Molecular Characterization and Prognosis of Lactate-Related Genes in Lung Adenocarcinoma

Author:

Guo Zixin12ORCID,Hu Liwen13,Wang Qingwen13,Wang Yujin13ORCID,Liu Xiao-Ping4,Chen Chen25,Li Sheng25ORCID,Hu Weidong13ORCID

Affiliation:

1. Department of Thoracic Surgery, Zhongnan Hospital of Wuhan University, Wuhan 430071, China

2. Department of Biological Repositories, Zhongnan Hospital of Wuhan University, Wuhan 430071, China

3. Hubei Key Laboratory of Tumor Biological Behaviors & Hubei Cancer Clinical Study Center, Wuhan 430071, China

4. Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China

5. Human Genetics Resource Preservation Center of Hubei Province, Wuhan 430071, China

Abstract

Objective: To explore the lactate-related genes (LRGs) in lung adenocarcinoma (LUAD) by various methods, construct a prognostic model, and explore the relationship between lactate subtypes and the immune tumor microenvironment (TME). Methods: 24 LRGs were collected. The mutation landscape and the prognosis value of LRGs were explored by using The Cancer Genome Atlas (TCGA) data. Consensus clustering analysis was used for different lactate subtype identification. Based on the lactate subtypes, we explore the landscape of TME cell infiltration. A risk-score was calculated by using the LASSO-Cox analysis. A quantitative real-time PCR assay was utilized to validate the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients. Results: Comparing the normal samples, 18 LRGs were differentially expressed in tumor samples, which revealed that the differential expression of LRGs may be related to Copy Number Variation (CNV) alterations. The two distinct lactate subtypes were defined. Compared to patients in the LRGcluster A group, LUAD patients in the LRGcluster B group achieved better survival. The prognostic model was constructed based on differentially expressed genes (DEGs) via the LASSO-Cox analysis, which showed the accuracy of predicting the prognosis of LUAD patients using the ROC curve. A high-risk score was related to a high immune score, stromal score, and tumor mutation burden (TMB). Patients had better OS with low risk compared with those with high risk. The sensitivities of different risk groups to chemotherapeutic drugs were explored. Finally, the expression of characteristic genes in clinical cancer tissues and paracarinoma tissues from LUAD patients was verified via qRT-PCR. Conclusions: The lactate subtypes were independent prognostic biomarkers in LUAD. Additionally, the difference in the lactate subtypes was an indispensable feature for the individual TME. The comprehensive evaluation of the lactate subtypes in the single tumor would help us to understand the infiltration characteristics of TME and guide immunotherapy strategies.

Funder

Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund

Publisher

MDPI AG

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