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Comparative Secretome Profiling and Mutant Protein Identification in Metastatic Prostate Cancer Cells by Quantitative Mass Spectrometry-based Proteomics.
Kwon, Oh Kwang; Jeon, Ju Mi; Sung, Eunji; Na, Ann-Yea; Kim, Sun Joo; Lee, Sangkyu.
Afiliação
  • Kwon OK; College of Pharmacy, Research Institute of Pharmaceutical Sciences, BK21 Plus KNU Multi-Omics-based Creative Drug Research Team, Kyungpook National University, Daegu, Republic of Korea.
  • Jeon JM; College of Pharmacy, Research Institute of Pharmaceutical Sciences, BK21 Plus KNU Multi-Omics-based Creative Drug Research Team, Kyungpook National University, Daegu, Republic of Korea.
  • Sung E; College of Pharmacy, Research Institute of Pharmaceutical Sciences, BK21 Plus KNU Multi-Omics-based Creative Drug Research Team, Kyungpook National University, Daegu, Republic of Korea.
  • Na AY; College of Pharmacy, Research Institute of Pharmaceutical Sciences, BK21 Plus KNU Multi-Omics-based Creative Drug Research Team, Kyungpook National University, Daegu, Republic of Korea.
  • Kim SJ; College of Pharmacy, Research Institute of Pharmaceutical Sciences, BK21 Plus KNU Multi-Omics-based Creative Drug Research Team, Kyungpook National University, Daegu, Republic of Korea.
  • Lee S; College of Pharmacy, Research Institute of Pharmaceutical Sciences, BK21 Plus KNU Multi-Omics-based Creative Drug Research Team, Kyungpook National University, Daegu, Republic of Korea sangkyu@knu.ac.kr.
Cancer Genomics Proteomics ; 15(4): 279-290, 2018.
Article em En | MEDLINE | ID: mdl-29976633
ABSTRACT

BACKGROUND:

Secreted proteins play an important role in promoting cancer (PCa) cell migration and invasion. Proteogenomics helps elucidate the mechanism of diseases, discover therapeutic targets, and generate biomarkers for diagnosis through protein variations. MATERIALS AND

METHODS:

We carried out mass a spectrometry-based proteomic analysis of the conditioned media (CM) from two human prostate cancer cell lines, belonging to different metastatic sites, to identify potential metastatic and/or aggressive factors.

RESULTS:

We identified a total of 598 proteins, among which 561 were quantified based on proteomic analysis. Among the quantified proteins, 128 were up-regulated and 83 were down-regulated in DU145/PC3 cells. Six mutant peptides were identified in the CM of prostate cancer cell lines using proteogenomics approach.

CONCLUSION:

This is the first proteogenomics study in PCa aiming at exploring a new type of metastatic factor, which are mutant peptides, predicting a novel biomarker of metastatic PCa for diagnosis, prognosis and drug targeting.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Proteoma / Proteômica / Proteínas Mutantes / Espectrometria de Massas em Tandem / Proteínas de Neoplasias Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans / Male Idioma: En Revista: Cancer Genomics Proteomics Assunto da revista: BIOQUIMICA / GENETICA MEDICA / NEOPLASIAS Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Próstata / Proteoma / Proteômica / Proteínas Mutantes / Espectrometria de Massas em Tandem / Proteínas de Neoplasias Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans / Male Idioma: En Revista: Cancer Genomics Proteomics Assunto da revista: BIOQUIMICA / GENETICA MEDICA / NEOPLASIAS Ano de publicação: 2018 Tipo de documento: Article