Establishment and validation of a prognostic signature for lung adenocarcinoma based on metabolism‐related genes

Abstract

Background Given that dysregulated metabolism has been recently identified as a hallmark of cancer biology, this study aims to establish and validate a prognostic signature of lung adenocarcinoma (LUAD) based on metabolism-related genes (MRGs). Methods The gene sequencing data of LUAD samples with clinical information and the metabolism-related gene set were obtained from The Cancer Genome Atlas (TCGA) and Molecular Signatures Database (MSigDB), respectively. The differentially expressed MRGs were identified by Wilcoxon rank sum test. Then, univariate cox regression analysis was performed to identify MRGs that related to overall survival (OS). A prognostic signature was developed by multivariate Cox regression analysis. Furthermore, the signature was validated in the GSE31210 dataset. In addition, a nomogram that combined the prognostic signature was created for predicting the 1-, 3- and 5-year OS of LUAD. The accuracy of the nomogram prediction was evaluated using a calibration plot. Finally, cox regression analysis was applied to identify the prognostic value and clinical relationship of the signature in LUAD. Results A total of 116 differentially expressed MRGs were detected in the TCGA dataset. We found that 12 MRGs were most significantly associated with OS by using the univariate regression analysis in LUAD. Then, multivariate Cox regression analyses were applied to construct the prognostic signature, which consisted of six MRGs-aldolase A (ALDOA), catalase (CAT), ectonucleoside triphosphate diphosphohydrolase-2 (ENTPD2), glucosamine-phosphate N-acetyltransferase 1 (GNPNAT1), lactate dehydrogenase A (LDHA), and thymidylate synthetase (TYMS). The prognostic value of this signature was further successfully validated in the GSE31210 dataset. Furthermore, the calibration curve of the prognostic nomogram demonstrated good agreement between the predicted and observed survival rates for each of OS. Further analysis indicated that this signature could be an independent prognostic indicator after adjusting to other clinical factors. The high-risk group patients have higher levels of immune checkpoint molecules and are therefore more sensitive to immunotherapy. Finally, we confirmed six MRGs protein and mRNA expression in six lung cancer cell lines and firstly found that ENTPD2 might played an important role on LUAD cells colon formation and migration. Conclusions We established a prognostic signature based on MRGs for LUAD and validated the performance of the model, which may provide a promising tool for the diagnosis, individualized immuno-/chemotherapeutic strategies and prognosis in patients with LUAD.

MicroRNA-140-3p represses the proliferation, migration, invasion and angiogenesis of lung adenocarcinoma cells via targeting TYMS (thymidylate synthetase)

“…TYMS has been proved to be the downstream target gene of miR-375-3p, which enhances the chemosensitivity of CRC cells to 5-fluorouracil (5-Fu) [ 42 ]. Also, when it comes to LUAD, TYMS has been sorted as one of the differentially expressed metabolism-related genes (MRGs), which provides the evidence on the possible role of TYMS in LUAD [ 43 ]. However, its interaction with miR-140-3p, to be precisely, remained poorly understood.…”

A novel signature derived from metabolism-related genes GPT and SMS to predict prognosis of laryngeal squamous cell carcinoma

“…Least absolute shrinkage and selection operator (LASSO) analysis and multivariate Cox regression analysis were applied to construct a prognostic signature. The risk score formula of the prognostic signature was as follows: Risk score = coef * Exp (geneA) + coef * Exp (geneB) + coefi * Expi (genei) [ 33 , 34 ]. The 90 patients were divided into high- and low-risk groups according to the median risk score (1.244).…”

Metabolism-Related Bioinformatics Analysis Reveals That HPRT1 Facilitates the Progression of Oral Squamous Cell Carcinoma In Vitro

“…Currently, it is widely accepted that the metabolic mechanisms play crucial roles in the initiation and development of cancer. Studies have shown that metabolism-related genes are involved in lung cancer [ 14 ], gastric cancer [ 15 ], and liver cancer [ 16 ]. However, only a few investigations have focused extensively on the association of metabolic genes with OSCC.…”