How resistance and recurrence mechanisms can give important information on cancer therapy
Resistance is one of the major problems during cancer therapy, in fact two-thirds of cancer patients are affected by it. ‘Resistance’ in a cancer setting means an insensitivity to the drug(s) used for treatment; this can occur at different stages in a patient’s treatment cycle…
When a patient does not respond to the therapy from the get go, that’s called intrinsic resistance. In these cases the drugs are simply not compatible to fight the make up of tumour in that individual. When a patient initially responds to the treatment, but over the course of the therapy, becomes insensitive to the therapy, that’s called acquired resistance.
Resistance can emerge via a variety of mechanisms including:
One of the reasons defeating cancer is so difficult, and resistance is such a problem, is because cancers are made up of a genetically diverse populations of replicating cells. This mix of “populations”, or sub-clones, that make up a tumour is called intra-tumour heterogeneity. As each sub-clone responds differently to therapies, resistance in one — intrinsic or acquired — means the whole tumour will never be fully treated.
Intra-tumour heterogeneity can also be a reason for cancer recurrence, which is when the signs and symptoms of cancer return after a period of improvement, due to some cancer cells remaining after treatment. Recurrence can be local (in the same place it started), regional (in the lymph nodes near the place it started) or distant (in another part of the body from where it started, often lungs, liver, bone, brain). Failure to fully treat every sub-clone of a tumour will leave more cancer cells behind, therefore increasing the likelihood of relapse in a cancer patient.
Studies on mechanisms of cancer drug resistance and recurrence have yielded important information about how to reduce the likelihood of both, in order to improve cancer therapy. In the future, with advances in drug design and precision medicine, we will hopefully be able to target all the different cell types in a cancer. Today, a combination of molecular insights and precision targeting are becoming more common. However, it remains difficult to predict when resistance will be acquired or relapse will occur. We need longitudinal monitoring during and after therapy, to get cancer patients the right therapy at the right time. This is what we are working towards at CCG.ai with our dedicated team of researchers and engineers.