miércoles, 14 de noviembre de 2012

DREAMing Big to Solve Cancer Research Challenges ► NCI Cancer Bulletin for November 13, 2012 - National Cancer Institute

NCI Cancer Bulletin for November 13, 2012 - National Cancer Institute

DREAMing Big to Solve Cancer Research Challenges

DREAM logo
Earlier today, at the DREAM7 Conference Exit Disclaimer in San Francisco, representatives from the two best-performing teams in the NCI-DREAM Drug Sensitivity Prediction Challenge Exit Disclaimer took to the stage to unveil their methods. Members of the two teams, from Helsinki, Finland, and Dallas, TX, along with 50 other teams from around the world, spent several months this year putting their heads together to work on two related scientific challenges.

NCI-DREAM is part of a larger project known as DREAM (Dialogue for Reverse Engineering Assessments and Methods). Now in its seventh year, DREAM is one of a growing number of biomedical research endeavors that take advantage of crowdsourcing—outsourcing a task to a group or community through an open call or contest.

NCI partnered with DREAM to support innovative approaches to cancer research and to capitalize on the breadth of knowledge of the research community to develop better treatments for cancer patients.
Crowdsourcing "takes advantage of the strength of the broader community to expand our understanding of some difficult scientific problems," noted Dr. Dan Gallahan, deputy director of NCI's Division of Cancer Biology and one of the organizers of the NCI-DREAM challenge.

"The project was born to try to help the research community understand the limitations and strengths of our own methods," explained Dr. Gustavo Stolovitzky, an IBM computational biologist who has been a driving force behind the project. "Crowdsourcing also allows us to determine what the best method is for the solution that we are seeking."

Solve This!

Participants in the two-part challenge were asked to use a vast array of genomic information to build computer models that can predict the sensitivity of cancer cell lines to a set of small-molecule compounds or combinations of compounds. The goal of sub-challenge 1 was to predict the sensitivity of 18 breast cancer cell lines to 31 previously untested compounds, while the goal of sub-challenge 2 was to predict the activity of pairs of compounds on a diffuse large B-cell lymphoma (DLBCL) cell line.

Two researchers working together on a problemParticipants in the NCI-DREAM challenge spent several months working with their teammates on two related scientific problems.

Genomic data for NCI-DREAM were provided by Dr. Joe Gray of Oregon Health and Science University and Dr. Andrea Califano of Columbia University.

"Drug sensitivity prediction from genomic profiles is the core problem of personalized cancer medicine…. At the same time, the task is fascinating due to the challenges it poses [for] computational analysis," wrote Dr. Elisabeth Georgii, a postdoctoral researcher at Helsinki Institute for Information Technology HIIT, Aalto University, in an e-mail message. Dr. Georgii is representing TeamFIN, the best-performing team in sub-challenge 1.

The best-performing team in sub-challenge 2 hails from the University of Texas Southwestern (UTSW) Medical Center. Dr. Yang Xie, an assistant professor in the Department of Clinical Sciences at UTSW, is representing her team at the meeting. (A complete list of members from the best-performing DREAM challenge teams is available online Exit Disclaimer.)

The More the Merrier

In addition to a speaking invitation and travel expenses to the DREAM7 Conference in San Francisco for a team representative, the best-performing teams will publish a peer-reviewed Nature Biotechnology paper on the sub-challenge in which their method was the best performer.


If more people participate, it's more likely that we will find a method that will really hit the nail on the head.

—Dr. Gustavo Stolovitzky

"Incentives can go a long way to gather more people who try to solve the challenge. And if more people participate, it's more likely that we will find a method that will really hit the nail on the head," Dr. Stolovitzky noted.

The long-term goal of NCI-DREAM is to apply what was learned from the challenge to improve treatments for cancer patients. "This is the start of being able to make predictions of how to treat a patient based on his or her molecular profile," Dr. Gallahan explained. With that goal in mind, NCI plans to support the subsequent experimental validation and development of the top performing models in the challenge.

"Cancer is such a complex disease that we want to engage as many people in cancer research as possible" he continued. "And if crowdsourcing is one way that we can do that, then that's another tool in our arsenal."
Elia Ben-Ari

Collaborating to Improve Predictions of Breast Cancer Prognosis
The DREAM7 Conference also featured the Sage Bionetworks-DREAM Breast Cancer Prognosis Challenge Exit Disclaimer. The goal of this ongoing challenge is to assess the accuracy of computational models designed to predict breast cancer survival, based on clinical information about the patient's tumor as well as genome-wide molecular profiling data.
The challenge, run by Seattle-based Sage Bionetworks in collaboration with the DREAM Project, is an open computational challenge whose initial, model-building phase used genomic and clinical data from 2,000 women diagnosed with breast cancer. The challenge drew 354 participants—teams and individuals—from more than 35 countries.
Sage Bionetworks is supported in part by the Integrative Cancer Biology Program in NCI's Division of Cancer Biology.
“The Breast Cancer Challenge is an opportunity to leverage the crowd…and demonstrate what happens when you ask researchers to work together rather than on their own,” said Dr. Thea Norman, director of strategic development for Sage Bionetworks. Ultimately, she noted, Sage Bionetworks hopes to organize challenges that improve patients’ lives.
In the final phase of the challenge (expected to end by early 2013), the model that most accurately predicts survival when tested against a novel validation dataset of molecular and clinical data from approximately 250 breast cancer patients will be declared the winner.
Representatives of the two best-performing teams during the model-building phase—Columbia University’s Attractor Metagenes and the University of Pittsburgh’s PittTransMed—were awarded travel expenses and will speak at the DREAM7 Conference. The overall winner or winners of the challenge will publish their results in Science Translational Medicine.

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