实验技术与管理2025，Vol.42Issue(12)：71-78,8.DOI:10.16791/j.cnki.sjg.2025.12.008
基于非标记定量技术的肝癌血浆蛋白质组研究
Study on plasma proteomics of hepatocellular carcinoma based on label-free quantitative technology
摘要
Abstract
[Objective]Early symptoms of hepatocellular carcinoma(HCC)are often either absent or very vague;thus,most patients are diagnosed at advanced stages with poor prognoses.Therefore,it is particularly important to elucidate the molecular mechanism underlying the onset and progression of HCC,and to identify sensitive early diagnostic biomarkers.Ultra-performance liquid chromatography-tandem mass spectrometry plays a pivotal role in proteomic research.The significant differences in the abundance and complex composition of plasma proteins result in low protein identification.Here,the influence of different liquid chromatography gradient separation conditions on the identification of plasma proteins was investigated.Furthermore,the developed method was applied for proteomic analysis of plasma samples from HCC patients and healthy individuals to identify early diagnostic biomarkers for HCC.[Methods]The effectiveness of different liquid chromatography separation gradients(56,85,and 130 min)to identify plasma proteins was investigated.A standardized plasma analytical workflow suitable for proteomics research was established,which was combined with label-free quantitative proteomics technology,to screen differentially expressed proteins(DEPs)in plasma samples from HCC patients and healthy individuals.Bioinformatics analyses were performed to elucidate the molecular functions and biological processes of these DEPs associated with the pathogenesis of HCC.[Results]Extending the separation gradient from 56 to 85 and 130 min increased the number of identified plasma proteins from 588 to 988 and 1 261,respectively.Also,64.1%and 63.6%of the proteins identified with separation gradients of 56 and 85 min were also identified at 130 min.In total,563 proteins were identified,approximately 3.8 times more than individually obtained with a separation gradient of 130 min,which was attributed to the superior separation of complex peptides and greater protein identification coverage than achieved with the long separation gradient.Label-free quantitative analysis of the proteins from HCC patients and healthy individuals successfully quantified 2 062 protein groups.With cutoffs of p<0.05(t-test)and 1.5-fold difference,56 DEPs(33 up-regulated and 23 down-regulated)were identified in HCC patients.As many as 69.6%of the DEPs are reportedly associated with HCC,highly consistent with the results of previous studies.In addition,other DEPs not previously reported as biomarkers of HCC were significantly associated with liver cirrhosis,fatty liver,and liver fibrosis.Bioinformatics analysis indicated that many of the DEPs were closely associated with the onset and progression of HCC,such as serine-type endopeptidase inhibitor activity,haptoglobin binding action,immune response,and lipid transport.These results indicate that the identified DEPs may play crucial roles in the development of HCC Further research is ongoing to explore the potential of these DEPs as biomarkers of HCC.[Conclusions]The standardized plasma proteomics workflow established in this study not only provides a valuable methodological framework for subsequent investigations in this field but also offers diverse technical solutions for plasma proteome profiling.The quantitative results of the plasma protein profile obtained in this study provide data support for subsequent research on the mechanism of HCC development and the identification of potential biomarkers.关键词
超高效液相色谱串联质谱法/蛋白质组学/无标记定量/肝癌/生物标志物Key words
ultra-performance liquid chromatography-tandem mass spectrometry/proteomics/label-free quantification/hepatocellular carcinoma/biomarker分类
化学化工引用本文复制引用
LI Yilan,YU Wenjing,SHI Wenchao,LI Lan..基于非标记定量技术的肝癌血浆蛋白质组研究[J].实验技术与管理,2025,42(12):71-78,8.基金项目
北京理工大学实验室研究项目(2023BITSYA04) （2023BITSYA04）
中国分析测试协会高校分析测试分会第一届"皖仪科技"卓越工程师提升计划项目(测协发字[2024]19号) （测协发字[2024]19号）
