A novel epithelial-mesenchymal transition-related gene signature for prognosis prediction in patients with lung adenocarcinoma.

ABSTRACT: Traditional pathological diagnoses and clinical methods are insufficient to accurately predict the prognosis of lung adenocarcinoma (LUAD). Epithelial-mesenchymal transition (EMT) process is closely related to tumor cell migration. However, the prognostic value of EMT-related genes in LUAD is still unclear. In this study, we collected bulk RNA-sequencing (RNA-seq) and microarray data of LUAD patients from public databases and identified different expressed EMT-related genes in tumor and normal tissues. Then, we used the least absolute shrinkage and selection operator Cox regression model to develop a multigene signature in the cancer genome atlas (TCGA) cohort and validated the model in the OncoSG (Singapore Oncology Data Portal) cohort as well as other datasets. Finally, we constructed a

SUBMITTER: Feng S 

PROVIDER: S-EPMC8753132 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature