Hollings receives NCI grant to fund research to personalize GVHD treatment after bone marrow transplantation

MUSC Hollings Cancer Center researcher Sophie Paczesny, M.D., Ph.D., received a $628,188 grant from the National Cancer Institute (NCI) to use machine learning algorithms to improve graft-versus-host disease (GVHD) treatment strategies. Her studies will validate biomarker panels that may help doctors to determine each bone marrow transplant patient’s risk of developing chronic GVHD and adjust his or her immune suppression treatments accordingly.

Bone marrow transplants are a potentially curative therapy for blood and bone marrow cancers, such as leukemia. The donor immune cells kill the cancer, but they may also recognize the recipient’s normal cells. This leads to GVHD, which reportedly occurs in over 30% of patients surviving more than 100 days after receiving a bone marrow transplant (BMT). Chronic GVHD remains the most common long-term complication for BMT recipients.

Paczesny, who is chair of the Department of Microbiology and Immunology, as well as co-leader of the Cancer Immunology Program at Hollings Cancer Center, said, “Despite modern advances, up to 50% of bone marrow transplant patients still develop chronic GVHD. We cure leukemia but give the patient another disease. Currently, there are no validated laboratory tests to determine which patients are more likely to develop chronic GVHD. This grant is designed to address a major challenge in the treatment of chronic GVHD, since validated biomarkers improve doctors’ ability to personalize treatments.”

A pioneer in the field of GVHD biomarkers, Paczesny previously discovered the first GVHD biomarker. The biomarker, called ST2 (STimulation 2), is currently used in acute GVHD clinical trials. Paczesny said that it is easier to study acute GVHD first, since the skin, gut and liver are the three main areas targeted by the donor immune cells in the early days after bone marrow transplantation.

“Our goal is to translate the acute GVHD work to chronic GVHD, which is more challenging to study, since it can affect nearly all of the organs. It is also more complex to diagnose. Finding a blood test, or biomarker, that clearly indicates higher risk of chronic GVHD can help the field with this challenge,” said Paczesny.

A biomarker is any measurable substance found in an organism whose presence is clinically validated to indicate disease activity. The best biomarkers are often from plasma, which is the cell-free component of the blood. Biomarkers also may be found on the cells that circulate in the blood.

Paczesny will use a combination of stored plasma and blood cell samples from the National Blood and Marrow Transplant Clinical Trials Network (BMTCTN). Paczesny and her colleagues will study the samples from approximately 1,300 BMT recipients, collected 80 to 100 days after transplantation, which is the largest biomarker validation attempt in the chronic GVHD field.

“The goal for a chronic GVHD biomarker is to separate standard risk patients from high-risk patients. Doctors really want to see what is going on with biomarkers before a patient develops clinical signs of chronic GVHD. That way, standard risk patients can avoid taking extra steroids, which come with their own long-term health concerns,” said Paczesny.

Prior to these studies, the only therapeutic strategy for chronic GVHD patients was nonspecifically targeting the immune cells causing the damage with high doses of steroids. Paczesny hopes that once she has the best algorithm and combination of biomarkers to identify patients at high risk of developing chronic GVHD, it can be used in clinical trials. Patients identified as low risk for developing chronic GVHD can reduce steroid use more rapidly, while high-risk patients can receive increased immune-modulating drugs.

Paczesny will use the NCI funds to address challenging questions, such as whether plasma biomarkers or cellular biomarkers, or the combination of both, are better regarding specificity and sensitivity. Her team also seeks to uncover new key biologic drivers of chronic GVHD using the machine learning algorithms. Additionally, large patient data sets, such as this one, will allow the researchers to determine if there are any health disparities in chronic GVHD, such as differences between biomarker detection in different races.

“In the future, if we can validate a biomarker panel for chronic GVHD risk, then doctors will be able to apply personalized medicine in future studies based on rational and specific intervention. This will increase quality of life and outcomes for bone marrow transplant recipients,” said Paczesny.

Funding: 1R01CA264921-01A1

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