Single-cell RNA Sequencing Analysis Reveals Cancer-associated Fibroblast Signature for Prediction of Clinical Outcomes and Immunotherapy in Gastric Cancer

Abstract

Gastric cancer (GC) is a significant worldwide health concern and is a leading cause of cancer-related mortality. Immunotherapy has arisen as a promising strategy to stimulate the patient’s immune system in combating cancer cells. Nevertheless, the effectiveness of immunotherapy in individuals with gastric cancer (GC) is not yet optimal. Thus, it is crucial to discover biomarkers capable appof predicting the advantages of immunotherapy for tailored treatment. The tumor microenvironment (TME) and its constituents, including cancer-associated fibroblasts (CAFs), exert a substantial influence on immune responses and treatment outcomes. In this investigation, we utilized single-cell RNA sequencing to profile CAFs in GC and established a scoring method, referred to as the CAF score (CAFS), for the prediction of patient prognosis and response to immunotherapy. Through our analysis, we successfully identified distinct subgroups within CAFs based on CAF score (CAFS), namely CAFS-high and CAFS-low subgroups. Notably, we noted that individuals within the CAFS-high subgroup experienced a lessF favorable prognosis and displayed diminished responsiveness to immunotherapy in contrast to the CAFS low subgroup. Furthermore, we analyzed the mutation and immune characteristics of these subgroups, identifying differentially mutated genes and immune cell compositions. We established that CAFS could forecast treatment advantages in patients with gastric cancer, both for chemotherapy and immunotherapy. Its efficacy was additionally confirmed in contrast to other biomarkers, including Tumor Immune Dysfunction and Exclusion (TIDE) and Immunophenotypic Score (IPS). These findings emphasize the clinical relevance and potential utility of CAFS in guiding personalized treatment strategies for gastric cancer.