Literature DB >> 25815525

Antibody microarray profiling of osteosarcoma cell serum for identifying potential biomarkers.

Zi-Qiang Zhu1, Jin-Shan Tang2, Duan Gang1, Ming-Xing Wang1, Jian-Qiang Wang1, Zhou Lei1, Zhou Feng1, Ming-Liang Fang1, Lin Yan1.   

Abstract

The aim of the present study was to identify biomarkers in osteosarcoma (OS) cell serum by antibody microarray profiling, which may be used for OS diagnosis and therapy. An antibody microarray was used to detect the expression levels of cytokines in serum samples from 20 patients with OS and 20 healthy individuals. Significantly expressed cytokines in OS serum were selected when P<0.05 and fold change >2. An enzyme-linked immunosorbent assay (ELISA) was used to validate the antibody microarray results. Finally, classification accuracy was calculated by cluster analysis. Twenty one cytokines were significantly upregulated in OS cell serum samples compared with control samples. Expression of interleukin-6, monocyte chemoattractant protein-1, tumor growth factor-β, growth-related oncogene, hepatocyte growth factor, chemokine ligand 16, Endoglin, matrix metalloproteinase-9 and platelet-derived growth factor-AA was validated by ELISAs. OS serum samples and control samples were distinguished by significantly expressed cytokines with an accuracy of 95%. The results demonstrated that expressed cytokines identified by antibody microarray may be used as biomarkers for OS diagnosis and therapy.

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Year:  2015        PMID: 25815525     DOI: 10.3892/mmr.2015.3535

Source DB:  PubMed          Journal:  Mol Med Rep        ISSN: 1791-2997            Impact factor:   2.952


  2 in total

1.  Effects of collagen peptides intake on skin ageing and platelet release in chronologically aged mice revealed by cytokine array analysis.

Authors:  Hongdong Song; Ling Zhang; Yongkang Luo; Siqi Zhang; Bo Li
Journal:  J Cell Mol Med       Date:  2017-09-18       Impact factor: 5.310

2.  Development of novel gene signatures for the risk stratification of prognosis and diagnostic prediction of osteosarcoma patients using bioinformatics analysis.

Authors:  Guoquan Li; Baoliang Huang; Hao Wu; Hu Zhang
Journal:  Transl Cancer Res       Date:  2022-07       Impact factor: 0.496

  2 in total

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