Onco-proteogenomics: Multi-omics level data integration for accurate phenotype prediction.

The overall goal of translational oncology is to identify molecular alterations indicative of cancer or of responsiveness to specific therapeutic regimens. While next-generation sequencing has played a pioneering role in this quest, the latest advances in proteomic technologies promise to provide a...

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Publicado en:Critical Reviews in Clinical Laboratory Sciences Vol. 54; no. 6; pp. 414 - 433
Autores principales: Dimitrakopoulos, Lampros, Prassas, Ioannis, Diamandis, Eleftherios P., Charames, George S.
Formato: review tables/charts Journal Article
Publicado: Taylor & Francis Ltd Sep2017
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Taylor & Francis Ltd
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        atl: Onco-proteogenomics: Multi-omics level data integration for accurate phenotype prediction.
      aug:
        au:
          Dimitrakopoulos, Lampros
          Prassas, Ioannis
          Diamandis, Eleftherios P.
          Charames, George S.
        affil: Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
      sug:
        subj:
          Proteogenomics Methods
          Neoplasms Risk Factors
          Phenotype
          Molecular Biology
          Patient Centered Care
          Oncologic Care
          Individualized Medicine
          Genetics
          Sequence Analysis
          Technology, Medical
      ab: The overall goal of translational oncology is to identify molecular alterations indicative of cancer or of responsiveness to specific therapeutic regimens. While next-generation sequencing has played a pioneering role in this quest, the latest advances in proteomic technologies promise to provide a holistic approach to the further elucidation of tumor biology. Genetic information may be written in DNA and flow from DNA to RNA to protein, according to the central dogma of molecular biology, but the observed phenotype is dictated predominantly by the DNA protein coding region-derived proteotype. Proteomics holds the potential to bridge the gap between genotype and phenotype, because the powerful analytical tool of mass spectrometry has reached a point of maturity to serve this purpose effectively. This integration of “omics” data has given birth to the novel field of onco-proteogenomics, which has much to offer to precision medicine and personalized patient management. Here, we review briefly how each “omics” technology has individually contributed to cancer research, discuss technological and computational advances that have contributed to the realization of onco-proteogenomics, and summarize current and future translational applications.
      pubtype: Academic Journal
      doctype:
        review
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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