Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status
Purpose: Due to poor prognosis and immunotherapy failure of skin cutaneous melanoma (SKCM), this study sought to find necroptosis-related biomarkers to predict prognosis and improve the situation with predicted immunotherapy drugs. Experimental Design: The Cancer Genome Atlas (TCGA) and The Genotype...
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-01-01
|
| Series: | Journal of Personalized Medicine |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2075-4426/13/2/245 |
| _version_ | 1797619978770317312 |
|---|---|
| author | Xiaoying Cao Jiaming He An Chen Jianhua Ran Jing Li Dilong Chen Hengshu Zhang |
| author_facet | Xiaoying Cao Jiaming He An Chen Jianhua Ran Jing Li Dilong Chen Hengshu Zhang |
| author_sort | Xiaoying Cao |
| collection | DOAJ |
| description | Purpose: Due to poor prognosis and immunotherapy failure of skin cutaneous melanoma (SKCM), this study sought to find necroptosis-related biomarkers to predict prognosis and improve the situation with predicted immunotherapy drugs. Experimental Design: The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression Program (GTEx) database were utilized to recognize the differential necroptosis-related genes (NRGs). Univariate Cox (uni-Cox) and least absolute shrinkage and selection operator (LASSO) Cox analysis were utilized for prognostic signature establishment. The signature was verified in the internal cohort. To assess the signature’s prediction performance, the area under the curve (AUC) of receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) analyses, multivariate Cox (multi-Cox) regression, nomogram, and calibration curves were performed. The molecular and immunological aspects were also reviewed using single-sample gene set enrichment analysis (ssGSEA). Cluster analysis was performed to identify the different types of SKCM. Finally, the expression of the signature gene was verified by immunohistochemical staining. Results: On basis of the 67 NRGs, 4 necroptosis-related genes (FASLG, PLK1, EGFR, and TNFRSF21) were constructed to predict SKCM prognosis. The area’s 1-, 3-, and 5-year OS under the AUC curve was 0.673, 0.649, and 0.677, respectively. High-risk individuals had significantly lower overall survival (OS) compared to low-risk patients. Immunological status and tumor cell infiltration in high-risk groups were significantly lower, indicating an immune system that was suppressed. In addition, hot and cold tumors could be obtained by cluster analysis, which is helpful for accurate treatment. Cluster 1 was considered a hot tumor and more susceptible to immunotherapy. Immunohistochemical results were consistent with positive and negative regulation of coefficients in signature. Conclusion: The results of this finding supported that NRGs could predict prognosis and help make a distinction between the cold and hot tumors for improving personalized therapy for SKCM. |
| first_indexed | 2024-03-11T08:34:39Z |
| format | Article |
| id | doaj.art-7fc00bf00b674e928b0bea0e5035b809 |
| institution | Directory Open Access Journal |
| issn | 2075-4426 |
| language | English |
| last_indexed | 2024-03-11T08:34:39Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Personalized Medicine |
| spelling | doaj.art-7fc00bf00b674e928b0bea0e5035b8092023-11-16T21:32:46ZengMDPI AGJournal of Personalized Medicine2075-44262023-01-0113224510.3390/jpm13020245Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment StatusXiaoying Cao0Jiaming He1An Chen2Jianhua Ran3Jing Li4Dilong Chen5Hengshu Zhang6Department of Plastic and Burn Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, ChinaLaboratory of Stem Cells and Tissue Engineering, College of Basic Medical, Chongqing Medical University, Chongqing 400016, ChinaLaboratory of Stem Cells and Tissue Engineering, College of Basic Medical, Chongqing Medical University, Chongqing 400016, ChinaNeuroscience Research Center, College of Basic Medical, Chongqing Medical University, Chongqing 400016, ChinaLaboratory of Stem Cells and Tissue Engineering, College of Basic Medical, Chongqing Medical University, Chongqing 400016, ChinaChongqing Key Laboratory of Development and Utilization of Genuine Medicinal Materials in Three Gorges Reservoir Area, Chongqing Three Gorges Medical College, Chongqing 404120, ChinaDepartment of Plastic and Burn Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, ChinaPurpose: Due to poor prognosis and immunotherapy failure of skin cutaneous melanoma (SKCM), this study sought to find necroptosis-related biomarkers to predict prognosis and improve the situation with predicted immunotherapy drugs. Experimental Design: The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression Program (GTEx) database were utilized to recognize the differential necroptosis-related genes (NRGs). Univariate Cox (uni-Cox) and least absolute shrinkage and selection operator (LASSO) Cox analysis were utilized for prognostic signature establishment. The signature was verified in the internal cohort. To assess the signature’s prediction performance, the area under the curve (AUC) of receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) analyses, multivariate Cox (multi-Cox) regression, nomogram, and calibration curves were performed. The molecular and immunological aspects were also reviewed using single-sample gene set enrichment analysis (ssGSEA). Cluster analysis was performed to identify the different types of SKCM. Finally, the expression of the signature gene was verified by immunohistochemical staining. Results: On basis of the 67 NRGs, 4 necroptosis-related genes (FASLG, PLK1, EGFR, and TNFRSF21) were constructed to predict SKCM prognosis. The area’s 1-, 3-, and 5-year OS under the AUC curve was 0.673, 0.649, and 0.677, respectively. High-risk individuals had significantly lower overall survival (OS) compared to low-risk patients. Immunological status and tumor cell infiltration in high-risk groups were significantly lower, indicating an immune system that was suppressed. In addition, hot and cold tumors could be obtained by cluster analysis, which is helpful for accurate treatment. Cluster 1 was considered a hot tumor and more susceptible to immunotherapy. Immunohistochemical results were consistent with positive and negative regulation of coefficients in signature. Conclusion: The results of this finding supported that NRGs could predict prognosis and help make a distinction between the cold and hot tumors for improving personalized therapy for SKCM.https://www.mdpi.com/2075-4426/13/2/245skin cutaneous melanoma (skcm)necroptosisprognosisbioinformaticstumor microenvironment |
| spellingShingle | Xiaoying Cao Jiaming He An Chen Jianhua Ran Jing Li Dilong Chen Hengshu Zhang Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status Journal of Personalized Medicine skin cutaneous melanoma (skcm) necroptosis prognosis bioinformatics tumor microenvironment |
| title | Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status |
| title_full | Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status |
| title_fullStr | Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status |
| title_full_unstemmed | Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status |
| title_short | Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status |
| title_sort | comprehensive analysis of necroptosis landscape in skin cutaneous melanoma for appealing its implications in prognosis estimation and microenvironment status |
| topic | skin cutaneous melanoma (skcm) necroptosis prognosis bioinformatics tumor microenvironment |
| url | https://www.mdpi.com/2075-4426/13/2/245 |
| work_keys_str_mv | AT xiaoyingcao comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus AT jiaminghe comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus AT anchen comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus AT jianhuaran comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus AT jingli comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus AT dilongchen comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus AT hengshuzhang comprehensiveanalysisofnecroptosislandscapeinskincutaneousmelanomaforappealingitsimplicationsinprognosisestimationandmicroenvironmentstatus |