The challenge that we face these days is our understanding of breast cancer has really exploded since we were able to really generate deep genomic and transcriptomic data on breast cancer. We now recognize the potential for maybe 30 or 40 different subtypes of breast cancer.
And so, we’re moving with these prognostic and predictive molecular tests to really try and identify specific agents which can work for some specific subgroups of cancers...
The challenge that we face these days is our understanding of breast cancer has really exploded since we were able to really generate deep genomic and transcriptomic data on breast cancer. We now recognize the potential for maybe 30 or 40 different subtypes of breast cancer.
And so, we’re moving with these prognostic and predictive molecular tests to really try and identify specific agents which can work for some specific subgroups of cancers. What we’re seeing in our work, alongside that which we presented at ESMO, was that integrating different parts of the omics universe if you want to call it that, the transcriptomics, the genomics, even proteomics and metanomics, can give you clues as to how to treat breast cancer. And the challenge going ahead is for us to take those signatures, those driver pathways which we’re identifying and really challenge them with novel drugs and make sure we do map the best treatment for individual subgroups of patients to the best outcomes and the best drugs.
This is something that’s worked very well in lung cancer and we’re seeing emerging data in prostate and other cancers, and it’s time I think for us in the breast cancer community to grasp that challenge. To look at focused smaller trials in molecularly defined subgroups and take treatment to the next level for our patients.