Prognostic Model to Predict Post-Autologous Stem-Cell Transplantation Outcomes in Classical Hodgkin Lymphoma
This week we profile a recent publication in the Journal of Clinical Oncology from the laboratory of
Dr. Christian Steidl at the BC Cancer Agency.
Can you provide a brief overview of your lab’s current research focus?
My lab is focused on translational lymphoma research, which means translating basic science discoveries into diagnostic tests and better treatments for patients suffering from lymphoma. Lymphoma is the umbrella term for so called Hodgkin and Non-Hodgkin lymphomas. Lymphoma is the fifth most frequent cancer in Canada.
What is the significance of the findings in this publication?
Cancers, including Hodgkin lymphoma can change their face over time. Specifically in Hodgkin lymphoma, we have shown that the so called tumor microenvironment changes form initial diagnosis to relapse.
This has implications for prognostication, treatment resistance and the rational choice of therapies in the era of personalized medicine. In the Journal of Clinical Oncology publication, we have developed an assay, called RHL30, at the time point of disease relapse when testing is most needed for physicians and patients to make decisions about the next line of treatments. To perform the test, a relapse biopsy is needed to confirm the original diagnosis and to determine the risk for subsequent treatment failure of high-dose chemotherapy and autologous stem cell transplantation, the current treatment standard.
What are the next steps for this research?
The next step is to test RHL30 in clinical trials that investigate novel treatment alternatives to the current treatment standard (high-dose chemotherapy + autologous stem cell transplantation). If successful, we can be confident that patients classified as high-risk by RHL30 can be effectively treated with modern targeted and immunotherapies.
This research was funded by:
Canadian Institutes of Health Research
Genome Canada /Genome BC
BC Cancer Foundation
Michael-Smith Foundation for Health Research