Researchers at Laval University are tracking molecular signatures that could one day make it possible to personalize the dose of radiation administered to a cancer patient.
Radiotherapy currently adopts a “one size fits all” approach which is not necessarily the most effective, explained Professor Venkata Manem, who is affiliated with the Faculty of Medicine of Laval University and the Research Center of Quebec University Hospital.
“In chemotherapy, in comparison, there are hundreds of compounds and we choose the right one for the right patient,” he recalled. But in radiotherapy, we look at the characteristics of the patient, their age, their sex, if they smoke and so on. […], but we are not interested in the biological characteristics of the tumor. »
If we found, for example, that the tumor is more resistant, we could administer a higher dose of radiation to increase the chances of cure and reduce the risk of relapse, he added. On the other hand, if it were discovered that the tumor is more vulnerable, a lower dose of radiation could be used, which would minimize unwanted side effects for the patient.
“We are trying to both reduce the toxicity (of the treatment) for the patient and increase the chances of survival,” summarized the researcher.
The work of Professor Manem and his team is part of the trend of “precision medicine” or “personalized medicine”, which has developed at lightning speed in recent years, since doctors have found that it is by taking into account the particular genetic characteristics of the patient and their tumor that they can develop the most effective treatment.
The same approach could be taken in radiotherapy, the researcher believes: with the availability of tissue-specific data, it could eventually be possible to obtain signatures for different types of cancers such as breast, prostate and lung cancers. , he said.
Even if all tumors are different, and even if they are classified in the same group, at the same stage and with the same anatomical characteristics, the response to radiotherapy may be influenced by factors such as the mutations present, the microenvironment and the immune component.
The team therefore used cell line data combined with bioinformatics and machine learning-based approaches to target a molecular indicator of sensitivity that could be subject to preclinical testing before being translated to the clinic.
“About half of patients will receive radiotherapy as part of their treatment, whether for palliative or curative purposes,” Professor Manem said. So when we give radiotherapy, it has to be precise. Should a patient receive a higher dose? A lower dose because it’s combined with chemotherapy? You have to know. »
The next step in the research will be to validate these molecular signatures with patient data and develop a clinical test using methods based on machine learning. The team also wishes to identify radiosensitizing compounds likely to increase the therapeutic effectiveness of radiation.
The findings of this new study were published by the medical journal BMC Cancer.