We translate novel therapies to benefit patients by rapidly bringing patients new therapies derived from data driven predictions and validated by advanced genomic technology… faster than has ever been possible.

Multiple Myeloma Therapy

Workflow for precision medicine of multiple myeloma

Multiple Myeloma (MM) is a genetically complex and heterogeneous malignancy of plasma cells affecting more than 30,000 patients each year in the United States, making it the second most common hematologic malignancy. The causal drivers of MM pathogenesis are still unclear, and treatment is administered empirically on the basis of recurrence risk rather than genetic events.

Typically, the trajectory of MM is characterized by a pattern of recurrent remissions and relapses, with patients becoming increasingly refractory to treatment. As patients progress through advanced disease and receive multiple lines of therapy, they are left with fewer and fewer treatment options.

Our research addresses the major challenge of devising optimal treatment strategies tailored to the characteristics of the individual patient’s disease and aims to transform the current paradigm of empirical clinical application. Our approach to personalized therapy of MM is based on the integration of novel sequencing technologies with advanced computational modeling and drug databases to guide drug selection. Therapy is designed by using a comprehensive patient profile generated based on DNA/RNA sequencing and clinical data to identify and prioritize clinically actionable alterations. The analysis of intra-tumor heterogeneity and of the tumor microenvironment by single-cell technologies and mass cytometry further broadens the scope of treatment by enabling combinatorial therapy and targeted immunotherapy.

The results of our pilot clinical trial with relapsed/refractory MM patients have demonstrated the feasibility and early efficacy of our pipeline, highlighting the clear benefits of incorporating RNA sequencing for drug selection.

Mendelian Disease Therapies

Mendelian Disease therapy development and drug discovery has been an ongoing focus of the Department of Genetics and Genomics Sciences for many years with great success. We have developed novel therapeutics and repurposed methods for drug discovery to treat a variety of single-gene genetic diseases.

Some examples include the development of Fabrazyme®, an enzyme replacement therapy (ERT) for Fabry disease, from preclinical (animal) studies through successful Phase 4 clinical trials in patients, and developing and performing the preclinical studies and ongoing clinical studies for an ERT for Niemann-Pick type B disease. To develop and evaluate enzyme replacement therapy for Fabry and Neimann-Pick B disease, knock-out mice were generated, and high-level expression of the respective recombinant enzyme was accomplished.  We have also pioneered other therapeutic approaches for genetic disorders including pharmacological chaperone therapy for Fabry disease and preclinical AAV-medicated gene therapy and RNA interference therapy studies, both for Acute Intermittent Porphyria.

Featured Scientist: Robert Desnick

Drug Discovery for Rare Mendelian Diseases

Virtual Drug Repurposing

Analysis of big data identifies that patients with inflammatory bowel disease who were exposed to anti-TNFα therapy at various doses (shades of yellow) were less likely to develop Parkinson’s disease (maroon) compared to those patients who were not exposed to anti-TNFα therapy.

The Icahn Institute is leading efforts in the newly emerging field of virtual clinical drug repurposing trials, which are cost-efficient and powerful for generating novel hypotheses based on patient data, instead of costly and lengthy animal studies, for an initial preclinical evaluation. Specifically, this approach allows for the results of high-throughput drug screening, either experimental or in silico to be validated using analysis of big data in large population-based cohorts. For example, Icahn Institute researchers queried existing longitudinal data of more than 170 million people in administrative claims databases. Following on the strong genetic and epidemiological links that they established between the Crohn’s disease, a type of inflammatory bowel disease (IBD), and Parkinson’s disease, they assessed whether administration of anti-tumor necrosis factor alpha therapy (anti-TNFα), an effective therapy for IBD, would affect the future risk of Parkinson’s disease. Indeed, compared to IBD patients without anti-TNFα therapy, IBD patients exposed to anti-TNFα therapy exhibited a substantial reduction in their risk of developing Parkinson’s disease. These results generated a strong interest to consider anti-TNFα therapies for the prevention and treatment of Parkinson’s disease. Drugs showing initial promise in “virtual trials” can then be evaluated in preclinical R&D and, potentially, may inform future clinical trials.

Population Genomic Health

Worldwide frequency of the Steel Syndrome variant (Belbin et al., eLife, 2017)

We are in the midst of a genomic revolution in medicine. By studying our complete genetic code and understanding how it relates to health and disease, we will be better able to target diagnoses and therapies, and even predict and prevent disease. Today, genomics is helping us find the cause of rare diseases, understand the development of cancer, and even track infections in hospitals. As genomics moves into the mainstream, professionals across health systems need to be ready.

The Center for Population Genomic Health is a new initiative to accelerate the integration of genomics into clinical care throughout the Mount Sinai Health System, changing the way we practice medicine. The mission is to bring advancements in data science and genomic discovery into frontline clinical care and pioneer the integration of genomics into medical training and practice. This will include the patient-centered practice of genomic medicine in primary care, genomic medicine outreach across the health system, and leveraging data science and technology advances to translate the latest science for clinical care.

Personalized Cancer Vaccines

The contents of a personalized cancer vaccine are selected by identifying cancer-specific mutations and predicting whether they could be effectively targeted by the patient’s immune system. The selected mutated peptides are then synthesized, combined with an immunostimulatory adjuvant, and injected into the patient.

Personalized cancer vaccines are designed to elicit an immune response targeting the specific mutations found in an individual’s tumor. Researchers at the Icahn Institute develop and maintain a collection of open source tools for identifying tumor mutations and predicting their potential for immune recognition. Our pipeline is currently being used to select the patient-specific vaccines for three phase I clinical trials (NCT02721043; NCT03223103; NCT03359239). Trials such as these represent an extreme form of personalized medicine, in which the object of investigation is a predictive algorithm, rather than just a compound.

While clinical trials of personalized vaccines have shown some promising early results, there remain many unresolved questions on which mutant antigens to include in a vaccine and what other therapies to combine them with. Our work, therefore, includes research on antigen presentation and the anti-tumor immune response, as well as computational methods development for working with next-generation sequencing data.