Liu Wenhu, Wang Qiang, Chang Jinxia, Bhetuwal Anup, Bhattarai Nisha, Zhang Fan, Tang Jiancai
School of Pharmacy, School of Basic Medical Sciences & Forensic Medical, North Sichuan Medical College, Nanchong, China.
Department of Clinical Laboratory, Translational Medicine Research Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
Clin Proteomics. 2022 May 24;19(1):18. doi: 10.1186/s12014-022-09357-x.
Esophageal squamous cell carcinoma (ESCC) is a common digestive tract malignant tumor with high incidence and dismal prognosis worldwide. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of ESCC are not unequivocally understood yet. The serum proteome may provide valuable clues for the early diagnosis of ESCC and the discovery of novel molecular insights.
In the current study, an optimized proteomics approach was employed to discover novel serum-based biomarkers for ESCC, and unveil abnormal signal pathways. Gene ontology (GO) enrichment analysis was done by Gene Set Enrichment Analysis (GSEA) and Metascape database, respectively. Pathway analysis was accomplished by GeneCards database. The correlation coefficient was assessed using Pearson and distance correlation analyses. Prioritized candidates were further verified in two independent validation sets by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) staining.
A total of 633 non-redundant proteins were identified in the serum of patients with ESCC, of which 59 and 10 proteins displayed a more than 1.5-fold increase or decrease compared with healthy controls. Verification was performed for six candidate biomarkers, including S100A8/A9, SAA1, ENO1, TPI1 and PGAM1. Receiver operating characteristics (ROC) curve plotting showed the high diagnostic sensitivity and specificity of these six protein molecules as a biomarker panel: the area under characteristic curve (AUC) is up to 0.945. Differentially expressed proteins were subjected to functional enrichment analysis, which revealed the dysregulation of signaling pathways mainly involved in glycolysis, TLR4, HIF-1α, Cori cycle, TCA cycle, folate metabolism, and platelet degranulation. The latter finding was all the more noteworthy as a strong positive correlation was discovered between activated glycolysis and TLR4 pathways and unfavorable clinicopathological TNM stages in ESCC.
Our findings propose a potential serum biomarker panel for the early detection and diagnosis of ESCC, which could potentially broaden insights into the characteristics of ESCC from the proteomic perspective.
食管鳞状细胞癌（ESCC）是一种常见的消化道恶性肿瘤，在全球范围内发病率高且预后不佳。然而，ESCC临床诊断的可靠生物标志物及其潜在的信号通路仍未完全明确。血清蛋白质组可能为ESCC的早期诊断和新分子见解的发现提供有价值的线索。
在本研究中，采用优化的蛋白质组学方法来发现ESCC基于血清的新型生物标志物，并揭示异常信号通路。基因本体（GO）富集分析分别通过基因集富集分析（GSEA）和Metascape数据库完成。通路分析通过GeneCards数据库完成。使用Pearson和距离相关性分析评估相关系数。通过酶联免疫吸附测定（ELISA）和免疫组织化学（IHC）染色在两个独立的验证集中进一步验证优先候选物。
在ESCC患者血清中共鉴定出633种非冗余蛋白，其中59种和10种蛋白与健康对照相比显示出超过1.5倍的增加或减少。对六种候选生物标志物进行了验证，包括S100A8/A9、SAA1、ENO1、TPI1和PGAM1。受试者工作特征（ROC）曲线绘制显示这六种蛋白质分子作为生物标志物组合具有高诊断敏感性和特异性：特征曲线下面积（AUC）高达0.945。对差异表达蛋白进行功能富集分析，揭示了主要参与糖酵解、TLR4、HIF-1α、科里循环、三羧酸循环、叶酸代谢和血小板脱颗粒的信号通路失调。后一发现更值得注意，因为在ESCC中发现活化的糖酵解和TLR4通路与不利的临床病理TNM分期之间存在强正相关。
我们的研究结果提出了一种用于ESCC早期检测和诊断的潜在血清生物标志物组合，这可能从蛋白质组学角度潜在地拓宽对ESCC特征的认识。
