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...

Descripción completa

Detalles Bibliográficos
Autores principales: Cheng, Si, Li, Zhe, Zhang, Wenhao, Sun, Zhiqiang, Fan, Zhigang, Luo, Judong, Liu, Hui
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