Honors & Awards
Graduate Research Fellowship, National Science Foundation (2015)
Edgar Engleman, Doctoral Dissertation Advisor (AC)
San Francisco, CA
Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 T cells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection.
View details for DOI 10.1016/j.cell.2016.12.022
View details for PubMedID 28111070
There is an urgent need in oncology to link molecular aberrations in tumors with therapeutics that can be administered in a personalized fashion. One approach identifies synthetic-lethal genetic interactions or dependencies that cancer cells acquire in the presence of specific mutations. Using engineered isogenic cells, we generated a systematic and quantitative chemical-genetic interaction map that charts the influence of 51 aberrant cancer genes on 90 drug responses. The dataset strongly predicts drug responses found in cancer cell line collections, indicating that isogenic cells can model complex cellular contexts. Applying this dataset to triple-negative breast cancer, we report clinically actionable interactions with the MYC oncogene, including resistance to AKT-PI3K pathway inhibitors and an unexpected sensitivity to dasatinib through LYN inhibition in a synthetic lethal manner, providing new drug and biomarker pairs for clinical investigation. This scalable approach enables the prediction of drug responses from patient data and can accelerate the development of new genotype-directed therapies.Determining how the plethora of genomic abnormalities that exist within a given tumor cell affects drug responses remains a major challenge in oncology. Here, we develop a new mapping approach to connect cancer genotypes to drug responses using engineered isogenic cell lines and demonstrate how the resulting dataset can guide clinical interrogation.
View details for DOI 10.1158/2159-8290.CD-14-0552
View details for Web of Science ID 000349393600024
View details for PubMedID 25501949
View details for PubMedCentralID PMC4407699
Oncogenic mutations in the BRAF kinase occur in 6-8% of nonsmall cell lung cancers (NSCLCs), accounting for more than 90,000 deaths annually worldwide. The biological and clinical relevance of these BRAF mutations in NSCLC is incompletely understood. Here we demonstrate that human NSCLC cells with BRAF(V600E), but not other BRAF mutations, initially are sensitive to BRAF-inhibitor treatment. However, these BRAF(V600E) NSCLC cells rapidly acquire resistance to BRAF inhibition through at least one of two discrete molecular mechanisms: (i) loss of full-length BRAF(V600E) coupled with expression of an aberrant form of BRAF(V600E) that retains RAF pathway dependence or (ii) constitutive autocrine EGF receptor (EGFR) signaling driven by c-Jun-mediated EGFR ligand expression. BRAF(V600E) cells with EGFR-driven resistance are characterized by hyperphosphorylated protein kinase AKT, a biomarker we validated in BRAF inhibitor-resistant NSCLC clinical specimens. These data reveal the multifaceted molecular mechanisms by which NSCLCs establish and regulate BRAF oncogene dependence, provide insights into BRAF-EGFR signaling crosstalk, and uncover mechanism-based strategies to optimize clinical responses to BRAF oncogene inhibition.
View details for DOI 10.1073/pnas.1320956111
View details for Web of Science ID 000331396500008
View details for PubMedID 24550319
View details for PubMedCentralID PMC3932924