Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Identification and validation of prognostically relevant gene signature in melanoma

Gao, Yali, Li, Yaling, Niu, Xueli, Wu, Yutong, Guan, Xiuhao, Hong, Yuxiao, Chen, Hongduo and Song, Bing 2020. Identification and validation of prognostically relevant gene signature in melanoma. BioMed Research International , 5323614. 10.1155/2020/5323614

[img] PDF - Published Version
Available under License Creative Commons Attribution.

Download (3MB)

Abstract

Background. Currently, effective genetic markers are limited to predict the clinical outcome of melanoma. High-throughput multiomics sequencing data have provided a valuable approach for the identification of genes associated with cancer prognosis. Method. The multidimensional data of melanoma patients, including clinical, genomic, and transcriptomic data, were obtained from The Cancer Genome Atlas (TCGA). These samples were then randomly divided into two groups, one for training dataset and the other for validation dataset. In order to select reliable biomarkers, we screened prognosis-related genes, copy number variation genes, and SNP variation genes and integrated these genes to further select features using random forests in the training dataset. We screened for robust biomarkers and established a gene-related prognostic model. Finally, we verified the selected biomarkers in the test sets (GSE19234 and GSE65904) and on clinical samples extracted from melanoma patients using qRT-PCR and immunohistochemistry analysis. Results. We obtained 1569 prognostic-related genes and 1101 copy-amplification, 1093 copy-deletions, and 92 significant mutations in genomic variants. These genomic variant genes were closely related to the development of tumors and genes that integrate genomic variation. A total of 141 candidate genes were obtained from prognosis-related genes. Six characteristic genes (IQCE, RFX6, GPAA1, BAHCC1, CLEC2B, and AGAP2) were selected by random forest feature selection, many of which have been reported to be associated with tumor progression. Cox regression analysis was used to establish a 6-gene signature. Experimental verification with qRT-PCR and immunohistochemical staining proved that these selected genes were indeed expressed at a significantly higher level compared with the normal tissues. This signature comprised an independent prognostic factor for melanoma patients. Conclusions. We constructed a 6-gene signature (IQCE, RFX6, GPAA1, BAHCC1, CLEC2B, and AGAP2) as a novel prognostic marker for predicting the survival of melanoma patients.

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Dentistry
Publisher: Hindawi Publishing Corporation
ISSN: 2314-6133
Date of First Compliant Deposit: 8 June 2020
Date of Acceptance: 15 April 2020
Last Modified: 08 Jun 2020 15:30
URI: http://orca.cf.ac.uk/id/eprint/132240

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics