Non-small cell lung cancer (NSCLC)

Although about a third of patients with non-small cell lung cancer (NSCLC) present with resectable disease, a majority will experience death and relapse from their cancer. Exciting recent advances in the use of immune checkpoint inhibition in this early stage space presents a promising way forward for our patients. As the most commonly mutated oncogene, activating KRAS mutations are found in 30% of lung adenocarcinomas; G12C mutations have been associated with higher risk of recurrence following resection. Adagrasib (MRTX849), a potent, highly selective novel small molecule inhibitor of KRAS G12C, has shown promise in previously treated advanced NSCLC. Our study represents a novel application of precision oncology in the resectable NSCLC disease setting with the neoadjuvant use of adagrasib monotherapy or in combination with immune checkpoint inhibition. We will identify safety and clinical efficacy signals of both of these therapeutic approaches. Leveraging our institutional expertise of using single- cell transcriptomics of tumor- infiltrating lymphocytes (TIL), we will evaluate neoantigen-specific transcriptional programs with a focus on KRAS-specific changes, and correlate with clinical outcomes. Overall, our study aims to ultimately improve cure rates of resectable KRAS G12C-mutated NSCLC.

Genomic discoveries of driver-gene alterations in lung cancer have led to development of effective target therapeutics; however patients who initially respond to the therapy inevitably experience regrowth of the disease. The reversible drug-tolerant persister (DTP) stage, where cells enter a quiescence, is gaining attention as a major source of non-genetic drug resistance. In our EGFR-TKI-induced DTP model, we found a marked overload of repressive chromatin modification (H3K9me3 and H3K27me3) reminiscent of a quiescent state. In Aim1, we seek to characterize the epigenomic dynamics of DTP stage in RET-positive lung cancer under Selpercatinib treatment, and determine the roles of histone-modifying enzymes on maintaining DTP stage as potential combinatorial therapeutic targets. The process of DTP development requires terminally differentiated cells to regain plasticity and undergo re-differentiation, while the origin of DTP plasticity remains unknown. A recent scRNA-seq study from lung cancer biopsies representing DTP states showed an elevated alveolar signature. During lung regeneration, an alveolar lineage factor HOPX is required for the AT1 plasticity to regenerate AT2 cells upon injury, suggesting a differentiation potential of HOPX(+) cells. Our data showed HOPX is an early marker for treatment-induced DTP and necessary for DTP development, where our scATAC-seq data exhibited increased epigenomic heterogeneity. We hypothesize DTP contains heterogeneous subpopulations that hijack developmental pathways to sustain plasticity for subsequent differentiation. In Aim2, we will determine the role of HOPX and associated developmental pathways in RET-induced DTP model, to identify novel targets determining the DTP plasticity thereby preventing relapse from heterogeneous pathways to acquire Selpercatinib resistance.

Fusions in the RET proto-oncogene account for ~2% of non-small cell lung cancers (NSCLC). Despite initial failures tied to the use of multi-kinase inhibitors, recent selective RET inhibitors have proven remarkably more successful. However, patients eventually recur on these therapies, highlighting the need for other therapeutic alternatives. Immunotherapies have been unsuccessful in patients harboring RET fusions, likely in part due to their low tumor mutational burden. Neoantigens are immunogenic antigens which are derived from somatic mutations, resulting in antigen-specific killing by T lymphocytes. Importantly, insertions, deletions, and gene fusions may exhibit increased immunogenicity, due to their accrued dissimilarity with unmutated transcripts and proteins, which may provide a unique opportunity to target RET fusions using T cell receptor engineering approaches. Accordingly, we hypothesize that RET fusions are immunogenic and can be effectively recognized using T cell receptor engineering approaches. To confirm this hypothesis, we propose to identify RET fusion-derived neoantigens, identify and isolate the T cells which recognize them, and engineer T cells to kill targets in vitro. Through this work, we aim to generate a library of TCRs which could be used off-the-shelf to target the two dominant RET fusions (KIF5B-RET=75%; CCDC6-RET=25%) and 10 most prevalent HLA alleles in the United States, in order to afford new therapeutic alternatives to the overwhelming majority of patients harboring RET fusions in NSCLC.

Patients with RET-rearranged non-small cell lung cancer (RET+ NSCLC) demonstrate dramatic responses to RET tyrosine kinase inhibitors (TKIs). An important category of acquired resistance is through bypass signaling that circumvents the RET pathway altogether. When a dominant pathway (such as the RET fusion) is inhibited by a TKI (such as pralsetinib or selpercatinib), recruitment of bypass signaling can allow the cancer cell to sustain critical oncogenic pathways. We have generated RET cancer cell lines resistant to both pralsetinib and selpercatinib, LC-2/ad (CCDC6-RET) and CUTO42 (EML4-RET), that demonstrate sensitivity to afatinib, suggesting that EGFR activation is a possible mechanism of resistance. Similarly, MET amplification has been observed as an important bypass signal, seen in up to 15% of RET resistant cases. However, this is likely an under-estimate of the true spectrum of MET-mediated resistance. First, there is no consensus on what copy number (or gene-to-centromere ratio) defines MET amplification in the acquired resistance setting. Second, MET amplification is likely one of many potential mechanisms of MET-mediated resistance. Finally, the level of MET signaling needed for cancer cells to survive in the presence of a RET TKIs may be different than if MET was a de novo driver oncogene. Our central hypothesis is that MET and EGFR expression are present at baseline to varying degrees among patients with RET+ NSCLC. The use of RET TKIs selects for cancer clones that efficiently and effectively utilize bypass signaling through pre-existing EGFR and MET pathways where both have been described as mechanisms of resistance in oncogene-driven subtypes of lung cancer. Amivantamab (JNJ-61186372) is an EGFR-MET bispecific antibody that has shown synergistic inhibition of tumor growth when combined with EGFR TKIs such as lazertinib. In the ongoing CHRYSALIS Phase 1/2 study of amivantamab with lazertinib, an objective response rate of 29% was seen among 28 patients who had no identifiable mechanism of resistance to EGFR or MET TKIs. One interpretation is that several patients in this analysis had EGFR or MET signaling as a mechanism of resistance that were not being captured through traditional biomarker assays. We anticipate that a similar scenario will be present among patients with RET+ NSCLC progressing on RET TKIs. I have written an investigator-initiated trial (IIT) titled “A phase 1/2, open label, study of amivantamab (JNJ-61186372) among participants with advanced NSCLC harbouring ALK, ROS1, and RET gene fusions progressing on tyrosine kinase inhibitors without identifiable mechanisms of acquired resistance” that has already been approved and funded by Janssen. This trial will have a dedicated RET cohort that will allow us an opportunity to obtain samples pre and post-amivantamab. This infrastructure will allow us to readily test the relevance of MET and

RET fusions occur in 2-3% cases of lung cancer and there are currently two FDA-approved RET-specific inhibitors, selpercatinib and pralsetinib, for the treatment of patients with RET fusion positive lung or thyroid cancers. Therapeutic resistance eventually emerges, however, and studies have shown that RET-dependent mechanisms of resistance include acquired resistance mutations that alter drug binding. Further, RET fusions and mutations are heterogeneous and the impact of specific fusion partners and RET variants on drug sensitivity is poorly understood. In a recent publication in Nature, our group reported that for a related driver oncogene, EGFR, both primary and acquired resistance mutations can be classified into distinct structural groups that correlate with drug sensitivity and resistance. This structure-function based classification has important advantages 1) structure-based groups predicted drug response significantly better than standard exon-based approaches, 2) this classification enabled us to match drugs for more than ~99% of atypical mutations where currently less than 50% of mutations have an FDA approved drug. In addition, preliminary preclinical and clinical data suggests that two RET-independent mechanisms of resistance- signal bypass and lineage shift-may also drive resistance even in the presence of effective RET inhibition. Applying methodologies we established for elucidating EGFR inhibitor resistance, we will develop a structure-function based classification which can immediately impact clinical decisions for selecting therapies; comprehensively characterize RET-dependent and -independent mechanisms of resistance and biomarkers to assess them; and develop rational therapeutic strategies to overcome resistance which can guide patient selection for future clinical studies.

On-/off-target resistance mechanisms to RET tyrosine kinase inhibition (TKI) are not identified in ~40% of patients with RET fusion-positive lung cancers. As such, focusing solely on genomic alterations (e.g. mutation/amplification) limits our ability to develop novel therapies for all patients. This project addresses the unmet need of identifying and characterizing alternate resistance mechanisms to selective RET TKI therapy via epigenetic mechanisms leading to altered programs of gene expression. As with other oncogene-TKI pairs, we hypothesize that epigenetic re-programming and lineage plasticity drives resistance to RET TKIs. Serial pre- and post-TKI tumor samples will be interrogated (DEG/GSEA analysis) via complementary methylome (EPIC) and transcriptomic (RNAseq) profiling. Pathologic review and immunohistochemical profiling for markers of squamous (p40, CK5/6), small cell (chromogranin, synaptophysin), and epithelial-mesenchymal (E/N-cadherin, vimentin) transformation will be performed. Candidate resistance pathways will be explored in engineered isogenic overexpression/knockout models and our institutional library of xenografts generated from patients treated with a selective RET TKI on a registrational program or standard of care. Genetic manipulation of targets that we and others have associated with licensing lineage plasticity (e.g. myrAKT, MYC, EZH2, and beta-catenin) in RET fusion-positive models to induce histologic transformation will be performed. These analyses will define strategies to constrain or abrogate therapeutic resistance.

Background: Patients with NSCLC whose tumors harbor a targetable molecular alteration have improved outcomes when they receive targeted therapy. Historically, targetable alterations have been associated with specific patient characteristics such as female gender, young age, non-smokers, and Asians. Given this association, patients with characteristics not commonly associated with targetable mutations do not always receive timely and complete molecular testing. We hypothesize that male gender, age >65, history of smoking, African American race and Hispanic ethnicity will be independently associated with delayed detection and treatment of a targetable alteration. We will evaluate the impact of delayed targeted therapy on overall survival and brain metastasis development.

Methods: We will perform a retrospective cohort study of approximately 2200 patients with EGFR, ALK or ROS1 targetable alterations obtained through multi-institution retrospective chart review. Multivariate logistic regression will be used to evaluate the association of patient characteristics with complete molecular testing prior to first-line therapy, targeted therapy as first-line therapy, and development of brain metastases. Kaplan-Meier methodology will be used to estimate median overall survival. The log rank test will be used to compare median overall survivals. Multivariate Cox Regression will further evaluate interactions between delayed targeted therapy and patient characteristics as well as help control for potential confounders.

Importance: This will be the first study to evaluate the impact of delayed detection and delayed treatment of driver mutations in NSCLC. This information is critical to designing interventions to improve outcomes in patient groups with characteristics not usually associated with driver mutations.

A common source of lung cancer morbidity is presented by incidental pulmonary nodules (IPNs), which can represent missed cancers when incompletely followed. Underrepresented patients are particularly at risk of guidelines discordant care. Our institution cares for a large proportion of these minority communities. We therefore propose to develop a comprehensive program for the identification, risk stratification and management of IPNs identified through imaging in the emergency setting. We first seek to incorporate lung nodule detection and management software into our electronic medical record (EMR). To facilitate recognition of nodules, we will utilize natural language processing to screen and flag imaging. A multidisciplinary ensemble of practitioners will validate findings and participate in management. At the crux of this team will be a patient navigator to communicate with patients and assist in follow-up. We next seek to create an IPN risk prediction algorithm. Clinical and radiographic elements from the EMR will be subjected to artificial intelligence-based review to automatically leverage data towards a machine learning-derived algorithm. The final element of our proposal will investigate a blood-based gene expression assay as a marker for malignancy. Following its evaluation using a cohort of biobanked samples, we will apply this RNA-based detection assay to look for markers of malignancy to facilitate the early detection of lung cancers. We ultimately seek to improve lung cancer care within our largely underserved population through a combination of incorporating patients with IPNs into the health care system and providing appropriate and automated risk stratification to expedite care and diagnosis.

Lung cancer remains the leading cause of cancer death worldwide and clinical trials show that annual lung cancer screening with low-dose Computed Tomography can reduce lung cancer-related mortality by 20%. Marginalized populations are disproportionately affected by lung cancer and our prior work has shown that these disparities extend to lung cancer screening; in a national cohort of Veterans we found that Black Veterans, those with mental health disorders and lower income were less likely to adhere to lung cancer screening follow-up recommendations. Currently, little is known about how to optimize lung cancer screening in underserved populations and marginalized populations from diverse backgrounds.

This proposed project focuses on identifying barriers and facilitators to lung cancer screening at the patient, provider, facility and community-levels. We plan to use mixed methods to quantitatively explore factors associated with delayed or lack of adherence to lung cancer screening and then perform in-depth qualitative analysis to identify which factors are critical and modifiable. We will use an implementation strategy mapping tool to select evidence-based strategies best suited to address the identified barriers and develop a tailored implementation plan to improve adherence to lung cancer screening, both overall and among underserved populations, at Baystate Health System. This work is critical in achieving equity in lung cancer screening and improving overall lung cancer mortality among patients.

Veterans have significantly greater rates of lung cancer and mortality as compared to civilians. In our prior work, these disparities are partly due to lack of receipt of evidence-based cancer care especially among patients with complex comorbidities, psychosocial concerns, and limited social support, characteristics common among Veteran populations. The overall goal of this research is to overcome structural barriers to ensure delivery of evidence-based lung cancer care among Veterans. In our prior work we identified workforce shortages along with complex psychosocial factors and medical conditions that prevent Veterans from fully engaging in their care. We used community-based participatory research and expert panel methods to develop Engagement of Patients with Advanced Cancer (EPAC) – an intervention that integrates community health workers into care.1 In our randomized trial, EPAC improved evidence-based end-of-life care, Veteran satisfaction and reduced acute care use and total healthcare costs. In this study, with our established Advisory Board comprised of Veterans, caregivers, oncology clinicians, and VA leaders, we will refine EPAC to incorporate evidence-based lung cancer care (Aim 1). We will randomize 60 Veterans newly diagnosed with advanced lung cancer to establish feasibility of the refined EPAC intervention (primary outcome) and secondarily, the effects on evidence-based lung cancer care and Veteran activation (Aim 2). The results will inform a multisite randomized study in the VA.