Unraveling Prognostic Signatures in Lung Adenocarcinoma: Insights from Extracellular Matrix-Related Genes

: Lung cancer is the fourth most common cancer in Iran and accounts for approximately ۱۰,۰۰۰ deaths, making it the second leading cause of mortality among cancer patients. The extracellular matrix (ECM), comprising a dynamic network of macromolecules, profoundly influences cancer development and therapeutic responses within tumor microenvironments. In the context of lung adenocarcinoma (LUAD), unraveling the molecular intricacies of ECM-related genes assumes critical importance for effective prognostic classification. Our study aimed to elucidate how ECM-related gene profiles impact overall survival in LUAD patients. Methods: ECM-related gene sets were curated from the Molecular Signatures Database (MSigDB). These gene sets encompassed critical players involved in cell-matrix interactions, remodeling, and signaling pathways. Cox regression and Least Absolute Shrinkage and Selection Operator (LASSO) analyses were applied to the ECM-related gene set. Prognostic genes were identified based on their association with overall survival. Also, LUAD patients were categorized into high-risk and low-risk groups based on their risk scores’ median value. Kaplan-Meier survival curves were generated to visualize patient outcomes based on risk groups defined by the model. The discriminatory capacity of the model was assessed through Receiver Operating Characteristic (ROC) curves. Results: The prognostic model of LUAD was generated based on ۲۳ ECM-related genes identified through Cox and LASSO regression. Notable genes within this set include CTSG, KAZALD۱, OGFOD۲, MEP۱A, F۱۳A۱, LOXL۲, CTSL, ADAMTS۷, SERPINA۱۰, PCSK۶, ADAM۱۵, HABP۲, SERPINH۱, ADAM۳۳, ITIH۲, CD۱۰۹, ADAMTS۱۳, ADAMTS۱۵, SERPINB۷, HTRA۴, F۲, ADAMTSL۵, and ASTL. Our survival analysis demonstrated significantly improved outcomes in the low-risk patient group, while the high-risk group exhibited a poorer prognosis. Additionally, ROC curves validated the model’s accuracy in predicting overall survival at one, two, and three years. Conclusion: Our study investigated the impact of ECM-related genes on LUAD outcomes through a prognostic model that accurately and stably predicted survival. In addition, results shed light on the role of ECM-related genes in LUAD patients' survival. Overall, understanding ECM-related gene dynamics enhances prognostic precision in LUAD.

کلیدواژه ها:

Lung Adenocarcinoma ، Extracellular Matrix ، Prognosis ، Overall Survival