Development and validation of polyamines metabolism-associated gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma

Frontiers in Immunology

Immunology

Lingye Zhu¹  Xiaoying Huang¹  Mengyu Chai¹  Ning Wang¹  Jingjing Liu¹  Chang Yu² 

[1] Division of Pulmonary Medicine, the First Affiliated Hospital of Wenzhou Medical University, Key Laboratory of Heart and Lung, Wenzhou, Zhejiang, China;Intervention Department, the First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China;

关键词: lung adenocarcinoma;    polyamines metabolism;    prognosis;    tumor microenvironment;    immunotherapy response;   

DOI  :  10.3389/fimmu.2023.1070953

 received in 2022-10-15, accepted in 2023-05-22,  发布年份 2023

来源: Frontiers

【 摘 要 】

BackgroundPolyamines metabolism is closely related to tumor development and progression, as well as tumor microenvironment (TME). In this study, we focused on exploring whether polyamines metabolism-associated genes would provide prognosis and immunotherapy response prediction in lung adenocarcinoma (LUAD).MethodsThe expression profile data of polyamines metabolism-associated genes were acquired from the Cancer Genome Atlas (TCGA) database. Utilizing the least absolute shrinkage and selection operator (LASSO) algorithm, we created a risk score model according to polyamines metabolism-associated gene signatures. Meanwhile, an independent cohort (GSE72094) was employed to validate this model. Through the univariate and multivariate Cox regression analyses, the independent prognostic factors were identified. Subsequently, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to detect their expression in LUAD cells. By consensus clustering analysis, polyamines metabolism-associated subgroups were determined in LUAD patients, with differential gene expression, prognosis, and immune characteristics analyses explored.ResultsA total of 59 polyamines metabolism genes were collected for this study, of which 14 genes were identified for the construction of risk score model using LASSO method. High- and low- risk groups of LUAD patients in TCGA cohort were distinguished via this model, and high-risk group presented dismal clinical outcomes. The same prognostic prediction of this model had been also validated in GSE72094 cohort. Meanwhile, three independent prognostic factors (PSMC6, SMOX, SMS) were determined for constructing the nomogram, and they were all upregulated in LUAD cells. In addition, two distinct subgroups (C1 and C2) were identified in LUAD patients. Comparing the two subgroups, 291 differentially expressed genes (DEGs) were acquired, mainly enriching in organelle fission, nuclear division, and cell cycle. Comparing to C1 subgroup, the patients in C2 subgroup had favorable clinical outcomes, increased immune cells infiltration, and effective immunotherapy response.ConclusionThis study identified polyamines metabolism-associated gene signatures for predicting the patients’ survival, and they were also linked to immune cells infiltration and immunotherapy response in LUAD patients.

【 授权许可】

Unknown   
Copyright © 2023 Wang, Chai, Zhu, Liu, Yu and Huang