Literature DB >> 29654727

Comparative proteomic analysis of human malignant ascitic fluids for the development of gastric cancer biomarkers.

Jonghwa Jin1, Minsoo Son1, Hyeyoon Kim2, Hyeyeon Kim2, Seong-Ho Kong3, Hark Kyun Kim4, Youngsoo Kim5, Dohyun Han6.   

Abstract

OBJECTIVES: Malignant ascites is a sign of peritoneal seeding, which is one of the most frequent forms of incurable distant metastasis. Because the development of malignant ascites is associated with an extremely poor prognosis, determining whether it resulted from peritoneal seeding has critical clinical implications in diagnosis, choice of treatment, and active surveillance. At present, the molecular characterizations of malignant ascites are especially limited in case of gastric cancer. We aimed to identify malignant ascites-specific proteins that may contribute to the development of alternative methods for diagnosis and therapeutic monitoring and also increase our understanding of the pathophysiology of peritoneal seeding. DESIGN &
METHODS: First, comprehensive proteomic strategies were employed to construct an in-depth proteome of ascitic fluids. Label-free quantitative proteomic analysis was subsequently performed to identify candidates that can differentiate between malignant ascitic fluilds of gastric cancer patients from benign ascitic fluids. Finally, two candidate proteins were verified by ELISA in 84 samples with gastric cancer or liver cirrhosis.
RESULTS: Comprehensive proteome profiling resulted in the identification of 5347 ascites proteins. Using label-free quantification, we identified 299 proteins that were differentially expressed in ascitic fluids between liver cirrhosis and stage IV gastric cancer patients. In addition, we identified 645 proteins that were significantly expressed in ascitic fluids between liver cirrhosis and gastric cancer patients with peritoneal seeding. Finally, Gastriscin and Periostin that can distinguish malignant ascites from benign ascites were verified by ELISA.
CONCLUSIONS: This study identified and verified protein markers that can distinguish malignant ascites with or without peritoneal seeding from benign ascites. Consequently, our results could be a significant resource for gastric cancer research and biomarker discovery in the diagnosis of malignant ascites.
Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Gastric cancer; Label-free quantification; Malignant ascites; Peritoneal seeding; Quantitative proteomics

Mesh:

Substances:

Year:  2018        PMID: 29654727     DOI: 10.1016/j.clinbiochem.2018.04.003

Source DB:  PubMed          Journal:  Clin Biochem        ISSN: 0009-9120            Impact factor:   3.281


  5 in total

1.  Apolipoprotein C-II induces EMT to promote gastric cancer peritoneal metastasis via PI3K/AKT/mTOR pathway.

Authors:  Chao Wang; Zhi Yang; En Xu; Xiaofei Shen; Xingzhou Wang; Zijian Li; Heng Yu; Kai Chen; Qiongyuan Hu; Xuefeng Xia; Song Liu; Wenxian Guan
Journal:  Clin Transl Med       Date:  2021-08

2.  Ligand-mediated PAI-1 inhibition in a mouse model of peritoneal carcinomatosis.

Authors:  Josephine Hendrikson; Ying Liu; Wai Har Ng; Jing Yi Lee; Abner Herbert Lim; Jui Wan Loh; Cedric C Y Ng; Whee Sze Ong; Joey Wee-Shan Tan; Qiu Xuan Tan; Gillian Ng; Nicholas B Shannon; Weng Khong Lim; Tony K H Lim; Clarinda Chua; Jolene Si Min Wong; Grace Hwei Ching Tan; Jimmy Bok Yan So; Khay Guan Yeoh; Bin Tean Teh; Claramae Shulyn Chia; Khee Chee Soo; Oi Lian Kon; Iain Beehuat Tan; Jason Yongsheng Chan; Melissa Ching Ching Teo; Chin-Ann J Ong
Journal:  Cell Rep Med       Date:  2022-02-15

Review 3.  Recent advances in mass spectrometry based clinical proteomics: applications to cancer research.

Authors:  Andrew Macklin; Shahbaz Khan; Thomas Kislinger
Journal:  Clin Proteomics       Date:  2020-05-24       Impact factor: 3.988

4.  Identification of TUBB2A by quantitative proteomic analysis as a novel biomarker for the prediction of distant metastatic breast cancer.

Authors:  Dongyoon Shin; Joonho Park; Dohyun Han; Ji Hye Moon; Han Suk Ryu; Youngsoo Kim
Journal:  Clin Proteomics       Date:  2020-05-24       Impact factor: 3.988

5.  Evaluation of periostin level for predicting severity and chronicity of childhood atopic dermatitis.

Authors:  Deniz Ozceker; Esra Yucel; Sevgi Sipahi; Fatih Dilek; Emin Ozkaya; Eray Metin Guler; Abdurrahim Kocyigit; Nermin Guler; Zeynep Tamay
Journal:  Postepy Dermatol Alergol       Date:  2019-11-12       Impact factor: 1.837

  5 in total

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