Dr. Dan Avi Landau Discusses How Combining an Evolutionary Perspective with Genomic Methods Advances CLL Treatment

Dan Landau, M.D., Ph.D. recently sat down to speak with The Video Journal of Hematology Oncology about how technology with drive future advances in the treatment of CLL. Currently we understand that a malignant population such as a population of CLL cells in any patient, is actually not uniform but composed of multiple sub-populations, which continuously compete, evolve and create diversity. The therapeutic challenge is that in each patient, we are not dealing with one disease but with a collection of many diseases.

Therefore, it is not surprising that therapies can fail. With new genomic technologies, it is now possible to survey this genetic complexity for large cohorts of patients in order to understand the processes underlying the complexity. By taking an evolutionary perspective and combining it with genomic methods, we can infer the past history of disease and use this information to predict its future.

Dr Landau points out how today data science approaches are already being used to predict real world outcomes in advertising or on the stock market for example. However, data science approaches are not really being applied in cancer research. Further, he discusses non-genetic sources of diversity, such as epigenetics and spatial location. All of these layers of information need to be considered in order to understand the evolutionary process.

Finally, he discusses the idea of measuring clonal kinetics directly in patients, i.e. measuring the rate of growth of each clone with each therapy and come up with an optimized therapeutic approach through the use of algorithms; he considers this approach to be a radical extension of the precision medicine paradigm.

Mathematical Analysis of Drug Resistance in CLL

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Dan Avi Landau, M.D., Ph.D.

According to a recent study published in Nature Communications by Weill Cornell Medicine investigator Dr. Dan Avi Landau the rate at which genetically mutated cancer cells grow could be a key to explaining why some CLL patients develop resistance to treatment. Dr. Landau’s findings demonstrate how an individual’s cell mutations can influence that individual’s response to treatment, leading to the development of resistance to treatments like ibrutinib. CLL patients who are treatment resistant require treatment strategies that take account of their treatment resistance. Using mathematical modeling researchers investigated how:

 “…some patients with chronic lymphocytic leukemia (CLL)…become resistant to the drug ibrutinib, which is used to treat the disease once other chemotherapy drugs have failed. They performed mathematical modeling of the growth rates of the sensitive and resistant cells, and discovered that a small cluster of cancer cells survived ibrutinib therapy due to a genetic mutation that was present prior to treatment, allowing these ibrutinib-resistant cells to multiply and the disease to progress unabated. The findings could offer scientists a framework to guide the development of combination therapies that overcome drug resistance in CLL and in other cancers.”

These findings could potentially allow for physicians to develop more precise treatment plans for patients. In theory physicians could be more easily able to treat their patients not just for their present conditions, but also take into account their future conditions.

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