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Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy.

ABSTRACT: BACKGROUND:Proteomics may help us better understand the changes of multiple proteins involved in oncogenesis and progression of prostate cancer(PCa) and identify more diagnostic and prognostic biomarkers. The aim of this study was to screen biomarkers of PCa by the proteomics analysis using isobaric tags for relative and absolute quantification(iTRAQ). METHODS:The patients undergoing prostate biopsies were classified into 3 groups according to pathological results: benign prostate hyperplasia (BPH, n = 20), PCa(n = 20) and BPH with local prostatic intraepithelial neoplasm(PIN, n = 10). Then, all the specimens from these patients were analyzed by iTRAQ and two-dimensional liquid chromatography-tandem mass spectrometry (2DLC-MS/MS). The Gene Ontology(GO) function and the transcription regulation networks of the differentially expressed were analyzed by MetaCore software. Western blotting and Immunohistochemical staining were used to analyze the interesting proteins. RESULT:A total of 760 proteins were identified from 13787 distinct peptides, including two common proteins that enjoy clinical application: prostate specific antigen (PSA) and prostatic acid phosphatase(PAP). Proteins that expressed differentially between PCa and BPH group were further analyzed. Compared with BPH, 20 proteins were significantly differentially up-regulated (>1.5-fold) while 26 were significantly down-regulated in PCa(<0.66-fold). In term of GO database, the differentially expressed proteins were divided into 3 categories: cellular component(CC), molecular function (MF) and biological process(BP). The top 5 transcription regulation networks of the differentially expressed proteins were initiated through activation of SP1, p53, YY1, androgen receptor(AR) and c-Myc The overexpression of periostin in PCa was verified by western blotting and immunohistochemical staining. CONCLUSION:Our study indicates that the iTRAQ technology is a new strategy for global proteomics analysis of the tissues of PCa. A significant up-regulation of periostin in PCa compared to BPH may provide clues for not only a promising biomarker for the prognosis of PCa but also a potential target for therapeutical intervention.

SUBMITTER: Sun C

PROVIDER: S-EPMC3100237 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy.

Sun Chuanyu C Song Chao C Ma Zhicheng Z Xu Ke K Zhang Yang Y Jin Hong H Tong Shijun S Ding Weihong W Xia Guowei G Ding Qiang Q

Proteome science 20110419

<h4>Background</h4>Proteomics may help us better understand the changes of multiple proteins involved in oncogenesis and progression of prostate cancer(PCa) and identify more diagnostic and prognostic biomarkers. The aim of this study was to screen biomarkers of PCa by the proteomics analysis using isobaric tags for relative and absolute quantification(iTRAQ).<h4>Methods</h4>The patients undergoing prostate biopsies were classified into 3 groups according to pathological results: benign prostate ...[more]

PMID: 21504578

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Project description:BackgroundThe tumor microenvironment (TME) plays a crucial role in the initiation and progression of cancer. Bladder cancer (BLCA) is a malignant tumor of the genitourinary system. Its heterogeneity results in significant differences in the prognosis of patients. To date, this is still a huge challenge for clinical treatment. In recent years, more and more evidence showed that dysregulation of transcription factors (TFs) plays an important role in tumor progression, invasion, and metastasis. Unfortunately, the role of TFs on the tumor microenvironment in bladder cancer is unclear.MethodsThe original data of BLCA and corresponding adjacent tissues were obtained from The Cancer Genome Atlas (TCGA) database. TFs were downloaded from the Animal Transcription Factor DataBase (Animal TFDB). Intersection analysis was used to obtain TFs that were differentially expressed between tumor and adjacent tissues. Gene Set Cancer Analysis (GSCALite) and CIBERSORT software were used to reveal the key differentially expressed TFs (DE-TFs). Subsequently, UALCAN and Human Protein Atlas (HPA) databases were used to disclose the expression of key DE-TFs in BLCA. The K-M curve divulged the relationship between the key DE-TFs and the patient's overall survival (OS), and the univariate and multivariate Cox regression analyses were conducted to explore independent prognostic factors. The cluster profiler package and Gene Set Enrichment Analysis (GSEA) were used for functional enrichment of genes related to the key DE-TFs. Finally, CIBERSORT software analyzed the immune landscape of BLCA.ResultsWe obtained a total of 117 BLCA-related DE-TFs. Among them, ETV7 was identified as the key DE-TFs due to its association with the autophagy activation pathway and various immune cells in cancer. Online databases of UALCAN and HPA indicated that ETV7 was overexpressed in tumors and negatively correlated with tumor severity. The K-M curve showed that the OS of patients with high expression of ETV7 was poor, which indicated that it was an independent prognostic factor. Functional enrichment of 87 DEGs between ETV7-high and -low expression groups indicated that it was closely related to the immune response and the functions of a variety of immune cells. Finally, CIBERSORT results proved that the high and low expression of ETV7 also caused significant differences in the tumor immune microenvironment of patients.ConclusionOverall, we proved that the transcription factor ETV7 was a novel prognostic factor, which may improve the individualized outcome prediction in BLCA by regulating the tumor immune microenvironment.

Dataset Information

Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy.

Publications

Periostin identified as a potential biomarker of prostate cancer by iTRAQ-proteomics analysis of prostate biopsy.

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