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PTRF/cavin-1 and MIF proteins are identified as non-small cell lung cancer biomarkers by label-free proteomics. [artículo]

Por: Agulló Ortuño, María Teresa [Oncología Médica].
Colaborador(es): Servicio de Oncología Médica.
Editor: PloS One, 2012Descripción: 7(3):e33752.Recursos en línea: Acceso libre Resumen: With the completion of the human genome sequence, biomedical sciences have entered in the "omics" era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer.
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Artículo Artículo PC12723 (Navegar estantería) Disponible

Formato Vancouver:
Gámez-Pozo A, Sánchez-Navarro I, Calvo E, Agulló-Ortuño MT, López-Vacas R, Díaz E, Camafeita E, Nistal M, Madero R, Espinosa E, López JA, Fresno Vara JÁ. PTRF/cavin-1 and MIF proteins are identified as non-small cell lung cancer biomarkers by label-free proteomics. PLoS One. 2012;7(3):e33752.

PMID: 22461895

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With the completion of the human genome sequence, biomedical sciences have entered in the "omics" era, mainly due to high-throughput genomics techniques and the recent application of mass spectrometry to proteomics analyses. However, there is still a time lag between these technological advances and their application in the clinical setting. Our work is designed to build bridges between high-performance proteomics and clinical routine. Protein extracts were obtained from fresh frozen normal lung and non-small cell lung cancer samples. We applied a phosphopeptide enrichment followed by LC-MS/MS. Subsequent label-free quantification and bioinformatics analyses were performed. We assessed protein patterns on these samples, showing dozens of differential markers between normal and tumor tissue. Gene ontology and interactome analyses identified signaling pathways altered on tumor tissue. We have identified two proteins, PTRF/cavin-1 and MIF, which are differentially expressed between normal lung and non-small cell lung cancer. These potential biomarkers were validated using western blot and immunohistochemistry. The application of discovery-based proteomics analyses in clinical samples allowed us to identify new potential biomarkers and therapeutic targets in non-small cell lung cancer.

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