Identification of Anoikis‐Related Genes in Gastric Cancer: Bioinformatics and Experimental Validation

TL;DR

This study identifies genes related to anoikis in gastric cancer, linking them to metastasis and prognosis, and validates one gene's role in cancer progression.

Contribution

Novel identification of anoikis-related genes and subtypes in gastric cancer with experimental validation of CYP1B1's role in tumor progression.

Findings

Three gastric cancer subtypes with distinct anoikis gene expression, immune infiltration, and biological pathways were identified.

CYP1B1 was validated as highly expressed in gastric cancer and promotes cell survival, invasion, and tumor progression.

A nomogram based on 33 prognostic genes showed good consistency for predicting patient outcomes.

Abstract

Distant metastasis is the main reason for the poor prognosis of gastric cancer, and anoikis refers to the cell death caused when cells detach from the extracellular matrix or adhere in incorrect locations, playing an important role in the distant metastasis of gastric cancer.

Download the TCGA‐STAD dataset and the anoikis gene set, and filter out the differentially expressed anoikis genes. Perform consensus clustering of gastric cancer samples, and conduct Weighted Gene Correlation Network Analysis (WGCNA), enrichment analysis, and immune infiltration analysis for the expression characteristics of each subtype, while also filtering the genes with differential expression between subtypes. Additionally, through COX survival analysis, identify anoikis genes related to gastric cancer prognosis and establish a nomogram. Finally, validate the differentially expressed gene CYP1B1 in vivo and in vitro through clinical samples, cell culture, and the establishment of an anoikis model.

Three subtypes of gastric cancer with anoikis genes were identified, each exhibiting different expression characteristics, biological pathways, and immune cell infiltration. The abundance of activated NK cells, memory B cells, and M2 macrophages showed significant differences among the three subtypes. We screened four differentially expressed gene sets and five genes (CYP1B1, EQTN, NRXN2, TBC1D3E, TCEAL5) among the three subtypes. Through survival analysis, we identified 33 independent prognostic genes and constructed a nomogram, with calibration curves indicating good consistency. Finally, we selected CYP1B1 for experimental validation, and in vivo and in vitro experiments demonstrated that CYP1B1 is highly expressed in gastric cancer, participates in the resistance to cell death in gastric cancer cells, and promotes the invasion, migration, and tumor progression of gastric cancer cells.

The expression patterns of subtypes based on differentially expressed genes related to anoikis in gastric cancer vary, providing theoretical support for the future of personalized treatment for gastric cancer.

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