Your browser doesn't support javascript.
loading
Pathway analysis of genomic pathology tests for prognostic cancer subtyping.
Lyudovyk, Olga; Shen, Yufeng; Tatonetti, Nicholas P; Hsiao, Susan J; Mansukhani, Mahesh M; Weng, Chunhua.
Afiliação
  • Lyudovyk O; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Shen Y; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Tatonetti NP; Department of Biomedical Informatics, Columbia University, New York, NY, USA.
  • Hsiao SJ; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA.
  • Mansukhani MM; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY, USA.
  • Weng C; Department of Biomedical Informatics, Columbia University, New York, NY, USA. Electronic address: chunhua@columbia.edu.
J Biomed Inform ; 98: 103286, 2019 10.
Article em En | MEDLINE | ID: mdl-31499184
Genomic test results collected during the provision of medical care and stored in Electronic Health Record (EHR) systems represent an opportunity for clinical research into disease heterogeneity and clinical outcomes. In this paper, we evaluate the use of genomic test reports ordered for cancer patients in order to derive cancer subtypes and to identify biological pathways predictive of poor survival outcomes. A novel method is proposed to calculate patient similarity based on affected biological pathways rather than gene mutations. We demonstrate that this approach identifies subtypes of prognostic value and biological pathways linked to survival, with implications for precision treatment selection and a better understanding of the underlying disease. We also share lessons learned regarding the opportunities and challenges of secondary use of observational genomic data to conduct such research.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prognóstico / Informática Médica / Genômica / Neoplasias Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Female / Humans / Male Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Prognóstico / Informática Médica / Genômica / Neoplasias Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Female / Humans / Male Idioma: En Ano de publicação: 2019 Tipo de documento: Article