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

IF 3.1 2区医学 Q2 ONCOLOGY Cancer Medicine Pub Date : 2025-04-22 DOI:10.1002/cam4.70907

Chao Song, Wenbo Liu, Xiaoyu Wang, Xin Liu, Zhiran Yang, Yingying Wang, Qun Zhao, Yong Li, Mingming Zhang, Bibo Tan

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Abstract

Introduction

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.

Methods

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.

Results

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.

Conclusion

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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胃癌嗜酸症相关基因的鉴定：生物信息学和实验验证

远处转移是胃癌预后不良的主要原因，anoikis是指细胞脱离细胞外基质或粘附位置不正确而导致的细胞死亡，在胃癌的远处转移中起重要作用。方法下载TCGA-STAD数据集和anoikis基因集，过滤出差异表达的anoikis基因。对胃癌样本进行共识聚类，对各亚型的表达特征进行加权基因相关网络分析（Weighted Gene Correlation Network Analysis， WGCNA）、富集分析、免疫浸润分析，同时对亚型间差异表达的基因进行筛选。另外，通过COX生存分析，鉴定与胃癌预后相关的anoikis基因，建立nomogram。最后，通过临床样本、细胞培养和anoikis模型的建立，在体内和体外验证差异表达基因CYP1B1。结果鉴定出3种携带anoikis基因的胃癌亚型，每种亚型具有不同的表达特征、生物学途径和免疫细胞浸润情况。活化NK细胞、记忆B细胞和M2巨噬细胞的丰度在三种亚型之间存在显著差异。我们在三个亚型中筛选了4个差异表达基因组和5个基因（CYP1B1、EQTN、NRXN2、TBC1D3E、TCEAL5）。通过生存分析，我们鉴定出33个独立的预后基因，并构建了nomogram，校正曲线一致性较好。最后，我们选择CYP1B1进行实验验证，体内和体外实验表明，CYP1B1在胃癌中高表达，参与胃癌细胞对细胞死亡的抵抗，促进胃癌细胞的侵袭、迁移和肿瘤进展。结论基于anoikis相关差异表达基因的亚型在胃癌中的表达模式存在差异，为未来胃癌的个性化治疗提供理论支持。

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来源期刊

Cancer Medicine ONCOLOGY-

CiteScore

5.50

自引率

2.50%

发文量

907

审稿时长

19 weeks

期刊介绍： Cancer Medicine is a peer-reviewed, open access, interdisciplinary journal providing rapid publication of research from global biomedical researchers across the cancer sciences. The journal will consider submissions from all oncologic specialties, including, but not limited to, the following areas: Clinical Cancer Research Translational research ∙ clinical trials ∙ chemotherapy ∙ radiation therapy ∙ surgical therapy ∙ clinical observations ∙ clinical guidelines ∙ genetic consultation ∙ ethical considerations Cancer Biology: Molecular biology ∙ cellular biology ∙ molecular genetics ∙ genomics ∙ immunology ∙ epigenetics ∙ metabolic studies ∙ proteomics ∙ cytopathology ∙ carcinogenesis ∙ drug discovery and delivery. Cancer Prevention: Behavioral science ∙ psychosocial studies ∙ screening ∙ nutrition ∙ epidemiology and prevention ∙ community outreach. Bioinformatics: Gene expressions profiles ∙ gene regulation networks ∙ genome bioinformatics ∙ pathwayanalysis ∙ prognostic biomarkers. Cancer Medicine publishes original research articles, systematic reviews, meta-analyses, and research methods papers, along with invited editorials and commentaries. Original research papers must report well-conducted research with conclusions supported by the data presented in the paper.