Here, we investigate Provocative Question PQD1: How does the selective pressure imposed by the use of different types and doses of targeted therapies modify the evolution of drug resistance? The effectiveness of targeted therapy to prolong survival in cancer patients is limited by the inevitable development of drug resistance. Cancer populations constantly evolve, enabling subpopulations of cells to adapt and ultimately overcome drug treatment. A comprehensive understanding of potential drug-resistance mechanisms and their therapeutic vulnerabilities will form the basis for finding optimal targeted treatment plans of drug-resistant tumors. A common strategy for studying mechanisms of drug resistance is to generate a drug-resistant cancer population under a single selective pressure, and characterize its vulnerabilities using population-averaged assays. However, it is unclear which selective pressures should be varied to encourage the emergence and evolution of uncharacterized drug mechanisms. There are a virtually limitless number of parameters that could be varied, and it is unclear which would be productive to explore. Further, population-averaged assays largely characterize the fittest clones; clinically relevant mechanisms, which may appear at low frequencies in experimental settings, will be missed. As a result, the drug-resistance landscape has not been systematically explored. Here, we propose that drug resistance can be broadly surveyed instead by isolating and studying individual drug-resistant clones derived under a small number of selection conditions. We leverage the natural heterogeneity of cancer, traditionally viewed as an impediment for understanding the disease, to reveal the range of possible resistance mechanisms. Our preliminary studies strongly suggest that this strategy will unmask diverse drug mechanisms. To address PQD1, we assess the diversity of resistance mechanisms present in a cancer population and how this diversity changes in response to different selective pressures.
In Aim 1, we use a shotgun approach for isolating large numbers of resistant clones from cancer populations treated with different targeted therapies.
In Aim 2, we map our clonal populations into resistance classes defined by common therapeutic vulnerabilities.
In Aim 3, we test how our resistant clones evolve under new selective pressures.

Public Health Relevance

The effectiveness of targeted therapy to prolong survival in cancer patients is limited by the development of drug resistance. We propose to leverage the constantly evolving nature and dramatic cell-to-cell differences present in cancer to reveal the range of possible drug-resistance mechanisms. Our approach will allow us to identify targetable vulnerabilities and empower us to suggest rational, next-line therapies.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA185404-03
Application #
9109592
Study Section
Special Emphasis Panel (ZCA1)
Program Officer
Forry, Suzanne L
Project Start
2014-08-01
Project End
2018-07-31
Budget Start
2016-08-01
Budget End
2017-07-31
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118
Thurley, Kevin; Wu, Lani F; Altschuler, Steven J (2018) Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions. Cell Syst 6:355-367.e5
Mender, Ilgen; LaRanger, Ryan; Luitel, Krishna et al. (2018) Telomerase-Mediated Strategy for Overcoming Non-Small Cell Lung Cancer Targeted Therapy and Chemotherapy Resistance. Neoplasia 20:826-837
Rajaram, Satwik; Heinrich, Louise E; Gordan, John D et al. (2017) Sampling strategies to capture single-cell heterogeneity. Nat Methods 14:967-970
Deb, Dhruba; Rajaram, Satwik; Larsen, Jill E et al. (2017) Combination Therapy Targeting BCL6 and Phospho-STAT3 Defeats Intratumor Heterogeneity in a Subset of Non-Small Cell Lung Cancers. Cancer Res 77:3070-3081
Ramirez, Michael; Rajaram, Satwik; Steininger, Robert J et al. (2016) Diverse drug-resistance mechanisms can emerge from drug-tolerant cancer persister cells. Nat Commun 7:10690
Zhang, Elizabeth R; Liu, Shanshan; Wu, Lani F et al. (2016) Chemoattractant concentration-dependent tuning of ERK signaling dynamics in migrating neutrophils. Sci Signal 9:ra122
Diz-Muñoz, Alba; Thurley, Kevin; Chintamen, Sana et al. (2016) Membrane Tension Acts Through PLD2 and mTORC2 to Limit Actin Network Assembly During Neutrophil Migration. PLoS Biol 14:e1002474
Langen, Marion; Agi, Egemen; Altschuler, Dylan J et al. (2015) The Developmental Rules of Neural Superposition in Drosophila. Cell 162:120-33