Prediction of cancer recurrence based on spatial analysis opens a new chapter in personalized treatm

Mondo Technology Updated on 2024-01-31

In today's advanced medical technology, a study completed by Cedar-Sinai cancer researchers may be a new way to determine whether immune system cancer patients who have undergone bone marrow transplants will be able to. The study, published in the Journal of Clinical Oncology, uses a new technique called spatial analysis that may provide a more precise direction for future targeting**.

Akil Merchan, M.D., co-director of the Cedars-Sinai Lymphoma Program, said, "Our approach responds more accurately to Hodgkin lymphoma patients than the state-of-the-art approach currently available. This study is the first to demonstrate the promise of this advanced technology in a clinical setting – meaning that this discovery has the potential to be applied in a variety of cancer types. ”

Hodgkin lymphoma is a type of cancer that affects the lymphatic system, which includes the bone marrow, lymph nodes, and mucous membranes, organs and tissues that help protect the body from infection.

*Hodgkin lymphoma typically involves a bone marrow transplant using the patient's own healthy blood stem cells, which helps the bone marrow recover and produce new immune cells to fight cancer cells.

The new test developed by Cedars-Sinai is able to identify a group of patients who may remain disease-free after stem cell transplantation, and for these post-transplant patients, the goal is to end the follow-up and save them from the potentially life-threatening extra**. The results of the study can also help design clinical trials to determine ways to help patients who have not undergone transplantation.

In the study, the researchers analyzed biopsies from 169 patients with Hodgkin lymphoma. They compared the cells and tissues surrounding the tumors of patients with bone marrow transplants** to those surrounding the tumors of patients with post-transplant cancer**.

By looking at the distance between cancer cells and other cell types, they were able to ** the cancer's response to transplantation using the patient's own stem cells.

The study leverages massive datasets combined with machine learning to focus on two or three key data points that can be used for clinical testing, which patients are broadly available for post-transplant risk, and allows clinicians to adjust protocols accordingly.

The study's co-first author, Dr. Alexander Xu, a research scientist at Cedars-Sinai Cancer, emphasized the value of this quantitative tool. Diagnosis and ** usually involve judgment. Because research is quantitative, it is important to maintain consistency of patient-to-patient and clinic-to-clinic results.

Researchers are exploring the creation of such a test. They are also working on projects to identify similar** tests for other types of cancer.

This work opens up new avenues for the development of space biomarkers that can guide cancer patients in a precise, targeted way, and translating this cutting-edge research into clinically deployable tests will help bring hope for precision medicine to a growing number of patients, ultimately benefiting patients with multiple cancer types.

Reference: 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.

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