Association of proteomics with lymph node metastasis in early gastric cancer patients

IF 4.2 2区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY Biochimica et biophysica acta. Molecular basis of disease Pub Date : 2025-03-05 DOI:10.1016/j.bbadis.2025.167773

Botao Yan , Xiaoyu Dong , Zaizeng Wu , Dexin Chen , Wei Jiang , Jiaxin Cheng , Gang Chen , Jun Yan

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Abstract

Surgical decision making for early gastric cancer (EGC) is heavily influenced by its metastasis into the lymph nodes. Currently, the clinicopathological features of EGC cannot be used to accurately distinguish between EGC patients with and without lymph node metastasis. Our retrospective case-matching study included a total of 132 samples from 66 pairs of EGC patients with or without lymph node metastasis and conducted proteomic assays. By comparing the lymph node metastasis group and the nonmetastasis group, we found that two proteins, GABARAPL2 and NAV1, were significantly associated with lymph node metastasis in EGC patients. Our prediction model using protein biomarkers had good prediction accuracy, with an area under the curve (AUC) of 0.87, a sensitivity of 0.78, a specificity of 0.89, and an accuracy of 0.84, which can help distinguish between EGC patients with and without lymph node metastasis and guide the decision-making process for performing tailored surgery.

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早期胃癌（EGC）淋巴结转移对手术决策有很大影响。目前，EGC的临床病理特征还不能用于准确区分有淋巴结转移和无淋巴结转移的EGC患者。我们的回顾性病例配对研究共纳入了66对有或无淋巴结转移的EGC患者的132份样本，并进行了蛋白质组学检测。通过比较淋巴结转移组和非转移组，我们发现GABARAPL2和NAV1这两种蛋白质与EGC患者的淋巴结转移有显著相关性。我们利用蛋白质生物标志物建立的预测模型具有良好的预测准确性，其曲线下面积（AUC）为0.87，灵敏度为0.78，特异度为0.89，准确度为0.84，有助于区分有淋巴结转移和无淋巴结转移的EGC患者，并为实施有针对性的手术提供决策指导。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Biochimica et biophysica acta. Molecular basis of disease 生物-生化与分子生物学

CiteScore

12.30

自引率

0.00%

发文量

218

审稿时长

32 days

期刊介绍： BBA Molecular Basis of Disease addresses the biochemistry and molecular genetics of disease processes and models of human disease. This journal covers aspects of aging, cancer, metabolic-, neurological-, and immunological-based disease. Manuscripts focused on using animal models to elucidate biochemical and mechanistic insight in each of these conditions, are particularly encouraged. Manuscripts should emphasize the underlying mechanisms of disease pathways and provide novel contributions to the understanding and/or treatment of these disorders. Highly descriptive and method development submissions may be declined without full review. The submission of uninvited reviews to BBA - Molecular Basis of Disease is strongly discouraged, and any such uninvited review should be accompanied by a coverletter outlining the compelling reasons why the review should be considered.