# Uncovering Principles of Adaptive Regulation in Cancer Resistance Through Deep Evolutionary Profiling

> **NIH NIH K99** · DANA-FARBER CANCER INST · 2020 · $170,640

## Abstract

Project Summary: This proposal outlines a five-year research and career development
program aimed at building a data-driven, quantitative framework for the evolution of
cancer resistance. The basis for this application draws heavily on the candidate’s prior
MD/PhD training in cancer biology and evolutionary genomics through the combined
Harvard-MIT Health Sciences Technology program, and leverages his current
appointments as both a senior medical oncology fellow in the combined Dana
Farber/Massachusetts General Hospital CancerCare Program as well as a post-doctoral
research fellow at the Broad Institute under Drs. Gad Getz and Eric Lander. The joint
experimental and computational aims proposed here represent a fundamentally new
research agenda that draws on core expertise from each of the candidate’s supervising
laboratories. Along with a series of relevant didactics and career building activities,
these studies will form the basis of his transition to an independent tenure track position
as a physician-scientist guided by the goal of enabling long-term cancer control.
Abstract: The proliferation of targeted therapies and immunotherapies over the last
decade has heralded an unprecedented era in cancer treatment. However, durable
disease control is still the exception in advanced cancers, due in large part to the
emergence of resistance. The objective of this work is to use a combination of
experimental and computational approaches to shed light on the underlying evolutionary
rules governing cancer resistance. This is guided by the central hypothesis that the
evolution of resistance is in large part predictable from features of the pre-treatment
genome and therapy. In particular, three Specific Aims will be evaluated: (1) To assess
for trends in the diversity of resistance across 10 cancer cell line models, (2) To assess
the role of mutational diversity in promoting resistance, and (3) To assess the role of
therapy in defining the resistance bottleneck. Taken together, this work will advance the
field by establishing both a mathematical and experimental foundation for understanding
cancer resistance. At the same time, it will furnish an array of novel genetic and
epigenetic targets for future basic and applied studies. Given that some modes of
resistance may be shared across treatment modalities – and in particular between
targeted therapy and immunotherapy – this work is anticipated to have broad relevance.

## Key facts

- **NIH application ID:** 9880937
- **Project number:** 1K99CA245897-01
- **Recipient organization:** DANA-FARBER CANCER INST
- **Principal Investigator:** Arvind Ravi
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $170,640
- **Award type:** 1
- **Project period:** 2020-07-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9880937

## Citation

> US National Institutes of Health, RePORTER application 9880937, Uncovering Principles of Adaptive Regulation in Cancer Resistance Through Deep Evolutionary Profiling (1K99CA245897-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9880937. Licensed CC0.

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