Unraveling Molecular Differences of Gastric Cancer by Label-Free Quantitative Proteomics Analysis

International Journal of Molecular Sciences

Kazem M. Azadzoi¹  Weihua Wang²  Qin Wang²  Wei Wang²  Zhen Yan²  Peng Dai²  Ruirui Jing³  Jing-Hua Yang³  Fengqin Wang³ 

[1] Departments of Surgery and Urology, Boston Veterans Affairs Healthcare System, Boston University School of Medicine, Boston, MA 02130, USA;State Key Laboratory of Cancer Biology, Department of Pharmacogenomics, School of Pharmacy, Fourth Military Medical University, Xi’an 710032, China;The Cancer Research Center, School of Medicine, Shandong University, Jinan 250012, China;

关键词: gastric cancer;    LC-MS/MS;    Label-free quantitative proteomics;    heterogeneous nuclear ribonucleoprotein;    Y-box binding protein 1;   

DOI  :  10.3390/ijms17010069

来源: DOAJ

【 摘 要 】

Gastric cancer (GC) has significant morbidity and mortality worldwide and especially in China. Its molecular pathogenesis has not been thoroughly elaborated. The acknowledged biomarkers for diagnosis, prognosis, recurrence monitoring and treatment are lacking. Proteins from matched pairs of human GC and adjacent tissues were analyzed by a coupled label-free Mass Spectrometry (MS) approach, followed by functional annotation with software analysis. Nano-LC-MS/MS, quantitative real-time polymerase chain reaction (qRT-PCR), western blot and immunohistochemistry were used to validate dysregulated proteins. One hundred forty-six dysregulated proteins with more than twofold expressions were quantified, 22 of which were first reported to be relevant with GC. Most of them were involved in cancers and gastrointestinal disease. The expression of a panel of four upregulated nucleic acid binding proteins, heterogeneous nuclear ribonucleoprotein hnRNPA2B1, hnRNPD, hnRNPL and Y-box binding protein 1 (YBX-1) were validated by Nano-LC-MS/MS, qRT-PCR, western blot and immunohistochemistry assays in ten GC patients’ tissues. They were located in the keynotes of a predicted interaction network and might play important roles in abnormal cell growth. The label-free quantitative proteomic approach provides a deeper understanding and novel insight into GC-related molecular changes and possible mechanisms. It also provides some potential biomarkers for clinical diagnosis.

【 授权许可】

Unknown