Precision medicine needs pioneering clinical bioinformaticians

Success in precision medicine depends on accessing high-quality genetic and molecular data from large, well-annotated patient cohorts that couple biological samples to comprehensive clinical data, which in conjunction can lead to effective therapies. From such a scenario emerges the need for a new professional profile, an expert bioinformatician with training in clinical areas who can make sense of multi-omics data to improve therapeutic interventions in patients, and the design of optimized basket trials. In this review, we first describe the main policies and international initiatives that focus on precision medicine. Secondly, we review the currently ongoing clinical trials in precision medicine, introducing the concept of 'precision bioinformatics', and we describe current pioneering bioinformatics efforts aimed at implementing tools and computational infrastructures for precision medicine in health institutions around the world. Thirdly, we discuss the challenges related to the clinical training of bioinformaticians, and the urgent need for computational specialists capable of assimilating medical terminologies and protocols to address real clinical questions. We also propose some skills required to carry out common tasks in clinical bioinformatics and some tips for emergent groups. Finally, we explore the future perspectives and the challenges faced by precision medicine bioinformatics.

[1]  B. Taylor,et al.  Implementing Genome-Driven Oncology , 2017, Cell.

[2]  Geoffrey S. Ginsburg,et al.  Realizing the Full Potential of Precision Medicine in Health and Health Care. , 2016, JAMA.

[3]  Ash A. Alizadeh,et al.  Toward understanding and exploiting tumor heterogeneity , 2015, Nature Medicine.

[4]  Yann Joly,et al.  Public–Private Partnerships in Cloud-Computing Services in the Context of Genomic Research , 2017, Front. Med..

[5]  W. Riley,et al.  Precision Public Health for the Era of Precision Medicine. , 2016, American journal of preventive medicine.

[6]  Clara Gaff,et al.  Prospective comparison of the cost-effectiveness of clinical whole-exome sequencing with that of usual care overwhelmingly supports early use and reimbursement , 2017, Genetics in Medicine.

[7]  Xiaoqian Jiang,et al.  Addressing Beacon re-identification attacks: quantification and mitigation of privacy risks , 2017, J. Am. Medical Informatics Assoc..

[8]  Francisco Salavert,et al.  A web-based interactive framework to assist in the prioritization of disease candidate genes in whole-exome sequencing studies , 2014, Nucleic Acids Res..

[9]  R. Gibbs,et al.  Genomic analyses identify molecular subtypes of pancreatic cancer , 2016, Nature.

[10]  E. Feldman,et al.  The Genetic Information Nondiscrimination Act (GINA): Public Policy and Medical Practice in the Age of Personalized Medicine , 2011, Journal of General Internal Medicine.

[11]  Eduardo G Moros,et al.  The future of personalised radiotherapy for head and neck cancer. , 2017, The Lancet. Oncology.

[12]  Rachel G Liao,et al.  A federated ecosystem for sharing genomic, clinical data , 2016, Science.

[13]  Marylyn D. Ritchie,et al.  Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study , 2016, Science.

[14]  Yingdong Zhao,et al.  GeneMed: An Informatics Hub for the Coordination of Next-Generation Sequencing Studies that Support Precision Oncology Clinical Trials , 2015, Cancer informatics.

[15]  Sara Reardon,et al.  Giant study poses DNA data-sharing dilemma , 2015, Nature.

[16]  Potter Wickware Training in a hybrid discipline , 2001, Nature.

[17]  Orion J. Buske,et al.  The Matchmaker Exchange: A Platform for Rare Disease Gene Discovery , 2015, Human mutation.

[18]  Yingdong Zhao,et al.  OpenGeneMed: a portable, flexible and customizable informatics hub for the coordination of next-generation sequencing studies in support of precision medicine trials , 2016, Briefings Bioinform..

[19]  Niko Beerenwinkel,et al.  Genomic variant annotation workflow for clinical applications. , 2016, F1000Research.

[20]  Andrew V Biankin,et al.  The road to precision oncology , 2017, Nature Genetics.

[21]  K. Kinzler,et al.  Cancer Genome Landscapes , 2013, Science.

[22]  Emmanuel Barillot,et al.  Bioinformatics for precision medicine in oncology: principles and application to the SHIVA clinical trial , 2014, Front. Genet..

[23]  Alaina G. Levine An explosion of bioinformatics careers , 2014 .

[24]  Allison P. Heath,et al.  Toward a Shared Vision for Cancer Genomic Data. , 2016, The New England journal of medicine.

[25]  Mark Lawler,et al.  From Rosalind Franklin to Barack Obama: Data Sharing Challenges and Solutions in Genomics and Personalised Medicine , 2017, The New bioethics : a multidisciplinary journal of biotechnology and the body.

[26]  Philippe Hupé,et al.  Precision medicine in cancer: challenges and recommendations from an EU-funded cervical cancer biobanking study , 2016, British Journal of Cancer.

[27]  Jane Millar,et al.  The Need for a Global Language - SNOMED CT Introduction , 2016, Nursing Informatics.

[28]  Celia W. G. van Gelder,et al.  A Quick Guide to Genomics and Bioinformatics Training for Clinical and Public Audiences , 2014, PLoS Comput. Biol..

[29]  Michael R Clay,et al.  Bioinformatics Education in Pathology Training: Current Scope and Future Direction , 2017, Cancer informatics.

[30]  Frederick Marcus,et al.  Cancer Systems Biology, Bioinformatics and Medicine , 2011 .

[31]  Vicki Brower,et al.  NCI-MATCH pairs tumor mutations with matching drugs , 2015, Nature Biotechnology.

[32]  Mark Cobbold,et al.  Tracking Genomic Cancer Evolution for Precision Medicine: The Lung TRACERx Study , 2014, PLoS biology.

[33]  Jill C. Rubinstein Perspectives on an Education in Computational Biology and Medicine , 2012, The Yale journal of biology and medicine.

[34]  Scott McGrath,et al.  Building towards precision medicine: empowering medical professionals for the next revolution , 2016, BMC Medical Genomics.

[35]  Brian Hazlehurst,et al.  CER Hub: An informatics platform for conducting comparative effectiveness research using multi-institutional, heterogeneous, electronic clinical data , 2015, Int. J. Medical Informatics.

[36]  Steven A. Roberts,et al.  Mutational heterogeneity in cancer and the search for new cancer genes , 2014 .

[37]  Josephine T. Daub,et al.  267 Spanish Exomes Reveal Population-Specific Differences in Disease-Related Genetic Variation , 2016, Molecular biology and evolution.

[38]  Marc-Thorsten Hütt,et al.  Interdisciplinary approach towards a systems medicine toolbox using the example of inflammatory diseases , 2016, Briefings Bioinform..

[39]  Jan O. Korbel,et al.  Computing patient data in the cloud: practical and legal considerations for genetics and genomics research in Europe and internationally , 2017, Genome Medicine.

[40]  Gabriele Weiler,et al.  The p-medicine portal—a collaboration platform for research in personalised medicine , 2014, Ecancermedicalscience.

[41]  Michael Eisenstein,et al.  Big data: The power of petabytes , 2015, Nature.

[42]  L. F. A. Wessels,et al.  Towards a global cancer knowledge network: dissecting the current international cancer genomic sequencing landscape , 2017, Annals of oncology : official journal of the European Society for Medical Oncology.

[43]  Patrick Granton,et al.  Radiomics: extracting more information from medical images using advanced feature analysis. , 2012, European journal of cancer.

[44]  Jeffrey Chang,et al.  Core services: Reward bioinformaticians , 2015, Nature.

[45]  Ricardo Villamarín-Salomón,et al.  ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..

[46]  Lucila Ohno-Machado,et al.  Integrated precision medicine: the role of electronic health records in delivering personalized treatment , 2017, Wiley interdisciplinary reviews. Systems biology and medicine.

[47]  Mercè Crosas,et al.  Data Authorship as an Incentive to Data Sharing. , 2017, The New England journal of medicine.

[48]  S. Mundlos,et al.  The Human Phenotype Ontology , 2010, Clinical genetics.

[49]  Joaquín Dopazo,et al.  A web tool for the design and management of panels of genes for targeted enrichment and massive sequencing for clinical applications , 2014, Nucleic Acids Res..

[50]  Alberto Anguita,et al.  p-medicine: A Medical Informatics Platform for Integrated Large Scale Heterogeneous Patient Data , 2014, AMIA.

[51]  E. V. van Beek,et al.  Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art. , 2017, European journal of radiology.

[52]  Alfonso Valencia,et al.  RUbioSeq: a suite of parallelized pipelines to automate exome variation and bisulfite-seq analyses , 2013, Bioinform..

[53]  A. Chen,et al.  Defining precision: The precision medicine initiative trials NCI-MPACT and NCI-MATCH. , 2017, Current problems in cancer.

[54]  Nicolas Servant,et al.  Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open-label, proof-of-concept, randomised, controlled phase 2 trial. , 2015, The Lancet. Oncology.

[55]  David J. Sims,et al.  Analytical Validation and Application of a Targeted Next-Generation Sequencing Mutation-Detection Assay for Use in Treatment Assignment in the NCI-MPACT Trial. , 2016, The Journal of molecular diagnostics : JMD.

[56]  Michael P. Schroeder,et al.  In silico prescription of anticancer drugs to cohorts of 28 tumor types reveals targeting opportunities. , 2015, Cancer cell.

[57]  David Haussler,et al.  Sharing Clinical and Genomic Data on Cancer - The Need for Global Solutions. , 2017, The New England journal of medicine.

[58]  Anna Tramontano,et al.  Education and Research Infrastructures , 2011 .

[59]  Werner Dubitzky,et al.  Computational Systems Biomedicine , 2016, Briefings Bioinform..

[60]  P. A. Futreal,et al.  Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. , 2012, The New England journal of medicine.

[61]  A. Valencia,et al.  Getting personalized cancer genome analysis into the clinic: the challenges in bioinformatics , 2012, Genome Medicine.

[62]  A. Redig,et al.  Basket trials and the evolution of clinical trial design in an era of genomic medicine. , 2015, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[63]  D. Ledbetter,et al.  The Geisinger MyCode Community Health Initiative: an electronic health record-linked biobank for Precision Medicine research , 2015, Genetics in Medicine.

[64]  F Martin-Sanchez,et al.  Training health professionals in bioinformatics. Experiences and lessons learned. , 2010, Methods of information in medicine.

[65]  Subha Madhavan,et al.  G-DOC Plus – an integrative bioinformatics platform for precision medicine , 2016, BMC Bioinformatics.

[66]  Hans Clevers,et al.  Interrogating open issues in cancer precision medicine with patient-derived xenografts , 2017, Nature Reviews Cancer.

[67]  Benjamin J. Raphael,et al.  Mutational landscape and significance across 12 major cancer types , 2013, Nature.

[68]  Alfonso Valencia,et al.  Integrated Next-Generation Sequencing and Avatar Mouse Models for Personalized Cancer Treatment , 2014, Clinical Cancer Research.

[69]  Federico Morán,et al.  Best practices in bioinformatics training for life scientists , 2013, Briefings Bioinform..

[70]  Farid Neema,et al.  Data sharing , 1998 .

[71]  Riccardo Miotto,et al.  Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams , 2016, Briefings Bioinform..

[72]  H. Rehm Evolving health care through personal genomics , 2017, Nature Reviews Genetics.

[73]  David J. Duffy Problems, challenges and promises: perspectives on precision medicine , 2016, Briefings Bioinform..

[74]  Lisa Rosenbaum,et al.  Bridging the Data-Sharing Divide - Seeing the Devil in the Details, Not the Other Camp. , 2017, The New England journal of medicine.

[75]  Stefan Schulz,et al.  Ontology patterns-based transformation of clinical information , 2014, MIE.

[76]  Dan Boneh,et al.  Deriving genomic diagnoses without revealing patient genomes , 2017, Science.

[77]  Tin Wee Tan,et al.  Integrating translational bioinformatics into the medical curriculum , 2014, International journal of medical education.

[78]  Manuel Hidalgo,et al.  Patient-derived xenograft models: an emerging platform for translational cancer research. , 2014, Cancer discovery.

[79]  Celia W. G. van Gelder,et al.  GOBLET: The Global Organisation for Bioinformatics Learning, Education and Training , 2015, PLoS Comput. Biol..

[80]  Jure Acimovic,et al.  Training in Systems Approaches for the Next Generation of Life Scientists and Medical Doctors. , 2016, Methods in molecular biology.