Identification of Genes Related to Immune Infiltration in the Tumor Microenvironment of Cutaneous Melanoma

Abstract

Cutaneous melanoma (CM) is the leading cause of skin cancer deaths and is typically diagnosed at an advanced stage, resulting in a poor prognosis. The tumor microenvironment (TME) plays a significant role in tumorigenesis and CM progression, but the dynamic regulation of immune and stromal components is not yet fully understood. In the present study, we quantified the ratio between immune and stromal components and the proportion of tumor-infiltrating immune cells (TICs), based on the ESTIMATE and CIBERSORT computational methods, in 471 cases of skin CM (SKCM) obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were analyzed by univariate Cox regression analysis, least absolute shrinkage, and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis to identify prognosis-related genes. The developed prognosis model contains ten genes, which are all vital for patient prognosis. The areas under the curve (AUC) values for the developed prognostic model at 1, 3, 5, and 10 years were 0.832, 0.831, 0.880, and 0.857 in the training dataset, respectively. The GSE54467 dataset was used as a validation set to determine the predictive ability of the prognostic signature. Protein–protein interaction (PPI) analysis and weighted gene co-expression network analysis (WGCNA) were used to verify “real” hub genes closely related to the TME. These hub genes were verified for differential expression by immunohistochemistry (IHC) analyses. In conclusion, this study might provide potential diagnostic and prognostic biomarkers for CM.

C1QA, C1QB, and GZMB are novel prognostic biomarkers of skin cutaneous melanoma relating tumor microenvironment

“…3 F,M,T). Overall stage was usually investigated by comparing stage 0–II and stage III–IV 19 , 20 ; thus, we compared the three scores on the basis of stage 0–II and stage III–IV. Interestingly, the StromalScore and ESTIMATEScore in stage III–IV were higher in those in stage 0–II significantly ( P = 0.0055 and P = 0.013, respectively) (Fig.…”

Unravelling the landscape of skin cancer through single-cell transcriptomics

“…identified cytotoxic and exhausted subpopulations that predict prognosis [40] . Other studies have used deconvolution algorithms to link levels of infiltrating immune cells with survival and nominate genes that may be involved in this process [62] , [63] , [64] . Deconvolution was also been applied to cSCC by Ji et al., who linked TSK-like expression with CAF activity in several TCGA cancer types [37] .…”

HLA-DRB1: A new potential prognostic factor and therapeutic target of cutaneous melanoma and an indicator of tumor microenvironment remodeling

“…Cutaneous melanoma (CM) is a highly aggressive malignancy caused by the malignant transformation of melanocytes and it is also the most common type of skin cancer [1][2][3]. According to the latest population-based cancer occurrence data released by the American Cancer Society, 100,350 new cutaneous melanoma cases and 6850 cutaneous melanoma deaths are expected in the United States in 2020, 4% increase in new cases and 5% decrease in deaths compared to 2019 [4,5].…”

“…Multiple studies have revealed that genetic mutations and the alterations of TME led to the spread of melanoma [9][10][11][12][13]. With the rapid development of high-throughput sequencing technologies, it has become more convenient to detect gene expression during tumor progression, providing effective targets for diagnosis and treatment, but there is still a lack of reliable biomarkers to monitor treatment effects [3]. Consequently, there is an urgent need to find microenvironment-related genes that affect the prognosis of CM patients.…”