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TransMed COSI Track Presentations

Attention Conference Presenters - please review the Speaker Information Page available here
TransMed KEYNOTE: Metavariable based genome-phenome integrative analysis to facilitate personalized cancer medicine
Date: Tuesday, July 25
Time: 8:40 a.m.-9:15 a.m.
Room: Meeting Hall IV
  • Anguraj Sadanandam, The Institute of Cancer Research, United Kingdom

Presentation Overview: Show

Heterogeneity in treatment responses and prognosis (phenotypes) in cancers can be attributed to differences in genome, transcriptome, proteome and metabolome (multi-omics) profiles of individual patient tumours. Previously, we discretely integrated gene expression, microRNA, mutation and metabolome profiles from tumour samples and associated them with the clinical variables. However, integrating multi-omics data profiles simultaneously is not straight-forward since the biological system is dynamic and subject to multiple levels of regulations associated with phenotypes. In addition, integrating multi-omics data (with different units and scales/magnitudes) from different platforms can introduce bias that need to be taken into account. Hence, an efficient approach to data integration needs capturing all the information from genome and phenome for a comprehensive subtype discovery. Along this line, we have developed a data integration framework that can simultaneously integrate multiple high-throughput omics datasets from different platforms to discover functional subtypes (i.e. subtypes whose biological meaning is known) and their associated multi-omics biomarkers and clinical variables. This integrative analysis improves the power of capturing different levels of heterogeneity in tumours and interactions between genome and phenome profiles.

Short Profile: Sadanandam completed his interdisciplinary (wet-lab and computational biology) Ph.D. from the USA, and continued postdoc under Professors Joe Gray and Douglas Hanahan (USA and Switzerland). Briefly worked at Swiss Institute of Bioinformatics. Currently leading Systems and Precision Medicine team at the Institute of Cancer Research (ICR) with Honarary Appointment from Royal Marsden Hospital (RMH). His team uses cutting-edge wet-lab and computational biology to focus on inter- and intra-tumoral heterogeneity at the genetic, epigenetic, molecular and metabolic levels and to understand how they contribute to variations in metastatic potential, prognosis and therapeutic responses in patients. To this end, Sadanandam and colleagues have classified different tumor types including breast cancer cell lines, and pancreatic and colorectal tumours and cell lines into distinct molecular and/or drug response subtypes (Heiser and Sadanandam et al. PNAS 2012, Collisson and Sadanandam et al. Nature Medicine 2011, Sadanandam et al. Nature Medicine 2013, Sadanandam et al. Cancer Discovery 2015, and Colorectal Cancer Subtyping Consortium based Nature Medicine, 2015). In addition, they have identified subtype-specific cellular origin and molecular mechanisms and suggested possible precise therapies using combined (systems biology) wet-lab and bioinformatics approaches. These subtypes are being explored by clinicians for potential applications in the clinic. Currently, their goal is to identify and refine tumor subtype-specific robust biomarkers using integrated genome and phenome analysis, develop and validate biomarker-based companion diagnostic assays, screen for targeted therapies and understand their mechanisms of action using pre-clinical (both in vitro and in vivo) studies.

Molecular signatures that can be transferred across different omics platforms
Date: Tuesday, July 25
Time: 9:15 a.m.-9:30 a.m.
Room: Meeting Hall IV
  • Rainer Spang, University of Regensburg, Germany
  • Peter J. Oefner, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany, Germany
  • Wolfram Klapper, Department of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel/Christian-Albrecht University, Kiel, Germany
  • Neus Masqué-Soler, Department of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel/Christian-Albrecht University, Kiel, Germany
  • Monika Szczepanowski, Department of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel/Christian-Albrecht University, Kiel, Germany
  • Julia Richter, Department of Pathology, Hematopathology Section and Lymph Node Registry, University Hospital Schleswig-Holstein, Campus Kiel/Christian-Albrecht University, Kiel, Germany
  • Wolfram Gronwald, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany, Germany
  • Christian W. Kohler, Statistical Bioinformatics, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany, Germany
  • Jörg Reinders, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany, Germany
  • Thorsten Rehberg, Statistical Bioinformatics, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany, Germany
  • Philipp Schwarzfischer, Institute of Functional Genomics, University of Regensburg, Regensburg, Germany, Germany
  • Michael Altenbuchinger, University of Regensburg, Germany
The 100,000 genomes project
Date: Tuesday, July 25
Time: 10:00 a.m.-10:35 a.m.
Room: Meeting Hall IV
  • Tim Hubbard, King's College London, United Kingdom

Presentation Overview: Show

The 100,000 genomes project sets out to mainstream whole genome sequencing for treatment into the UK National Health Service (NHS). Genomics England, set up in 2013 to deliver the project, has established sample handling, sequencing and interpretation pipelines to enable whole genome sequences to be analysed for rare diseases and cancer with individual reports returned to clinicians. In parallel, NHS England has set up a national network of thirteen NHS Genome Medicine Centres (GMCs) involving >80 hospitals to identify and consent eligible patients with unmet clinical need, delivering samples for sequencing with
associated clinical data. As of June 2017 more than 23,000 genomes have been sequenced related to more than 9,000 affected individuals and more than 2,000 interpretation reports have been fed back to GMCs. The secure, scalable high performance-computing environment where all data processing takes place is also configured to support research and will be used by the >2,500 researchers who are members of the Genomics England Clinical Interpretation Partnership (GeCIP). The construction of a dual use data environment within a health system provides a model for future translational human research, moving from restricted cohorts of research subjects to analysis of patient data from whole health systems while respecting data privacy, allowing comorbidities and longitudinal health data to be better taken into account. I will discuss the progress of the project and its impact on personalised medicine in the UK.

Biography:
Professor Tim Hubbard is Head of the Department of Medical & Molecular Genetics at King's College London and Director of Bioinformatics for King's Health Partners. He is also Head of Genome Analysis at Genomics England, the company set up by the Department of Health to execute the 100,000 genomes project, which aims to mainstream the use of whole genome sequence analysis for treatment in the UK National Health Service (NHS). Until 2013 he was Head of Informatics at the Wellcome Trust Sanger Institute where he was one of the organisers of the sequencing of the human genome. In 1999 he co-founded the Ensembl project to analysis, organise and provide access to the human genome and from 2007 led the GENCODE project to annotate the structure of all human genes.

Association testing of bisulfite sequencing methylation data via a Laplace approximation
Date: Tuesday, July 25
Time: 10:35 a.m.-10:50 a.m.
Room: Meeting Hall IV
  • Omer Weissbrod, Weizmann Institute of Science, Israel
Identification of Associations between Genotypes and Longitudinal Phenotypes via Temporally-constrained Group Sparse Canonical Correlation Analysis
Date: Tuesday, July 25
Time: 10:50 a.m.-11:05 a.m.
Room: Meeting Hall IV
  • Daoqiang Zhang, Nanjing University of Aeronautics and Astronautics, China
  • Andrew Saykin, Indiana University, United States
  • Li Shen, Indiana University, United States
  • Shannon Risacher, Indiana University, United States
  • Jingwen Yan, Indiana University, United States
  • Xiaohui Yao, Indiana University, United States
  • Chanxiu Li, Nanjing University of Aeronautics and Astronautics, China
  • Xiaoke Hao, Nanjing University of Aeronautics and Astronautics, China
Predicting phenotypes from microarrays using amplified, initially marginal, eigenvector regression
Date: Tuesday, July 25
Time: 11:05 a.m.-11:20 a.m.
Room: Meeting Hall IV
  • Daniel Mcdonald, Indiana University, United States
  • Lei Ding, Indiana University Bloomington, United States
Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression
Date: Tuesday, July 25
Time: 11:20 a.m.-11:35 a.m.
Room: Meeting Hall IV
  • Tero Aittokallio, Institute of Molecular Medicine Finland, University of Helsinki, Finland
  • Krister Wennerberg, Institute of Molecular Medicine Finland, University of Helsinki, Finland
  • Suleiman Ali Khan, Institute of Molecular Medicine Finland, University of Helsinki, Finland
  • Muhammad Ammad-Ud-Din, Institute of Molecular Medicine Finland, University of Helsinki, Finland
Epigenomic profiling of glioblastoma through treatment and progression
Date: Tuesday, July 25
Time: 11:35 a.m.-11:45 a.m.
Room: Meeting Hall IV
  • Johanna Klughammer, CeMM, Austria
Predicting cancer sequential treatments and drug repurposing with SATIE
Date: Tuesday, July 25
Time: 11:45 a.m.-12:00 p.m.
Room: Meeting Hall IV
  • Fatima Al-Shahrour, Spanish National Research Cancer Centre, CNIO, Spain
  • Gonzalo Gómez-López, Spanish National Research Cancer Centre, CNIO, Spain
  • Julián Carretero, Departament de Fisiologia, Facultat de Farmacia, Universitat de Valencia, Spain
  • Inés Pulido, Departament de Fisiologia, Facultat de Farmacia, Universitat de Valencia, Spain
  • Kevin Troulé, Spanish National Research Cancer Centre, CNIO, Spain
  • Coral Fustero-Torre, Spanish National Research Cancer Centre, CNIO, Spain
  • Andres Cañada, Spanish National Research Cancer Centre, CNIO, Spain
  • Miriam Rubio-Camarillo, Spanish National Research Cancer Centre, CNIO, Spain
  • Javier Perales-Patón, Spanish National Research Cancer Centre, CNIO, Spain
  • Héctor Tejero, Spanish National Research Cancer Centre, CNIO, Spain
canSAR: an integrated knowledgebase for cancer research and drug discovery
Date: Tuesday, July 25
Time: 12:00 p.m.-12:15 p.m.
Room: Meeting Hall IV
  • Bissan Al-Lazikani, The Institute of Cancer Research, United Kingdom
  • Patrizio Di Micco, The Institute of Cancer Research, United Kingdom
  • Albert Antolin, The Institute of Cancer Research, United Kingdom
  • Costas Mitsopoulos, The Institute of Cancer Research, United Kingdom
  • Joe Tym, The Institute of Cancer Research, United Kingdom
  • Elizabeth Coker, The Institute of Cancer Research, United Kingdom
Integrative analysis of personalized, multidimensional datasets of glioblastoma patients
Date: Tuesday, July 25
Time: 12:15 p.m.-12:30 p.m.
Room: Meeting Hall IV
  • Nikolaus Fortelny, CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Austria
TransMed KEYNOTE: The Internet of FAIR data and Services
Date: Tuesday, July 25
Time: 2:00 p.m.-2:35 p.m.
Room: Meeting Hall IV
  • Barend Mons, Leiden University Medical Center,
Using Multi-Scale Genetic, Protein, Neuroimaging and Clinical Data for Predicting Alzheimer's Disease and Reconstruction of Relevant Biological Mechanisms
Date: Tuesday, July 25
Time: 2:35 p.m.-2:50 p.m.
Room: Meeting Hall IV
  • Holger Fröhlich, University of Bonn, UCB Biosciences GmbH, Germany
  • Martin Hofmann-Apitius, Fraunhofer SCAI, University of Bonn, Germany
  • Anandhi Iyappan, Fraunhofer SCAI, University of Bonn, Germany
  • Shashank Khanna, Fraunhofer SCAI, University of Bonn, Germany
Understanding human disease relationships through integrated molecular and clinical analysis
Date: Tuesday, July 25
Time: 2:50 p.m.-3:05 p.m.
Room: Meeting Hall IV
  • Purvesh Khatri, Stanford University, United States
  • Nigam Shah, Stanford University, United States
  • Timothy Sweeney, Stanford University, United States
  • Paul J. Utz, Stanford University, United States
  • Shane Lofgren, Stanford University, United States
  • Erika Bongen, Stanford University, United States
  • Charles Liu, Stanford University, United States
  • Greg Gaskins, Stanford University, United States
  • Francesco Vallania, Stanford University, United States
  • Rohit Vashisht, Stanford University, United States
  • Winston Haynes, Stanford University, United States
Integrating personalized gene expression profiles into predictive disease-associated gene pools
Date: Tuesday, July 25
Time: 3:05 p.m. - 3:20 p.m.
Room: Meeting Hall IV
  • Emre Guney, Institute for Research in Biomedicine (IRB Barcelona), Spain
Classification of Paediatric Inflammatory Bowel Disease using Machine Learning
Date: Tuesday, July 25
Time: 3:20 p.m.-3:35 p.m.
Room: Meeting Hall IV
  • Enrico Mossotto, University of Southampton, United Kingdom
  • James Ashton, University of Southampton, United Kingdom
  • Tracy Coelho, University of Southampton, United Kingdom
  • Mark Beattie, Southampton Children’s Hospital, United Kingdom
  • Benjamin MacArthur, University of Southampton, United Kingdom
  • Sarah Ennis, University of Southampton, United Kingdom
Pseudotemporal disease trajectories from cross-sectional data
Date: Tuesday, July 25
Time: 3:35 p.m.-3:50 p.m.
Room: Meeting Hall IV
  • Christopher Yau, University of Birmingham, United Kingdom
  • Kieran Campbell, University of Oxford, United Kingdom
Integrating genomics and transcriptomics to dissect the pathogenic mechanism of X-Linked Dystonia-Parkinsonism
Date: Tuesday, July 25
Time: 3:50 p.m.-4:00 p.m.
Room: Meeting Hall IV
  • Jyotsna Dhakal, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, United States
  • Ashok Ragavendran, Center for Genomic Medicine, Massachusetts General Hospital, United States
  • Criscely Go, Department of Behavorial Medicine, Jose Reyes Memorial Medical Center, Manila, Philippines
  • Marisela Elizabeth Dy, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, United States
  • Carrie Hanscom, Center for Genomic Medicine, Massachusetts General Hospital, United States
  • Harrison Brand, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • Benjamin Currall, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • Alexei Stortchevoi, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • Christine A. Vaine, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • Ryan L. Collins, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • Dadi Gao, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • David Shin, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • William T. Hendriks, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • Tatsiana Aneichyk, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • Rachita Yadav, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
  • Naoto Ito, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • Nutan Sharma, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • Xandra Breakefield, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • Laurie Ozelius, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • D. Cristopher Bragg, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
  • Michael Talkowski, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, United States
Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time
Date: Tuesday, July 25
Time: 4:00 p.m.-4:10 p.m.
Room: Meeting Hall IV
  • Anna Hake, Max-Planck-Institut für Informatik, Germany
Understanding human knockouts
Date: Tuesday, July 25
Time: 4:10 p.m.-4:20 p.m.
Room: Meeting Hall IV
  • Suganthi Balasubramanian, Regeneron Genetics Center, Regeneron Pharmaceuticals, United States
  • Yao Fu, Bina Technologies, Part of Roche Sequencing, United States
  • Mayur Pawashe, Yale University, United States
  • Patrick McGillivray, Yale University, United States
  • Mike Jin, Yale University, United States
  • Jeremy Liu, Yale University, United States
  • Konrad  Karczewski, Massachusetts General Hospital, United States
  • Daniel MacArthur, Massachusetts General Hospital, United States
  • Mark Gerstein, Yale University, United States