Identification of an autophagy- and macropinocytosis-related prognostic signature for the prediction of prognosis and therapeutic response in gastric cancer.

Abstract

Background: Traditional liquid biopsy markers show a low rate of positivity and accurate in gastric cancer. With the rapid advancement of sequencing technology, scientists have identified promising research avenues in this field. Autophagy and macropinocytosis utilize diverse pathways and mechanisms to supply resources and fuel for tumor growth. Nonetheless, their potential interplay introduces an untapped avenue for the discovery of novel tumor biomarkers.

Objective: To develop an innovative prognostic signature based on autophagy- and micropinocytosis-related genes, with the aim to predict the outcome and therapeutic response of gastric cancer patients. Additionally, to validate the prognostic impact of this signature, and elucidate the role of representative molecules in gastric cancer.

Methods: To construct and validate a prognostic signature for gastric cancer, bioinformatics methods such as COX regression, LASSO regression, survival analysis, ROC curve, and nomogram were utilized based on the sequencing and clinical data of gastric cancer patients retrieved from the TCGA and GEO databases. GSEA functional enrichment analyses were employed to predict the biological functions. Meanwhile, qRT-PCR and Western blot experiments were utilized to quantify the mRNA and protein expression levels. Furthermore, the EdU assay and colony formation assay were utilized to examine the cell proliferation ability while the Transwell assays were conducted to assess the migration and invasion abilities of gastric cancer cells.

Results: Through consistency clustering and univariate COX analyses, potential prognostic genes involved in both autophagy and macropinocytosis were identified. Based on these genes, a 9-gene signature was constructed, which demonstrated high accuracy in predicting gastric cancer patients' survival period, immunotherapeutic response, and chemotherapy drug tolerance. Furthermore, qRT-PCR analyses of gastric cancer tissue samples showed that the representative genes of this signature were aberrantly overexpressed in gastric cancer, with MATN3, as the most notable molecule, exhibiting significant carcinogenic effects on cancer cells by actively regulating their proliferation, migration, and invasion abilities.

Conclusion: Our newly created prognostic signature possesses significant potential as a biomarker for gastric cancer, while MATN3 is identified as an oncogenic factor in gastric cancer. This brings to light new perspectives, which can contribute to enhancing the diagnosis and treatment of gastric cancer.