Subtype classification based on t cell proliferation-related regulator genes and risk model for predicting outcomes
Qin Yang1, Weiyuan Zhu1, Han Gong2
1School of Basic Medicine, Shaoyang University, the First Affiliated Hospital of Shaoyang University, Shaoyang, Hunan, China.
Background:
Lung adenocarcinoma (LUAD), the major lung cancer histotype, represents 40% lung cancers. Currently, outcomes are remarkably different in LUAD patients with similar AJCC/UICC-TNM features. T cell proliferation-related regulator genes (TPRGs) relate to the proliferation, activity and function of T cells and tumor progression. The values of TPRGs in classifying LUAD patients and predicting outcomes remain unknown.
Methods:
Gene expression profile and corresponding clinical data were downloaded from TCGA and the GEO databases. We systematically analyzed the expression profile characteristics of 35 TPRGs in LUAD patients and investigated the differences in overall survival (OS), biology pathway, immunity and somatic mutation between different TPRGs-related subtypes. Subsequently, we constructed a TPRGs-related risk model in TCGA cohort to quantify risk scores using LASSO cox regression analysis and then validated this risk model in two GEO cohorts. LUAD patients were divided into high- and low-risk subtypes according to the median risk score. We systematically compared the biology pathway, immunity, somatic mutation and drug susceptibility between the two risk subtypes. Finally, we validate biological functions of two TPRGs-encoded proteins (DCLRE1B and HOMER1) in LUAD cells A549.
Results:
We identified different TPRGs-related subtypes (including cluster 1/cluster A and its counterpart cluster 2/cluster B). Compared to the cluster 1/cluster A subtype, cluster 2/cluster B subtype tended to have a prominent survival advantage with an immunosuppressive microenvironment and a higher somatic mutation frequency. Then, we constructed a TPRGs-related 6-gene risk model. The high-risk subtype characterized by higher somatic mutation frequency and lower immunotherapy response had a worse prognosis. This risk model was an independent prognostic factor and showed to be reliable and accurate for LUAD classification. Furthermore, subtypes with different risk scores were significantly associated with drug sensitivity. DCLRE1B and HOMER1 suppressed cell proliferation, migration and invasion in LUAD cells A549, which was in line with their prognostic values.
Conclusion:
We construed a novel stratification model of LUAD based on TPRGs, which can accurately and reliably predict the prognosis and might be used as a predictive tool for LUAD patients.
