YAP1 status defines two intrinsic subtypes of LCNEC with distinct molecular features and therapeutic vulnerabilities.

PURPOSE: Large cell neuroendocrine carcinoma (LCNEC) is a high-grade neuroendocrine malignancy that, like small cell lung cancer (SCLC), is associated with an absence of druggable oncogenic drivers and dismal prognosis. In contrast to SCLC, however, there is little evidence to guide optimal treatment strategies which are often adapted from SCLC and non-small cell lung cancer (NSCLC) approaches. EXPERIMENTAL DESIGN: To better define the biology of LCNEC, we analyzed cell line and patient genomic data and performed immunohistochemistry and single-cell (sc)RNAseq of core needle biopsies from LCNEC patients and preclinical models. RESULTS: Here, we demonstrate that the presence or absence of YAP1 distinguishes two subsets of LCNEC. The YAP1-high subset is mesenchymal and inflamed and characterized, alongside TP53 mutations, by co-occurring alterations in CDKN2A/B and SMARCA4. Therapeutically, the YAP1-high subset demonstrates vulnerability to MEK and AXL targeting strategies, including a novel preclinical AXL CAR-T cell. Meanwhile, the YAP1-low subset is epithelial and immune-cold and more commonly features TP53 and RB1 co-mutations, similar to those observed in pure SCLC. Notably, the YAP1-low subset is also characterized by expression of SCLC subtype-defining transcription factors - especially ASCL1 and NEUROD1 - and, as expected given its transcriptional similarities to SCLC, exhibits putative vulnerabilities reminiscent of SCLC, including Delta-like ligand 3 (DLL3) and CD56 targeting, as with novel preclinical DLL3 and CD56 CAR T-cells, and DNA damage repair (DDR) inhibition. CONCLUSION: YAP1 defines distinct subsets of LCNEC with unique biology. These findings highlight the potential for YAP1 to guide personalized treatment strategies for LCNEC.

DNA damage response signatures are associated with frontline chemotherapy response and routes of tumor evolution in extensive stage small cell lung cancer.

Introduction: A hallmark of small cell lung cancer (SCLC) is its recalcitrance to therapy. While most SCLCs respond to frontline therapy, resistance inevitably develops. Identifying phenotypes potentiating chemoresistance and immune evasion is a crucial unmet need. Previous reports have linked upregulation of the DNA damage response (DDR) machinery to chemoresistance and immune evasion across cancers. However, it is unknown if SCLCs exhibit distinct DDR phenotypes. Methods: To study SCLC DDR phenotypes, we developed a new DDR gene analysis method and applied it to SCLC clinical samples, in vitro , and in vivo model systems. We then investigated how DDR regulation is associated with SCLC biology, chemotherapy response, and tumor evolution following therapy. Results: Using multi-omic profiling, we demonstrate that SCLC tumors cluster into three DDR phenotypes with unique molecular features. Hallmarks of these DDR clusters include differential expression of DNA repair genes, increased replication stress, and heightened G2/M cell cycle arrest. SCLCs with elevated DDR phenotypes exhibit increased neuroendocrine features and decreased "inflamed" biomarkers, both within and across SCLC subtypes. Treatment naive DDR status identified SCLC patients with different responses to frontline chemotherapy. Tumors with initial DDR Intermediate and DDR High phenotypes demonstrated greater tendency for subtype switching and emergence of heterogeneous phenotypes following treatment. Conclusions: We establish that SCLC can be classified into one of three distinct, clinically relevant DDR clusters. Our data demonstrates that DDR status plays a key role in shaping SCLC phenotypes, chemotherapy response, and patterns of tumor evolution. Future work targeting DDR specific phenotypes will be instrumental in improving patient outcomes.

CoCo-ST: Comparing and Contrasting Spatial Transcriptomics data sets using graph contrastive learning.

Traditional feature dimension reduction methods have been widely used to uncover biological patterns or structures within individual spatial transcriptomics data. However, these methods are designed to yield feature representations that emphasize patterns or structures with dominant high variance, such as the normal tissue spatial pattern in a precancer setting. Consequently, they may inadvertently overlook patterns of interest that are potentially masked by these high-variance structures. Herein we present our graph contrastive feature representation method called CoCo-ST (Comparing and Contrasting Spatial Transcriptomics) to overcome this limitation. By incorporating a background data set representing normal tissue, this approach enhances the identification of interesting patterns in a target data set representing precancerous tissue. Simultaneously, it mitigates the influence of dominant common patterns shared by the background and target data sets. This enables discerning biologically relevant features crucial for capturing tissue-specific patterns, a capability we showcased through the analysis of serial mouse precancerous lung tissue samples.

Molecular classification and biomarkers of outcome with immunotherapy in extensive-stage small-cell lung cancer: analyses of the CASPIAN phase 3 study.

BACKGROUND: We explored potential predictive biomarkers of immunotherapy response in patients with extensive-stage small-cell lung cancer (ES-SCLC) treated with durvalumab (D) + tremelimumab (T) + etoposide-platinum (EP), D + EP, or EP in the randomized phase 3 CASPIAN trial. METHODS: 805 treatment-naïve patients with ES-SCLC were randomized (1:1:1) to receive D + T + EP, D + EP, or EP. The primary endpoint was overall survival (OS). Patients were required to provide an archived tumor tissue block (or ≥ 15 newly cut unstained slides) at screening, if these samples existed. After assessment for programmed cell death ligand-1 expression and tissue tumor mutational burden, residual tissue was used for additional molecular profiling including by RNA sequencing and immunohistochemistry. RESULTS: In 182 patients with transcriptional molecular subtyping, OS with D ± T + EP was numerically highest in the SCLC-inflamed subtype (n = 10, median 24.0 months). Patients derived benefit from immunotherapy across subtypes; thus, additional biomarkers were investigated. OS benefit with D ± T + EP versus EP was greater with high versus low CD8A expression/CD8 cell density by immunohistochemistry, but with no additional benefit with D + T + EP versus D + EP. OS benefit with D + T + EP versus D + EP was associated with high expression of CD4 (median 25.9 vs. 11.4 months) and antigen-presenting and processing machinery (25.9 vs. 14.6 months) and MHC I and II (23.6 vs. 17.3 months) gene signatures, and with higher MHC I expression by immunohistochemistry. CONCLUSIONS: These findings demonstrate the tumor microenvironment is important in mediating better outcomes with D ± T + EP in ES-SCLC, with canonical immune markers associated with hypothesized immunotherapy mechanisms of action defining patient subsets that respond to D ± T. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03043872.

Joint multi-omics discriminant analysis with consistent representation learning using PANDA.

Integrative multi-omics analysis provides deeper insight and enables better and more realistic modeling of the underlying biology and causes of diseases than does single omics analysis. Although several integrative multi-omics analysis methods have been proposed and demonstrated promising results in integrating distinct omics datasets, inconsistent distribution of the different omics data, which is caused by technology variations, poses a challenge for paired integrative multi-omics methods. In addition, the existing discriminant analysis-based integrative methods do not effectively exploit correlation and consistent discriminant structures, necessitating a compromise between correlation and discrimination in using these methods. Herein we present PAN-omics Discriminant Analysis (PANDA), a joint discriminant analysis method that seeks omics-specific discriminant common spaces by jointly learning consistent discriminant latent representations for each omics. PANDA jointly maximizes between-class and minimizes within-class omics variations in a common space and simultaneously models the relationships among omics at the consistency representation and cross-omics correlation levels, overcoming the need for compromise between discrimination and correlation as with the existing integrative multi-omics methods. Because of the consistency representation learning incorporated into the objective function of PANDA, this method seeks a common discriminant space to minimize the differences in distributions among omics, can lead to a more robust latent representations than other methods, and is against the inconsistency of the different omics. We compared PANDA to 10 other state-of-the-art multi-omics data integration methods using both simulated and real-world multi-omics datasets and found that PANDA consistently outperformed them while providing meaningful discriminant latent representations. PANDA is implemented using both R and MATLAB, with codes available at https://github.com/WuLabMDA/PANDA.

Comprehensive analysis of transcription factor-based molecular subtypes and their correlation to clinical outcomes in small-cell lung cancer.

BACKGROUND: Recent studies have reported the predictive and prognostic value of novel transcriptional factor-based molecular subtypes in small-cell lung cancer (SCLC). We conducted an in-depth analysis pairing multi-omics data with immunohistochemistry (IHC) to elucidate the underlying characteristics associated with differences in clinical outcomes between subtypes. METHODS: IHC (n = 252), target exome sequencing (n = 422), and whole transcriptome sequencing (WTS, n = 189) data generated from 427 patients (86.4% males, 13.6% females) with SCLC were comprehensively analysed. The differences in the mutation profile, gene expression profile, and inflammed signatures were analysed according to the IHC-based molecular subtype. FINDINGS: IHC-based molecular subtyping, comprised of 90 limited-disease (35.7%) and 162 extensive-disease (64.3%), revealed a high incidence of ASCL1 subtype (IHC-A, 56.3%) followed by ASCL1/NEUROD1 co-expressed (IHC-AN, 17.9%), NEUROD1 (IHC-N, 12.3%), POU2F3 (IHC-P, 9.1%), triple-negative (IHC-TN, 4.4%) subtypes. IHC-based subtype showing high concordance with WTS-based subtyping and non-negative matrix factorization (NMF) clusterization method. IHC-AN subtype resembled IHC-A (rather than IHC-N) in terms of both gene expression profiles and clinical outcomes. Favourable median overall survival was observed in IHC-A (15.2 months) compared to IHC-N (8.0 months, adjusted HR 2.3, 95% CI 1.4-3.9, p = 0.002) and IHC-P (8.3 months, adjusted HR 1.7, 95% CI 0.9-3.2, p = 0.076). Inflamed tumours made up 25% of cases (including 53% of IHC-P, 26% of IHC-A, 17% of IHC-AN, but only 11% of IHC-N). Consistent with recent findings, inflamed tumours were more likely to benefit from first-line immunotherapy treatment than non-inflamed phenotype (p = 0.002). INTERPRETATION: This study provides fundamental data, including the incidence and basic demographics of molecular subtypes of SCLC using both IHC and WTS from a comparably large, real-world Asian/non-Western patient cohort, showing high concordance with the previous NMF-based SCLC model. In addition, we revealed underlying biological pathway activities, immunogenicity, and treatment outcomes based on molecular subtype, possibly related to the difference in clinical outcomes, including immunotherapy response. FUNDING: This work was supported by AstraZeneca, Future Medicine 2030 Project of the Samsung Medical Center [grant number SMX1240011], the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) [grant number 2020R1C1C1010626] and the 7th AstraZeneca-KHIDI (Korea Health Industry Development Institute) oncology research program.

Immune heterogeneity in small-cell lung cancer and vulnerability to immune checkpoint blockade.

Atezolizumab (anti-PD-L1), combined with carboplatin and etoposide (CE), is now a standard of care for extensive-stage small-cell lung cancer (ES-SCLC). A clearer understanding of therapeutically relevant SCLC subsets could identify rational combination strategies and improve outcomes. We conduct transcriptomic analyses and non-negative matrix factorization on 271 pre-treatment patient tumor samples from IMpower133 and identify four subsets with general concordance to previously reported SCLC subtypes (SCLC-A, -N, -P, and -I). Deeper investigation into the immune heterogeneity uncovers two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes, demonstrating immune cell infiltration hallmarks. The NE tumors with low tumor-associated macrophage (TAM) but high T-effector signals demonstrate longer overall survival with PD-L1 blockade and CE versus CE alone than non-NE tumors with high TAM and high T-effector signal. Our study offers a clinically relevant approach to discriminate SCLC patients likely benefitting most from immunotherapies and highlights the complex mechanisms underlying immunotherapy responses.

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.

Impact of psychosocial factors on the success of neuromodulation treatment for patients with persistent pain.

INTRODUCTION: Significant interindividual variability in spinal cord stimulation (SCS) outcomes exists. Due to its high cost and risks of complications, criteria to guide patient selection for SCS trials and their outcomes would be helpful. With increased focus on the use of patient-reported outcomes to improve care, we aim to evaluate the National Institute of Health Patient Reported Outcome Measurement Information System measures for an association with successful SCS trials in patients with persistent pain. METHODS: Our prospective, observational study enrolled 60 patients with persistent pain who underwent an SCS trial. Patients completed demographic and Patient Reported Outcome Measurement Information System computer adaptive test (PROMIS CAT) assessments to measure self-reported pain interference, depression, anxiety, physical functioning, and sleep disturbance at the time they presented for placement of their trial device. RESULTS: Of the 58 patients who underwent successful electrode placement, 11 had an unsuccessful trial. There were no differences in patient demographics between patients with a successful and an unsuccessful trial. Patients who had a successful SCS trial reported lower pre-trial levels of anxiety, depression, and sleep disturbance and decreased post-trial levels of depression, sleep disturbance, and pain interference. CONCLUSIONS: We found that patients with high levels of depression, anxiety, and sleep disturbance using the PROMIS CAT were predictive of unsuccessful trials. In addition, we found that patients with successful SCS trials reported lower levels of these domains on PROMIS CAT administered at the end of the trial.

Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes.

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.

Clinical Pharmacology Profile of AMG 119, the First Chimeric Antigen Receptor T (CAR-T) Cell Therapy Targeting Delta-Like Ligand 3 (DLL3), in Patients with Relapsed/Refractory Small Cell Lung Cancer (SCLC).

With the promise of a potentially single-dose curative regimen, CAR-T cell therapies have brought a paradigm shift in the treatment and management of hematological malignancies with 6 approved products in the USA. However, there are no approved CAR-T cell therapies for solid tumors. Herein, we report the clinical pharmacology profile of AMG 119, the first CAR-T cell therapy targeting delta-like ligand 3 (DLL3), in patients with relapsed/refractory (R/R) small cell lung cancer (SCLC). AMG 119 demonstrated robust cellular expansion with long-lasting cell persistence and a favorable exposure-response relationship. AMG 119 has been demonstrated to be clinically safe and well tolerated at the doses tested, with no dose-limiting toxicities (DLTs) reported. This is the first publication of the clinical pharmacology profile of a CAR-T cell therapy in SCLC, with encouraging cellular kinetics data supporting the potential for CAR-T cell therapy in solid tumor space.

Real-World Efficacy and Safety of Amivantamab for EGFR-Mutant NSCLC.

INTRODUCTION: Amivantamab-vmjw (amivantamab) is a bispecific EGFR/MET antibody approved for patients with advanced NSCLC with EGFR exon 20 insertion mutations, after prior therapy. Nevertheless, the benefits and safety of amivantamab in other EGFR-mutant lung cancer, with or without osimertinib, and with concurrent radiation therapy, are less known. METHODS: We queried the MD Anderson Lung Cancer GEMINI, Fred Hutchinson Cancer Research Center, University of California Davis Comprehensive Cancer Center, and Stanford Cancer Center's database for patients with EGFR-mutant NSCLC treated with amivantamab, not on a clinical trial. The data analyzed included initial response, duration of treatment, and concomitant radiation safety in overall population and prespecified subgroups. RESULTS: A total of 61 patients received amivantamab. Median age was 65 (31-81) years old; 72.1% were female; and 77% were patients with never smoking history. Median number of prior lines of therapies was four. On the basis of tumor's EGFR mutation, 39 patients were in the classical mutation cohort, 15 patients in the exon 20 cohort, and seven patients in the atypical cohort. There were 37 patients (58.7%) who received amivantamab concomitantly with osimertinib and 25 patients (39.1%) who received concomitant radiation. Furthermore, 54 patients were assessable for response in the overall population; 19 patients (45.2%) had clinical response and disease control rate (DCR) was 64.3%. In the classical mutation cohort of the 33 assessable patients, 12 (36.4%) had clinical response and DCR was 48.5%. In the atypical mutation cohort, six of the seven patients (85.7%) had clinical response and DCR was 100%. Of the 13 assessable patients in the exon 20 cohort, five patients (35.7%) had clinical response and DCR was 64.3%. Adverse events reported with amivantamab use were similar as previously described in product labeling. No additional toxicities were noted when amivantamab was given with radiation with or without osimertinib. CONCLUSIONS: Our real-world multicenter analysis revealed that amivantamab is a potentially effective treatment option for patients with EGFR mutations outside of exon 20 insertion mutations. The combination of osimertinib with amivantamab is safe and feasible. Radiation therapy also seems safe when administered sequentially or concurrently with amivantamab.

Distinct patterns of auto-reactive antibodies associated with organ-specific immune-related adverse events.

The roles of preexisting auto-reactive antibodies in immune-related adverse events (irAEs) associated with immune checkpoint inhibitor therapy are not well defined. Here, we analyzed plasma samples longitudinally collected at predefined time points and at the time of irAEs from 58 patients with immunotherapy naïve metastatic non-small cell lung cancer treated on clinical protocol with ipilimumab and nivolumab. We used a proteomic microarray system capable of assaying antibody reactivity for IgG and IgM fractions against 120 antigens for systemically evaluating the correlations between auto-reactive antibodies and certain organ-specific irAEs. We found that distinct patterns of auto-reactive antibodies at baseline were associated with the subsequent development of organ-specific irAEs. Notably, ACHRG IgM was associated with pneumonitis, anti-cytokeratin 19 IgM with dermatitis, and anti-thyroglobulin IgG with hepatitis. These antibodies merit further investigation as potential biomarkers for identifying high-risk populations for irAEs and/or monitoring irAEs during immunotherapy treatment. Trial registration: ClinicalTrials.gov identifier: NCT03391869.

Clinical and molecular characterization of long-term survivors with extensive-stage small cell lung cancer treated with first-line atezolizumab plus carboplatin and etoposide.

OBJECTIVES: In the Phase I/III IMpower133 study, first-line atezolizumab plus carboplatin and etoposide (CP/ET) treatment for extensive-stage small cell lung cancer (ES-SCLC) significantly improved overall survival (OS) and progression-free survival versus placebo plus CP/ET. We explored patient and disease characteristics associated with long-term survival in IMpower133, and associations of differential gene expression and SCLC-A (ASCL1-driven), SCLC-N (NEUROD1-driven), SCLC-P (POU2F3-driven), and SCLC-inflamed (SCLC-I) transcriptional subtypes with long-term survival. MATERIALS AND METHODS: Patients with previously untreated ES-SCLC were randomized 1:1 to four 21-day cycles of CP/ET with atezolizumab or placebo. Long-term survivors (LTS) were defined as patients who lived ≥ 18 months post randomization. A generalized linear model was used to evaluate the odds of living ≥ 18 months. Differential gene expression was analyzed using RNA-sequencing data in LTS and non-LTS. OS was assessed by T-effector and B-cell gene signature expression. Distribution of SCLC transcriptional subtypes was assessed in LTS and non-LTS. RESULTS: More LTS were in the atezolizumab arm (34%) than in the placebo arm (20%). The odds ratio for living ≥ 18 months in the atezolizumab arm versus the placebo arm was 2.1 (P < 0.03). Enhanced immune-related signaling was seen in LTS in both arms. Exploratory OS analyses showed atezolizumab treatment benefit versus placebo across T-effector and B-cell gene signature expression subgroups. A higher proportion of LTS than non-LTS in both arms had the SCLC-I subtype; this difference was particularly pronounced in the atezolizumab arm. CONCLUSION: These exploratory analyses suggest that long-term survival is more likely with atezolizumab than placebo in ES-SCLC, confirming the treatment benefit of the IMpower133 regimen. CLINICALTRIAL: gov Identifier: NCT02763579.

Unfolding the secrets of small cell lung cancer progression: Novel approaches and insights through rapid autopsies.

The understanding of small cell lung cancer (SCLC) biology has increased dramatically in recent years, but the processes that allow SCLC to progress rapidly remain poorly understood. Here, we advocate the integration of rapid autopsies and preclinical models into SCLC research as a comprehensive strategy with the potential to revolutionize current treatment paradigms.

Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions.

Small cell lung cancer (SCLC) is characterized by rapid growth and high metastatic capacity. It has strong epidemiologic and biologic links to tobacco carcinogens. Although the majority of SCLCs exhibit neuroendocrine features, an important subset of tumors lacks these properties. Genomic profiling of SCLC reveals genetic instability, almost universal inactivation of the tumor suppressor genes TP53 and RB1, and a high mutation burden. Because of early metastasis, only a small fraction of patients are amenable to curative-intent lung resection, and these individuals require adjuvant platinum-etoposide chemotherapy. Therefore, the vast majority of patients are currently being treated with chemoradiation with or without immunotherapy. In patients with disease confined to the chest, standard therapy includes thoracic radiotherapy and concurrent platinum-etoposide chemotherapy. Patients with metastatic (extensive-stage) disease are treated with a combination of platinum-etoposide chemotherapy plus immunotherapy with an anti-programmed death-ligand 1 monoclonal antibody. Although SCLC is initially very responsive to platinum-based chemotherapy, these responses are transient because of the development of drug resistance. In recent years, the authors have witnessed an accelerating pace of biologic insights into the disease, leading to the redefinition of the SCLC classification scheme. This emerging knowledge of SCLC molecular subtypes has the potential to define unique therapeutic vulnerabilities. Synthesizing these new discoveries with the current knowledge of SCLC biology and clinical management may lead to unprecedented advances in SCLC patient care. Here, the authors present an overview of multimodal clinical approaches in SCLC, with a special focus on illuminating how recent advancements in SCLC research could accelerate clinical development.

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.

Novel therapeutic strategies for recurrent SCLC.

Therapeutic options for patients with relapsed SCLC are limited, and the prognosis in this setting remains poor. While clinical outcomes for frontline treatment have modestly improved with the introduction of immunotherapy, treatment in the second-line setting persists almost unchanged. In this review, current treatment options and recent advances in molecular biology are described. Emerging therapeutic options in this setting, and potential strategies to improve clinical outcomes of these patients are also addressed.

Neoadjuvant chemotherapy plus nivolumab with or without ipilimumab in operable non-small cell lung cancer: the phase 2 platform NEOSTAR trial.

Neoadjuvant ipilimumab + nivolumab (Ipi+Nivo) and nivolumab + chemotherapy (Nivo+CT) induce greater pathologic response rates than CT alone in patients with operable non-small cell lung cancer (NSCLC). The impact of adding ipilimumab to neoadjuvant Nivo+CT is unknown. Here we report the results and correlates of two arms of the phase 2 platform NEOSTAR trial testing neoadjuvant Nivo+CT and Ipi+Nivo+CT with major pathologic response (MPR) as the primary endpoint. MPR rates were 32.1% (7/22, 80% confidence interval (CI) 18.7-43.1%) in the Nivo+CT arm and 50% (11/22, 80% CI 34.6-61.1%) in the Ipi+Nivo+CT arm; the primary endpoint was met in both arms. In patients without known tumor EGFR/ALK alterations, MPR rates were 41.2% (7/17) and 62.5% (10/16) in the Nivo+CT and Ipi+Nivo+CT groups, respectively. No new safety signals were observed in either arm. Single-cell sequencing and multi-platform immune profiling (exploratory endpoints) underscored immune cell populations and phenotypes, including effector memory CD8+ T, B and myeloid cells and markers of tertiary lymphoid structures, that were preferentially increased in the Ipi+Nivo+CT cohort. Baseline fecal microbiota in patients with MPR were enriched with beneficial taxa, such as Akkermansia, and displayed reduced abundance of pro-inflammatory and pathogenic microbes. Neoadjuvant Ipi+Nivo+CT enhances pathologic responses and warrants further study in operable NSCLC. (ClinicalTrials.gov registration: NCT03158129 .).

BRAF v600E-mutant cancers treated with vemurafenib alone or in combination with everolimus, sorafenib, or crizotinib or with paclitaxel and carboplatin (VEM-PLUS) study.

Combined BRAF + MEK inhibition is FDA approved for BRAF V600E-mutant solid tumors except for colorectal cancer. However, beyond MAPK mediated resistance several other mechanisms of resistance such as activation of CRAF, ARAF, MET, P13K/AKT/mTOR pathway exist among other complex pathways. In the VEM-PLUS study, we performed a pooled analysis of four phase one studies evaluating the safety and efficacy of vemurafenib monotherapy and vemurafenib combined with targeted therapies (sorafenib, crizotinib, or everolimus) or carboplatin plus paclitaxel in advanced solid tumors harboring BRAF V600 mutations. When vemurafenib monotherapy was compared with the combination regimens, no significant differences in OS or PFS durations were noted, except for inferior OS in the vemurafenib and paclitaxel and carboplatin trial (P = 0.011; HR, 2.4; 95% CI, 1.22-4.7) and in crossover patients (P = 0.0025; HR, 2.089; 95% CI, 1.2-3.4). Patients naïve to prior BRAF inhibitors had statistically significantly improved OS at 12.6 months compared to 10.4 months in the BRAF therapy refractory group (P = 0.024; HR, 1.69; 95% CI 1.07-2.68). The median PFS was statistically significant between both groups, with 7 months in the BRAF therapy naïve group compared to 4.7 months in the BRAF therapy refractory group (P = 0.016; HR, 1.80; 95% CI 1.11-2.91). The confirmed ORR in the vemurafenib monotherapy trial (28%) was higher than that in the combination trials. Our findings suggest that, compared with vemurafenib monotherapy, combinations of vemurafenib with cytotoxic chemotherapy or with RAF- or mTOR-targeting agents do not significantly extend the OS or PFS of patients who have solid tumors with BRAF V600E mutations. Gaining a better understanding of the molecular mechanisms of BRAF inhibitor resistance, balancing toxicity and efficacy with novel trial designs are warranted.