Division of Precision Medicine Research | NYU Langone Health

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Division of Precision Medicine Division of Precision Medicine Research

Division of Precision Medicine Research

Researchers in the Division of Precision Medicine are conducting work around a broad range of research interests. Our investigative efforts on the following areas:

  • angiogenesis and atherosclerosis
  • novel molecular targets for the treatment of cancer
  • computational immunology research
  • cardiovascular multiomics research
  • risk prediction in clinical medicine
  • pharmacoepidemiology and drug safety and effectiveness

Machine Learning

The Tsirigos Lab, headed by Aristotelis Tsirigos, PhD, focuses on integrating multiple data modalities, from genomics to imaging, in order to build computational tools that can be used in clinical practice. In our most recent study, we showed that deep learning models trained on whole-slide images can accurately diagnose lung cancer types with an accuracy slightly better than a single pathologist.

We trained a deep convolutional neural network on whole-slide images obtained from The Cancer Genome Atlas, a landmark National Cancer Institute cancer genomics program, to accurately and automatically classify them into lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues, and biopsies (Coudray et al., 2018, Nat Med). These findings suggest that deep learning models can assist pathologists in the detection of cancer subtype and genotype (Kim et al., 2021, J Invest Dermatol) and predict clinical outcomes (Johannet et al., 2021, Clin Cancer Res).

In related work, we have used machine learning approaches (neural networks, random forests, elastic nets, and association rule mining) to predict response to therapy in cancer and identify biomarkers of sensitivity and resistance to drug treatment (Sakellaropoulos et al., 2019, Cell Rep).

Chromatin Organization and Epigenetics

The Tsirigos Lab investigates the role of chromatin organization in cancer. Our most recent study revealed extensive remodeling of the 3D chromatin architecture landscape in patients with acute leukemia and demonstrated that small-molecule inhibitors targeting either oncogenic signal transduction or epigenetic regulation can modulate leukemia-specific 3D chromatin interactions (Kloetgen et al., 2020, Nat Gen). We have shown that strong topologically associating domain (TAD) boundaries are found near super-enhancers and are frequently tandemly duplicated in cancer patients (Gong et al., 2018, Nat Commun). We have studied the importance of highly connected promoters and enhancers via 3D looping (promoter and enhancer hubs) during reprogramming (Campigli Di Giammartino et al., 2019, Nat Cell Bio) and differentiation (Zhang et al. 2020. Nat Commun).

In earlier work, we identified LUNAR1, a leukemia-specific lncRNA that regulates IGF1R in the context of a TAD (Trimarchi et al., 2014, Cell). We developed HiC-bench, a computational platform that enables comprehensive multitool multiparameter analyses of Hi-C/HiChIP data and integration with other genomics data (Lazaris et al., 2017, BMC Genomics). We also study alterations of histone modifications in leukemia that lead to the disruption of the normal epigenetic state. We first elucidated the role of the PRC2 complex as a tumor suppressor in acute T cell leukemia (Ntziachristos et al., 2012, Nat Med).

In a follow-up study, we delineated the role of the H3K27 demethylases JMJD3 and UTX in T-ALL. We showed that JMJD3 is essential for the initiation and maintenance of T-ALL, as it controls important oncogenic gene targets. By contrast, we found that UTX acts as a tumor suppressor and is frequently genetically inactivated in T-ALL (Ntziachristos et al., 2014, Nature).

Clinical Risk Prediction

Morgan E. Grams, MD, and her team focus on simplifying multidimensional data into actionable clinical indicators. She serves as a co-principal investigator of the Chronic Kidney Disease Prognosis Consortium (CKD-PC), a 200+ investigator global consortium with more than 20 million participants. In this setting, she and her team focus on developing, testing, and implementing analytic strategies to answer clinically meaningful questions.

The CKD-PC has developed and tested several risk tools for use in kidney donor candidates (Grams et al., 2016, N Engl J Med), patients with moderate and advanced chronic kidney disease (Tangri et al., 2016, JAMA; Grams et al., 2018, Kidney Int), patients with and without diabetes (Nelson et al., 2019, JAMA), as well as tools for converting laboratory measures of albuminuria (Sumida et al., 2020, Ann Intern Med). Dr. Grams has successfully implemented many of these risk tools into the electronic medical record for use in clinical care. The CKD-PC has also provided evidence for clinical guidelines and the adoption of surrogate endpoints by the U.S. Food and Drug Administration (FDA).


Dr. Grams also leads an ancillary consortium of electronic health record (EHR) cohorts to investigate care gaps and the safety and effectiveness of medications in real-world clinical practice. Her team has identified an association between proton pump inhibitors and the development of kidney disease (Lazarus et al., 2016, JAMA Int Med), provided evidence of metformin safety in moderate kidney disease (Lazarus et al., 2018, JAMA Int Med), and demonstrated the importance of continuing angiotensin converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) in advanced kidney disease (Qiao et al., 2020, JAMA Int Med), an area of clinical uncertainty.

Other areas of interest include agents to treat diabetes, direct oral anticoagulants, and antihypertensive agents and development of electrolyte disorders.

Integrative Omics

Dr. Grams and her team work to integrate multiple omics fields of the biological sciences to advance understanding of disease and health. Using data from multiple sources, including the African American Study of Kidney Disease and Hypertension, the Atherosclerosis Risk in Communities Study, and the Chronic Renal Insufficiency Cohort, the researchers study metabolomic and proteomic precursors of chronic disease, focusing on kidney disease (Grams et al., 2021, J Am Soc Neph; Luo et al., 2021, Clin J Am Soc Nephrol). They also evaluate polygenic risk scores for disease (Yu et al., 2021, J Am Soc Nephrol) as well as genetic determinants of metabolites and proteins (Rhee et al., 2022, Kidney Int; Luo et al., 2021, Kidney Int).


The Cronstein Laboratory, headed by Bruce N. Cronstein, MD, is focused on adenosine, a chemical that most cells and tissues release in response to stressors, such as hypoxia and inflammatory injury. In ongoing studies, the Cronstein Laboratory has demonstrated that adenosine, acting at its A2A receptors, is essential in maintaining chondrocyte homeostasis.

The researchers found that A2AR-deficient mice develop premature osteoarthritis. They also found that ecto-5'-nucleotidase deficiency in mice and humans leads to the development of osteoarthritis. Based on these findings, the researchers developed an intra-articular injection of liposomal preparations of adenosine and A2AR agonists, as well as a nanoparticle-bound adenosine. These novel agents are currently undergoing preclinical testing in preparation for therapeutic trials in osteoarthritis.

Bone Regeneration

The Cronstein Laboratory recently demonstrated that extracellular adenosine, acting at A2A and A2B receptors, promotes regeneration of bone and that the application of an agent, dipyridamole—which increases extracellular adenosine to three-dimensional printed scaffolds—dramatically improves bone regeneration at sites of critical bone defects. This approach is also useful for the repair of craniofacial abnormalities such as cleft palate.

Cancer Proteogenomics

As part of the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC), Kelly V. Ruggles, PhD, and her team are applying computational and statistical methods to model biological systems and measuring the effect these have on human health. Dr. Ruggles is analyzing the proteomics, genomics, and transcriptomics of tumors to gain deeper insights about the static and dynamic status of cancer.

Dr. Kelly V. Ruggles and Team
Kelly V. Ruggles, PhD, and her team work on cancer proteogenomics research at NYU Langone.

Computational Immunology

Dr. Ruggles’s laboratory is conducting research into human and mouse immunology in collaboration with the Division of Infectious Diseases and Immunology and the Department of Microbiology. The team is working on several projects using multiomic immunological profiling to gain a deeper understanding of immune activation and heterogeneity.

Cardiovascular Multiomics

Dr. Ruggles’s laboratory is part of the International Study of Comparative Health Effectiveness with Medical and Invasive Approaches (ISCHEMIA) trial, supported by a grant from the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH). As part of that collaboration, Dr. Ruggles and her team are developing novel methods that enable them to analyze multiomic data to characterize ischemic heart disease. The team’s goal is to understand the clinical manifestations of ischemic heart disease as well as the causes that drive its development.

Grants and Funding

The team’s research is largely funded by grants from the NIH, as well as private foundations and the pharmaceutical industry.