Cedars-Sinai Cancer researchers have discovered a new way to predict if a patient’s cancer of the immune system will reoccur after being treated with a bone marrow transplant. Their study, published in the peer-reviewed Journal of Clinical Oncology, is the first to use a novel technique called spatial profiling to predict patient outcomes and could lead to more precise, targeted treatment.
„Our method of predicting how patients with Hodgkin lymphoma will respond to treatment was more accurate than the currently most advanced method. Our work is also one of the first to show that this cutting-edge technique can be adapted for a clinical setting – a finding that may potentially be utilized for all cancer types.“
Akil Merchant, MD, Co-Director of the Lymphoma Program at Cedars-Sinai and Co-Senior Author of the study
Hodgkin lymphoma is a cancer that affects the lymph system, a network of organs and tissues – including bone marrow, lymph nodes, and mucous membranes – that protects the body from infections.
To treat Hodgkin lymphoma, doctors usually perform a stem cell transplantation using healthy blood stem cells from the patient’s own body to support bone marrow recovery and create new immune cells that can fight the cancer cells.
„Our new test, developed at Cedars-Sinai, allows us to identify a group of patients likely to remain disease-free after this stem cell transplantation,“ said Merchant. „For these post-transplant patients, the goal is to discontinue follow-up treatments and spare them additional therapy with potentially life-threatening side effects. Our findings could also help us design clinical trials to identify therapies to help patients who were not cured by their transplantation.“
In this study, conducted in collaboration with Christian Steidl, MD, PhD, of British Columbia Cancer, the researchers analyzed biopsies from 169 patients with Hodgkin lymphoma. They compared the cells and tissues immediately surrounding the tumors of patients who were cured by a bone marrow transplant with those of patients whose cancer recurred after the transplant.
By examining the distance between the cancer cells and other cell types, they were able to predict how the cancer would respond to a patient’s stem-cell transplantation.
„Our study utilized large data sets in combination with machine learning, allowing us to focus on two or three key data points that could be used in a clinical test,“ said Merchant. „The test could be widely deployed to predict which patients are at high risk of relapse after a transplantation and enable physicians to adjust their therapy accordingly.“
Alexander Xu, PhD, Research Scientist at Cedars-Sinai Cancer and Co-First Author of the study, emphasized the value of such a quantitative tool. „Diagnosis and prediction often require judgment. Since our study is quantitative, it will be important to maintain consistent results from patient to patient and from clinic to clinic,“ Xu said.
The investigators are exploring the development of such a test. They are also pursuing projects to develop similar predictive tests for other types of cancer.
„This work opens new avenues for the development of spatial biomarkers that can precisely and targetedly guide cancer patient treatment,“ said Dan Theodorescu, MD, PhD, Director of Cedars-Sinai Cancer and the PHASE ONE Distinguished Chair. „Translating this cutting-edge research into a test that can be used in a clinical setting will help make the promise of precision medicine accessible to an ever-growing number of patients – and ultimately benefit patients with many types of cancer.“
Aoki, T., et al. (2023). Spatially Resolved Tumor Microenvironment Predicts Treatment Outcomes in Relapsed/Refractory Hodgkin Lymphoma. Journal of Clinical Oncology. doi.org/10.1200/jco.23.01115.