The Icahn Genomics Institute is a biomedical and genomics research institute within the Icahn School of Medicine at Mount Sinai in New York City. Its aim is to establish a new generation of medicines that can better treat diseases afflicting the world, including cancer, heart disease and infectious pathogens. To do this, the institute’s doctors and scientists are developing and employing new types of treatments that utilize DNA and RNA based therapies, such as CRISPR, siRNA, RNA vaccines, and CAR T cells, and searching for novel drug targets through the use of functional genomics and data science. The institute is led by Brian Brown, a leading expert in gene therapy, genetic engineering, and molecular immunology.
Goals
The institute’s primary goal is to improve patient care through the use of gene, cell and nucleotide therapies. To achieve this goal, the Institute is formed of a cross-disciplinary mix of clinicians and scientists that include physicians treating patients with novel gene therapies in the Mount Sinai Health System, biologists developing and testing new drugs and drug platforms, and data scientists working to identify causative agents of disease that can be targeted for therapy by building predictive models that better characterize disease. These models are constructed with multiple layers of biological data, including gene expression, metabolite, DNA, and protein information, and are combined with phenotypic and clinical data, predictive modeling, and probabilistic analysis to try to elucidate the complex mechanisms of disease.
Research
Research at the institute falls into six areas:
RNA Therapeutics and Nanomedicines
Gene, CRISPR, and Cell Engineering
Asthma and allergies
Viral and Microbial Therapeutics
Cancer Gene and Cell Therapy
Therapeutic Target Discovery
Notable Academic Publications
Scientists from the institute published a paper in Nature Genetics in 2012 demonstrating the ability to derive enough information from non-DNA sources to identify individuals whose supposedly anonymized biological data is stored in large research databases. The authors reported that measuring RNA levels in tissue allowed them to infer a genetic barcode that could be used to match other materials to that same individual. This was noteworthy as validation of existing concerns among genomics scientists that it may not be possible to prevent the identification of an individual from genetic data even when that data is meant to be anonymous.
In a PLoS Biology paper, institute founding director Eric Schadt led a research team that utilized six different types of data (metabolite concentration, gene expression, DNA variation, DNA-protein binding, protein-metabolite interaction, and protein-protein interaction) to reconstruct networks involved in cell regulation.
In 2013, institute scientists published a paper in the journal Cell reporting findings from a network-based study of late-onset Alzheimer's disease. The researchers constructed gene regulatory networks and discovered a neural structure involved in a pathway associated with onset of the disease.
In January 2014, scientists from the institute’s Division of Psychiatric Genomics including Pamela Sklar published two papers in the journal Nature that explored the genetic complexity of schizophrenia. The exome sequencing studies of populations in Bulgaria and Sweden revealed that the disorder is likely caused by a lot of rare genetic mutations rather than a few common mutations. The projects also established the world’s largest database on schizophrenia.
In May 2014, institute faculty published proof-of-concept findings to support the clinical development of RNA interference therapy for acute hepatic porphyria which led to the development of givosiran as the first therapy for acute hepatic porphyria, approved by the FDA in 2019. Institute researchers and clinicians also led the Phase 3 clinical trials for givosiran.
Institute director, Brian Brown, developed a new CRISPR imaging technology called Perturb-map capable of identifying regulators in tumor microenvironments. The findings were published in Cell in 2022. Perturb-map was used in this study to identify the cytokine interferon gamma, IFNg, and the tumor growth factor beta receptor, TGFbR, as regulators of two pathways significantly affecting tumor growth, architecture, and immune cell recruitment.