Brief Report: Comprehensive Clinicogenomic Profiling of Small Cell Transformation From EGFR-Mutant NSCLC Informs Potential Therapeutic Targets.

Introduction: NSCLC transformation to SCLC has been best characterized with EGFR-mutant NSCLC, with emerging case reports seen in ALK, RET, and KRAS-altered NSCLC. Previous reports revealed transformed SCLC from EGFR-mutant NSCLC portends very poor prognosis and lack effective treatment. Genomic analyses revealed TP53 and RB1 loss of function increase the risk of SCLC transformation. Little has been reported on the detailed clinicogenomic characteristics and potential therapeutic targets for this patient population. Methods: In this study, we conducted a single-center retrospective analysis of clinical and genomic characteristics of patients with EGFR-mutant NSCLC transformed to SCLC. Demographic data, treatment course, and clinical molecular testing reports were extracted from electronic medical records. Kaplan-Meier analyses were used to estimate survival outcomes. Next generation sequencing-based assays was used to identify EGFR and co-occurring genetic alterations in tissue or plasma before and after SCLC transformation. Single-cell RNA sequencing (scRNA-seq) was performed on a patient-derived-xenograft model generated from a patient with EGFR-NSCLC transformed SCLC tumor. Results: A total of 34 patients were identified in our study. Median age at initial diagnosis was 58, and median time to SCLC transformation was 24.2 months. 68% were female and 82% were never smokers. 79% of patients were diagnosed as stage IV disease, and over half had brain metastases at baseline. Median overall survival of the entire cohort was 38.3 months from initial diagnoses and 12.4 months from time of SCLC transformation. Most patients harbored EGFR exon19 deletions as opposed to exon21 L858R alteration. Continuing EGFR tyrosine kinase inhibitor post-transformation did not improve overall survival compared with those patients where tyrosine kinase inhibitor was stopped in our cohort. In the 20 paired pretransformed and post-transformed patient samples, statistically significant enrichment was seen with PIK3CA alterations (p = 0.04) post-transformation. Profiling of longitudinal liquid biopsy samples suggest emergence of SCLC genetic alterations before biopsy-proven SCLC, as shown by increasing variant allele frequency of TP53, RB1, PIK3CA alterations. ScRNA-seq revealed potential therapeutic targets including DLL3, CD276 (B7-H3) and PTK7 were widely expressed in transformed SCLC. Conclusions: SCLC transformation is a potential treatment resistance mechanism in driver-mutant NSCLC. In our cohort of 34 EGFR-mutant NSCLC, poor prognosis was observed after SCLC transformation. Clinicogenomic analyses of paired and longitudinal samples identified genomic alterations emerging post-transformation and scRNA-seq reveal potential therapeutic targets in this population. Further studies are needed to rigorously validate biomarkers and therapeutic targets for this patient population.

Targeting BCL2 Overcomes Resistance and Augments Response to Aurora Kinase B Inhibition by AZD2811 in Small Cell Lung Cancer.

PURPOSE: Therapeutic resistance to frontline therapy develops rapidly in small cell lung cancer (SCLC). Treatment options are also limited by the lack of targetable driver mutations. Therefore, there is an unmet need for developing better therapeutic strategies and biomarkers of response. Aurora kinase B (AURKB) inhibition exploits an inherent genomic vulnerability in SCLC and is a promising therapeutic approach. Here, we identify biomarkers of response and develop rational combinations with AURKB inhibition to improve treatment efficacy. EXPERIMENTAL DESIGN: Selective AURKB inhibitor AZD2811 was profiled in a large panel of SCLC cell lines (n = 57) and patient-derived xenograft (PDX) models. Proteomic and transcriptomic profiles were analyzed to identify candidate biomarkers of response and resistance. Effects on polyploidy, DNA damage, and apoptosis were measured by flow cytometry and Western blotting. Rational drug combinations were validated in SCLC cell lines and PDX models. RESULTS: AZD2811 showed potent growth inhibitory activity in a subset of SCLC, often characterized by, but not limited to, high cMYC expression. Importantly, high BCL2 expression predicted resistance to AURKB inhibitor response in SCLC, independent of cMYC status. AZD2811-induced DNA damage and apoptosis were suppressed by high BCL2 levels, while combining AZD2811 with a BCL2 inhibitor significantly sensitized resistant models. In vivo, sustained tumor growth reduction and regression was achieved even with intermittent dosing of AZD2811 and venetoclax, an FDA-approved BCL2 inhibitor. CONCLUSIONS: BCL2 inhibition overcomes intrinsic resistance and enhances sensitivity to AURKB inhibition in SCLC preclinical models.

Dynamic expression of Schlafen 11 (SLFN11) in circulating tumour cells as a liquid biomarker in small cell lung cancer.

INTRODUCTION: Small cell lung cancer (SCLC) is an aggressive malignancy with no established biomarkers. Schlafen 11(SLFN11), a DNA/RNA helicase that sensitises cancer cells to DNA-damaging agents, has emerged as a promising predictive biomarker for several drug classes including platinum and PARP inhibitors. Detection of SLFN11 in circulating tumour cells (CTCs) may provide a valuable alternative to tissue sampling. METHODS: SLFN11 expression was evaluated in tumour samples and characterised in circulating tumour cells (CTC) longitudinally to determine its potential role as a biomarker of response. RESULTS: Among 196 SCLC tumours, 51% expressed SLFN11 by IHC. In addition, 20/29 extra-thoracic high-grade neuroendocrine tumours expressed SLFN11 expression. In 64 blood samples from 42 SCLC patients, 83% (53/64) of samples had detectable CTCs, and SLFN11-positive CTCs were detected in 55% (29/53). Patients actively receiving platinum treatment had the lowest number of CTCs and a lower percentage of SLFN11-positive CTCs (p = 0.014). Analysis from patients with longitudinal samples suggest a decrease in CTC number and in SLFN11 expression that correlates with clinical response. CONCLUSIONS: SLFN11 levels can be monitored in CTCs from SCLC patients using non-invasive liquid biopsies. The ability to detect SLFN11 in CTCs from SCLC patients adds a valuable tool for the detection and longitudinal monitoring of this promising biomarker.

Targeting MYC-enhanced glycolysis for the treatment of small cell lung cancer.

INTRODUCTION: The transcription factor MYC is overexpressed in 30% of small cell lung cancer (SCLC) tumors and is known to modulate the balance between two major pathways of metabolism: glycolysis and mitochondrial respiration. This duality of MYC underscores the importance of further investigation into its role in SCLC metabolism and could lead to insights into metabolic targeting approaches. METHODS: We investigated differences in metabolic pathways in transcriptional and metabolomics datasets based on cMYC expression in patient and cell line samples. Metabolic pathway utilization was evaluated by flow cytometry and Seahorse extracellular flux methodology. Glycolysis inhibition was evaluated in vitro and in vivo using PFK158, a small molecular inhibitor of PFKFB3. RESULTS: MYC-overexpressing SCLC patient samples and cell lines exhibited increased glycolysis gene expression directly mediated by MYC. Further, MYC-overexpressing cell lines displayed enhanced glycolysis consistent with the Warburg effect, while cell lines with low MYC expression appeared more reliant on oxidative metabolism. Inhibition of glycolysis with PFK158 preferentially attenuated glucose uptake, ATP production, and lactate in MYC-overexpressing cell lines. Treatment with PFK158 in xenografts delayed tumor growth and decreased glycolysis gene expression. CONCLUSIONS: Our study highlights an in-depth characterization of SCLC metabolic programming and presents glycolysis as a targetable mechanism downstream of MYC that could offer therapeutic benefit in a subset of SCLC patients.

Lung Cancer Models Reveal Severe Acute Respiratory Syndrome Coronavirus 2-Induced Epithelial-to-Mesenchymal Transition Contributes to Coronavirus Disease 2019 Pathophysiology.

INTRODUCTION: Coronavirus disease 2019 is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which enters host cells through the cell surface proteins ACE2 and TMPRSS2. METHODS: Using a variety of normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2. RESULTS: We find that ACE2 expression is restricted to a select population of epithelial cells. Notably, infection with SARS-CoV-2 in cancer cell lines, bronchial organoids, and patient nasal epithelium induces metabolic and transcriptional changes consistent with epithelial-to-mesenchymal transition (EMT), including up-regulation of ZEB1 and AXL, resulting in an increased EMT score. In addition, a transcriptional loss of genes associated with tight junction function occurs with SARS-CoV-2 infection. The SARS-CoV-2 receptor, ACE2, is repressed by EMT through the transforming growth factor-ß, ZEB1 overexpression, and onset of EGFR tyrosine kinase inhibitor resistance. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state, associated with a loss of tight junction components with acute respiratory distress syndrome-protective effects. AXL inhibition and ZEB1 reduction, as with bemcentinib, offer a potential strategy to reverse this effect. CONCLUSIONS: These observations highlight the use of aerodigestive and, especially, lung cancer model systems in exploring the pathogenesis of SARS-CoV-2 and other respiratory viruses and offer important insights into the potential mechanisms underlying the morbidity and mortality of coronavirus disease 2019 in healthy patients and patients with cancer alike.

Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities.

Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data and non-negative matrix factorization, we identify four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed gene signature (SCLC-A, N, P, and I, respectively). SCLC-I experiences the greatest benefit from the addition of immunotherapy to chemotherapy, while the other subtypes each have distinct vulnerabilities, including to inhibitors of PARP, Aurora kinases, or BCL-2. Cisplatin treatment of SCLC-A patient-derived xenografts induces intratumoral shifts toward SCLC-I, supporting subtype switching as a mechanism of acquired platinum resistance. We propose that matching baseline tumor subtype to therapy, as well as manipulating subtype switching on therapy, may enhance depth and duration of response for SCLC patients.

Dual Inhibition of MEK and AXL Targets Tumor Cell Heterogeneity and Prevents Resistant Outgrowth Mediated by the Epithelial-to-Mesenchymal Transition in NSCLC.

The epithelial-to-mesenchymal transition (EMT) is a dynamic epigenetic reprogramming event that occurs in a subset of tumor cells and is an initiating step toward invasion and distant metastasis. The process is reversible and gives plasticity to cancer cells to survive under variable conditions, with the acquisition of cancer stem cell-like characteristics and features such as drug resistance. Therefore, understanding survival dependencies of cells along the phenotypic spectrum of EMT will provide better strategies to target the spatial and temporal heterogeneity of tumors and prevent their ability to bypass single-inhibitor treatment strategies. To address this, we integrated the data from a selective drug screen in epithelial and mesenchymal KRAS/p53 (KP)-mutant lung tumor cells with separate datasets including reverse-phase protein array and an in vivo shRNA dropout screen. These orthogonal approaches identified AXL and MEK as potential mesenchymal and epithelial cell survival dependencies, respectively. To capture the dynamicity of EMT, incorporation of a dual fluorescence EMT sensor system into murine KP lung cancer models enabled real-time analysis of the epigenetic state of tumor cells and assessment of the efficacy of single agent or combination treatment with AXL and MEK inhibitors. Both two- and three-dimensional culture systems and in vivo models revealed that this combination treatment strategy of MEK plus AXL inhibition synergistically killed lung cancer cells by specifically targeting each phenotypic subpopulation. In conclusion, these results indicate that cotargeting the specific vulnerabilities of EMT subpopulations can prevent EMT-mediated drug resistance, effectively controlling tumor cell growth and metastasis. SIGNIFICANCE: This study shows that a novel combination of MEK and AXL inhibitors effectively bypasses EMT-mediated drug resistance in KRAS/p53-mutant non-small cell lung cancer by targeting EMT subpopulations, thereby preventing tumor cell survival.

AXL Inhibition Induces DNA Damage and Replication Stress in Non-Small Cell Lung Cancer Cells and Promotes Sensitivity to ATR Inhibitors.

AXL, a TAM (TYRO3, AXL, and MERTK) family receptor tyrosine kinase, is increasingly being recognized as a key determinant of resistance to targeted therapies, as well as chemotherapy and radiation in non-small cell lung cancer (NSCLC) and other cancers. We further show here that high levels of AXL and epithelial-to-mesenchymal transition were frequently expressed in subsets of both treatment-naïve and treatment-relapsed NSCLC. Previously, we and others have demonstrated a role for AXL in mediating DNA damage response (DDR), as well as resistance to inhibition of WEE1, a replication stress response kinase. Here, we show that BGB324 (bemcentinib), a selective small-molecule AXL inhibitor, caused DNA damage and induced replication stress, indicated by ATR/CHK1 phosphorylation, more significantly in TP53-deficient NSCLC cell lines. Similar effects were also observed in large-cell neuroendocrine carcinoma (LCNEC) cell lines. High AXL protein levels were also associated with resistance to ATR inhibition. Combined inhibition of AXL and ATR significantly decreased cell proliferation of NSCLC and LCNEC cell lines. Mechanistically, combined inhibition of AXL and ATR significantly increased RPA32 hyperphosphorylation and DNA double-strand breaks and induced markers of mitotic catastrophe. Notably, NSCLC cell lines with low levels of SLFN11, a known predictive biomarker for platinum and PARP inhibitor sensitivity, were more sensitive to AXL/ATR cotargeting. These findings demonstrate a novel and unexpected role for AXL in replication stress tolerance, with potential therapeutic implications. IMPLICATIONS: These findings demonstrate that the combination of AXL and ATR inhibitors could be a promising therapeutic combination for NSCLC, LCNEC, and other cancers.

SLFN11 biomarker status predicts response to lurbinectedin as a single agent and in combination with ATR inhibition in small cell lung cancer.

BACKGROUND: Lurbinectedin recently received FDA accelerated approval as a second line treatment option for metastatic small cell lung cancer (SCLC). However, there are currently no established biomarkers to predict SCLC sensitivity or resistance to lurbinectedin or preclinical studies to guide rational combinations. METHODS: Drug sensitivity was assayed in proliferation assays and xenograft models. Baseline proteomic profiling was performed by reverse-phase protein array. Lurbinectedin-induced changes in intracellular signaling pathways were assayed by Western blot. RESULTS: Among 21 human SCLC cell lines, cytotoxicity was observed following lurbinectedin treatment at a low dose (median IC50 0.46 nM, range, 0.06-1.83 nM). Notably, cell lines with high expression of Schlafen-11 (SLFN11) protein, a promising biomarker of response to other DNA damaging agents (e.g., chemotherapy, PARP inhibitors), were more sensitive to single-agent lurbinectedin (FC =3.2, P=0.005). SLFN11 was validated as a biomarker of sensitivity to lurbinectedin using siRNA knockdown and in xenografts representing SLFN11 high and low SCLC. Replication stress and DNA damage markers (e.g., γH2AX, phosphorylated CHK1, phosphorylated RPA32) increased in SCLC cell lines following treatment with lurbinectedin. Lurbinectedin also induced PD-L1 expression via cGAS-STING pathway activation. Finally, the combination of lurbinectedin with the ataxia telangiectasia and Rad3-related protein (ATR) inhibitors ceralasertib and berzosertib showed a greater than additive effect in SLFN11-low models. CONCLUSIONS: Together our data confirm the activity of lurbinectedin across a large cohort of SCLC models and identify SLFN11 as a top candidate biomarker for lurbinectedin sensitivity. In SLFN11-low SCLC cell lines which are relatively resistance to lurbinectedin, the addition of an ATR inhibitor to lurbinectedin re-sensitized otherwise resistant cells, confirming previous observations that SLFN11 is a master regulator of DNA damage response independent of ATR, and the absence of SLFN11 leads to synthetic lethality with ATR inhibition. This study provides a rationale for lurbinectedin in combination with ATR inhibitors to overcome resistance in SCLC with low SLFN11 expression.

Lung cancer models reveal SARS-CoV-2-induced EMT contributes to COVID-19 pathophysiology.

COVID-19 is an infectious disease caused by SARS-CoV-2, which enters host cells via the cell surface proteins ACE2 and TMPRSS2. Using a variety of normal and malignant models and tissues from the aerodigestive and respiratory tracts, we investigated the expression and regulation of ACE2 and TMPRSS2. We find that ACE2 expression is restricted to a select population of highly epithelial cells. Notably, infection with SARS-CoV-2 in cancer cell lines, bronchial organoids, and patient nasal epithelium, induces metabolic and transcriptional changes consistent with epithelial to mesenchymal transition (EMT), including upregulation of ZEB1 and AXL, resulting in an increased EMT score. Additionally, a transcriptional loss of genes associated with tight junction function occurs with SARS-CoV-2 infection. The SARS-CoV-2 receptor, ACE2, is repressed by EMT via TGFbeta, ZEB1 overexpression and onset of EGFR TKI inhibitor resistance. This suggests a novel model of SARS-CoV-2 pathogenesis in which infected cells shift toward an increasingly mesenchymal state, associated with a loss of tight junction components with acute respiratory distress syndrome-protective effects. AXL-inhibition and ZEB1-reduction, as with bemcentinib, offers a potential strategy to reverse this effect. These observations highlight the utility of aerodigestive and, especially, lung cancer model systems in exploring the pathogenesis of SARS-CoV-2 and other respiratory viruses, and offer important insights into the potential mechanisms underlying the morbidity and mortality of COVID-19 in healthy patients and cancer patients alike.

STING Pathway Expression Identifies NSCLC With an Immune-Responsive Phenotype.

INTRODUCTION: Although the combination of anti-programmed cell death-1 or anti-programmed cell death ligand-1 (PD-L1) with platinum chemotherapy is a standard of care for NSCLC, clinical responses vary. Even though predictive biomarkers (which include PD-L1 expression, tumor mutational burden, and inflamed immune microenvironment) are validated for immunotherapy, their relevance to chemoimmunotherapy combinations is less clear. We have recently reported that activation of the stimulator of interferon genes (STING) innate immune pathway enhances immunotherapy response in SCLC. Here, we hypothesize that STING pathway activation may predict and underlie predictive correlates of antitumor immunity in NSCLC. METHODS: We analyzed transcriptomic and proteomic profiles in two NSCLC cohorts from our institution (treatment-naive patients in the Profiling of Resistance Patterns and Oncogenic Signaling Pathways in Evaluation of Cancers of the Thorax study and relapsed patients in the Biomarker-Integrated Approaches of Targeted Therapy for Lung Cancer Elimination study) and The Cancer Genome Atlas (N = 1320). Tumors were stratified by STING activation on the basis of protein or mRNA expression of cyclic GMP-AMP synthase, phospho-STING, and STING-mediated chemokines (chemokine ligand 5 [CCL5] and C-X-C motif chemokine 10 [CXCL10]). STING activation in patient tumors and in platinum-treated preclinical NSCLC models was correlated with biomarkers of immunotherapy response. RESULTS: STING activation is associated with higher levels of intrinsic DNA damage, targetable immune checkpoints, and chemokines in treatment-naive and relapsed lung adenocarcinoma. We observed that tumors with lower STING and immune gene expression show higher frequency of serine-threonine kinase 11 (STK11) mutations; however, we identified a subset of these tumors that are TP53 comutated and display high immune- and STING-related gene expression. Treatment with cisplatin increases STING pathway activation and PD-L1 expression in multiple NSCLC preclinical models, including adeno- and squamous cell carcinoma. CONCLUSIONS: STING pathway activation in NSCLC predicts features of immunotherapy response and is enhanced by cisplatin treatment. This suggests a possible predictive biomarker and mechanism for improved response to chemoimmunotherapy combinations.

Combination Treatment of the Oral CHK1 Inhibitor, SRA737, and Low-Dose Gemcitabine Enhances the Effect of Programmed Death Ligand 1 Blockade by Modulating the Immune Microenvironment in SCLC.

INTRODUCTION: Despite the enthusiasm surrounding cancer immunotherapy, most SCLC patients show very modest response to immune checkpoint inhibitor monotherapy treatment. Therefore, there is growing interest in combining immune checkpoint blockade with chemotherapy and other treatments to enhance immune checkpoint blockade efficacy. Based on favorable clinical trial results, chemotherapy and immunotherapy combinations have been recently approved by the U.S. Food and Drug Administration for frontline treatment for SCLC. METHODS AND RESULTS: Here, we show that combined treatment of SRA737, an oral CHK1 inhibitor, and anti-programmed death ligand 1 (PD-L1) leads to an antitumor response in multiple cancer models, including SCLC. We further show that combining low, non-cytotoxic doses of gemcitabine with SRA737 + anti-PD-L1/anti-PD-1 significantly increased antitumorigenic CD8+ cytotoxic T cells, dendritic cells, and M1 macrophage populations in an SCLC model. This regimen also led to a significant decrease in immunosuppressive M2 macrophage and myeloid-derived suppressor cell populations, as well as an increase in the expression of the type I interferon beta 1 gene, IFNß, and chemokines, CCL5 and CXCL10. CONCLUSIONS: Given that anti-PD-L1/anti-PD-1 drugs have recently been approved as monotherapy and in combination with chemotherapy for the treatment of SCLC, and that the SRA737 + low dose gemcitabine regimen is currently in clinical trials for SCLC and other malignancies, our preclinical data provide a strong rational for combining this regimen with inhibitors of the PD-L1/PD-1 pathway.

Integrated Approaches for the Use of Large Datasets to Identify Rational Therapies for the Treatment of Lung Cancers.

The benefit and burden of contemporary techniques for the molecular characterization of samples is the vast amount of data generated. In the era of "big data", it has become imperative that we develop multi-disciplinary teams combining scientists, clinicians, and data analysts. In this review, we discuss a number of approaches developed by our University of Texas MD Anderson Lung Cancer Multidisciplinary Program to process and utilize such large datasets with the goal of identifying rational therapeutic options for biomarker-driven patient subsets. Large integrated datasets such as the The Cancer Genome Atlas (TCGA) for patient samples and the Cancer Cell Line Encyclopedia (CCLE) for tumor derived cell lines include genomic, transcriptomic, methylation, miRNA, and proteomic profiling alongside clinical data. To best use these datasets to address urgent questions such as whether we can define molecular subtypes of disease with specific therapeutic vulnerabilities, to quantify states such as epithelial-to-mesenchymal transition that are associated with resistance to treatment, or to identify potential therapeutic agents in models of cancer that are resistant to standard treatments required the development of tools for systematic, unbiased high-throughput analysis. Together, such tools, used in a multi-disciplinary environment, can be leveraged to identify novel treatments for molecularly defined subsets of cancer patients, which can be easily and rapidly translated from benchtop to bedside.

Differential Sensitivity Analysis for Resistant Malignancies (DISARM) Identifies Common Candidate Therapies across Platinum-Resistant Cancers.

PURPOSE: Despite a growing arsenal of approved drugs, therapeutic resistance remains a formidable and, often, insurmountable challenge in cancer treatment. The mechanisms underlying therapeutic resistance remain largely unresolved and, thus, examples of effective combinatorial or sequential strategies to combat resistance are rare. Here, we present Differential Sensitivity Analysis for Resistant Malignancies (DISARM), a novel, integrated drug screen analysis tool designed to address this dilemma. EXPERIMENTAL DESIGN: DISARM, a software package and web-based application, analyzes drug response data to prioritize candidate therapies for models with resistance to a reference drug and to assess whether response to a reference drug can be utilized to predict future response to other agents. Using cisplatin as our reference drug, we applied DISARM to models from nine cancers commonly treated with first-line platinum chemotherapy including recalcitrant malignancies such as small cell lung cancer (SCLC) and pancreatic adenocarcinoma (PAAD). RESULTS: In cisplatin-resistant models, DISARM identified novel candidates including multiple inhibitors of PI3K, MEK, and BCL-2, among other classes, across unrelated malignancies. Additionally, DISARM facilitated the selection of predictive biomarkers of response and identification of unique molecular subtypes, such as contrasting ASCL1-low/cMYC-high SCLC targetable by AURKA inhibitors and ASCL1-high/cMYC-low SCLC targetable by BCL-2 inhibitors. Utilizing these predictions, we assessed several of DISARM's top candidates, including inhibitors of AURKA, BCL-2, and HSP90, to confirm their activity in cisplatin-resistant SCLC models. CONCLUSIONS: DISARM represents the first validated tool to analyze large-scale in vitro drug response data to statistically optimize candidate drug and biomarker selection aimed at overcoming candidate drug resistance.

Randomized, Double-Blind, Phase II Study of Temozolomide in Combination With Either Veliparib or Placebo in Patients With Relapsed-Sensitive or Refractory Small-Cell Lung Cancer.

Purpose Both temozolomide (TMZ) and poly (ADP-ribose) polymerase (PARP) inhibitors are active in small-cell lung cancer (SCLC). This phase II, randomized, double-blind study evaluated whether addition of the PARP inhibitor veliparib to TMZ improves 4-month progression-free survival (PFS). Patients and Methods A total of 104 patients with recurrent SCLC were randomly assigned 1:1 to oral veliparib or placebo 40 mg twice daily, days 1 to 7, and oral TMZ 150 to 200 mg/m2/day, days 1 to 5, of a 28-day cycle until disease progression, unacceptable toxicity, or withdrawal of consent. Response was determined by imaging at weeks 4 and 8, and every 8 weeks thereafter. Improvement in PFS at 4 months was the primary end point. Secondary objectives included overall response rate (ORR), overall survival (OS), and safety and tolerability of veliparib with TMZ. Exploratory objectives included PARP-1 and SLFN11 immunohistochemical expression, MGMT promoter methylation, and circulating tumor cell quantification. Results No significant difference in 4-month PFS was noted between TMZ/veliparib (36%) and TMZ/placebo (27%; P = .19); median OS was also not improved significantly with TMZ/veliparib (8.2 months; 95% CI, 6.4 to 12.2 months; v 7.0 months; 95% CI, 5.3 to 9.5 months; P = .50). However, ORR was significantly higher in patients receiving TMZ/veliparib compared with TMZ/placebo (39% v 14%; P = .016). Grade 3/4 thrombocytopenia and neutropenia more commonly occurred with TMZ/veliparib: 50% versus 9% and 31% versus 7%, respectively. Significantly prolonged PFS (5.7 v 3.6 months; P = .009) and OS (12.2 v 7.5 months; P = .014) were observed in patients with SLFN11-positive tumors treated with TMZ/veliparib. Conclusion Four-month PFS and median OS did not differ between the two arms, whereas a significant improvement in ORR was observed with TMZ/veliparib. SLFN11 expression was associated with improved PFS and OS in patients receiving TMZ/veliparib, suggesting a promising biomarker of PARP-inhibitor sensitivity in SCLC.

Protein expression of TTF1 and cMYC define distinct molecular subgroups of small cell lung cancer with unique vulnerabilities to aurora kinase inhibition, DLL3 targeting, and other targeted therapies.

Small cell lung cancer (SCLC) is a recalcitrant cancer for which no new treatments have been approved in over 30 years. While molecular subtyping now guides treatment selection for patients with non-small cell lung cancer and other cancers, SCLC is still treated as a single disease entity. Using model-based clustering, we found two major proteomic subtypes of SCLC characterized by either high thyroid transcription factor-1 (TTF1)/low cMYC protein expression or high cMYC/low TTF1. Applying "drug target constellation" (DTECT) mapping, we further show that protein levels of TTF1 and cMYC predict response to targeted therapies including aurora kinase, Bcl2, and HSP90 inhibitors. Levels of TTF1 and DLL3 were also highly correlated in preclinical models and patient tumors. TTF1 (used in the diagnosis lung cancer) could therefore be used as a surrogate of DLL3 expression to identify patients who may respond to the DLL3 antibody-drug conjugate rovalpituzumab tesirine. These findings suggest that TTF1, cMYC or other protein markers identified here could be used to identify subgroups of SCLC patients who may respond preferentially to several emerging targeted therapies.

A phase 2, open-label, multi-center study of amuvatinib in combination with platinum etoposide chemotherapy in platinum-refractory small cell lung cancer patients.

BACKGROUND: Amuvatinib (MP-470) is a multi-targeted kinase inhibitor with potent activity against c-Kit, synergistic with DNA-damaging agents. We evaluated amuvatinib in combination with platinum-etoposide (EP) chemotherapy by objective response rate, survival, and tolerability in platinum-refractory small cell lung cancer (SCLC) patients. METHODS: This study used a Simon 2-stage design requiring ≥3 centrally confirmed responses in the first 21 subjects. Subjects received EP with 300 mg amuvatinib orally three times daily in cycles of 21 days. A three-day amuvatinib run-in period before EP occurred in Cycle 1. Subjects received the same EP chemotherapy regimen given prior to progression/relapse. RESULTS: Among 23 subjects treated, we observed four PRs (17.4%) per RECIST 1.1, only two of which were centrally confirmed (8.7%, response duration 119, 151 days). Three subjects (13%) had confirmed stable disease. c-Kit H-score was ≥100 in two subjects whose respective durations of disease control were 151 and 256 days. CONCLUSIONS: The addition of amuvatinib to EP chemotherapy in unselected, platinum-refractory SCLC did not meet the primary endpoint of ≥3 confirmed responses in stage 1. However, high c-Kit expression in two subjects with durable disease control suggests the potential for further study of amuvatinib in SCLC patients with high c-Kit expression.

Dynamic variations in epithelial-to-mesenchymal transition (EMT), ATM, and SLFN11 govern response to PARP inhibitors and cisplatin in small cell lung cancer.

Small cell lung cancer (SCLC) is one of the most aggressive forms of cancer, with a 5-year survival <7%. A major barrier to progress is the absence of predictive biomarkers for chemotherapy and novel targeted agents such as PARP inhibitors. Using a high-throughput, integrated proteomic, transcriptomic, and genomic analysis of SCLC patient-derived xenografts (PDXs) and profiled cell lines, we identified biomarkers of drug sensitivity and determined their prevalence in patient tumors. In contrast to breast and ovarian cancer, PARP inhibitor response was not associated with mutations in homologous recombination (HR) genes (e.g., BRCA1/2) or HRD scores. Instead, we found several proteomic markers that predicted PDX response, including high levels of SLFN11 and E-cadherin and low ATM. SLFN11 and E-cadherin were also significantly associated with in vitro sensitivity to cisplatin and topoisomerase1/2 inhibitors (all commonly used in SCLC). Treatment with cisplatin or PARP inhibitors downregulated SLFN11 and E-cadherin, possibly explaining the rapid development of therapeutic resistance in SCLC. Supporting their functional role, silencing SLFN11 reduced in vitro sensitivity and drug-induced DNA damage; whereas ATM knockdown or pharmacologic inhibition enhanced sensitivity. Notably, SCLC with mesenchymal phenotypes (i.e., loss of E-cadherin and high epithelial-to-mesenchymal transition (EMT) signature scores) displayed striking alterations in expression of miR200 family and key SCLC genes (e.g., NEUROD1, ASCL1, ALDH1A1, MYCL1). Thus, SLFN11, EMT, and ATM mediate therapeutic response in SCLC and warrant further clinical investigation as predictive biomarkers.

Activation of the PI3K/mTOR Pathway following PARP Inhibition in Small Cell Lung Cancer.

Small cell lung cancer (SCLC) is an aggressive malignancy with limited treatment options. We previously found that PARP is overexpressed in SCLC and that targeting PARP reduces cell line and tumor growth in preclinical models. However, SCLC cell lines with PI3K/mTOR pathway activation were relatively less sensitive to PARP inhibition. In this study, we investigated the proteomic changes in PI3K/mTOR and other pathways that occur following PAPR inhibition and/or knockdown in vitro and in vivo. Using reverse-phase protein array, we found the proteins most significantly upregulated following treatment with the PARP inhibitors olaparib and rucaparib were in the PI3K/mTOR pathway (p-mTOR, p-AKT, and pS6) (p≤0.02). Furthermore, amongst the most significantly down-regulated proteins were LKB1 and its targets AMPK and TSC, which negatively regulate the PI3K pathway (p≤0.042). Following PARP knockdown in cell lines, phosphorylated mTOR, AKT and S6 were elevated and LKB1 signaling was diminished. Global ATP concentrations increased following PARP inhibition (p≤0.02) leading us to hypothesize that the observed increased PI3K/mTOR pathway activation following PARP inhibition results from decreased ATP usage and a subsequent decrease in stress response signaling via LKB1. Based on these results, we then investigated whether co-targeting with a PARP and PI3K inhibitor (BKM-120) would work better than either single agent alone. A majority of SCLC cell lines were sensitive to BKM-120 at clinically achievable doses, and cMYC expression was the strongest biomarker of response. At clinically achievable doses of talazoparib (the most potent PARP inhibitor in SCLC clinical testing) and BKM-120, an additive effect was observed in vitro. When tested in two SCLC animal models, a greater than additive interaction was seen (p≤0.008). The data presented here suggest that combining PARP and PI3K inhibitors enhances the effect of either agent alone in preclinical models of SCLC, warranting further investigation of such combinations in SCLC patients.

A Patient-Derived, Pan-Cancer EMT Signature Identifies Global Molecular Alterations and Immune Target Enrichment Following Epithelial-to-Mesenchymal Transition.

PURPOSE: We previously demonstrated the association between epithelial-to-mesenchymal transition (EMT) and drug response in lung cancer using an EMT signature derived in cancer cell lines. Given the contribution of tumor microenvironments to EMT, we extended our investigation of EMT to patient tumors from 11 cancer types to develop a pan-cancer EMT signature. EXPERIMENTAL DESIGN: Using the pan-cancer EMT signature, we conducted an integrated, global analysis of genomic and proteomic profiles associated with EMT across 1,934 tumors including breast, lung, colon, ovarian, and bladder cancers. Differences in outcome and in vitro drug response corresponding to expression of the pan-cancer EMT signature were also investigated. RESULTS: Compared with the lung cancer EMT signature, the patient-derived, pan-cancer EMT signature encompasses a set of core EMT genes that correlate even more strongly with known EMT markers across diverse tumor types and identifies differences in drug sensitivity and global molecular alterations at the DNA, RNA, and protein levels. Among those changes associated with EMT, pathway analysis revealed a strong correlation between EMT and immune activation. Further supervised analysis demonstrated high expression of immune checkpoints and other druggable immune targets, such as PD1, PD-L1, CTLA4, OX40L, and PD-L2, in tumors with the most mesenchymal EMT scores. Elevated PD-L1 protein expression in mesenchymal tumors was confirmed by IHC in an independent lung cancer cohort. CONCLUSIONS: This new signature provides a novel, patient-based, histology-independent tool for the investigation of EMT and offers insights into potential novel therapeutic targets for mesenchymal tumors, independent of cancer type, including immune checkpoints.