Identification of prognostic genes in uveal melanoma microenvironment

Abstract

Background Uveal melanoma (UM) is the most common primary intraocular malignancy in adults. Many previous studies have demonstrated that the infiltrating of immune and stromal cells in the tumor microenvironment contributes significantly to prognosis. Methods Dataset TCGA-UVM, download from TCGA portal, was taken as the training cohort, and GSE22138, obtained from GEO database, was set as the validation cohort. ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to initial screen for potential prognostic genes. Then these genes entered into the validation cohort for validation using the same methods as that in the training cohort. Moreover, we conducted correlation analyses between the genes obtained in the validation cohort and the status of chromosome 3, chromosome 8q, and tumor metastasis to get prognosis genes. At last, the immune infiltration analysis was performed between the prognostic genes and 6 main kinds of tumor-infiltrating immune cells (TICs) for understanding the role of the genes in the tumor microenvironment. Results 959 intersection DEGs were found in the UM microenvironment. Kaplan-Meier and Cox analysis was then performed in the training and validation cohorts on these DEGs, and 52 genes were identified with potential prognostic value. After comparing the 52 genes to chromosome 3, chromosome 8q, and metastasis, we obtained 21 genes as the prognostic genes. The immune infiltration analysis showed that Neutrophil had the potential prognostic ability, and almost every prognostic gene we had identified was correlated with abundances of Neutrophil and CD8+ T Cell. Conclusions Identifying 21 prognosis genes (SERPINB9, EDNRB, RAPGEF3, HFE, RNF43, ZNF415, IL12RB2, MTUS1, NEDD9, ZNF667, AZGP1, WARS, GEM, RAB31, CALHM2, CA12, MYEOV, CELF2, SLCO5A1, ISM1, and PAPSS2) could accurately identify patients' prognosis and had close interactions with Neutrophil in the tumor environment, which may provide UM patients with personalized prognosis prediction and new treatment insights.

Construction of a Promising Tumor-Infiltrating CD8+ T Cells Gene Signature to Improve Prediction of the Prognosis and Immune Response of Uveal Melanoma

“…It is consistent with previous studies that CD8+ T cell refers to favorable prognosis in CM and predicts poor prognosis in UM (Azimi et al, 2012;Gartrell et al, 2018;Wang et al, 2020). Besides, Luo et al recently identified several prognostic genes in UM, and almost every gene was correlated with abundance in CD8+ T cell (Luo and Ma, 2020). Hence, it is urgent to explore the adaptive immune response gene signature to improve the effect of tumorinfiltrating CD8+ T cell targeting approaches and the response of immunotherapies in UM.…”

Additive Role of Immune System Infiltration and Angiogenesis in Uveal Melanoma Progression

“…Contrary to what is found in other tumors, lymphocytic infiltration is related to poor prognosis. In a similar vein, a study by Luo and Ma [ 22 ] in UM also associated CD8 lymphocytic infiltration with poor prognosis (univariate analysis), and B-cell infiltration with better prognosis (multivariate analysis). This association between inflammation and poor prognosis in uveal melanoma has already been described in individual studies [ 14 , 23 , 24 , 25 ].…”

Bioinformatic Analysis Reveals Central Role for Tumor-Infiltrating Immune Cells in Uveal Melanoma Progression

“…While our results need further verification in different experimental settings, the CIBERSORTx algorithm we employed has been extensively validated with techniques such as flow cytometry, mass cytometry, immunohistochemistry, and single-cell RNA-seq by multiple different groups, providing robust data confirming its accuracy [40,[63][64][65]. Nevertheless, others have already created mRNA/miRNA/DNA-based scores with strong prognostic values in UM tumors [33,[66][67][68][69][70][71][72]. Rather than compete with them, our foremost motive for creating the cell type-based prognostic score was to select the cell types playing a prime role in the biology of UM progression Previous research has identified extensive lymphocyte infiltration as a negative prognostic factor in UM; however, the prognostic role of individual subsets was not assessed Another dominant subset of tumor-infiltrating immune cells is macrophages.…”