Development and validation of focal adhesion-related genes signature in gastric cancer - Zhao, Guanghui; Luo, Tianqi; Liu, Zexian; Li, Jianjun (Frontiers in Genetics, 2023)
Background:This study aims to build a focal adhesion-related genes-based prognostic signature (FAS) to accurately predict gastric cancer (GC) prognosis and identify key prognostic genes related to GC. Results: Gene expression and clinical data of GC patients were sourced from Gene Expression Omnibus and The Cancer Genome Atlas . Subsequently, the GEO dataset was randomly distributed into training and test cohorts. The TCGA dataset was used to validate the external cohort. Lasso Cox regression was used to detect OS-related genes in the GEO cohort. A risk score model was established according to the screened genes. A nomogram, based on the clinical characteristics and risk score, was generated to predict the prognosis of GC patients. Using ime-dependent receiver operating characteristic (ROC) and calibration performances, we evaluated the models' validity. The patients were grouped into a high- or low-risk group depending on the risk score. Low-risk patients exhibited higher OS than high-risk patients (entire cohort: p<0.001; training cohort: p<0.001, test cohort: p<0.001). Furthermore, we found a correlation between high-risk GC and extracellular matrix (ECM) receptor interaction , high infiltration of macrophages, CD44, and HLA-DOA. Conclusions: The generated model based on the genetic characteristics of the focal adhesion prognostic gene can aid in the prognosis of GC patients in the future.