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PhD Course in Genomic Medicine 2017

Enlarged view: The medical research location Zurich

Abstract

Genomic technologies are not only changing the way biomedical research is performed, but they also have an increasing impact on medical diagnostics and treatment. However, using genomic data in a clinical setting is challenging. It requires an interdisciplinary approach, including knowledge of the measurement technologies, of computational and statistical methods for analyzing the data they produce, and of clinical procedures to translate the results into improved healthcare.

This 1-week PhD block course on "Genomic Medicine" has been designed to help preparing the next generation of clinical and biomedical researchers for this transformation. It addresses clinical as well as basic biomedical and computational scientists. The goal of the course is to provide a broad overview of Genomic Medicine and to prepare participants to contribute to Genomic Medicine in interdisciplinary teams.

Content

The course covered the following topics:

  • Omics technologies
  • Computational and statistical analysis of omics data
  • Biomarker discovery
  • Reproducibility
  • Genomic clinical trials
  • Precision medicine: genome-based treatment optimization
  • Ethical and legal aspects of Genomic Medicine
  • Commercial applications of Genomic Medicine
  • Genomic Medicine case studies

Prerequisites

None.

Credit Points

Upon successful completion of the performance assessment, students received 2 ECTS credit points.

Performance Assessment

During the week students worked in small groups on selected Genomic Medicine research papers. They solved tasks, presented and discussed their results on the last day in front of the plenum. Find the list of student tasks at the end of this page.

Date & Location

November 27 - December 1, 2017, 09:15 - 17:00, ML H 43, ETH Zurich

Schedule

The Downloadfinal schedule has been released.  

Student Tasks

Task Titles & Papers

1.   Reproducible science external page(Munafò et al. 2017; Ioannidis 2005) (DownloadTask (PDF, 28 KB))

2.   Dealing with incidental findings in clinical genomics data external page(Kalia et al. 2017) (DownloadTask (PDF, 37 KB))

3.   Molecular tumor board external page(Rennert et al. 2016) (DownloadTask (PDF, 28 KB))

4.   Seamless adaptive clinical trials external page(Siu et al. 2017) (DownloadTask (PDF, 28 KB))

5.   Molecular profiling external page(Crosetto et al. 2015) (DownloadTask (PDF, 26 KB))

6.   Cancer genomics in clinical trials external page(Simon and Roychowdhury 2013) (DownloadTask (PDF, 25 KB))

7.   Deep learning on EHRs external page(Choi et al. 2016) (DownloadTask (PDF, 25 KB))

8.   Single-cell RNA sequencing & data analysis external page(Papalexi and Satija 2017) (DownloadTask (PDF, 25 KB))

9.   Liquid biopsies using circulating tumour DNA external page(Dawson et al. 2013) (DownloadTask (PDF, 26 KB))

 

During the introduction six projects will be chosen for presentation on Friday, December 1. Each project will have 4-5 participating students

Literature

external pageChoi, E., Bahadori, M.T., Schuetz, A., Stewart, W.F. and Sun, J. 2016. Doctor AI: predicting clinical events via recurrent neural networks. JMLR workshop and conference proceedings 56, pp. 301–318.

external pageCrosetto, N., Bienko, M. and van Oudenaarden, A. 2015. Spatially resolved transcriptomics and beyond. Nature Reviews. Genetics 16(1), pp. 57–66.

external pageDawson, S.-J., Tsui, D.W.Y., Murtaza, M., Biggs, H., Rueda, O.M., Chin, S.-F., Dunning, M.J., Gale, D., Forshew, T., Mahler-Araujo, B., Rajan, S., Humphray, S., Becq, J., Halsall, D., Wallis, M., Bentley, D., Caldas, C. and Rosenfeld, N. 2013. Analysis of circulating tumor DNA to monitor metastatic breast cancer. The New England Journal of Medicine 368(13), pp. 1199–1209.

external pageIoannidis, J.P.A. 2005. Why most published research findings are false. PLoS Medicine 2(8), p. e124.

external pageKalia, S.S., Adelman, K., Bale, S.J., Chung, W.K., Eng, C., Evans, J.P., Herman, G.E., Hufnagel, S.B., Klein, T.E., Korf, B.R., McKelvey, K.D., Ormond, K.E., Richards, C.S., Vlangos, C.N., Watson, M., Martin, C.L. and Miller, D.T. 2017. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genetics in Medicine 19(2), pp. 249–255.

external pageMunafò, M.R., Nosek, B.A., Bishop, D.V.M., Button, K.S., Chambers, C.D., Percie du Sert, N., Simonsohn, U., Wagenmakers, E., Ware, J.J. and Ioannidis, J.P.A. 2017. A manifesto for reproducible science. Nature human behaviour 1(1), p. 0021.

external pagePapalexi, E. and Satija, R. 2017. Single-cell RNA sequencing to explore immune cell heterogeneity. Nature Reviews. Immunology.

external pageRennert, H., Eng, K., Zhang, T., Tan, A., Xiang, J., Romanel, A., Kim, R., Tam, W., Liu, Y.-C., Bhinder, B., Cyrta, J., Beltran, H., Robinson, B., Mosquera, J.M., Fernandes, H., Demichelis, F., Sboner, A., Kluk, M., Rubin, M.A. and Elemento, O. 2016. Development and validation of a whole-exome sequencing test for simultaneous detection of point mutations, indels and copy-number alterations for precision cancer care. npj Genomic Medicine 1.

external pageSimon, R. and Roychowdhury, S. 2013. Implementing personalized cancer genomics in clinical trials. Nature Reviews. Drug Discovery 12(5), pp. 358–369.

external pageSiu, L.L., Ivy, S.P., Dixon, E.L., Gravell, A.E., Reeves, S.A. and Rosner, G.L. 2017. Challenges and opportunities in adapting clinical trial design for immunotherapies. Clinical Cancer Research 23(17), pp. 4950–4958.

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