The immune response‐related mutational signatures and driver genes in non‐small‐cell lung cancer

Abstract

Immune checkpoint blockade (ICB) therapy has achieved remarkable clinical benefit in non‐small‐cell lung cancer (NSCLC), but our understanding of biomarkers that predict the response to ICB remain obscure. Here we integrated somatic mutational profile and clinicopathologic information from 113 NSCLC patients treated by ICB (CTLA‐4/PD‐1). High tumor mutation burden (TMB) and neoantigen burden were identified significantly associated with improved efficacy in NSCLC immunotherapy. Furthermore, we identified apolipoprotein B mRNA editing enzyme, catalytic polypeptide‐like (APOBEC) mutational signature was markedly associated with responding of ICB therapy (log‐rank test, P = .001; odds ratio (OR), 0.18 [95% CI, 0.06‐0.50], P < .001). The association with progression‐free survival remained statistically significant after controlling for age, sex, histological type, smoking, PD‐L1 expression, hypermutation, smoking signature and mismatch repair (MMR) (HR, 0.30 [95% CI, 0.12‐0.75], P = .010). Combined high TMB with APOBEC signature preferably predict immunotherapy responders in NSCLC cohort. The CIBERSORT algorithm revealed that high APOBEC mutational activity samples were associated with increased infiltration of CD4 memory activated T cells, CD8+ T cells and natural killer (NK) cells, but reduced infiltration of regulatory T cells. Besides, individual genes mutation of IFNGR1 or VTCN1 were only found in responders; however, the PTEN mutation was only found in non‐responders (Fisher's exact test, all P < .05). These findings may be applicable for guiding immunotherapy for patients with NSCLC.

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

“…34 There is evidence that the APOBEC mutational signature is a potential predictive marker for PD-1 immunotherapy response in NSCLC. 13,35 In our genomic meta-analysis, we identified that signature 1 was associated with shortened survival time in patients with TNBC and suggested a significant association with tumor escape from immunological surveillance. A recent study indicated that short-term chemotherapy (e.g., doxorubicin and cisplatin) may induce a more favorable tumor microenvironment and increase the likelihood of response to PD-1 blockade in TNBC.…”

“…The ligand-binding chain (alpha) of the gamma interferon receptor encoding gene IFNGR1, acted in IFNγ pathways, and its mutation was reported to regulate the immune response to PD-1 treatment. 13,32 Mutations patterns of signature 1 were commonly found in most cancer types (BRCA, LUAD, PRAD, etc. ), known as clock-like mutational process properties, which showed a correlation between the number of mutations and age at diagnosis.…”

“…TMB was largely attributed to genomic instability. To rule out the influence of confounding factors, we incorporated genomic integrity maintenance-associated genes (mutations in BRCA1/2, ATR, and SMGs in TNBC), extracted mutational signatures (1,3,13), and clinical features (age, grade, histology type, and lymph node status) into the Bayesian logistic regression model. The association between signature 1 and TMB remained statistically significant after adjusting for such factors (OR, 0.19 [95%CI, 0.11-0.32]; P < .001; Figure 5c).…”

Advancing CAR T-Cell Therapy for Solid Tumors: Lessons Learned from Lymphoma Treatment

“…Multiple reviews describe barriers to successful clinical application of CAR T-cell therapy, other T-cell-based therapies, and CIs [21][22][23]. The key mechanisms of tumor immunoevasion include: (1) impaired molecular trafficking into the tumor (caused by pro-tumoral endothelium [24,25], altered chemokine profile [26][27][28], and stiff stroma [29]); (2) microenvironment-mediated alterations that include hyperacidity and increased potassium level [30], presence of myeloid derived suppressor cells (MDSCs) [31,32], tumor-associated macrophages (TAMs) [33], and their cytokines/chemokines; and (3) modulation of tumor-specific molecular pathways [34], e.g., phosphatase and tensin homolog (PTEN)/phosphoinositide 3-kinase (PI3K) [35][36][37], Janus kinase 1 (JAK1)/2 [38][39][40], isocitrate dehydrogenase (IDH) [41,42], interferon-gamma (IFNγ) and tumor necrosis factor alpha (TNFα) [43], and microRNAs and exosomes [44].…”

Development and validation of an immune-related prognostic signature for ovarian cancer based on weighted gene co-expression network analysis

“…Huang et al reported that the oncolytic adenovirus carrying the SIRPα-IgG1 Fc fusion gene could block CD47 signaling in ovarian cancer cells, therefore, increasing macrophage in ltration and killing ovarian cancer cells [8] . In addition, the total mutational burden (TMB) was also correlated with cancer prognoses and affected immune responses in the tumor microenvironment [9] .…”