基于血清蛋白质组学的TAGLN2、CTSD等5种早期胃癌生物标志物的发现及初步验证

杜可为, 张尚弟, 胡文飞, 高山, 甘建新, 尤崇革

  1. 1.兰州大学第二医院检验医学中心,甘肃 兰州 730030
    2.兰州大学第二医院普外科,甘肃 兰州 730030
  • 收稿日期:2025-03-03 修回日期:2025-05-30 出版日期:2025-06-30 发布日期:2025-07-14
  • 通信作者: 尤崇革(ORCID: 0000-0002-3671-596X),教授,主任检验技师,博士研究生导师。
  • 作者简介:杜可为(ORCID: 0009-0000-7000-8006),兰州大学第二临床医学院在读硕士研究生。

摘要/Abstract

摘要:

背景与目的: 胃癌作为常见恶性肿瘤之一,早期诊断和治疗对改善患者预后至关重要。本研究基于早期胃癌患者的血清定量蛋白质组学研究,旨在发现潜在诊断早期胃癌的生物标志物。方法: 收集2023年6月—12月在兰州大学第二医院就诊的原发性胃癌患者血清的临床资料与体检的健康对照人群的血清资料。所有资料根据本研究的纳入和排除标准进行筛选。使用数据依赖性的采集模式(data-dependent acquisition,DDA)建立蛋白质谱图库后,数据非依赖性的扫描模式(data-independent acquisition,DIA)对各样本进行单独分析。通过STRING数据库分析蛋白组学中胃癌血清中表达上调的蛋白质相互作用,采用KEGG与基因本体GO数据库分析蛋白质对应基因的信号转导通路与功能注释。通过GEPIA2分析基因在胃癌与非胃癌组织中的表达水平,Kaplan-Meier Plotter分析各基因对应胃癌患者的总生存期。利用定量反转录聚合酶链反应(quantitative reverse transcription polymerase chain reaction,qRT-PCR)法验证差异基因在临床胃癌及癌旁组织中的表达。本研究获得兰州大学第二医院研究伦理委员会的批准(伦理批号:2023A-459)并豁免知情同意。结果: 最终入组并获得30例原发性胃癌患者血清与29例健康对照人群血清资料,另获得8例癌旁组织资料。采用血清定量蛋白质组学共鉴定到666种交集蛋白,其中在胃癌组中有16种蛋白质对应基因表达上调,22种表达下调(P<0.05,|FC|≥1.5)。STRING数据库分析显示,10种上调蛋白质处于互作网络中,KEGG与GO分析表明基因与癌症发生、发展的生物过程密切相关。GEPIA 2与Kaplan-Meier Plotter分析显示B2MTAGLN2CTSDHSP90AB1SH3BGRL3CFL1共计6个基因在胃癌组中高表达(P<0.05)且预后不良。qRT-PCR结果表明,TAGLN2CTSDSH3BGRL3CFL1HSP90AB1在胃癌组织中高表达(P <0.05)。结论: TAGLN2CTSDSH3BGRL3CFL1HSP90AB1具有作为诊断早期胃癌的血清生物标志物的潜力,有利于胃癌的早诊早治。

关键词: 蛋白质组学, 胃癌, 生物标志物, 早期诊断

Abstract:

Background and purpose: Gastric cancer, as one of the most common malignant tumors, requires early diagnosis and treatment to improve patient prognosis. This study, based on serum quantitative proteomics research of early-stage gastric cancer patients and non-gastric cancer patients, aims to identify potential diagnostic biomarkers for early gastric cancer. Methods: Serum samples from primary gastric cancer patients and healthy control individuals were collected from Lanzhou University Second Hospital between June and December 2023, following inclusion and exclusion criteria. A protein spectral library was established using Data-Dependent Acquisition (DDA) mode, and each sample was analyzed using Data-Independent Acquisition (DIA) mode. The STRING database was used to analyze protein-protein interactions of upregulated proteins in gastric cancer serum. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were used to analyze the pathways and functional annotations of the corresponding genes. Gene expression levels in gastric cancer and non-gastric cancer tissues were analyzed using GEPIA 2, and overall survival of each gene in gastric cancer was analyzed using Kaplan-Meier Plotter. Differential gene expression in clinical gastric cancer and adjacent tissues was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) This study was approved by the Ethics Committee of Lanzhou University Second Hospital (Ethical No.: 2023A-459) and was exempt from the informed consent. Results: Finally, serum samples from 30 primary gastric cancer patients, 29 healthy control individuals, along with the para-cancerous tissues from 8 patients were collected. A total of 666 intersecting proteins were identified through serum quantitative proteomics. Among them, 16 proteins showed upregulated expression and 22 proteins showed downregulated expression in the gastric cancer group (P<0.05, |FC|≥1.5). STRING database analysis showed that 10 upregulated proteins were involved in interaction networks. KEGG and GO analysis indicated that these genes were closely related to the biological processes of cancer occurrence and development. GEPIA 2 and Kaplan-Meier Plotter analysis showed that 6 genes, B2M, TAGLN2, CTSD, HSP90AB1, SH3BGRL3, and CFL1, which were highly expressed in the gastric cancer group (P<0.05) and associated with poor prognosis. Clinical verification by qRT-PCR confirmed that TAGLN2, CTSD, SH3BGRL3, CFL1 and HSP90AB1 were highly expressed in gastric cancer tissues (P<0.05). Conclusion: TAGLN2, CTSD, SH3BGRL3, CFL1, and HSP90AB1 have the potential to serve as clinical early gastric cancer diagnostic serum biomarkers, which may facilitate early diagnosis and treatment of gastric cancer.

Key words: Proteomics, Gastric cancer, Biomarkers, Early diagnosis

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