4.5 Article

Mass spectrometric proteomics profiles of in vivo tumor secretomes:: Capillary ultrafiltration sampling of regressive tumor masses

期刊

PROTEOMICS
卷 6, 期 22, 页码 6107-6116

出版社

WILEY
DOI: 10.1002/pmic.200600287

关键词

capillary ultrafiltration sampling; MS; regressive tumors; secretomes

资金

  1. NCI NIH HHS [CA 16672, R01-CA79820, CA 46523, U01 CA105345] Funding Source: Medline
  2. NCRR NIH HHS [1-R21-RR022754] Funding Source: Medline
  3. NIAID NIH HHS [5 U54 AI057157-02, 1-R21-AI58002, 1-R01 AI067395, R01-AI50150] Funding Source: Medline
  4. NIAMS NIH HHS [P30-AR050948] Funding Source: Medline
  5. NIEHS NIH HHS [ES07784] Funding Source: Medline

向作者/读者索取更多资源

Identification of in vivo secreted peptides/proteins (secretomes) in tumor masses has the potential to provide important biomarkers and therapeutic targets for cancer therapy. However, limitations of existing technologies have made obtaining these secretomes for analysis extremely difficult. Here we employed an in vivo sampling technique using capillary ultrafiltration (CUF) probes to collect secretomes directly from tumor masses. Mass spectrometric proteomics approaches were then used to identify the tumor secretomes. A UV-induced skin fibrosarcoma cell line (UV-2240) was subcutaneously injected into C3H/NeH mice, resulting in tumor masses that initially progressed, then regressed and eventually eradicated. We then implanted CUF probes into tumor masses at the progressive and regressive stage. Five secreted proteins (cyclophilin-A, S100A4, profilin-1, thymosin beta 4 and 10), previously associated with tumor progression, were identified from tumor masses at the progressive stage. Five secreted proteins including three protease inhibitors (fetuin-A, alpha-1 antitrypsin 1-6, and contrapsin) were identified from tumor masses at the regressive stage. The technique involving CUF probes linked to mass spectrometric proteomics reinforces systems biology studies of cell-cell interactions and is potentially applicable to the discovery of in vivo biomarkers in human disease.

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