Prognostic model of lung adenocarcinoma from the perspective of cancer-associated fibroblasts using single-cell and bulk RNA-sequencing.
Journal:
Scientific reports
Published Date:
Jul 1, 2025
Abstract
Cancer-associated fibroblasts (CAFs) play important roles in the progression of lung adenocarcinoma (LUAD). We examined CAF subgroups via gene ontology, pseudo-time, and cell communication analyses and explored their prognostic value in LUAD using a digital cytometric machine learning algorithm. Next, we got a prognostic model based on CAF subgroups. We also screened potential therapeutic target genes in LUAD and experimentally validated the proliferation, migration, and invasion phenotypes related to these target genes. We identified myofibroblastic CAFs (MyCAFs) and Immune-related CAFs (ImmCAFs) as the major CAF subgroups in LUAD. Further, our inverse convolution algorithm showed that MyCAFs have prognostic potential in LUAD, and via LASSO-COX model regression, we obtained a MyCAFs-related prognostic model. We found POSTN as a potential therapeutic target in LUAD. These findings serve as a foundation for further studies on CAFs.
