Open AccessSurvival‑related risk score of lung adenocarcinoma identified by weight gene co‑expression network analysis
Author(s) -
He Wang,
Di Lu,
Xiguang Liu,
Jianjun Jiang,
Siyang Feng,
Xiaoying Dong,
Xiaoshun Shi,
Hua Wu,
Gang Xiong,
Haofei Wang,
Kaican Cai
Publication year - 2019
Publication title -
oncology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 54
eISSN - 1792-1082
pISSN - 1792-1074
DOI - 10.3892/ol.2019.10795
Subject(s) - lasso (programming language) , adenocarcinoma , lung cancer , proportional hazards model , oncology , oncogene , survival analysis , gene , molecular medicine , cancer , medicine , biology , bioinformatics , cell cycle , genetics , computer science , world wide web
The present study aimed to identify the novel biomarkers and underlying molecular mechanisms of lung adenocarcinoma (LAC) to aid in its diagnosis, prognosis, prediction, disease monitoring and emerging therapies. Data from a total of 498 LAC samples were collected from The Cancer Genome Atlas and divided into two sets by stratified randomization based on pathological Tumor-Node-Metastasis stage. The training set was comprised of 348 samples and the validation set was comprised of 150 samples. A total of 123 samples from the training set for patients who completed follow-up were analyzed by weighted gene co-expression network analysis. A module was identified that contained 113 protein-coding genes that were positively associated with overall survival (OS). A least absolute shrinkage and selection operator (LASSO) Cox regression model was constructed and four survival-associated genes (OPN3, GALNT2, FAM83A and KYNU) were retained. Risk score, calculated by the linear combination of each gene expression multiplied by the LASSO coefficient, could successfully discriminate between patients with LAC exhibiting low and high OS time in both sets. The results from the present study indicate that this risk score may contribute to potential diagnostic and therapeutic strategies for LAC management.