This work helps explain why glioblastoma, one of the most aggressive forms of brain cancer, becomes resistant to treatment.
One of the lead authors, Dr. David Nathanson, professor of molecular and medical pharmacology at the David Geffen School of Medicine at UCLA, said: “Many cancer treatments are based on the genetic profile of the patient’s tumor. However, genomic features alone do not always predict how the tumor will respond to therapy.
Our research goes beyond the genetic blueprint of the tumor, and takes into account the results of functional tests to identify how living cancer cells may respond to treatments.”
A much clearer picture of which treatments work
- Genetic profiling analyzes the genetic composition of the tumor;
- functional profiling, observes the behavior of cancer cells in response to treatments;
- combine these 2 techniques allows us to more precisely predict the extent to which glioblastoma will respond to treatments and therefore target it more effectively.
The glioblastoma is notoriously complex to treat due to its ability to resist cell death or apoptosis, but also its rapid adaptation to therapies. Traditional precision genomic medicine uses DNA sequencing to identify genetic mutations in tumors and match those mutations to specific therapies, however this approach only provides a snapshot of the tumor’s likely response. This approach may not predict treatment success because it does not take into account the dynamic behavior of cancer cells.
- L’integration of functional profiling genomic data to assess the resistance of glioblastoma to apoptosis will make it possible to better measure the responses of cancer cells to treatments which aim to trigger cell death in real time;
- standard therapies such as radiotherapy or chemotherapy can modify the functioning of the tumor’s self-destruction mechanism, but this effect depends on specific genetic characteristics, with the involvement of key genes – like the p53 gene;
- ultimately, the development ofa machine learning tool called GAVA which combines genetic and functional data made it possible to predict which tumors would respond best to a combination of cancer treatments and drugs that block certain proteins.
A new approach therefore, more sophisticated, more holistic and ultimately more precise which will mark a milestone in the treatment of this deadly cancer, glioblastoma, and, more broadly, for precision medicine.
