Chronic inflammatory and autoimmune disorders are a significant source of global morbidity and are propagated by abnormal activity of lymphoid cells. Additionally, lymphomas are a group of cancers that target the lymphatic system, which comprises, in part, the body’s immune system and plays an important role in responding to infections and diseases that may arise. The lymphatic system is principally comprised of the bone marrow, spleen, thymus and lymph nodes, as well as lymphatic vessels, which carry lymph and white blood cells throughout the body. The American Cancer Society estimates that there will be ~90,000 cases of lymphoma in 2024 and resulting in more than 20,000 deaths. According to the World Health Organization, there were more than 630,000 cases of non-Hodgkin and Hodgkin lymphoma, the two main types of lymphoma, resulting in more 273,000 deaths worldwide in 2022. Lymphomas, and specifically non-Hodgkin lymphoma, consistently ranks among the 10 most diagnosed cancers and among the 15 cancers with the highest mortality rates.
Our study aims to utilize large dataset, such as the UK Biobank, to understand how clinical history, genetics, demographics and socioeconomics affect the risk of patients being diagnosed lymphoma and how patients will respond to treatment. In the course of this project, we will develop new computational methods using the UK biobank dataset, which will be further validated in internal datasets to identify patents at risk of developing lymphomas as utilize a data driven approach to understand different disease subtypes and how patients respond to treatment.
Rare cancers pose a difficulty in utilizing data driven approaches due to their low incidence rates. We will utilize the UK Biobank dataset in concert with the clinical data at MSKCC to interrogate how patients with rare cancers respond to treatments and aim to identify any genetic or clinical indictors that are associated with a more beneficial outcome in the treatment of rare cancers.