Precision medicine requires the delivery of individually adapted medical care based on the genetic characteristics of each patient and his/her tumour. Today, technological advances (e.g., next-generation sequencing) are providing unprecedented opportunities to draw a comprehensive picture of the tumor genomics landscape and ultimately enable individualized treatment. Several PM clinical trials are underway using treatment algorithms to assign patients to specific targeted therapies based on tumour molecular. Examples of these trials include metastatic disease from all cancer typessuch as the SHIVA trial, MPACT and the WINTHER trial, as well as disease-specific trials such as the SAFIRO2 trials.
Some of the criteria taken into account to design treatment algorithms for future PM trials, includes specification of the technology used for molecular profiling, the definition of ‘targetable’ molecular alterations and targeted agents and the prioritization of targetable molecular alterations in patients whose tumours have more than a single alteration. It goes without saying that in order to evaluate the efficiency of treatment algorithms in guiding therapy, it needs to produce interpretable and reproducible results [Le Tourneau et al, 2015].
A step beyond this is the added complexity of the tumour-immune cell interactions and the impact of immune-oncology agents on this. These agents are particularly exciting because they can induce a durable anti-tumour response, with some patients achieving disease control for many years. However, not all patients benefit and researchers are now investing their efforts into finding predictive biomarkers of response and resistance. For computational biology, our lack of understanding of tumour biology and drug pharmacology makes treatment algorithms difficult to design [Harris, et al 2016].
The success of cancer immunotherapies today are based on agents that induce or augment immune responses to cancer. This takes the form of monotherapies – use of checkpoint blockers, vaccination with neoantigens and adoptive T cell transfer. Additionally we have combinations of these therapies as well as their combinations to targeted therapies. An infrastructure for precision oncology based on these strategies requires state-of-the-art molecular tools, such as the NGS instruments and dedicated IT systems depicted in the image below [Hackl, et al 2016]: