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The  has begun. Computational biologists and math wizards of all stripes are invited to enter the competition, which calls on statistically inclined members of the public to develop predictive computational models that reveal which genes are most essential to the survival of various cancer subtypes.

Cancer strikes when alterations in the genome cause cells to replicate uncontrollably. But not every type of cancer is triggered by mutations in the same genes, which means that not every cancer has the same genetic strengths and weaknesses. The goal of this project is to use a crowd-based competition to develop predictive models that can infer gene dependencies in cancer cells – that is, to what level genes have become essential to a cancer cell’s survival – using experimental data from tests on cultures of cancer cell lines. An additional goal is to find a small set of biomarkers (e.g., number of copies of a gene, expression levels of a gene) that best predict gene dependency scores for a gene or set of genes. Participants will be provided with data from experiments on 45 cancer cell lines to help them build their mathematical models, with additional cell line data reserved for a later round that will determine the winning entry.

The Ó³»­´«Ã½ Instititue has partnered with the  and  to run the challenge, which like past DREAM Challenges is designed to enlist diverse communities of scientists to competitively solve specific problems in biomedicine. Twenty-seven Challenges have been successfully launched to date, but this is the Ó³»­´«Ã½'s first. 

The Ó³»­´«Ã½-DREAM Challenge builds on Project Achilles, a collaborative project led by Ó³»­´«Ã½ and Dana-Farber Cancer Institute researchers that aims to create a comprehensive catalog of cancer’s genetic vulnerabilities across many cancer subtypes, in order to identify new drug targets and guide therapeutic development. The promise of targeted cancer therapy requires both effective treatments and good biomarkers to identify patient populations likely to respond to those treatments. Therefore, a critical need exists to accurately predict what genes become essential for a wide variety of cancer subtypes.

Can you come up with a solution that will help develop cancer therapies?

For more information on the challenge, and to register for the competition, visit the home page.