New Grant Awardees Push Innovation in Precision Medicine

June 03, 2021

The annual Precision Medicine Pilot Grants have been awarded to five teams of  researchers conducting innovative basic science, translational, and clinical research across multiple diseases. 

Jointly awarded by the Columbia Precision Medicine Initiative (CPMI), the Herbert Irving Comprehensive Cancer Center (HICCC), and the Irving Institute for Clinical and Translational Research (Irving Institute), the Precision Medicine Pilot Grants underscore Columbia’s commitment to supporting diverse, cross-disciplinary research targeting the promise of precision medicine.

The five winning teams are being led by faculty at Columbia’s Vagelos College of Physicians & Surgeons (VP&S), including: Srilaxmi Bearelly, MD, associate  professor of ophthalmology; Brian Henick, MD, assistant professor of medicine; Chi-Min Ho, PhD, assistant professor of microbiology and immunology; Yufeng Shen, PhD, associate professor of systems biology and of biomedical informatics; and Xuebing Wu, PhD, assistant professor of systems biology and of medicine. The projects being funded are focusing on a range of research, from novel cancer therapeutics to health disparities research. 

The Vagelos Precision Medicine Pilot Grant program is made possible by a generous donation from Roy and Diana Vagelos and is intended to support groundbreaking basic research in the field of precision medicine. Each research team receives $100,000 in funding for one year. The researchers will present their projects at an annual symposium for the precision medicine awards in fall 2022.

Award-winning teams: 


Retinal Imaging and Deep Learning to Identify Maternal Risk & Reduce Racial Disparities

Lead Investigator: Srilaxmi Bearelly, MD
Co-Investigators: Ronald Wapner, MD and Andrew Laine, DSc 

Pictures of the back of the eye help us to understand blood vessel changes in disease and health. One of the primary aims of this study is to understand if there are changes in blood vessels in the retina prior to the development of preeclampsia. Preeclampsia is a serious disease of pregnancy that can lead to morbidity and mortality and is more common among racial and ethnic minorities. There is an enormous unmet need to detect preeclampsia at early pre-clinical stages to prevent mortality. The retinal imaging (photo of the back of the eye), is a technique that is non-invasive, requires no dilation, and involves minimal risk to patients. It will be performed on 1,500 pregnant subjects. The goal is to tailor prenatal medical care (prevention, diagnosis, and ultimately treatment of this disease) to the individual patient.


Patient-Derived Organoids to Model and Manipulate Tumor Regulatory Dependencies in Esophageal Adenocarcinoma

Lead Investigator: Brian Henick, MD
Co-Investigators: Andrea Califano, Dr; Chao Lu, PhD; Hiroshi Nakagawa, MD

Patients with advanced/metastatic esophageal adenocarcinoma (EAC) suffer poor outcomes despite new drug approvals, perhaps because EAC actually represents multiple cancer subtypes not easily distinguishable with conventional techniques. Studying tumor RNA, the Califano laboratory has developed algorithms that can delineate EAC subtypes based on the differential activity of Master Regulator (MR) proteins that mechanistically govern tumor cells’ transcriptional states, amenable to confirmation in model systems. Manipulating MRs genetically or with drugs identified by the CLIA-certified OncoTreat algorithm can help repurpose existing drugs  for use in EAC subtypes on a case-by-case basis. Testing drug efficacy in tumor models by this approach could identify promising new therapies for multiple EAC subtypes simultaneously. Patient-derived organoids (PDOs) are an efficient model system that can recapitulate tumor biology and likelihood of treatment response. The team plans to confirm that human EAC share MRs with their derived PDOs in the Nakagawa laboratory. In the Lu laboratory, they will experimentally knock out MRs predicted to be most essential in each PDO, and finally test a library of drugs to identify those most likely to benefit each EAC subtype.


Direct Visualization of Malaria Parasite Invasion Using Cryoelectron Tomography

Lead Investigator: Chi-Min Ho, PhD
Co-Investigator: David Cobb, PhD

Half the world’s population lives at risk of contracting malaria, which results in more than 400,000 deaths per year. Malaria is caused by malaria parasites that make us sick by invading and replicating inside our red blood cells. In order to enter human red blood cells, the malaria parasite, Plasmodium falciparum, assembles large protein complexes that bind to protein receptors displayed on the surface of the host red blood cell. These large invasion complexes are essential for the parasite to be able to attach to and enter the red blood cell.  The components of these invasion complexes are attractive targets for the development of new anti-malarial therapies and vaccines. Unfortunately, the complexes are short-lived, making them difficult to isolate for structural and functional studies. Drs. Ho and Cobb aim to overcome this obstacle by leveraging recent advances in in situ cryoelectron tomography to directly visualize the full invasion machinery in frozen samples of malaria parasites captured in the act of invading human red blood cells. 


Develop New Computational Methods to Predict Functional Impact of Missense Variants Based on Protein Structure Using Machine Learning

Lead Investigator: Yufeng Shen, PhD 
Co-Investigator: Mohammed AlQuraishi, PhD

Accurate and scalable interpretation of genomic variation is a critical component to realize the full potential of high-throughput sequencing in human genetics and genomic medicine. Missense variants account for most of protein-coding variants with potentially large functional impact; however, most of them do not contribute to disease. The inability to accurately predict their functional impact is a critical hurdle to identifying risk genes in genetic research studies. This project aims to develop new computational methods to predict functional impact of missense variants by leveraging the latest machine learning methods, protein structure, and large genome sequence data of diverse populations. The proposed methods will improve the utility of genome sequencing and enable new discoveries in genetic studies and clinical diagnosis. 


A Special Ribosome in the Heart: Understanding how Mutations in Ribosomal Protein RPL3L Cause Neonatal Dilated Cardiomyopathy by Using Patient-derived iPSCs and Genetically Engineered Mice

Lead Investigator: Xuebing Wu, PhD
Co-Investigators: Steven Marx, MD; Teresa Lee, MD; Mythily Ganapathi, PhD

Mutations in genes can cause severe heart failure in infants. We do not yet fully understand which genes will cause infantile heart failure and what drives it. The research team recently discovered such mutations in RPL3L gene, which encodes a component of the ribosome, the machinery responsible for decoding genetic information and make proteins in every cell. Although initially we thought every human cell has the same ribosome, it turns out in heart and skeletal muscle cells, ribosomes are different from all other human cells as they replace another protein with RPL3L. This project will study the molecular and cellular mechanisms of the special ribosome by using patient-derived stem cells and genetically engineered mouse models. The project’s aim is to help elucidate why heart and muscle cells require a special ribosome, and understand how the mutation causes infantile heart failure.