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基于无标记全蛋白质组分析的胃癌诊断价值的潜在生物标志物筛选。

Screening of Potential Biomarkers for Gastric Cancer with Diagnostic Value Using Label-free Global Proteome Analysis.

机构信息

Department of Surgical Oncology and General Surgery, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Affiliated Hospital of China Medical University, Shenyang 110001, China.

Department of Surgical Oncology and General Surgery, Key Laboratory of Precision Diagnosis and Treatment of Gastrointestinal Tumors, Ministry of Education, The First Affiliated Hospital of China Medical University, Shenyang 110001, China.

出版信息

Genomics Proteomics Bioinformatics. 2020 Dec;18(6):679-695. doi: 10.1016/j.gpb.2020.06.012. Epub 2021 Feb 17.

DOI:10.1016/j.gpb.2020.06.012
PMID:33607292
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8377014/
Abstract

Gastric cancer (GC) is known as a top malignant type of tumors worldwide. Despite the recent decrease in mortality rates, the prognosis remains poor. Therefore, it is necessary to find novel biomarkers with early diagnostic value for GC. In this study, we present a large-scale proteomic analysis of 30 GC tissues and 30 matched healthy tissues using label-free global proteome profiling. Our results identified 537 differentially expressed proteins, including 280 upregulated and 257 downregulated proteins. The ingenuity pathway analysis (IPA) results indicated that the sirtuin signaling pathway was the most activated pathway in GC tissues whereas oxidative phosphorylation was the most inhibited. Moreover, the most activated molecular function was cellular movement, including tissue invasion by tumor cell lines. Based on IPA results, 15 hub proteins were screened. Using the receiver operating characteristic curve, most of hub proteins showed a high diagnostic power in distinguishing between tumors and healthy controls. A four-protein (ATP5B-ATP5O-NDUFB4-NDUFB8) diagnostic signature was built using a random forest model. The area under the curve (AUC) values of this model were 0.996 and 0.886 for the training and testing sets, respectively, suggesting that the four-protein signature has a high diagnostic power. This signature was further tested with independent datasets using plasma enzyme-linked immune sorbent assays, resulting in an AUC value of 0.778 for distinguishing GC tissues from healthy controls, and using immunohistochemical tissue microarray analysis, resulting in an AUC value of 0.805. In conclusion, this study identifies potential biomarkers and improves our understanding of the pathogenesis, providing novel therapeutic targets for GC.

摘要

胃癌(GC)是世界范围内恶性程度较高的肿瘤之一。尽管近年来死亡率有所下降,但预后仍然较差。因此,有必要寻找具有早期诊断价值的新型 GC 生物标志物。在本研究中,我们使用无标记的全局蛋白质组谱分析方法对 30 例 GC 组织和 30 例匹配的健康组织进行了大规模的蛋白质组分析。我们的研究结果确定了 537 个差异表达蛋白,包括 280 个上调蛋白和 257 个下调蛋白。IPA 结果表明,sirtuin 信号通路是 GC 组织中最活跃的通路,而氧化磷酸化是最受抑制的通路。此外,最活跃的分子功能是细胞运动,包括肿瘤细胞系的组织侵袭。基于 IPA 结果,筛选出 15 个枢纽蛋白。使用接收器操作特征曲线,大多数枢纽蛋白在区分肿瘤和健康对照方面具有较高的诊断能力。使用随机森林模型构建了一个由 4 种蛋白(ATP5B-ATP5O-NDUFB4-NDUFB8)组成的诊断特征。该模型在训练集和测试集的 AUC 值分别为 0.996 和 0.886,表明该四蛋白特征具有较高的诊断能力。使用独立的血浆酶联免疫吸附测定数据集进一步测试该特征,结果表明其区分 GC 组织和健康对照的 AUC 值为 0.778,使用免疫组织化学组织微阵列分析的 AUC 值为 0.805。总之,本研究确定了潜在的生物标志物,加深了我们对发病机制的理解,为 GC 提供了新的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/5c782f07b0df/fx4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/2802c64834fd/gr1.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/f87fd2f8a572/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/7571f9b04616/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/bbbc395f30a6/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/1c0087dfa9a9/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/15a1f669e31b/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/bd142085bc3e/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/f173cfff23d2/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/190f75a3f622/fx2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/eebcc9893eba/fx3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/5c782f07b0df/fx4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/2802c64834fd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/e7640eb5b99e/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/f87fd2f8a572/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/7571f9b04616/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/bbbc395f30a6/gr5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/1c0087dfa9a9/gr6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/15a1f669e31b/gr7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/bd142085bc3e/gr8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/f173cfff23d2/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/190f75a3f622/fx2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/eebcc9893eba/fx3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0de3/8377014/5c782f07b0df/fx4.jpg

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