Literature DB >> 31499184

Pathway analysis of genomic pathology tests for prognostic cancer subtyping.

Olga Lyudovyk1, Yufeng Shen1, Nicholas P Tatonetti1, Susan J Hsiao2, Mahesh M Mansukhani2, Chunhua Weng3.   

Abstract

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.
Copyright © 2019 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computational cancer subtyping; Deep phenotyping; Pathway analysis; Secondary use of genomic data; Survival analysis

Mesh:

Year:  2019        PMID: 31499184      PMCID: PMC7136846          DOI: 10.1016/j.jbi.2019.103286

Source DB:  PubMed          Journal:  J Biomed Inform        ISSN: 1532-0464            Impact factor:   6.317


  34 in total

1.  A novel signaling pathway impact analysis.

Authors:  Adi Laurentiu Tarca; Sorin Draghici; Purvesh Khatri; Sonia S Hassan; Pooja Mittal; Jung-Sun Kim; Chong Jai Kim; Juan Pedro Kusanovic; Roberto Romero
Journal:  Bioinformatics       Date:  2008-11-05       Impact factor: 6.937

2.  The Gene Expression Omnibus Database.

Authors:  Emily Clough; Tanya Barrett
Journal:  Methods Mol Biol       Date:  2016

3.  NoMAS: A Computational Approach to Find Mutated Subnetworks Associated With Survival in Genome-Wide Cancer Studies.

Authors:  Federico Altieri; Tommy V Hansen; Fabio Vandin
Journal:  Front Genet       Date:  2019-04-10       Impact factor: 4.599

4.  Clinical Genomic Profiling of a Diverse Array of Oncology Specimens at a Large Academic Cancer Center: Identification of Targetable Variants and Experience with Reimbursement.

Authors:  Anthony N Sireci; Vimla S Aggarwal; Andrew T Turk; Tatyana Gindin; Mahesh M Mansukhani; Susan J Hsiao
Journal:  J Mol Diagn       Date:  2016-12-23       Impact factor: 5.568

5.  Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example.

Authors:  Samuel Aronson; Lawrence Babb; Darren Ames; Richard A Gibbs; Eric Venner; John J Connelly; Keith Marsolo; Chunhua Weng; Marc S Williams; Andrea L Hartzler; Wayne H Liang; James D Ralston; Emily Beth Devine; Shawn Murphy; Christopher G Chute; Pedro J Caraballo; Iftikhar J Kullo; Robert R Freimuth; Luke V Rasmussen; Firas H Wehbe; Josh F Peterson; Jamie R Robinson; Ken Wiley; Casey Overby Taylor
Journal:  J Am Med Inform Assoc       Date:  2018-10-01       Impact factor: 4.497

6.  MutPred Splice: machine learning-based prediction of exonic variants that disrupt splicing.

Authors:  Matthew Mort; Timothy Sterne-Weiler; Biao Li; Edward V Ball; David N Cooper; Predrag Radivojac; Jeremy R Sanford; Sean D Mooney
Journal:  Genome Biol       Date:  2014-01-13       Impact factor: 13.583

7.  Mutational landscape and significance across 12 major cancer types.

Authors:  Cyriac Kandoth; Michael D McLellan; Fabio Vandin; Kai Ye; Beifang Niu; Charles Lu; Mingchao Xie; Qunyuan Zhang; Joshua F McMichael; Matthew A Wyczalkowski; Mark D M Leiserson; Christopher A Miller; John S Welch; Matthew J Walter; Michael C Wendl; Timothy J Ley; Richard K Wilson; Benjamin J Raphael; Li Ding
Journal:  Nature       Date:  2013-10-17       Impact factor: 49.962

8.  ClinVar: public archive of interpretations of clinically relevant variants.

Authors:  Melissa J Landrum; Jennifer M Lee; Mark Benson; Garth Brown; Chen Chao; Shanmuga Chitipiralla; Baoshan Gu; Jennifer Hart; Douglas Hoffman; Jeffrey Hoover; Wonhee Jang; Kenneth Katz; Michael Ovetsky; George Riley; Amanjeev Sethi; Ray Tully; Ricardo Villamarin-Salomon; Wendy Rubinstein; Donna R Maglott
Journal:  Nucleic Acids Res       Date:  2015-11-17       Impact factor: 16.971

9.  When loss-of-function is loss of function: assessing mutational signatures and impact of loss-of-function genetic variants.

Authors:  Kymberleigh A Pagel; Vikas Pejaver; Guan Ning Lin; Hyun-Jun Nam; Matthew Mort; David N Cooper; Jonathan Sebat; Lilia M Iakoucheva; Sean D Mooney; Predrag Radivojac
Journal:  Bioinformatics       Date:  2017-07-15       Impact factor: 6.937

Review 10.  PUMA, a critical mediator of cell death--one decade on from its discovery.

Authors:  Paweł Hikisz; Zofia M Kiliańska
Journal:  Cell Mol Biol Lett       Date:  2012-09-20       Impact factor: 5.787

View more
  1 in total

1.  Deep phenotyping: Embracing complexity and temporality-Towards scalability, portability, and interoperability.

Authors:  Chunhua Weng; Nigam H Shah; George Hripcsak
Journal:  J Biomed Inform       Date:  2020-04-23       Impact factor: 6.317

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.