Identification of metabolism-related genes for predicting peritoneal metastasis in patients with gastric cancer

Abstract

Objective The reprogramming of metabolism is an important factor in the metastatic process of cancer. In our study, we intended to investigate the predictive value of metabolism-related genes (MRGs) in recurrent gastric cancer (GC) patients with peritoneal metastasis. Methods The sequencing data of mRNA of GC patients were obtained from Asian Cancer Research Group (ACRG) and the GEO databases (GSE53276). The differentially expressed MRGs (DE-MRGs) between a cell line without peritoneal metastasis (HSC60) and one with peritoneal metastasis (60As6) were analyzed with the Limma package. According to the LASSO regression, eight MRGs were identified as crucially related to peritoneal seeding recurrence in patients. Then, disease free survival related genes were screened using Cox regression, and a promising prognostic model was constructed based on 8 MRGs. We trained and verified it in two independent cohort. Results We confirmed 713 DE-MRGs and the enriched pathways. Pathway analysis found that the MRG-related pathways were related to tumor metabolism development. With the help of Kaplan–Meier analysis, we found that the group with higher risk scores had worse rates of peritoneal seeding recurrence than the group with lower scores in the cohorts. Conclusions This study developed an eight-gene signature correlated with metabolism that could predict peritoneal seeding recurrence for GC patients. This signature could be a promising prognostic model, providing better strategy in treatment.

Metabolic and immune‐related gene signatures: Predictive stratification and prognostic implications in gastric cancer

“…12 The ACRG gene expression profiling data were obtained from the NCBI Gene Expression Omnibus (GSE62254) and the gene somatic mutation and clinical data were downloaded from the literature. 11 The TCGA-STAD dataset was downloaded from the GDC data portal (https://portal.gdc.cancer.gov/). MIG gene lists were obtained through the Kyoto Encyclopedia of Genes and Genomes (KEGG) PATHWAY Database (http://software.…”

“…9 Several studies have demonstrated the potential of immune and metabolic gene-based signatures for predicting GC prognosis and guiding treatment decisions. 10,11 However, challenges remain in the development and validation of these signatures, such as the need for large, high-quality datasets and the identification of robust biomarkers that can be translated into the clinic. In this paper, we will review recent advances in the construction of immune and metabolic gene-based prognosis signatures in GC and discuss their potential clinical applications.…”

“…Several studies have demonstrated the potential of immune and metabolic gene‐based signatures for predicting GC prognosis and guiding treatment decisions 10,11 . However, challenges remain in the development and validation of these signatures, such as the need for large, high‐quality datasets and the identification of robust biomarkers that can be translated into the clinic.…”

Gastric cancer peritoneal metastasis related signature predicts prognosis and sensitivity to immunotherapy in gastric cancer

“…GCPM has been linked to various clinicopathological characteristics, genetic mutations and molecular signatures. [8][9][10] However, the usefulness of these histopathology and molecular classifications in clinical practice remains limited.…”

“…It is recommended to adopt a combination of systemic therapy and peritoneal‐directed treatment strategies, such as intraperitoneal chemotherapy, which have demonstrated an encouraging trend towards improved disease outcomes. GCPM has been linked to various clinicopathological characteristics, genetic mutations and molecular signatures 8–10 . However, the usefulness of these histopathology and molecular classifications in clinical practice remains limited.…”