Overcoming resistance to targeted therapy in cancer Project Summary The challenge of drug resistance represents a pervasive barrier that confounds the ultimate goal of cure or long-term control of metastatic cancer. Intensive studies of resistance to targeted therapies by our group in recent years have revealed three over-arching challenges. First, resistance is multifactorial: many individual resistance mechanisms thwart the efficacy of various targeted anticancer therapeutic regimens, and there is no evidence that their discovery has saturated. Second, resistance is heterogeneous: multiple different resistance mechanisms often arise in a given patient-even within a single tumor lesion1. Third, resistance is vastly under-sampled in the clinical arena: few paired pre-treatment and post-resistance biopsies are obtained clinically, and such tissues are only seldom subjected to systematic characterization2. The guiding hypothesis of this research is that the spectrum of resistance mechanisms for any given cancer therapeutic modality might coalesce onto a much smaller set of critical downstream effector nodes. Discerning the mechanisms operant within such points of coalescence should yield new insights into oncogenic dependencies and illuminate guiding principles for the design of novel therapeutic combinations. In recent years, we have evaluated this coalescence hypothesis by systematically characterizing mechanisms of resistance to MAP kinase pathway inhibition in BRAF-mutant melanoma and other oncogene- driven cancers. Indeed, many individual MAP kinase resistance mechanisms may coalesce at the level of transcriptional (or chromatin) regulation. This convergence re-engages core MAPK transcriptional program(s) or alternative (ERK-independent) transcriptional programs arising from bypass signaling or germane to pathway-indifferent cell states. Accordingly, one objective of this work is to define the convergent downstream outputs elaborated by MAP kinase inhibitor resistance mechanisms, and the factors that govern them. In parallel, we will characterize the coalescence of resistance mechanisms to targeted therapeutics in other cancers. Finally, we will describe drug-resistant and drug-indifferent cell states in treatment-refractory tumors. Detailed characterization of resistance categories and the mechanistic coalescence implied therein may reveal fundamental new insights into the nature of cancer dependencies and their evolution during tumor progression and treatment. Insights gleaned from this research may aid the design of higher-order therapeutic combinations that attack multiple tumor dependencies and resistance nodes. This framework for studying the mechanistic coalescence that underpins drug resistance is applicable to many cancer types. Therefore, these efforts could offer guiding principles that become generalizable across many tumor types and therapeutic modalities.

Public Health Relevance

Most patients with advanced cancer die because their tumor cells develop resistance to medical treatment. Based on our extensive research on drug resistance in melanoma, we have proposed a new framework for understanding drug resistance. The goal of this research is to test this hypothesis deeply in melanoma and other cancers using experimental and clinical approaches. As a result, we expect to reveal new discoveries that could be used in the design of drug combinations capable of overcoming cancer drug resistance.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Unknown (R35)
Project #
3R35CA197737-02S1
Application #
9247961
Study Section
Special Emphasis Panel (ZCA1 (M1))
Program Officer
Forry, Suzanne L
Project Start
2015-08-24
Project End
2018-07-31
Budget Start
2016-08-01
Budget End
2017-07-31
Support Year
2
Fiscal Year
2016
Total Cost
$86,961
Indirect Cost
$37,269
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
02215
Le, Xiuning; Antony, Rajee; Razavi, Pedram et al. (2016) Systematic Functional Characterization of Resistance to PI3K Inhibition in Breast Cancer. Cancer Discov 6:1134-1147
Tirosh, Itay; Izar, Benjamin; Prakadan, Sanjay M et al. (2016) Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science 352:189-96