Cargando…
Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma
Skin cutaneous melanoma (SKCM) is the major cause of death for skin cancer patients, its high metastasis often leads to poor prognosis of patients with malignant melanoma. However, the molecular mechanisms underlying metastatic melanoma remain to be elucidated. In this study we aim to identify and v...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820192/ https://www.ncbi.nlm.nih.gov/pubmed/33490091 http://dx.doi.org/10.3389/fcell.2020.630790 |
_version_ | 1783639155641679872 |
---|---|
author | Cheng, Si Li, Zhe Zhang, Wenhao Sun, Zhiqiang Fan, Zhigang Luo, Judong Liu, Hui |
author_facet | Cheng, Si Li, Zhe Zhang, Wenhao Sun, Zhiqiang Fan, Zhigang Luo, Judong Liu, Hui |
author_sort | Cheng, Si |
collection | PubMed |
description | Skin cutaneous melanoma (SKCM) is the major cause of death for skin cancer patients, its high metastasis often leads to poor prognosis of patients with malignant melanoma. However, the molecular mechanisms underlying metastatic melanoma remain to be elucidated. In this study we aim to identify and validate prognostic biomarkers associated with metastatic melanoma. We first construct a co-expression network using large-scale public gene expression profiles from GEO, from which candidate genes are screened out using weighted gene co-expression network analysis (WGCNA). A total of eight modules are established via the average linkage hierarchical clustering, and 111 hub genes are identified from the clinically significant modules. Next, two other datasets from GEO and TCGA are used for further screening of biomarker genes related to prognosis of metastatic melanoma, and identified 11 key genes via survival analysis. We find that IL10RA has the highest correlation with clinically important modules among all identified biomarker genes. Further in vitro biochemical experiments, including CCK8 assays, wound-healing assays and transwell assays, have verified that IL10RA can significantly inhibit the proliferation, migration and invasion of melanoma cells. Furthermore, gene set enrichment analysis shows that PI3K-AKT signaling pathway is significantly enriched in metastatic melanoma with highly expressed IL10RA, indicating that IL10RA mediates in metastatic melanoma via PI3K-AKT pathway. |
format | Online Article Text |
id | pubmed-7820192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78201922021-01-23 Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma Cheng, Si Li, Zhe Zhang, Wenhao Sun, Zhiqiang Fan, Zhigang Luo, Judong Liu, Hui Front Cell Dev Biol Cell and Developmental Biology Skin cutaneous melanoma (SKCM) is the major cause of death for skin cancer patients, its high metastasis often leads to poor prognosis of patients with malignant melanoma. However, the molecular mechanisms underlying metastatic melanoma remain to be elucidated. In this study we aim to identify and validate prognostic biomarkers associated with metastatic melanoma. We first construct a co-expression network using large-scale public gene expression profiles from GEO, from which candidate genes are screened out using weighted gene co-expression network analysis (WGCNA). A total of eight modules are established via the average linkage hierarchical clustering, and 111 hub genes are identified from the clinically significant modules. Next, two other datasets from GEO and TCGA are used for further screening of biomarker genes related to prognosis of metastatic melanoma, and identified 11 key genes via survival analysis. We find that IL10RA has the highest correlation with clinically important modules among all identified biomarker genes. Further in vitro biochemical experiments, including CCK8 assays, wound-healing assays and transwell assays, have verified that IL10RA can significantly inhibit the proliferation, migration and invasion of melanoma cells. Furthermore, gene set enrichment analysis shows that PI3K-AKT signaling pathway is significantly enriched in metastatic melanoma with highly expressed IL10RA, indicating that IL10RA mediates in metastatic melanoma via PI3K-AKT pathway. Frontiers Media S.A. 2021-01-08 /pmc/articles/PMC7820192/ /pubmed/33490091 http://dx.doi.org/10.3389/fcell.2020.630790 Text en Copyright © 2021 Cheng, Li, Zhang, Sun, Fan, Luo and Liu. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cell and Developmental Biology Cheng, Si Li, Zhe Zhang, Wenhao Sun, Zhiqiang Fan, Zhigang Luo, Judong Liu, Hui Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma |
title | Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma |
title_full | Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma |
title_fullStr | Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma |
title_full_unstemmed | Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma |
title_short | Identification of IL10RA by Weighted Correlation Network Analysis and in vitro Validation of Its Association With Prognosis of Metastatic Melanoma |
title_sort | identification of il10ra by weighted correlation network analysis and in vitro validation of its association with prognosis of metastatic melanoma |
topic | Cell and Developmental Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7820192/ https://www.ncbi.nlm.nih.gov/pubmed/33490091 http://dx.doi.org/10.3389/fcell.2020.630790 |
work_keys_str_mv | AT chengsi identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma AT lizhe identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma AT zhangwenhao identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma AT sunzhiqiang identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma AT fanzhigang identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma AT luojudong identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma AT liuhui identificationofil10rabyweightedcorrelationnetworkanalysisandinvitrovalidationofitsassociationwithprognosisofmetastaticmelanoma |