The answer is yes. Finnish researchers have developed a triumphant solution for predicting responses of breast cancer cells to a set of cancer drugs. The prediction is based on the genomic profiles of the cancer cells. Harnessing genomic profiles of cells in choosing the best treatment is considered the holy grail of personalised medicine.
The team led by Professor Samuel Kaski from Helsinki institute of Information Technology (HIIT), a joint research centre of Aalto University and University of Helsinki, Finland, presented its winning solution at the DREAM 2012 conference on November 13 in San Francisco. The team's solution outperformed 47 other teams in the prediction challenge world-wide.
Computational methods integrate multiple views of the genomic profile of cancer cells
It is well known that drug therapies may effectively kill cancer cells in one patient, but not in another patient suffering from the same type of cancer. However, the molecular determinants underlying the differences in drug response have not so far been sufficiently understood.
-The goal in computational personalised medicine is to develop models which predict drug sensitivity of cells from their genomic profiles, Kaski explains.
The organisers of the NCI-Dream challenge provided data of breast cancer cells for the training of computational sensitivity prediction models. They evaluated the participants' models on test measurements of drugs that were unknown to the participants.