Research Paper Volume 13, Issue 19 pp 23036—23071
Low expression of endoplasmic reticulum stress-related gene SERP1 is associated with poor prognosis and immune infiltration in skin cutaneous melanoma
- 1 Department of Anesthesiology, Sichuan Cancer Center, Sichuan Cancer Hospital and Institute, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan Province, China
- 2 Department of Anesthesiology, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
- 3 Department of Anesthesiology, The Second People’s Hospital of Yibin, Yibin, Sichuan Province, China
Received: July 19, 2021 Accepted: September 20, 2021 Published: October 5, 2021
https://doi.org/10.18632/aging.203594How to Cite
Copyright: © 2021 Fan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Stress-associated endoplasmic reticulum protein 1 (SERP1) is a gene induced by endoplasmic reticulum (ER) stress and a major contributor to multiple tumor types. Skin cutaneous melanoma (SKCM) is a highly aggressive and fatal cancer with poor treatment outcomes after progression. In this study, we evaluated SERP1’s role in tumorigenesis, prognosis, and immune infiltration in SKCM. Patients with SKCM had low SERP1 expression. We identified differentially expressed genes between high- and low-SERP1 expression groups and conducted functional, pathway, and gene enrichment analyses. Protein–protein (PPI) and gene–gene interaction (GGI) networks were constructed via STRING and GeneMANIA, respectively. SERP1 mutation information was obtained through cBioPortal; location in the skin was identified through the Human Protein Atlas. Kaplan–Meier analysis revealed an association between low SERP1 expression and overall survival (OS), disease-specific survival (DSS), progress-free interval (PFI) rates, and worse prognosis in patients with multiple clinicopathological features. Cox regression analysis and nomograms further presented SERP1 level as an independent prognostic factor for patients with SKCM. Furthermore, there were significant correlations between SERP1 expression and immune infiltrates; thus, low SERP1 expression is associated with immune cell infiltration and can be considered a poor prognostic biomarker in patients with SKCM.
Stress-associated endoplasmic reticulum protein 1 (SERP1) is a gene induced by endoplasmic reticulum (ER) stress and a major contributor to multiple tumor types. Skin cutaneous melanoma (SKCM) is a highly aggressive and fatal cancer with poor treatment outcomes after progression. In this study, we evaluated SERP1’s role in tumorigenesis, prognosis, and immune infiltration in SKCM. Patients with SKCM had low SERP1 expression. We identified differentially expressed genes between high- and low-SERP1 expression groups and conducted functional, pathway, and gene enrichment analyses. Protein–protein (PPI) and gene–gene interaction (GGI) networks were constructed via STRING and GeneMANIA, respectively. SERP1 mutation information was obtained through cBioPortal; location in the skin were identified through the Human Protein Atlas. Kaplan–Meier analysis revealed an association between low SERP1 expression and overall survival (OS), disease-specific survival (DSS), progress-free interval (PFI) rates, and worse prognosis in patients with multiple clinicopathological features. Cox regression analysis and nomograms further presented SERP1 level as an independent prognostic factor for patients with SKCM. Furthermore, there were significant correlations between SERP1 expression and immune infiltrates; thus, low SERP1 expression is associated with immune cell infiltration and can be considered a poor prognostic biomarker in patients with SKCM.
Abbreviations
SKCM: Skin Cutaneous Melanoma; SERP1: Stress associated endoplasmic reticulum protein 1; ER: Endoplasmic reticulum; TCGA: The Cancer Genome Atlas; GTEx: Genotype-Tissue Expression; PPI: Protein-protein interaction; GGI: Gene–gene interaction; GO: Gene Ontology; KEGG: Genes and Genomes; GSEA: Gene set enrichment analyses; TPM: transcripts per million; FPKM: Fragments Per Kilobase per Million; DEGs: differentially expressed genes; OS: overall survival; DSS: disease specific survival; PFI: progress free interval; BP: biological process; MF: molecular function; CC: cellular component; HR: hazard ratio; CI: confidence interval; AUC: areas under the ROC curve; ROS: reactive oxygen species; UPR: unfolded protein response; TME: tumor microenvironment; ECM: extracellular matrix; MDSC: myeloid-derived suppressor cells; MMPs: matrix metalloproteinase; TAMs: tumor-associated macrophages; UPR: Unfolded protein response.