CC BY-NC-ND 4.0 · Yearb Med Inform 2018; 27(01): 223-226
DOI: 10.1055/s-0038-1667086
Section 11: Cancer Informatics
Synopsis
Georg Thieme Verlag KG Stuttgart

Cancer Informatics in 2017: A New Beginning and a Bright Future

Jeremy L. Warner
1   Associate Professor, Departments of Medicine and Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
,
Debra A. Patt
2   Vice President, Texas Oncology, Austin, TX, USA
,
Section Editors for the IMIA Yearbook Section on Cancer Informatics › Institutsangaben
Weitere Informationen

Publikationsverlauf

Publikationsdatum:
29. August 2018 (online)

Summary

Objective: To summarize significant research contributions on cancer informatics published in 2017.

Methods: An extensive search using PubMed/Medline, Google Scholar, and manual review was conducted to identify the scientific contributions published in 2017 that address topics in cancer informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of three best papers was conducted by the editorial board of the Yearbook.

Results: Results: The three selected best papers present studies addressing many facets of cancer informatics, with immediate applicability in the research and clinical domains.

Conclusion: Cancer informatics is a broad and vigorous subfield of biomedical informatics. Strides in knowledge management, crowdsourcing, and visualization are especially notable in 2017.

 
  • References

  • 1 Mathé E, Hays JL, Stover DG, Chen JL. The omics revolution continues: the maturation of high-throughput biological data sources. Yearb Med Inform 2018; 211-22
  • 2 Lamy J-B, Séroussi B, Griffon N, Kerdelhué G, Jaulent MC, Bouaud J. Toward a formalization of the process to select IMIA Yearbook best papers. Methods Inf Med 2015; 54 (02) 135-44
  • 3 Chakravarty D, Gao J, Phillips S, Kundra R, Zhang H, Wang J. et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol 2017 Jul;2017
  • 4 Newton Y, Novak AM, Swatloski T, McColl DC, Chopra S, Graim K. et al. TumorMap: exploring the molecular similarities of cancer samples in an interactive portal. Cancer Res 2017; Nov 1; 77 (21) e111-4
  • 5 Seyednasrollah F, Koestler DC, Wang T, Piccolo SR, Vega R, Greiner R. et al. A DREAM Challenge to build prediction models for short-term discontinuation of docetaxel in metastatic castration-resistant prostate cancer. JCO Clin Cancer Inform 2017; Aug 4; (01) 1-15
  • 6 Guinney J, Wang T, Laajala TD, Winner KK, Bare JC, Neto EC. et al. Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data. Lancet Oncol 2017; 18 (01) 132-42
  • 7 Huang L, Fernandes H, Zia H, Tavassoli P, Rennert H, Pisapia D. et al. The cancer Precision Medicine Knowledge Base for structured clinical-grade mutations and interpretations. J Am Med Inform Assoc 2017; May; 24 (03) 513-9
  • 8 Kurnit KC, Bailey AM, Zeng J, Johnson AM, Shufean MA, Brusco L. et al. “Personalized Cancer Therapy”: a publicly available precision oncology resource. Cancer Re. 2017; 01; 77 (21) e123-6
  • 9 Griffith M, Spies NC, Krysiak K, McMichael JF, Coffman AC, Danos AM. et al. CIViC is a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer. Nat Genet 2017; Jan 31; 49 (02) 170-4
  • 10 Micheel CM, Lovly CM, Levy MA. My Cancer Genome. Cancer Genet 2014; Jun 1; 207 (06) 289
  • 11 AACR Project GENIE Consortium. AACR Project GENIE: powering precision medicine through an international consortium. Cancer Discov 2017; Aug; 7 (08) 818-31
  • 12 Bui N, Henry S, Wood D, Wakelee HA, Neal JW. Chart review versus an automated bioinformatic approach to assess real-world crizotinib effectiveness in anaplastic lymphoma kinase–positive non–small-cell lung cancer. JCO Clin Cancer Inform 2017; Mar 13; (01) 1-6
  • 13 Gao S, Young MT, Qiu JX, Yoon HJ, Christian JB, Fearn PA. et al. Hierarchical attention networks for information extraction from cancer pathology reports. J Am Med Inform Assoc 2017 Nov 16;
  • 14 Savova GK, Tseytlin E, Finan S, Castine M, Miller T, Medvedeva O. et al. DeepPhe: a natural language processing system for extracting cancer phenotypes from clinical records. Cancer Res 2017; Nov 1; 77 (21) e115-8
  • 15 Hughes KS, Ambinder EP, Hess GP, Yu PP, Bernstam EV, Routbort MJ. et al. Identifying health information technology needs of oncologists to facilitate the adoption of genomic medicine: recommendations from the 2016 American Society of Clinical Oncology Omics and Precision Oncology workshop. J Clin Oncol 2017; Sep 20; 35 (27) 3153-9
  • 16 Li MM, Datto M, Duncavage EJ, Kulkarni S, Lindeman NI, Roy S. et al. Standards and guidelines for the interpretation and reporting of sequence variants in cancer. J Mol Diagn 2017; Jan 1; 19 (01) 4-23
  • 17 Tang C, Zhou L, Plasek J, Rozenblum R, Bates D. Comment topic evolution on a cancer institution's Facebook page. Appl Clin Inform 2017; Aug 23; 8 (03) 854-65
  • 18 Wysham NG, Wolf SP, Samsa G, Abernethy AP, LeBlanc TW. Integration of electronic patient-reported outcomes into routine cancer care: an analysis of factors affecting data completeness. JCO Clin Cancer Inform 2017; Feb 22; (01) 1-10
  • 19 Yin Z, Malin B, Warner J, Hsueh PY, Chen CH. The power of the patient voice: learning indicators of treatment adherence from an online breast cancer forum. Proceedings of the Eleventh International AAAI Conference on Web and Social Media; 2017. p. 337–46
  • 20 Gandy LM, Gumm J, Blackford AL, Fertig EJ, Diaz LA. A software application for mining and presenting relevant cancer clinical trials per cancer mutation. Cancer Inform 2017; 16: 1176935117711940