Development of an IFNγ response‐related signature for predicting the survival of cutaneous melanoma

xloma.fota13 shared this article with you from Inoreader Development of an IFNγ response‐related signature for predicting the survival of cutaneous melanoma Via Cancer Medicine We established an effective five‐IFNγ response‐related gene‐based risk score, which has potential to be a novel prognostic signature and may provide insight into tumor immune microenvironment of cutaneous melanoma. Abstract Background The tumor microenvironment (TME) plays a critical role in tumorigenesis, development, and therapeutic efficacy. Major advances have been achieved in the treatment of various cancers through immunotherapy. Nevertheless, only a minority of patients have positive responses to immunotherapy, which is partly due to conditions of the immunosuppressive microenvironment. Therefore, it is essential to identify prognostic biomarkers that reflect heterogeneous landscapes of the TME. Methods and materials Based upon the ESTIMATE algorithm, we evaluated the infiltrating levels of immune and stromal components derived from patients afflicted by various types of cancer from The Cancer Genome Atlas database (TCGA). According to respective patient immune and stromal scores, we categorized cases into high‐ and low‐scoring subgroups for each cancer type to explore associations between TME and patient prognosis. Gene Set Enrichment Analyses (GSEA) were conducted and genes enriched in IFNγ response signaling pathway were selected to facilitate establishment of a risk model for predicting overall survival (OS). Furthermore, we investigated the associations between the prognostic signature and tumor immune infiltration landscape by using CIBERSORT algorithm and TIMER database. Results Among the cancers assessed, the immune scores for skin cutaneous melanoma (SKCM) were the most significantly correlated with patients' survival time (P < .0001). We identified and validated a five‐IFNγ response‐related gene signature (UBE2L6, PARP14, IFIH1, IRF2, and GBP4), which was closely correlated with the prognosis for SKCM afflicted patients. Multivariate Cox regression analysis indicated that this risk model was an independent prognostic factor for SKCM. Tumor‐infiltrating lymphocytes and specific immune checkpoint molecules had notably differential levels of expression in high‐ compared to low‐risk samples. Conclusion In this study, we established a novel five‐IFNγ response‐related gene signature that provided a better and increasingly comprehensive understanding of tumor immune landscape, and which demonstrated good performance in predicting outcomes for patients afflicted by SKCM. View on the web Inoreader. Take back control of your news feed. Follow us on Twitter and Facebook.