Stage IV

Despite recent advances, locally advanced non-small cell lung cancer (LA-NSCLC) continues to have a high degree of morbidity and mortality related to both disease progression and sequelae from treatment. The purpose of this study is to develop and evaluate a more personalized radiation therapy (RT) approach with the potential to reduce time and financial burden to patients and increase tumor control. Patients undergoing fractionated RT with concurrent systemic therapy for LA-NSCLC will be treated to a total dose of 60 Gy with the number of fractions determined by ability to meet key dose constraints resulting in a shorter treatment course and higher biologic effective dose (BED) among those treated with shorter fractionation. To reduce the iterative time to determine fractionation schedule and standardize the"‘isotoxic hypofractionation" approach, we will employ a previously developed automated RT planning technique after delineation of the tumor and organs at risk. Fifty patients will be enrolled in a prospective non-randomized 2-stage trial to test the primary objective of whether isotoxic hypofractionation results in an acceptable rate of grade 2 or higher toxicity. Secondary endpoints will include G3+ toxicity, local control, progression free survival and overall survival. Finally, to better inform future "isotoxic" dosing strategies we will evaluate additional predictors of radiation toxicity using established retrospective cohorts through the Stanford Cancer Institute and the Veteran’s Affairs Information and Computing Infrastructure (VINCI).

Though the introduction of immune checkpoint inhibitors (ICI) has improved outcomes for patients with stage III non-small-cell lung cancer, most patients do not have robust tumor responses to ICI and real-world patients discontinue ICI due to toxicity at a higher rate than clinical trial populations. There is an unmet need to develop predictive models to identify patients at risk of poor ICI response, high risk of ICI toxicity, and high risk of non-cancer mortality, as these patients are unlikely to benefit from ICI and may require treatment intensification or de-intensification, selection of alternative therapies, or enrollment on clinical trials. In this proposal we seek to leverage the richness and national scale of Veterans Affairs (VA) clinical data to develop statistical models to predict ICI efficacy, toxicity, and non-cancer mortality. We will evaluate specific hypotheses generated from preclinical research and use machine-learning approaches to identify new predictors from high-dimensional VA healthcare data. These models will be integrated into a unified multistate model, allowing prediction of the individualized overall survival benefit of ICI for each patient. Clinical decision-making based on model predictions will be compared to other decision making strategies using decision-curve analysis. This work will identify novel biomarkers of ICI efficacy and toxicity, validate putative ICI effect modifiers from the preclinical literature, and develop the first unified model for ICI clinical benefit. If successful, this tool can be used for patient counseling, physician decision-making, and identification of patients likely to benefit from alternative therapies, treatment de-escalation, or clinical trial enrollment.

The targeted-therapy (TT) osimertinib is frontline standard-of-care for patients with advanced non-small cell lung cancer (NSCLC) harboring mutations in the epidermal growth factor receptor (EGFR) gene. However, nearly all patients develop resistance, at which point treatments are limited. While revolutionary for many cancers, anti-PD-(L)1 immune checkpoint blockade (ICB) has been ineffective in EGFR-mutated(m) NSCLC. Targeting angiogenesis, and specifically vascular endothelial growth factor (VEGF), may be key to changing this. VEGF promotes immunosuppression through multiple mechanisms including inhibition of cytotoxic T-cell trafficking and promotion of regulatory T-cell proliferation. Pre-clinical and clinical evidence has revealed activated EGFR to be a dominant regulator of angiogenesis in EGFRm NSCLC, with increased expression of VEGF and hypoxia inducible factor-1α observed in EGFRm compared to wild-type NSCLC. Clinically, combination chemotherapy with anti-PD-L1 and VEGF blockade has shown efficacy signals in EGFRm NSCLC. However, whether upregulated VEGF potentiates the uninflamed tumor immune microenvironment (TIME), and underlies the observed synergy of these therapies in EGFRm NSCLC, remains unexplored. It is further unknown if VEGF inhibition can be combined with PD-1 blockade to promote benefit in the absence of chemotherapy, or whether blockade of additional checkpoints can further expand anti-tumor immune populations, specifically NK cells, which appear to be upregulated in EGFRm NSCLC responsive to ICB. To address these impactful questions, we have designed a single-arm translationally-focused phase 2 clinical trial assessing the efficacy of tiragolumab (anti-TIGIT) plus atezolizumab (anti-PD-L1) and bevacizumab (anti-VEGF) in advanced TT-refractory, ICB-naïve, EGFRm NSCLC. Critically, the proposed analyses detailed herein of tumor and blood samples obtained pre- and on-treatment will focus on (1) immunopathologic features of ICB resistance in EGFRm-NSCLC and (2) TIME infiltration and immunologic reprogramming imparted by these therapies. The findings from this study will help to define the innate barriers preventing induction of durable anti-tumor immunity by ICB in EGFRm NSCLC, and identify strategies to overcome them.

Rearrangement of the BRAF gene results in a potent oncogene that is a driver in 2.8% of NSCLC with BRAF alterations. To date there is no approve targeted therapy for any cancer type with BRAF fusions. Studies by our group and others have shown that mutant-specific BRAF kinase inhibitors do no inhibit BRAF fusion kinases. Instead, pan-RAF inhibitors seem more effective as therapy for cancer cells harboring these fusions. We therefore hypothesize that targeting BRAF fusions with pan-RAF inhibitors are likely to be effective therapy for this molecularly defined subset of NSCLC. Our goal in this proposal is to generate the preclinical data necessary to propel a phase 1 clinical trial of a pan-RAF inhibitor specific to patients with NSCLC harboring a BRAF fusion. We have generated seven preclinical disease models with BRAF rearrangement, including two NSLC patient-derived xenograft models with matching cell lines that will allow this project to go forward immediately. In Aim 1 we propose to generate additional NSCLC PDX, organoid and cell line models that will expand the platforms available to examine the efficacy of these BRAF inhibitors. We will test the efficacy of three pan-RAF inhibitors (LY3009120, belvarafenib, KIN-2787) in vitro and in vivo in Aim 2. We believe that combination therapy may eventually be necessary to extend the duration of response to BRAF targeted therapy. To find candidates that can be exploited for combination therapy, in Aim 3 we will map the signaling pathways that are activated by BRAF fusions in isogenic cell lines and inhibited specifically by BRAF inhibitors in cells with BRAF fusions. Given that resistance to therapy is inevitable, we will seek to generate resistance to the three pan-RAF inhibitors in vitro and in vivo and then identify and validate potential mechanisms of resistance. To be able to bring the goals of this proposal to fruition, I have assembled a team with clinical, translational and basic research expertise to help guide me. As a thoracic oncologist with clinical trial expertise, I am ideally situated to translate the findings of this study to the clinic.

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.