Identifying and targeting evolutionary trajectories in cancer

NIH RePORTER · NIH · R01 · $340,788 · view on reporter.nih.gov ↗

Abstract

Project Summary/Abstract Tumor evolution represents the fundamental obstacle to providing durable cures for cancer patients. This problem has become increasingly apparent with the recent and clinical use of targeted therapeutics. While small molecule inhibitors of cancer-promoting oncogenes have led to unprecedented tumor regression in some leukemias, melanomas and non-small cell lung cancers, these tumors inevitably relapse as chemorefractory (to the initial therapeutic) malignancies within a year or two of initial treatment. In some cases, therapies exist to target drug resistant disease. Yet, diverse mechanisms or “evolutionary trajectories” can lead to distinct forms of resistance to front-line therapies, and each of these mechanisms may require a distinct second generation therapy. This represents the current reality of targeted therapeutics, in which we treat relapsed tumors with agents that target the drug resistant state, creating an unwinnable resistance arms race. Thus, modern therapies have generally failed to yield prolongued cancer remission or disease management. In fact, only BCR-ABL inhibitors in Chronic Myelogenous Leukemia have consistently achieved long-term cancer remissions. We recently discovered a phenomenon of “temporal collateral sensitivity” in leukemia, whereby distinct intermediate stages in the evolution of resistance to targeted therapeutics present vulnerabilities for exploitation using small molecules from orthogonal drug classes. The existence of these evolutionary vulnerabilities provides us with a means of blocking potential routes to resistance and eradicating residual disease following front-line therapy. We believe this phenomenon is relevant to many other cancer types. Here, we propose to characterize the mechanism of temporal collateral sensitivity in BCR-ABL+ leukemia and ALK-driven lung cancer. We also plan to examine how temporal collateral sensitivity can be exploited in preclinical settings to target evolutionary trajectories towards drug resistance. We believe that this work will not only identify strategies for preempt drug resistance, but also reveal ways to combine these strategies to promote durable therapeutic responses.

Key facts

NIH application ID
9995439
Project number
5R01CA233477-02
Recipient
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Principal Investigator
Michael Hemann
Activity code
R01
Funding institute
NIH
Fiscal year
2020
Award amount
$340,788
Award type
5
Project period
2019-08-14 → 2024-07-31