Skin cutaneous melanoma (SKCM) is one of the most malignant skin cancers and remains a health concern worldwide. Pyroptosis is a newly recognized form of programmed cell death and plays a vital role in cancer progression. We aim to construct a prognostic model for SKCM patients based on pyroptosis-related genes (PRGs). SKCM patients from The Cancer Genome Atlas (TCGA) were divided into training and validation cohorts. We used GSE65904 downloaded from GEO database as an external validation cohort. We performed Cox regression and the least absolute shrinkage and selection operator (LASSO) regression to identify prognostic genes and built a risk score. Patients were divided into high- and low-risk groups based on the risk score. Differently expressed genes (DEGs), immune cell infiltration and immune-related pathways activation were compared between the two groups. We established a model containing 4 PRGs, i.e., GSDMA, GSDMC, AIM2 and NOD2. The overall survival (OS) time was significantly different between the 2 groups. The risk score was an independent predictor for prognosis in both the uni- and multi-variable Cox regressions. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that DEGs were enriched in immune-related pathways. Most types of immune cells were highly expressed in the low risk group. All immune pathways were significantly up-regulated in the low-risk group. In addition, low-risk patients had a better response to immune checkpoint inhibitors. Our novel pyroptosis-related gene signature could predict the prognosis of SKCM patients and their response to immune checkpoint inhibitors.
Citation: Zehao Niu, Yujian Xu, Yan Li, Youbai Chen, Yan Han. Construction and validation of a novel pyroptosis-related signature to predict prognosis in patients with cutaneous melanoma[J]. Mathematical Biosciences and Engineering, 2022, 19(1): 688-706. doi: 10.3934/mbe.2022031
Skin cutaneous melanoma (SKCM) is one of the most malignant skin cancers and remains a health concern worldwide. Pyroptosis is a newly recognized form of programmed cell death and plays a vital role in cancer progression. We aim to construct a prognostic model for SKCM patients based on pyroptosis-related genes (PRGs). SKCM patients from The Cancer Genome Atlas (TCGA) were divided into training and validation cohorts. We used GSE65904 downloaded from GEO database as an external validation cohort. We performed Cox regression and the least absolute shrinkage and selection operator (LASSO) regression to identify prognostic genes and built a risk score. Patients were divided into high- and low-risk groups based on the risk score. Differently expressed genes (DEGs), immune cell infiltration and immune-related pathways activation were compared between the two groups. We established a model containing 4 PRGs, i.e., GSDMA, GSDMC, AIM2 and NOD2. The overall survival (OS) time was significantly different between the 2 groups. The risk score was an independent predictor for prognosis in both the uni- and multi-variable Cox regressions. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that DEGs were enriched in immune-related pathways. Most types of immune cells were highly expressed in the low risk group. All immune pathways were significantly up-regulated in the low-risk group. In addition, low-risk patients had a better response to immune checkpoint inhibitors. Our novel pyroptosis-related gene signature could predict the prognosis of SKCM patients and their response to immune checkpoint inhibitors.
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Figures(7)
Zehao Niu, Yujian Xu, Yan Li, Youbai Chen, Yan Han. Construction and validation of a novel pyroptosis-related signature to predict prognosis in patients with cutaneous melanoma[J]. Mathematical Biosciences and Engineering, 2022, 19(1): 688-706. doi: 10.3934/mbe.2022031
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