Immune Microenvironment Related Competitive Endogenous RNA Network as Powerful Predictors for Melanoma Prognosis Based on WGCNA Analysis

Frontiers in Oncology
Yaqi ChengZhichong Wang

Abstract

Cutaneous melanoma is the most life-threatening skin malignant tumor due to its increasing metastasis and mortality rate. The abnormal competitive endogenous RNA network promotes the development of tumors and becomes biomarkers for the prognosis of various tumors. At the same time, the tumor immune microenvironment (TIME) is of great significance for tumor outcome and prognosis. From the perspective of TIME and ceRNA network, this study aims to explain the prognostic factors of cutaneous melanoma systematically and find novel and powerful biomarkers for target therapies. We obtained the transcriptome data of cutaneous melanoma from The Cancer Genome Atlas (TCGA) database, 3 survival-related mRNAs co-expression modules and 2 survival-related lncRNAs co-expression modules were identified through weighted gene co-expression network analysis (WCGNA), and 144 prognostic miRNAs were screened out by univariate Cox proportional hazard regression. Cox regression model and Kaplan-Meier survival analysis were employed to identify 4 hub prognostic mRNAs, and the prognostic ceRNA network consisting of 7 lncRNAs, 1 miRNA and 4 mRNAs was established. After analyzing the composition and proportion of total immune cells in cutaneous melanoma mi...Continue Reading

References

Aug 1, 1995·Molecular and Cellular Biology·G BaughmanS Bourgeois
Dec 4, 1998·BMJ : British Medical Journal·J M Bland, D G Altman
Jun 3, 1999·Annual Review of Public Health·L D Fisher, D Y Lin
May 2, 2006·Statistical Applications in Genetics and Molecular Biology·Bin Zhang, Steve Horvath
Mar 18, 2008·Nature·Valur EmilssonKari Stefansson
Dec 31, 2008·BMC Bioinformatics·Peter Langfelder, Steve Horvath
Aug 22, 2009·Cell Death and Differentiation·S RomanoM F Romano
Nov 18, 2009·Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology·Charles M BalchVernon K Sondak
Nov 6, 2010·Investigative Ophthalmology & Visual Science·Xiaoyan ChenLili Tu
Mar 30, 2012·Omics : a Journal of Integrative Biology·Guangchuang YuQing-Yu He
Aug 30, 2012·Nature Methods·Caroline A SchneiderKevin W Eliceiri
Nov 16, 2012·The Journal of Investigative Dermatology·Chonglin LuoStefan B Eichmüller
Jan 17, 2014·Nature·Yvonne TayPier Paolo Pandolfi
Sep 10, 2014·Current Protocols in Bioinformatics·Gang SuGary D Bader
Nov 8, 2014·Nucleic Acids Research·Nathan Wong, Xiaowei Wang
Mar 17, 2015·Trends in Immunology·Renato OstuniGioacchino Natoli
Mar 31, 2015·Nature Methods·Aaron M NewmanAsh A Alizadeh
Jun 2, 2015·The New England Journal of Medicine·James LarkinJedd D Wolchok
Jul 18, 2015·Experimental Dermatology·Shuai HaoDacheng He
Aug 13, 2015·ELife·Vikram AgarwalDavid P Bartel
Sep 12, 2015·Journal of Medical Genetics·Xiaolong QiWang Ma
Feb 5, 2016·Cancer Letters·Ting Wu, Yun Dai
Jan 6, 2017·Cancer Immunology Research·Dmitry I Gabrilovich
Aug 19, 2017·Science·Mathias UhlenFredrik Ponten
Oct 14, 2017·CA: a Cancer Journal for Clinicians·Jeffrey E GershenwaldUNKNOWN for members of the American Joint Committee on Cancer Melanoma Expert Panel and the International Melanoma Database and Disc
Nov 8, 2017·International Journal of Molecular Sciences·Gabriele Romano, Lawrence N Kwong
Nov 25, 2017·Journal of Neuro-oncology·Wen WangJizong Zhao
Jan 20, 2018·Cell Death and Differentiation·Meiying LuoYongfei Yang
Mar 16, 2018·Medical Science Monitor : International Medical Journal of Experimental and Clinical Research·Jianwen LongXianming Pi
Apr 25, 2018·Nature Medicine·Mikhail BinnewiesMatthew F Krummel
Sep 22, 2018·Lancet·Dirk SchadendorfSelma Ugurel
Nov 24, 2018·Dermatologic Clinics·Elisabeth Hamelin Tracey, Alok Vij
Nov 30, 2018·Journal of Cellular Biochemistry·Jia QiAn-Quan Shang
May 6, 2019·Current Treatment Options in Oncology·Ion G Motofei

❮ Previous
Next ❯

Citations

Sep 17, 2021·Essays in Biochemistry·Thomaz Lüscher-DiasHelder I Nakaya

❮ Previous
Next ❯

Datasets Mentioned

BETA
GSE98394
2500

Methods Mentioned

BETA
nucleotide exchange

Software Mentioned

WGCNA ” R package
R
ggplot2
WGCNA
Image J
Targetscan
WGCNA R
clusterProfiler
CIBERSORT
Cytoscape

Related Concepts

Related Feeds

Cancer -Omics

A variety of different high-throughput technologies can be used to identify the complete catalog of changes that characterize the molecular profile of cohorts of tumor samples. Discover the latest insights gained from cancer 'omics' in this feed.