Research Paper Volume 15, Issue 14 pp 6774—6797
Prognostic analysis of lung adenocarcinoma based on cancer-associated fibroblasts genes using scRNA-sequencing
- 1 Clinical School of Thoracic, Tianjin Medical University, Tianjin, China
- 2 Department of Thoracic Surgery, Tianjin Chest Hospital of Tianjin University, Tianjin, China
Received: March 21, 2023 Accepted: June 9, 2023 Published: July 11, 2023
https://doi.org/10.18632/aging.204838How 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.
Abstract
Cancer-associated fibroblasts (CAFs) are an important component of the tumor microenvironment (TME). CAFs can promote tumor occurrence and metastasis by promoting cancer cell proliferation, angiogenesis, extracellular matrix (ECM) remodeling, and drug resistance. Nevertheless, how CAFs are related to Lung adenocarcinoma (LUAD) has not yet been revealed, especially since the CAFs-related prediction model has yet to be established. We combined Single-cell RNA-sequencing (scRNA-seq) and Bulk-RNA data to develop a predictive model of 8 CAFs-associated genes. Our model predicted LUAD prognosis and immunotherapy efficacy. TME, mutation landscape and drug sensitivity differences were also systematically analyzed between the LUAD patients of high- and low-risk. Moreover, the model prognostic performance was validated in four independent validation cohorts in the Gene expression omnibus (GEO) and the IMvigor210 immunotherapy cohort.