Research Paper Volume 15, Issue 11 pp 4986—5006

Development of cancer-associated fibroblast-related gene signature for predicting the survival and immunotherapy response in lung adenocarcinoma

Yong Zhang1, *,#, , Fuyi Cheng1, *,#, , Jinhu Ma1, , Gang Shi1, , Hongxin Deng1, ,

  • 1 Department of Biotherapy, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu 610041, Sichuan, China
* Equal contribution
# Share first authorship

Received: March 1, 2023       Accepted: May 16, 2023       Published: June 6, 2023
How to Cite

Copyright: © 2023 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


The present study aims to construct a predictive model for prognosis and immunotherapy response in lung adenocarcinoma (LUAD). Transcriptome data were extracted from the Cancer Genome Atlas (TCGA), GSE41271, and IMvigor210. The weighted gene correlation network analysis was utilized to identify the hub modules related to immune/stromal cells. Then, univariate, LASSO, and multivariate Cox regression analyses were employed to develop a predictive signature based on genes of the hub module. Moreover, the association between the predictive signature and immunotherapy response was also investigated. As a result, seven genes (FGF10, SERINE2, LSAMP, STXBP5, PDE5A, GLI2, FRMD6) were screened to develop the cancer associated fibroblasts (CAFs)-related risk signature (CAFRS). LUAD patients with high-risk score underwent shortened Overall survival (OS). A strong correlation was found between CAFRS and immune infiltrations/functions. The gene set variation analysis showed that G2/M checkpoint, epithelial-mesenchymal transition, hypoxia, glycolysis, and PI3K-Akt-mTOR pathways were greatly enriched in the high-risk subgroup. Moreover, patients with higher risk score were less likely to respond to immunotherapy. A nomogram based on CAFRS and Stage presented a stronger predictive performance for OS than the single indicator. In conclusion, the CAFRS exhibited a potent predictive value for OS and immunotherapy response in LUAD.


LUAD: Lung adenocarcinoma; TCGA: The Cancer Genome Atlas; WGCNA: Weighted gene correlation network analysis; CAFs: Cancer-associated fibroblasts; CAFRS: CAFs-related risk signature; GSVA: Gene set variation analysis; EMT: Epithelial-mesenchymal transition; TMB: Tumor mutation burden; MSI-H: microsatellite instability-High; dMMR: deficient mismatch repair; TME: Tumor microenvironment; ssGSEA: Single sample gene set enrichment analysis; IPS: Immunophenoscore; CR: Complete response; PR: Partial response; SD: Stable disease; PD: Progressive disease; ROC: Receiver operating characteristic; OS: Overall survival; AUC: Area under the curve; qRT-PCR: Quantitative Real-Time PCR.