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Cancer stem cell scientists create tool to aid in planning treatment for leukemia
Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and is one of the most deadly. Although AML is treated as a single disease, patient response to intensive curative-intent chemotherapy varies. It is currently difficult to predict who will do well with standard treatment, and who will not benefit from standard treatment and might do better enrolling in a clinical trial where they may be offered novel therapies.

Acute myeloid leukemia (AML) is the most common form of acute leukemia in adults and is one of the most deadly. Although AML is treated as a single disease, patient response to intensive curative-intent chemotherapy varies. It is currently difficult to predict who will do well with standard treatment, and who will not benefit from standard treatment and might do better enrolling in a clinical trial where they may be offered novel therapies.

A group of researchers from the Princess Margaret Cancer Centre (PMCC), the University of Toronto and OICR Cancer Stem Cell Program, led by Dr. John Dick, along with other collaborators, have now developed a test that will help doctors identify, within a day or two of diagnosis, those patients who are most likely to not benefit from current therapy or may initially respond well to a therapy only to have their cancer return. Adding to the excitement about the tool is that it has been adapted to a common technology platform that is standard in many molecular diagnostic labs in Ontario, which means it could move fairly quickly into clinical care.

Dr. Jean Wang, an Affiliate Scientist with PMCC and a member of the OICR Cancer Stem Cell Program and her collaborators believe that their new tool will help clinicians by improving their ability to assess risk at the time of AML diagnosis, allowing them to identify potential alternative therapy for patients who are unlikely to benefit from standard treatment. The new tool is a gene signature named the LSC17 score as it comes from leukemia stem cells (LSC).

“Leukemia stem cells are often resistant to standard chemotherapy,” Wang explains. “Chemo is good at killing the bulk leukemia cells, and patients appear to go into remission, but often the leukemia stem cells are left behind and they can regrow the disease, causing relapse. By focusing on the leukemia stem cells, our tool captures the properties of the cells that are really driving the disease and the patient’s response to treatment.”

The LSC17 score is a signature of 17 stem cell genes that are expressed at high levels in leukemia stem cells. A patient’s blood or bone marrow sample is tested to measure the expression levels of the 17 genes; these are then used to calculate the score. Patients who have a higher score are deemed to be at a greater risk of death when given current standard therapy. Currently it is not known if alternative treatments will improve outcomes, but it is possible that clinical trails may result in better results for these high-risk patients.

“Right now in the clinic we don’t really have a rapid way to determine upfront who is at higher risk. Our new tool can do this quickly, allowing oncologists to direct those who are unlikely to benefit from standard treatment to clinical trials testing alternative therapies that may be of more benefit.” says Wang.

Wang and her collaborators are confident in the success of the tool due to the process by which they chose the 17 genes that make up the score. To identify stem cell genes, they took patient samples and tested them in a disease model to determine which genes were more highly expressed in leukemia stem cells. Stanley W. K. Ng, a senior PhD candidate in the lab of Dr. Peter Zandstra at the Institute of Biomaterials and Biomedical Engineering at the University of Toronto and co-lead author of the paper, used rigorous statistical approaches to compare the genes against data of about 500 AML patients whose outcomes (survival) were known. This led to identification of the minimal set of genes associated with different levels of survival and resulted in the final signature of 17 genes.

Adding to the group’s optimism about the LSC17 score is the fact that it is expected to be relatively easy to put into routine use in hospitals. This is because the test was developed on the NanoString platform, a cost-effective technology that is in use in molecular diagnostic laboratories in Ontario. The next steps to moving the LSC17 score into clinical use are an ongoing validation of the test in a clinical lab setting at PMCC and, following that, a prospective clinical trial of AML patients at PMCC.

Read the news release

Read the journal article