Comparative Analysis of Mutation Status and Immune Landscape for Squamous Cell Carcinomas at Different Anatomical sites

Abstract

ObjectiveIt has been controversial whether tumor mutation burden (TMB) affects the prognosis and the efficacy of immunotherapy in different tumor types. We provided a comprehensive analysis of mutation status and immune landscape of squamous cell carcinomas (SCCs) from four sites in order to investigate the relationship of TMB with prognosis and immune cell infiltration in different SCCs.MethodsThe transcriptome profiles and somatic mutation data of SCCs downloaded from the Cancer Genome Atlas (the Cancer Genome Atlas) database were analyzed and visualized. Then, TMB was calculated to analyze its correlations with prognosis and clinical features. Differentially expressed genes (DEGs) between the high and low TMB groups were screened for functional enrichment analysis. CIBERSORT algorithm was used to compare differences of immune cell infiltration between two groups in different SCCs. In addition, immune DEGs associated with prognosis were identified and risk prediction model was constructed via Cox regression analysis.ResultsMissense mutation was the most dominant mutation type in SCCs. The difference was that the top10 mutated genes varied widely among different SCCs. High TMB group had better prognosis in lung squamous cell carcinoma (LUSC) and cervical squamous cell carcinoma (CESC), while the result was reverse in head and neck squamous cell carcinoma (HNSCC) and esophageal squamous cell carcinoma (ESCC). In addition, patients with older age, smoking history, earlier pathological stage and no lymphatic invasion had higher TMB. The identified DEGs were mainly enriched in the regulation of immune system, muscular system and the activity of epidermal cells. The proportions of CD8+T cells, CD4+ memory T cells, follicular helper T cells, macrophages were distinct between two groups. The prognosis-related hub genes (CHGB, INHBA, LCN1 and VEGFC) screened were associated with poor prognosis.ConclusionThis study reveals the mutation status and immune cell infiltration of SCCs at different anatomical sites. TMB is closely related to the prognosis of SCCs, and its effects on prognosis are diverse in different SCCs, which might result from the situation of immune cell infiltration. These findings contribute to the exploration of biomarkers for predicting the efficacy of immunotherapy in SCCs and providing innovative insights for accurate application of immunotherapy.

Identification and Biological Validation of a Chemokine/Chemokine Receptor-Based Risk Model for Predicting Immunotherapeutic Response and Prognosis in Head and Neck Squamous Cell Carcinoma

“…Univariate and multivariate Cox analyses were also employed to determine if that risk score was an independent prognostic factor ( Figure 5 D). Recent studies have demonstrated that high tumor mutation burden (TMB) was associated with poor prognosis in HNSCC [ 7 ]. Considering the prognostic effects of TMB, we further examined the potential relationship between TMB and our risk model.…”

“…Notably, predictive biomarkers based on the intrinsic characteristics of the tumor, such as TMB and gene mutation, were also introduced in our study [ 28 ]. TMB is characterized by the number of tumor gene variants and has been widely used for immunotherapy assessment [ 7 , 29 ]. Recent studies observed that the tumor suppressor gene TP53 mutation was associated with high TMB [ 30 ], and it might predict prognostic outcomes for HNSCC patients.…”

“…Nevertheless, anti-PD-1 therapy failed to induce a response in 82% to 87% of patients [ 5 ]. It is reported that diverse factors might contribute to the low response rate of immunotherapy, including a complex mutation landscape [ 6 , 7 ], heterogeneity of the tumor microenvironment (TME) [ 8 ], etc.…”

RNA methylation patterns mediated by m 6 A regulators are involved in the regulation of immune microenvironment in hepatocellular carcinoma

“…The proportion of in ltrated immune cells was estimated using SSGSEA method. CIBERSORT (https://cibersort.stanford.edu/index.php) is used to characterize cell composition based on gene expression pro les of complex tissues [19]. CIBERSORT was combined with LM22 to estimate the proportion of 22 immune cell phenotypes among different groups.…”

Smoking Cessation after Cancer Diagnosis and Enhanced Therapy Response: Mechanisms and Significance

“…Checkpoint inhibitors are known to be significantly more effective in tumors with higher mutational burden, including lung cancers and skin cancers such as melanoma [ 14 , 15 ]. The efficacy of immunotherapy in lung cancer patients based on their smoking status thus calls for detailed examination [ 16 ], since tobacco smoke is known to induce DNA damage and mutations in several oncogenes and tumor suppressor genes [ 17 , 18 ], resulting in higher mutational burden [ 19 ]; this has been validated in multiple tumor types, including squamous cell carcinomas of the lung, and head and neck [ 20 , 21 ]. It has been suggested that the prevalence of cancer-specific mutated peptides, which are generated as a result of somatic mutations caused by smoking, might increase the prevalence of neo-antigen-specific T cells, enhancing the response to checkpoint blockade [ 22 ].…”