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. 2022 Apr 15;12(4):1727-1739.
eCollection 2022.

Identification of immune-related biomarkers associated with tumorigenesis and prognosis in skin cutaneous melanoma

Zhong-Hao Ji  1   2   3 , Wen-Zhi Ren  2 , Shuo Yang  2 , Dong-Xu Wang  2 , Zi-Ping Jiang  1   2 , Chao Lin  4 , Ye Jin  5 , Wen-Tai Tian  1
Affiliations

Identification of immune-related biomarkers associated with tumorigenesis and prognosis in skin cutaneous melanoma

Zhong-Hao Ji et al. Am J Cancer Res. .

Abstract

Skin cutaneous melanoma (SKCM) is one of the most malignant and aggressive forms of cancer. Investigating the mechanisms of carcinogenesis further could lead to the discovery of prognostic biomarkers that could be used to guide cancer treatment. In this study, we conducted integrative bioinformatics analyses of TCGA database, STRING, cBioPortal, TRRUST, The Human Protein Atlas, and DGIdb to determine which hub genes contributed to tumor progression and the cancer-associated immunology of SKCM. The results show that immune-related 873 differential genes grouped SKCM samples into subtypes. The initial results showed that the optimal number of clusters was two subgroups. Further analysis showed that there were significant differences in survival rate and immune infiltration level between the two subgroups. Subsequently, obtaining the different genes between groups, construct PPI to screen 6 hub genes (HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DRA, HLA-DRB1, HLA-DRB5). In total, 6 MHC class II molecules were significantly related to overall survival. We then analyzed the expression of these genes along with their mutation landscapes, transcription factor regulation, and drug regulatory networks. In summary, our study identified 6 MHC class II molecules (HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DRA, HLA-DRB1, HLA-DRB5) as important biomarkers in the occurrence and progression of SKCM tumors. Their expression levels are closely related to prognosis and immune infiltration and can help us better understand the tumorigenesis of SKCM.

Keywords: Cutaneous melanoma; HLA; biomarker; immune; infiltration; prognosis.

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Conflict of interest statement

None.

Figures

Figure 1
Figure 1
GO and KEGG analysis of the DEGs in SKCM. A. Volcano plot of differential gene expression analysis. B. GO and KEGG enrichment analysis. C. VN map showing the overlap of differential genes and immune-related genes.
Figure 2
Figure 2
Immune subtypes of SKCM samples and immune infiltration analysis. A. Two cluster subgroups. B. Overall Survival (OS) subgroup analysis. C. Immune infiltration analyses of two subgroups. D. Correlation of two subgroups with immune checkpoint genes expression. *P<0.05, **P<0.01, ***P<0.001.
Figure 3
Figure 3
Analysis of differential genes among two subgroups and screening of hub genes. A. Volcano plot of differential gene expression. B. PPI network and hub genes network of the DEGs using Cytoscape. (DEGs, differentially expressed genes; PPI, protein-protein interaction).
Figure 4
Figure 4
Six hub genes were identified (HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DRA, HLA-DRB1, and HLA-DRB5). A. The mRNA expression levels of 8 hub genes in SKCM. B, C. ROC curve of 8 hub genes in SKCM.
Figure 5
Figure 5
Validation of protein expression levels of hub genes in the HPA database.
Figure 6
Figure 6
Kaplan-Meier overall survival analysis of patients in the TCGA cohort.
Figure 7
Figure 7
Hub genes expression correlation and mutation analysis in SKCM (cBioPortal). A. Hub genes mutation analysis. B. Correction between different hub genes.
Figure 8
Figure 8
Analysis of the expression of the indicated transcription factors. A. The mRNA expression levels of the indicated transcription factors in SKCM. B. Correlation between transcription factors and hub genes expression (cBioPortal). C. Validation of protein expression levels of the indicated transcription factors in the HPA database.
Figure 9
Figure 9
Drug-gene interaction diagram. The yellow circle indicates the related hub gene, and the pink square indicates the drug.
See this image and copyright information in PMC

References

    1. Schadendorf D, van Akkooi ACJ, Berking C, Griewank KG, Gutzmer R, Hauschild A, Stang A, Roesch A, Ugurel S. Melanoma. Lancet. 2018;392:971–984. - PubMed
    1. Pasquali S, Hadjinicolaou AV, Chiarion Sileni V, Rossi CR, Mocellin S. Systemic treatments for metastatic cutaneous melanoma. Cochrane Database Syst Rev. 2018;2:CD011123. - PMC - PubMed
    1. Goodson AG, Grossman D. Strategies for early melanoma detection: approaches to the patient with nevi. J Am Acad Dermatol. 2009;60:719–735. - PMC - PubMed
    1. Barnes TA, Amir E. HYPE or HOPE: the prognostic value of infiltrating immune cells in cancer. Br J Cancer. 2018;118:e5. - PMC - PubMed
    1. Bajor DL, Mick R, Riese MJ, Huang AC, Sullivan B, Richman LP, Torigian DA, George SM, Stelekati E, Chen F, Melenhorst JJ, Lacey SF, Xu X, Wherry EJ, Gangadhar TC, Amaravadi RK, Schuchter LM, Vonderheide RH. Long-term outcomes of a phase I study of agonist CD40 antibody and CTLA-4 blockade in patients with metastatic melanoma. Oncoimmunology. 2018;7:e1468956. - PMC - PubMed

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