The ability of cancer cells to evolve and adapt to therapy is a challenge that limits treatment success and durability of responses. This is certainly the case in chronic lymphocytic leukemia (CLL), a malignancy of mature B cells that remains incurable, despite the potent cytolytic effects of both existing standard-of-care fludarabine-based combination chemotherapy, and newly developed targeted inhibitors such as ibrutinib and ABT199. We focus on a series of informative well-characterized clinical cohorts of patients that have relapsed following CLL therapy, ranging from conventional chemotherapy to novel agents (ibrutinib, ABT199, anti-PD1 antibody). Through integrated whole-exome and RNA-sequencing of these cohorts, we will characterize the extent of clonal evolution following exposure to these agents, and identify if there are consistent genetic loci associated with therapeutic resistance or progression (Aim 1). Mathematical modeling together with frequent serial analysis of the clonal composition of leukemias in relationship to treatment response and relapse can inform us regarding the clone-specific decline/growth kinetics as they occur in individual patients, and thereby enable dissection of the mechanisms of relapse or progression. Through this process, we will further estimate the sizes of clones with rare resistance mutations at the start of treatment; understand whether distinct relapse- associated genetic lesions result in accelerated clonal growth, or rather, in insensitivity to therapy; and validate the size of the resistant population in the starting population using novel single cell droplet sequencing technology (Aim 2). Finally, we will use CRISPR/Cas technology to model the novel resistance mutations in B cell lines and introduce these lines in combination with other mutated cell lines both in vitro and in vivo into immunodeficient mice, in order to test their fitness both prior to and during therapy (Aim 3). Altogether, the proposed analyses serve to provide an analytic framework for gaining vital information regarding the fitness of different genetic lesions with and without therapy, which may be immensely beneficial to the design of the next generation of therapeutic approaches to overcome the evolutionary capacity of cancer.

Public Health Relevance

Cancer therapies often fail as a consequence of cancer's resistance to treatment, which arises because cancer cells evolve to escape the effects of therapy. Using the knowledge of mutations in patient samples with chronic lymphocytic leukemia (gained from leukemia cell sequencing), we will use mathematical modeling together with new experimental data generated from unbiased bulk sequencing and novel single cell-based approaches together with animal studies to model clonal dynamics in order to uncover and quantify the evolution that leads to resistance to therapy.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Program Projects (P01)
Project #
5P01CA206978-03
Application #
9548937
Study Section
Special Emphasis Panel (ZCA1)
Project Start
Project End
Budget Start
2018-09-01
Budget End
2019-08-31
Support Year
3
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Dana-Farber Cancer Institute
Department
Type
DUNS #
076580745
City
Boston
State
MA
Country
United States
Zip Code
Ten Hacken, Elisa; Valentin, Rebecca; Regis, Fara Faye D et al. (2018) Splicing modulation sensitizes chronic lymphocytic leukemia cells to venetoclax by remodeling mitochondrial apoptotic dependencies. JCI Insight 3:
Lampson, Benjamin L; Brown, Jennifer R (2018) Are BTK and PLCG2 mutations necessary and sufficient for ibrutinib resistance in chronic lymphocytic leukemia? Expert Rev Hematol 11:185-194
Wang, Lili; Livak, Kenneth J; Wu, Catherine J (2018) High-dimension single-cell analysis applied to cancer. Mol Aspects Med 59:70-84
Landau, Dan A; Sun, Clare; Rosebrock, Daniel et al. (2017) The evolutionary landscape of chronic lymphocytic leukemia treated with ibrutinib targeted therapy. Nat Commun 8:2185
Compagno, Mara; Wang, Qi; Pighi, Chiara et al. (2017) Phosphatidylinositol 3-kinase ? blockade increases genomic instability in B cells. Nature 542:489-493
Ten Hacken, Elisa; Gui├Ęze, Romain; Wu, Catherine J (2017) SnapShot: Chronic Lymphocytic Leukemia. Cancer Cell 32:716-716.e1
Murphy, E J; Neuberg, D S; Rassenti, L Z et al. (2017) Leukemia-cell proliferation and disease progression in patients with early stage chronic lymphocytic leukemia. Leukemia 31:1348-1354
Deng, J; Isik, E; Fernandes, S M et al. (2017) Bruton's tyrosine kinase inhibition increases BCL-2 dependence and enhances sensitivity to venetoclax in chronic lymphocytic leukemia. Leukemia 31:2075-2084
Tiao, G; Improgo, M R; Kasar, S et al. (2017) Rare germline variants in ATM are associated with chronic lymphocytic leukemia. Leukemia 31:2244-2247
Wang, Lili; Fan, Jean; Francis, Joshua M et al. (2017) Integrated single-cell genetic and transcriptional analysis suggests novel drivers of chronic lymphocytic leukemia. Genome Res 27:1300-1311

Showing the most recent 10 out of 11 publications