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ASH 2022: An Individualized Approach to Treating AML Patients with Dr. Becker
Posted: Jan 12, 2023
ASH 2022: An Individualized Approach to Treating AML Patients with Dr. Becker image

Dr. Becker from City of Hope, a cancer treatment and research facility, told us about her exciting research surrounding individualized treatments for AML patients. Her study looked at reactivity to different drugs and drug combinations by testing patients cells against 170 different drugs. After also testing for mutations, and accounting for those, the best drugs were chosen for each patient individually. They found that patients who received the recommended drugs had better survival rates than patients who did not follow the recommended treatment plan, this was true even for patients who had relapsed recently after transplant and were in a poor risk category. 

Watch the interview, or read below, to hear Dr. Becker go on to talk about her excitement surrounding their use of artificial intelligence to help decide the best treatment options for patients, as well as her thoughts and research on the large variance of mutations not only between patients, but even within the cells that make up leukemia. 

“I’m Dr. Pamela Becker from City of Hope in Duarte, California. I will be telling you about a presentation that was set at the American Society for Hematology on December 11th, 2022.

I presented work on a clinical trial that enrolled patients with acute myeloid leukemia. It was a precision medicine trial, in that each patient had their cells tested in a laboratory test against 170 drugs and drug combinations and then we chose what the best drug were for the patient. In addition we tested for mutations and added the small molecule inhibitors that were appropriate for patients with those mutations. 

We presented the long-term follow up data which included overall survival. For the patients who were able to receive the drugs and drug combinations that we recommended, there was improved survival compared to those that had to go home or didn’t get insurance authorization or who’s doctors decided to choose other therapy, including other clinical trials, CAR-T cell trials and other options. 

It was very exciting to finally see this data and this was true not only for all patients enrolled in the study, but also for the patients who had relapsed early after allogeneic transplant. The patients who relapse after allogeneic transplant often are quite poor risk, they have very aggressive disease. Even for those patients, they were able to exhibit prolonged survival. So it was very exciting to be able to present that data. 

The session was a session that was on the latest developments, that were technological developments. I was also able, during this trial, to procure specimens from the patients. We were able to correlate gene expression with drug sensitivity or resistance. This will be very helpful for the future. This was a machine learning algorithm, machine learning is part of artificial intelligence and so we’re able now to use that information in a future clinical trial where we would choose drugs for patients. 

We also were able to develop another model which is the co-occurring mutations. So, patients who have blood malignancies exhibit usually more than one mutation, usually dozens- up to dozens of mutations. In order to best take those different mutations into account in terms of choosing treatment, we established a model with my colleagues at the Institute for Systems Biology wherein we can look at the patient's network of mutations and correlate those with the drug sensitivity or resistance. This is another way that we’ll be able to assign treatment in the future for these precision medicine approaches.

Lastly, we looked at the single cell mutation panels to try to identify what clones are present. For all of the blood cancers it’s known that there is representation of many different clones, there’s not just one. We think of it as, ‘oh, we have your cancer cell’ but there is actually a group of cancer cells for all the patients and they vary from each other. I was able to identify how many clones and what the relative composition is, again, that is something that we’ll be able to utilize in the future to make sure that as we apply these precision medicine approaches, that we are taking into account all the differences not only between patients, but amongst the cells that make up the Leukemia. So, again, this is a first demonstration of improved survival with a functional precision medicine approach. 

So we show a beautiful heat map that shows that every single patient, if you plot their results, for all the drugs, 170 drugs, that every single patient looks different from every other patient. So the question is, why are we ever giving the same drugs to all patients? So, anyway, it was really gratifying to be able to present that data yesterday.”
 

The author Mary Arnett

about the author
Mary Arnett

Mary joined HealthTree as the HealthTree for MDS Commnity Manager in 2022. She is passionate about giving power to patients through knowledge and health education. In her spare time, Mary loves attending concerts, spoiling her nieces and nephews, and experimenting in the kitchen.

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