International Working Group for Prognostication in MDS

Epidemiology & Biostatistics
Directory
Epidemiology
Biostatistics
Health Outcomes
Computational Oncology
Administrative Resources
Career Opportunities
Educational Opportunities
Departmental Newsletter

International Working Group for Prognostication in MDS

Share
Share

In collaboration with the International Working Group for Prognostication in MDS, we are leading a prospective sequencing study of well-annotated clinical samples collected by clinical and research collaborators around the world.

Our collaborators include:  

Austria

  • Hanusch Hospital
    • Tuechler, H.
  • Medical University of Vienna
    • Valent, P.

Brazil:

  • Federal University of Ceara
    • Pinheiro, R.
  • Hospital Israelita Albert Einstein
    • Santos, F.

Czech Republic:

  • Institute of Hematology and Blood Transfusion
    • Belickova, M.
    • Cermak, J.

France:

  • Hôpital Cochin
    • Fontenay, M.
  • Hôpital St Louis
    • Ades, L.
    • Fenaux, P.

Germany:

  • Hannover Medical School
    • Thol, F.
  • MLL Münchner Leukämielabor GmbH
    • Haferlach, T.
  • University Hospital Duesseldorf
    • Gatterman, N.
    • Germing, U.
  • University Medical Center Göttingen
    • Haase, D.

Greece:

  • Democritus University of Thrace
    • Kotsianidis, I.

Italy:

  • University of Pavia
    • Cazzola, M.
    • Della Porta, M.
    • Malcovati, L.
    • Santini, V.

Japan:

  • Kyoto University
    • Ogawa, S.

The Netherlands:

  • Cancer Center Amsterdam VU
    • van de Loosdrecht, A.
  • Radboud University Nijmegen Medical Centre
    • Jansen, J.

Spain:

  • Hospital La Fe
    • Cervera, J.
  • Hospital Universitario y Politecnico La Fe
    • Sanz, G.
  • Josep Carreras Leukaemia Research Institute (IJC)
    • Mallo, M.
    • Sole, F.

Sweden:

  • Karolinska Institute
    • Hellström Lindberg, E.
    • Ungerstedt, J.

Taiwan:

  • Chang Gung University
    • Shih, L.

UK:

  • The Leeds Teaching Hospitals NHS
    • Bowen, D.
    • Cargo, C.
  • Ninewells Hospital
    • Groves, M.
  • University of Cambridge
    • Green, T.
  • University of Oxford
    • Boultwood, J.
    • Pellagatti, A.
  • Weatherall Institute, Oxford
    • Vyas, P.
  • Wellcome Trust Sanger Institute
    • Campbell, P.

USA:

  • Cleveland Clinic
    • Maciejewski, J.
  • Dana Farber/Harvard Cancer Center
    • Graubert, T.
    • Lindsley, C.
    • Neuberg, D.
    • Stevenson, K.
  • Harvard Stem Cell Institute
    • Ebert, B.
  • Memorial Sloan Kettering Cancer Center
    • Klimek, V.
  • Moffitt Cancer Center
    • Padron, E.
  • Stanford University
    • Greenberg, P.
  • University of California, San Diego
    • Bejar, R.
  • Washington University in St. Louis
    • Walter, M.

So far we have 4,600 samples committed, and sequencing has started as of December 2015.

What sequencing will we perform?

As part of this project, we will perform targeted resequencing using custom capture against a comprehensive panel of genes (n=142) causally implicated in myeloid pathogenesis, as well as frequent regions of copy number alteration or loss of heterozygosity.

What is the sequencing process?

Samples will be subjected to QC, high-throughput capture enrichment, and massively parallel sequencing of barcoded libraries to achieve on-target coverage of 600-800x per region, thus allowing for the detection of minor subclones at diagnosis (>2% of cells). We will deliver an audit of all bona-fide acquired somatic mutations in these genes, including the mutation type (substitutions, indel, copy number), effect in protein (missense, nonsense), whether the mutation is a hotspot mutation, and whether for all mutations the associated variant allele fraction, which estimates the proportion of cells that harbour a mutation.  

What are the research outputs?

We will compare these data to samples with extended molecular annotation currently in the IWG database.

We will integrate mutation, cytogenetic, and clinical annotation to characterize the detailed patterns of co-mutation extending to recurrent secondary and tertiary genotypes and account for distinct mutation types and hotspots within genes.

We will study genetic determinants of clinical variables currently considered in diagnostic and prognostic algorithms and identify the strongest predictors of variance in features such as peripheral blood counts, bone marrow blasts, dysplasia, etc.

We will develop multivariate prognostic models that account for gene-by-gene interactions as well as genotype-phenotype correlations.

Using this information, we will support the development of refined prognostic score in MDS that considers patients’ diagnostic, clinical, and molecular profiles. 

We will deliver an online clinical decision support tool that considers demographic, clinical, and molecular variables to estimate a patient’s risk.

We will also deliver a molecular annotation tool for every gene in our panel to include frequency of mutation, MDS subtypes in which this mutation is present, and high-level clinical information. This will indicate all high-confidence somatic mutations found in these genes, to support future clinical interpretation of molecular findings in the clinic.

Our goal is to define a subset of informative variables to be considered in future diagnostic assays that are amenable to high-throughput and cost-effective turnaround in diagnostic and clinical laboratories worldwide.

Upon study completion, all data will be deposited in the IWG-PM database to support future collaborative efforts in MDS research. For more information, please contact us at [email protected].

This study is generously supported by the MDS Foundation (http://www.mds-foundation.org/).