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Comprehensive analysis of tumor microenvironment and identification of an immune signature to predict the prognosis and immunotherapeutic response in lung squamous cell carcinoma.
Annals of Translational Medicine 2021 April
Background: Tumor mutation burden (TMB) and immune microenvironment are important determinants of prognosis and immunotherapeutic efficacy for cancer patients. The aim of the present study was to develop an immune signature to effectively predict prognosis and immunotherapeutic response in patients with lung squamous cell carcinoma (LUSC).
Methods: TMB and immune microenvironment characteristics were comprehensively analyzed by multi-omics data in LUSC. The immune signature was further constructed and validated in multiple independent datasets by LASSO Cox regression analysis. Next, the value of immune signature in predicting the response of immunotherapy was evaluated. Finally, the possible mechanism of immune signature was also investigated.
Results: A novel immune signature based on 5 genes was constructed and validated to predict the prognosis of LUSC patients. These genes were filamin-C, Rho family GTPase 1, interleukin 4-induced gene-1, transglutaminase 2, and prostaglandin I2 synthase. High-risk patients had significantly poorer survival than low-risk patients. A nomogram was also developed based on the immune signature and tumor stage, which showed good application. Furthermore, we found that the immune signature had a significant correlation with immune checkpoint, microsatellite instability, tumor infiltrating lymphocytes, cytotoxic activity scores, and T-cell-inflamed score, suggesting low-risk patients are more likely to benefit from immunotherapy. Finally, functional enrichment and pathway analyses revealed several significantly enriched immune-related biological processes and metabolic pathways.
Conclusions: In the present study, we developed a novel immune signature that could predict prognosis and immunotherapeutic response in LUSC patients. The results not only help identify LUSC patients with poor survival, but also increase our understanding of the immune microenvironment and immunotherapy in LUSC.
Methods: TMB and immune microenvironment characteristics were comprehensively analyzed by multi-omics data in LUSC. The immune signature was further constructed and validated in multiple independent datasets by LASSO Cox regression analysis. Next, the value of immune signature in predicting the response of immunotherapy was evaluated. Finally, the possible mechanism of immune signature was also investigated.
Results: A novel immune signature based on 5 genes was constructed and validated to predict the prognosis of LUSC patients. These genes were filamin-C, Rho family GTPase 1, interleukin 4-induced gene-1, transglutaminase 2, and prostaglandin I2 synthase. High-risk patients had significantly poorer survival than low-risk patients. A nomogram was also developed based on the immune signature and tumor stage, which showed good application. Furthermore, we found that the immune signature had a significant correlation with immune checkpoint, microsatellite instability, tumor infiltrating lymphocytes, cytotoxic activity scores, and T-cell-inflamed score, suggesting low-risk patients are more likely to benefit from immunotherapy. Finally, functional enrichment and pathway analyses revealed several significantly enriched immune-related biological processes and metabolic pathways.
Conclusions: In the present study, we developed a novel immune signature that could predict prognosis and immunotherapeutic response in LUSC patients. The results not only help identify LUSC patients with poor survival, but also increase our understanding of the immune microenvironment and immunotherapy in LUSC.
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