Princeton works with partners to support the latest cancer research and accelerate the progress of life-science innovation toward real-world impact.

Princeton's contributions to cancer research stem from the distinction of the University's faculty in genomics, molecular biology, chemistry and computational biology. Below are a few highlights that represent the expanding scope of Princeton work related to cancer.

For more information on cancer research at Princeton, we encourage you to search Research With Princeton, a comprehensive and up-to-date database of research publications and projects, faculty profiles, Princeton research units, and scientific facilities available for use by external partners. 

Ludwig Princeton Branch focuses on cancer metabolism

In April 2021, Princeton became the home of a new branch of the Ludwig Institute for Cancer Research, an international community of distinguished scientists dedicated to preventing and controlling cancer. The Ludwig Princeton Branch is the first branch of Ludwig to focus primarily on cancer metabolism.

At the time the new branch was launched, University Provost Deborah A. Prentice said, “Ludwig chose Princeton because of our renowned strength in disciplines of critical importance to the study of cancer metabolism, including basic cancer research, metabolomics, genomics, biology, and the computational and physical sciences. This new partnership goes to the heart of what Princeton is all about. It draws on Princeton’s breadth of excellence in fundamental science to drive real-world breakthroughs at the cutting edge of cancer care.”

The Ludwig Princeton Branch is led by director Joshua Rabinowitz, a professor of chemistry and the Lewis-Sigler Institute for Integrative Genomics at Princeton. According to Rabinowitz, the Ludwig branch offers the opportunity "to capitalize on multiple areas where Princeton is a world leader and has world-leading technologies that hadn’t yet been applied to cancer. We want to continue to push the frontiers of those technologies, because ultimately technologies drive biological understanding, which opens up new avenues for cancer treatment and prevention.”

Yibin Kang, Princeton’s Warner-Lambert/Parke-Davis Professor of Molecular Biology, is a principal investigator and founding member of the branch. Eileen White, a distinguished professor of molecular biology and biochemistry at nearby Rutgers University and longtime collaborator with Princeton cancer researchers, is associate director. Clinical translation is conducted in partnership with RWJ Barnabas Health, Rutgers Cancer Institute of New Jersey and institutions throughout the region. 

A Princeton spinout tackles metastatic breast cancer

Professor Yibin Kang teamed with Mark Esposito, former Princeton postdoctoral research associate, to co-found Kayothera, a startup company developing therapies to treat late-stage and metastatic cancers that are fairly resistant to current chemotherapy and pharmaceutical treatments. The Princeton spinout uses discoveries found in Kang’s research lab at Princeton as a basis for new treatments that overcome the defenses of cancer cells. Kang and Esposito have also made contributions towards our understanding of the spread of cancer to bone and the protein that drives cancer’s aggressive spread, and have discovered a previously unknown cell organelle.

Computational biology: Princeton computer scientists use algorithms, data and machine learning to understand cancer

Princeton's strengths in the computational and life sciences come together to understand and advance human health in many ways, including in cancer research. Among the faculty applying computer science tools to understand cancer are Ben Raphael and Mona Singh.

Ben Raphael, a professor of computer science, takes an interdisciplinary and collaborative approach to cancer research using computing algorithms. In 2020, Raphael collaborated with an international team of researchers to seek a new understanding of cancer’s genetic origins, applying seven different pathway and network analysis methods to noncoding regions of whole genome sequences from more than 2,500 cancer patients.

Raphael's study contributed to our understanding of why two cancer patients with the same type of cancer can have different reactions to the same cancer treatment, due to each patient’s unique genome. Previously, Raphael and another team presented MACHINA, an algorithm that can track cancer metastasis by integrating DNA sequence data with information on where cells are located in the body.

Mona Singh, a professor of computer science and the Lewis-Sigler Institute for Integrative Genomics, focuses on interpreting genomes at the level of proteins and developing data-driven methods for predicting and characterizing protein interactions, specificity and networks — in both healthy and disease contexts. Singh combines biological knowledge with computational and machine learning techniques to uncover cancer-driver genes, genes with specific mutations in cancer genomes that are relevant for disease initiation or progression.

For more information on specific research topics, we encourage you to search Research With Princeton, a comprehensive and up-to-date database of research publications and projects, faculty profiles, research units and scientific facilities available for sharing with external partners. 

Events (Recordings of past events may be available)