associated with decreased tumor immunogenicity and immunocyte infiltration in TNBC. This negative correlation was also observed in lung adenocarcinoma and prostate cancer samples. Furthermore, we found that patients with mutational signature 1 were markedly associated with decreased tumor mutation burden, even after controlling for age, grade, histological type, lymph node status, mutations in BRCA1/2 and ATR, and APOBEC and homologous recombination repair deficiency signatures (OR, 0.19 [95% CI, 0.11-0.32]; P < .001). Overall, this study identified previously unreported SMGs and re-annotated that age-related signature 1 was associated with a weakened immune microenvironment and predictive of poor survival in TNBC, offering opportunities to stratify patients into optimal treatment plans based on genomic subtyping.

m6A regulator-based methylation modification patterns characterized by distinct tumor microenvironment immune profiles in colon cancer

“…Specifically, MutSigCV measures the significant enrichment of nonsilent somatic mutations in a gene by addressing mutational context-specific background mutation rates. Genes with statistically significant (q < 0.1) and certified in the human Cancer Cell lines Encyclopedia (CCLE) 49 were recognized as SMGs 50 ( Table S4 ). The mutational landscape of m 6 A modification genes and SMGs in TCGA-COAD cohort was depicted by the waterfall function of the R 'maftools' package 51 .…”

Association of clock-like mutational signature with immune checkpoint inhibitor outcome in patients with melanoma and NSCLC

“…The relationship between the specific mutational signature process (e.g., CC>AA and CC>TT dinucleotide substitutions) and the origin of pathogenesis (e.g., UV exposure and tobacco smoking) have been observed in melanoma and lung cancer; 11 , 17 , 18 however, the association with immune response and prognostic prediction are still ambiguous in such tumors. Recent advances suggested a negative correlation between immune infiltration and clock-like mutational signature across specific cancer types (melanoma, breast and stomach cancers) from The Cancer Genome Atlas (TCGA) datasets, 19 , 20 indicating that the common mutational process may have an impact on tumor immunogenicity.…”

A novel genomic classification system of gastric cancer via integrating multidimensional genomic characteristics

“…In molecular level, the distinction of these two subtypes was mainly attributed to the distribution of mutational signatures, i.e., enrichment of signature 1 (known as clock-like mutational process) in subtype 4. Signature 1 is commonly found in various types of cancer and is associated with patients' age at diagnosis [68], and it has been reported to be a negative prognostic factor in triple-negative breast cancer [69], while its clinical relevance in GC has not been reported yet. Multiple difference has also been found significant CNV between subtypes 3 and 4, and subtype 4 harbored significant amplifications in more regions than subtype 3 (Fig.…”