The second class of Damon Runyon Quantitative Biology Fellows, announced this month, will apply the tools of computational biology to generate and interpret cancer research data at extraordinary scale and resolution. From RNA sequencing data that pinpoints tumor cells to their exact location to three-dimensional models of cell-cell interaction, their projects extend the boundaries of what is possible in cancer research, allowing them to tackle fundamental biological and clinical questions.

Each postdoctoral scientist selected for this unique three-year award will receive independent funding ($240,000 total) to train under the joint mentorship of an established computational scientist and a cancer biologist. The grant was created to encourage quantitative scientists (from fields such as mathematics, physics, computer science, and engineering) to pursue careers in cancer research. By investing in the intersection of “wet” and “dry” lab, Damon Runyon aims to address the need for these specially trained scientists in the quest for new cancer treatments and cures. The awardees were selected by a distinguished committee of experts in the field.

“We’re entering a golden era for cancer research because of the explosion of insights we're having into cancer biology, genetics, and mechanisms. I think everyone would agree that a huge component of the big breakthroughs are going to come at this intersection of cancer biology, medicine, and computational science. If you believe that the role of computational science is going to be integral to the future of cancer discoveries, then we need to worry about whether we have enough leaders in this field. We should be investing in a new generation of leaders, and that’s the intent of this award,” said Todd R. Golub, MD, Damon Runyon Board Member and Chair of Damon Runyon Quantitative Biology Fellowship Award Selection Committee. In this year’s cohort of Fellows, they have found a team of emerging leaders who will join last year’s inaugural class in leading the development of this new field.

2021 Quantitative Biology Fellows

Tin Yi Chu, PhD, with mentors Dana Pe’er, PhD, and Elaine V. Fuchs, PhD, at Memorial Sloan Kettering Cancer Center, New York

Cancer cells form complex interactions with the various normal cells in their environment, including immune cells, fibroblasts, and blood vessels. These interactions are essential for cancer cells to grow, evade immune surveillance, and become metastatic or resistant to certain therapies. Spatial transcriptomics refers to a method of visualizing the distribution of RNA molecules in a tissue sample, allowing us to assign specific cell types to their locations. Dr. Chu aims to develop a statistical framework to infer how different cell types interact with each other based on spatial transcriptomics data. He will use this statistical framework to study cell-cell interactions in both colorectal cancer and inflammatory bowel disease, a risk factor for colorectal cancer.

Haripriya Vaidehi Narayanan, PhD, with mentors Alexander Hoffmann, PhD, and Roy Wollman, PhD, at University of California, Los Angeles

Immune B cells defend the human body from infections by quickly dividing to increase their numbers and mutating their immune receptors to adapt to new pathogens. However, such frequent division and mutation creates a high risk of blood cancers, like lymphomas and myelomas. Every B cell makes an important decision about its fate – to die, to divide a certain number of times, or to differentiate into an antibody-producing cell – based on the affinity of its receptor to an oncoming pathogen. Currently, it is not understood how the B cells’ receptor affinities influence their internal gene networks to determine their fates. By combining microscopy, genomics, and computational models, Dr. Narayanan aims to discover the precise mechanisms underlying the B cell immune response, so that we can predict, prevent, or alleviate B cell-related cancers without compromising immunity.

Esther Wershof, PhD, with mentors Dana Pe’er, PhD, and Anna-Katerina Hadjantonakis, PhD, at Memorial Sloan Kettering Cancer Center, New York

The formation of complex organs such as the lungs is a largely elusive process in human development, though the fact that these complex structures are successfully reproduced over and over again suggests a strong underlying set of biological rules. Further, it has been shown that tumors and metastases can be viewed as aberrant organs, employing many of the same programs as in normal development. Understanding these rules and how they can be hijacked are long-standing critical questions in cancer research. While fascinating discoveries have helped decipher some of these rules, cell differentiation is chiefly governed by the cell’s three-dimensional (3D) environment. Dr. Wershof is using 3D biological data to study the architecture of different cells and genes interacting with each other in 3D space. The goal is to derive the spatial rules that drive lung formation, which will be key to our understanding of lung tumorigenesis.