TN

Despite high tumor response rates, patients treated with osimertinib inevitably develop disease progression. Mechanisms of both intrinsic, adaptive, and acquired drug resistance remain incompletely understood on a genomic and proteomic level. Our overall objective is to find new targeted treatments and drug combinations that can tackle cancer evolution and drug resistance.

We seek to:

1. Understand biological determinants of response prior to therapy (poor prognosis features)
2. Utilize correct combination therapies in the first line to enhance response, based on biological features of subpopulations present at the start
3. Reprogram cells toward a more drug-sensitive state through understanding network plasticity.

More specifically, our aims are:

1. To define the genomic and proteomic characteristics of drug-tolerant persister cells (DTPCs) under dynamic treatment with osimertinib. Our goal is to identify new vulnerabilities in EGFR-mutant tumors which, when therapeutically targeted, can maximize the depth and duration of benefit to first-line osimertinib therapy.
2. To decipher mechanisms of altered cell cycle progression and osimertinib-induced DNA damage that drive tumor progression.

We have assembled a collaborative, multi-disciplinary team of laboratory scientists and clinical investigators combined with cutting edge technologies to assess genetic and proteomic heterogeneity at the single cell level, access to a robust pipeline of patient samples, and strong preliminary data to support our studies. The proposed aims are expected to define the molecular determinants of tumor heterogeneity and to develop rational therapeutic strategies for delaying / overcoming resistance. These synergistic aims are highly relevant to the current landscape of EGFR-mutant lung cancer.

Small cell lung cancer (SCLC) is among the most aggressive and deadly human cancers. It represents approximately 15% of all lung cancers, and it is responsible for over 30,000 deaths in the US and 200,000 deaths worldwide every year. SCLC responds to treatment but recurs frequently and aggressively, with the majority of patients dying within 12 months of diagnosis. No targeted therapies are yet available for SCLC. New strategies are needed to improve outcomes for patients with SCLC. This project will expand upon preliminary data identifying at least two distinct subpopulations of cells in SCLC cell lines and patient-derived xenografts comprising a neuroendocrine (NE) and mesenchymal-like (ML) set of cell line populations. Dr. Lehman and his team will use an innovative approach using mass cytometry, using rare earth antibody conjugates to antibody label more than 30 proteins simultaneously, including phospho and signaling proteins. This technique will establish at a single-cell resolution tumor heterogeneity and signaling in small cell lung carcinoma in multiple primary human samples as well as in patient-derived xenograft samples before and after chemotherapy treatment. This proposal aims to (1) characterize the signaling of subpopulations in human primary SCLCs at a single-cell resolution, (2) identify changes in tumor heterogeneity and in these subpopulations after chemotherapy treatment and relapse, and (3) disrupt and manipulate developmental signaling/ associated subpopulations (prototypically the HH [Hedgehog] and Notch/DLL3 pathways) to reduce tumor burden and lead to targeted rational combination therapy for SCLC.

The ALK tyrosine kinase inhibitor (TKI) crizotinib has demonstrated significant activity in patients with ALK+ lung cancer, but its efficacy is limited by the development of acquired resistance. One potential resistance mechanism involves activation of the EGFR and HER2 kinases. This activation occurs in the absence of EGFR/HER2 mutation or amplification, suggesting an alternative mechanism for up-regulation of these kinases. We discovered a novel association between ALK and the EGFR/HER2 negative regulator, MIG-6. MIG-6 is known to inhibit EGFR/HER2 kinase activity through direct binding. However, to date, there is no known link between ALK and MIG-6. In our preliminary data, we demonstrate that MIG-6 protein levels decrease after ALK TKI treatment, a process abrogated by addition of a proteasome inhibitor. Furthermore, MIG-6 transcript and total protein levels are decreased in ALK+/TKI resistant compared to isogenic ALK+/TKI sensitive cells. The decline in MIG-6 correlates with an increase in EGFR and HER2 protein levels in the resistant cells. Based upon these data, we hypothesize that ALK serves as an upstream regulator of MIG-6, and that MIG-6 suppression drives EGFR/HER2 activation in the ALK TKI resistant state. To test this hypothesis, we propose to: 1) elucidate the molecular mechanisms whereby ALK regulates MIG-6 expression, and 2) determine the mechanisms whereby MIG-6 contributes to EGFR/HER2 pathway activation in TKI-resistant ALK+ lung cancer cells. The proposed studies may lead to strategies that augment or restore expression of MIG-6 and therefore will represent a novel therapeutic approach for patients with acquired resistance to ALK inhibitor therapy.

The development of non-invasive diagnostic tools to detect lung cancer at an early stage is the subject of active investigations because of its enormous potential impact on the number-one cause of cancer-related deaths. We have recently discovered by shotgun proteomics profiling 164 candidate biomarkers that are differentially expressed in stage 1 lung cancer tissue compared to non-malignant matched controls tissues and found in the circulation. Validation of these candidates by traditional methods using western blot or ELISA is a slow, low throughput, and expensive process. In this application, we propose to take advantage of the individual’s immune response to capture and detect autoantibodies directed against these 164 candidate protein targets identified by shotgun proteomics. To achieve this goal, we intend (1) to establish immune-based assays for the detection and quantitation  of lung cancer autoantibodies using an indirect ELISA; (2) to validate the diagnostic performance of our autoantibody signature in blood samples from individuals with early-stage lung cancer or matched nodule controls; and (3) to determine whether the diagnostic performance of our panel of autoantibody signatures augments the diagnostic accuracy of known predictive models for the evaluation of lung nodules. These studies may lead to the development and early validation of a new molecular diagnostic tool for lung cancer.