Teams win big in new ’Omics’ cancer competition

Teams from McGill took honours in four of five research grants in the first-ever competition, earning a share of $1.5 million in funding in projects that combine AI, genomics and cancer

Earlier today, a Quebec based consortium of research institutes (Génome Québec, Oncopole and IVADO) announced the winners of their first-ever "Omics Data Against Cancer" competition, and McGill research teams were dominant. In fact, of the five selected teams no less than four of them included professors from McGill.

The new competition is intended to leverage the use of artificial intelligence (AI) in the ’Omic’ sciences (which refers to the biological sciences that end with -omics, such as genomics, transcriptomics, proteomics, or metabolomics) to achieve breakthroughs in cancer research.

"The results of this competition speak for themselves: McGill is defining the cutting edge of science," said Martha Crago, Vice-Principal, Research and Innovation. "I congratulate each of the winning teams and commend them for pushing the envelope of our collective knowledge in the fight against cancer."

The winning teams shared in a $1.5 million pool of funds to support their endeavours over the next two years. The following are the McGill-based projects:

  • Dr. Amin Emad (McGill University, Mila) and Dr. Morag Park (Rosalind and Morris Goodman Cancer Research Centre) are developing artificial intelligence models to predict response to drug combinations in poor-outcome cancer patients.
  • Dr. Ian Watson, Dr. Hamed Najafabadi (McGill University, Goodman Cancer Research Centre) and Dr. John Stagg (Université de Montréal, CHUM Research Centre) are developing "MELANO-PREDICT," a clinically applicable algorithm for predicting checkpoint inhibitor response in melanoma.
  • Dr. Jacques Drouin (Université de Montréal, Montréal Clinical Research Institute) and Professor Marc Bellemare (McGill University, Mila) are collaborating on decoding the cancer epigenome with novel artificial intelligence discovery tools.
  • Professor Mathieu Blanchette (McGill University, School of Computer Science) and his team are working on deciphering mechanisms of epigenetic alterations in cancer using 3D-genomics-informed deep learning.

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