An international consortium of groups from Canada, the United States and the United Kingdom have come together to create an innovative, cloud-based, public challenge running on the Google Cloud Platform to optimize the discovery of genetically distinct groups of cells within cancers that could respond differently to treatment and have different risk of spreading. The ICGC-TCGA DREAM Somatic Mutation Calling Heterogeneity (SMC-Het) Challenge is the first project in the world to marry crowd-sourced benchmarking and cloud-based execution of DNA sequencing analysis pipelines to improve our understanding of tumour DNA. The Challenge launched on November 16, 2015 and will run until May 2016. Sign up to participate at: https://www.synapse.org/SMCHet.
Cancer remains a leading cause of death throughout the world because of its ability to evade even the best available therapies. Recent advances in DNA sequencing enabled patients' tumours to be analyzed in unprecedented detail. This has revealed that tumour cells do not all share the same DNA- rather some tumour cells have evolved unique genetic characteristics that cause them to respond differently to therapy. This means that effective treatment requires understanding the many different populations of cancer cells present in each patient.
"We know that cancers are made up of many different populations of cells, known as 'subclones', and understanding the relationships between these subclones is critical in developing successful long term treatments." – David Wedge, Staff Scientist at the Wellcome Trust Sanger Institute.
The Challenge tackles three key questions about the sub-clonality of cancer: how many subclones are within any given tumour, how did these subclones grow and evolve, and which genetic mutations are present in each subclones? Using a method to simulate DNA sequencing data that closely mimics data from real human tumours, which was initially developed as part of a previous DREAM challenge, the team has created a set of 50 tumours with distinctive life-histories and evolutions. Contestants will create tools in the cloud using Google Compute Engine that will be run in Galaxy, a widely-used open-source platform for performing biomedical research. Contestants will also use Docker images to setup the environment for their tool to run in, allowing the tools to easily be ported to other systems. Further, the use of Docker images and the tools' compatibility with Galaxy ensures that all submissions are immediately usable after the Challenge, creating a new library of algorithms that researchers can use in future studies and allowing the results of these studies to be compared in an objective way.
In many scientific challenges, participants are provided the data set to do the analysis on their own systems, and send the results back for evaluation.
"In that model, we lose reproducibility. By requiring contestants to submit their methods in a portable format, the Challenge will have a truly hidden testing set to improve unbiased evaluation" said Kyle Ellrott, researcher with the Knight Cancer Institute at Oregon Health & Science University, and assistant professor at the OHSU School of Medicine Computational Biology Program. "This also means that their results will be immediately available to all members of the scientific community for large scale analysis of different data sets."
To incentivize a high level of participation, all individuals and teams that submit a final model will be invited as consortium co-authors on an overview paper of the Challenge that will be submitted to Nature Biotechnology, as the official journal partner of the Challenge, and top performers will receive travel awards and speaking invitations at the 2016 DREAM Conference, the 2016 Sage Congress or a similar event. The overall winning algorithms for each sub-challenge will be run on a subset of the ICGC pan-cancer dataset of 2500 whole-genome sequences (subset size will depend on computational characteristics of the winning method).
"Objectively and independently assessing the quality of subclonal reconstruction algorithms is the only way that cancer researchers can make informed decisions about the tools that they use. The Challenge goes beyond informing end users about which tools to use by making available these tools in a trivial to build and run format. Only by collaborating across international borders were we able to bring together the scientific expertise and technical resources needed to make the Challenge happen." – Amit Deshwar, PhD Candidate with Quaid Morris's Lab in the Donnelly Centre at the University of Toronto
OICR is an innovative cancer research and development institute dedicated to prevention, early detection, diagnosis and treatment of cancer. The Institute is an independent, not-for-profit corporation, supported by the Government of Ontario. OICR and its funding partners support research programs that involve more than 1,700 investigators, clinician scientists, research staff and trainees in research institutes and in universities across the Province of Ontario as well as at its headquarters. OICR has key research program efforts underway in small molecules, biologics, stem cells, imaging, genomics, informatics and bio-computing.
Donnelly Centre is an interdisciplinary research institute at the University of Toronto where scientists from diverse fields make discoveries into the fundamentals of biology and use these insights to improve human health. Founded in 2005 with the investment from the government of Canada and private sector contributions, the Centre has quickly established itself as a major international hub for biomedical research. Today the Donnelly Centre houses 35 principal investigators and 500 trainees and staff, who explore biology at all levels – from genes to proteins to cells. With partnerships that include the biotech sector and major Toronto hospitals, the Centre is well positioned to turn basic discovery into tangible advances in medicine.
About Sage Bionetworks
Sage Bionetworks is a nonprofit biomedical research organization, founded in 2009, with a vision to promote innovations in personalized medicine by enabling a community-based approach to scientific inquiries and discoveries. In pursuit of this Mission, Sage Bionetworks is working with others to assemble an information Commons for biomedicine that (1) is supported by an open compute space (Synapse: http://www.synapse.org), (2) supports open research collaborations and innovative DREAM Challenges, and (3) empowers citizens and patients with the tools to partner with researchers and share their data through Sage's BRIDGE platform in order to drive the research studies that matter most to them.
About DREAM Challenges
The Dialogue on Reverse Engineering Assessment and Methods (DREAM) Challenges pose fundamental questions about systems biology and translational medicine. A. Califano (Columbia University) and Gustavo Stolovitzky (IBM Research and the Icahn School of Medicine at Mount Sinai) founded the group in 2006. The DREAM Challenges, designed and run by a community of researchers from a variety of organizations, invite participants to propose solutions while fostering collaboration and building communities in the process. Expertise and institutional support are provided by Sage Bionetworks, along with the infrastructure to host challenges via their Synapse platform.
Thea Norman, 206-667-3192
Christopher Needles, 416-673-8505