Small Cell Lung Cancer Screen of Oncology Drugs, Investigational Agents, and Gene and microRNA Expression

Targeting DNA Damage Response Deficiency in Thoracic Cancers

Thoracic cancers comprise non-small cell lung cancers (NSCLCs), small cell lung cancers (SCLCs) and malignant pleural mesotheliomas (MPM). Collectively, they account for the highest rate of death from malignancy worldwide. Genomic instability is a universal feature of cancer, which fuels mutations and tumour evolution. Deficiencies in DNA damage response (DDR) genes amplify genomic instability. Homologous recombination deficiency (HRD), resulting from BRCA1/BRCA2 inactivation, is exploited for therapeutic synthetic lethality with poly-ADP ribose polymerase (PARP) inhibitors in breast and ovarian cancers, as well as in prostate and pancreatic cancers. However, DDR deficiency and its therapeutic implications are less well established in thoracic cancers. Emerging evidence suggests that a subset of thoracic cancers may harbour DDR deficiency and may, thus, be effectively targeted with DDR agents. Here, we review the current evidence surrounding DDR in thoracic cancers and discuss the challenges and promise for achieving clinical benefit with such therapeutics.

Emerging advances in defining the molecular and therapeutic landscape of small-cell lung cancer

Small-cell lung cancer (SCLC) has traditionally been considered a recalcitrant cancer with a dismal prognosis, with only modest advances in therapeutic strategies over the past several decades. Comprehensive genomic assessments of SCLC have revealed that most of these tumours harbour deletions of the tumour-suppressor genes TP53 and RB1 but, in contrast to non-small-cell lung cancer, have failed to identify targetable alterations. The expression status of four transcription factors with key roles in SCLC pathogenesis defines distinct molecular subtypes of the disease, potentially enabling specific therapeutic approaches. Overexpression and amplification of MYC paralogues also affect the biology and therapeutic vulnerabilities of SCLC. Several other attractive targets have emerged in the past few years, including inhibitors of DNA-damage-response pathways, epigenetic modifiers, antibody-drug conjugates and chimeric antigen receptor T cells. However, the rapid development of therapeutic resistance and lack of biomarkers for effective selection of patients with SCLC are ongoing challenges. Emerging single-cell RNA sequencing data are providing insights into the plasticity and intratumoural and intertumoural heterogeneity of SCLC that might be associated with therapeutic resistance. In this Review, we provide a comprehensive overview of the latest advances in genomic and transcriptomic characterization of SCLC with a particular focus on opportunities for translation into new therapeutic approaches to improve patient outcomes.

Differential NEUROD1, ASCL1, and POU2F3 Expression Defines Molecular Subsets of Bladder Small Cell/Neuroendocrine Carcinoma with Prognostic Implications

Small cell carcinomas (SMC) of the lung are now molecularly classified based on the expression of transcriptional regulators (NEUROD1, ASCL1, POU2F3, YAP1) and DLL3, which has emerged as an investigational therapeutic target. PLCG2 has been shown to identify a distinct subpopulation of lung SMC with stem cell-like and pro-metastasis features and poor prognosis. We analyzed the expression of these novel neuroendocrine markers and their association with traditional neuroendocrine markers and patient outcomes in a cohort of bladder neuroendocrine carcinoma (NEC) consisting of 103 SMC and 19 large cell neuroendocrine carcinomas (LCNEC) assembled in tissue microarrays. Co-expression patterns were assessed and integrated with detailed clinical annotation including overall (OS) and recurrence free survival (RFS) and response to neoadjuvant/adjuvant chemotherapy. We identified five distinct molecular subtypes in bladder SMC based on expression of ASCL1, NEUROD1 and POU2F3: ASCL1+/NEUROD1- (n=33; 34%), ASCL1-/NEUROD1+ (n=21; 21%), ASCL1+/NEUROD1+ (n=17; 17%), POU2F3+ (n=22, 22%), and ASCL1-/NEUROD1-/POU2F3- (n=5, 5%). POU2F3+ tumors were mutually exclusive with those expressing ASCL1 and NEUROD1 and exhibited lower expression of traditional neuroendocrine markers. PLCG2 expression was noted in 33 tumors (32%) and was highly correlated with POU2F3 expression (p < 0.001). DLL3 expression was high in both SMC (n=72, 82%) and LCNEC (n=11, 85%). YAP1 expression was enriched in non- neuroendocrine components and negatively correlated with all neuroendocrine markers. In patients without metastatic disease who underwent radical cystectomy, PLCG2+ or POU2F3+ tumors had shorter RFS and OS (p<0.05), but their expression was not associated with metastasis status or response to neoadjuvant/adjuvant chemotherapy. In conclusion, NEC of the bladder can be divided into distinct molecular subtypes based on the expression of ASCL1, NEUROD1 and POU2F3. POU2F3 expressing tumors represent an ASCL1/NEUROD1-negative subset of bladder NEC characterized by lower expression of traditional neuroendocrine markers. Marker expression patterns were similar in SMC and LCNEC. Expression of PLCG2 and POU2F3 was associated with shorter recurrence-free and overall survival. DLL3 was expressed at high levels in both SMC and LCNEC of the bladder, nominating it as a potential therapeutic target.

Small Cell Lung Carcinoma Cells Depend on KIF11 for Survival

Few efficacious treatment options are available for patients with small cell lung carcinoma (SCLC), indicating the need to develop novel therapeutic approaches. In this study, we explored kinesin family member 11 (KIF11), a potential therapeutic target in SCLC. An analysis of publicly available data suggested that KIF11 mRNA expression levels are significantly higher in SCLC tissues than in normal lung tissues. When KIF11 was targeted by RNA interference or a small-molecule inhibitor (SB743921) in two SCLC cell lines, Lu-135 and NCI-H69, cell cycle progression was arrested at the G2/M phase with complete growth suppression. Further work suggested that the two cell lines were more significantly affected when both KIF11 and BCL2L1, an anti-apoptotic BCL2 family member, were inhibited. This dual inhibition resulted in markedly decreased cell viability. These findings collectively indicate that SCLC cells are critically dependent on KIF11 activity for survival and/or proliferation, as well as that KIF11 inhibition could be a new strategy for SCLC treatment.

Sarcoma_CellminerCDB: A tool to interrogate the genomic and functional characteristics of a comprehensive collection of sarcoma cell lines

Sarcomas are a diverse group of rare malignancies composed of multiple different clinical and molecular subtypes. Due to their rarity and heterogeneity, basic, translational, and clinical research in sarcoma has trailed behind that of other cancers. Outcomes for patients remain generally poor due to an incomplete understanding of disease biology and a lack of novel therapies. To address some of the limitations impeding preclinical sarcoma research, we have developed Sarcoma_CellMinerCDB, a publicly available interactive tool that merges publicly available sarcoma cell line data and newly generated omics data to create a comprehensive database of genomic, transcriptomic, methylomic, proteomic, metabolic, and pharmacologic data on 133 annotated sarcoma cell lines. The reproducibility, functionality, biological relevance, and therapeutic applications of Sarcoma_CellMinerCDB described herein are powerful tools to address and generate biological questions and test hypotheses for translational research. Sarcoma_CellMinerCDB (https://discover.nci.nih.gov/SarcomaCellMinerCDB) aims to contribute to advancing the preclinical study of sarcoma.

Blocking the angiopoietin-2-dependent integrin β-1 signaling axis abrogates small cell lung cancer invasion and metastasis

Small cell lung cancer (SCLC) is the most aggressive lung cancer entity with an extremely limited therapeutic outcome. Most patients are diagnosed at an extensive stage. However, the molecular mechanisms driving SCLC invasion and metastasis remain largely elusive. We used an autochthonous SCLC mouse model and matched samples from patients with primary and metastatic SCLC to investigate the molecular characteristics of tumor metastasis. We demonstrate that tumor cell invasion and liver metastasis in SCLC are triggered by an Angiopoietin-2 (ANG-2)/Integrin β-1-dependent pathway in tumor cells, mediated by focal adhesion kinase/Src kinase signaling. Strikingly, CRISPR-Cas9 KO of Integrin β-1 or blocking Integrin β-1 signaling by an anti-ANG-2 treatment abrogates liver metastasis formation in vivo. Interestingly, analysis of a unique collection of matched samples from patients with primary and metastatic SCLC confirmed a strong increase of Integrin β-1 in liver metastasis in comparison with the primary tumor. We further show that ANG-2 blockade combined with PD-1-targeted by anti-PD-1 treatment displays synergistic treatment effects in SCLC. Together, our data demonstrate a fundamental role of ANG-2/Integrin β-1 signaling in SCLC cells for tumor cell invasion and liver metastasis and provide a potentially new effective treatment strategy for patients with SCLC.

Characterization of zinc finger protein 536, a neuroendocrine regulator, using pan-cancer analysis

BACKGROUND

Previous studies suggested that zinc finger protein 536 (ZNF536) was abundant in the central brain and regulated neuronal differentiation. However, the role of ZNF536 in cancer has remained unclear.

METHODS

ZNF536 mutation, copy number alteration, DNA methylation, and RNA expression were explored using public portals. Data from The Cancer Genome Atlas (TCGA) were utilized to analyze pathways and tumor microenvironment (TME), with a focus on prognosis in both TCGA and immunotherapy pan-cancer cohorts. Methylated ZNF536 from small cell lung cancer (SCLC) cell lines were utilized to train with probes for conducting enrichment analysis. Single-cell RNA profile demonstrated the sublocalization and co-expression of ZNF536, and validated its targets by qPCR.

RESULTS

Genetic alterations in ZNF536 were found to be high-frequency and a single sample could harbor different variations. ZNF536 at chromosome 19q12 exerted a bypass effect on CCNE1, supported by CRISPR data. For lung cancer, ZNF536 mutation was associated with longer survival in primary lung adenocarcinoma (LUAD), but its prognosis was poor in metastatic LUAD and SCLC. Importantly, ZNF536 mutation and amplification had opposite prognoses in Stand Up To Cancer-Mark Foundation (SU2C-MARK) LUAD cohort. ZNF536 mutation altered the patterns of genomic alterations in tumors, and had distinct impacts on the signaling pathways and TME compared to ZNF536 amplification. Additionally, ZNF536 expression was predominantly in endocrine tumors and brain tissues. High-dimensional analysis supported this finding and further revealed regulators of ZNF536. Considering that the methylation of ZNF536 was involved in the synaptic pathway associated with neuroendocrine neoplasms, demonstrating both diagnostic and prognostic value. Moreover, we experimentally verified ZNF536 upregulated neuroendocrine markers.

CONCLUSIONS

Our results showed that ZNF536 alterations in cancer, including variations in copy number, mutation, and methylation. We proved the involvement of ZNF536 in neuroendocrine regulation, and identified highly altered ZNF536 as a potential biomarker for immunotherapy.

Updates on Urinary Bladder Tumors With Neuroendocrine Features

The most common neuroendocrine tumor in the urinary bladder is small cell carcinoma, which can be pure or mixed with components of urothelial or other histologic subtypes. Large cell neuroendocrine carcinoma of the bladder is rare and remains ill-defined but is increasingly recognized. Well-differentiated neuroendocrine tumor and paraganglioma can arise in the bladder but are very rare in this location. Recent advances in molecular characterization allowed for better classification and may offer improved stratification of these tumors.

Acquired Cross-Resistance in Small Cell Lung Cancer due to Extrachromosomal DNA Amplification of MYC Paralogs

Small cell lung cancer (SCLC) presents as a highly chemosensitive malignancy but acquires cross-resistance after relapse. This transformation is nearly inevitable in patients but has been difficult to capture in laboratory models. Here, we present a preclinical system that recapitulates acquired cross-resistance, developed from 51 patient-derived xenograft (PDX) models. Each model was tested in vivo against three clinical regimens: cisplatin plus etoposide, olaparib plus temozolomide, and topotecan. These drug-response profiles captured hallmark clinical features of SCLC, such as the emergence of treatment-refractory disease after early relapse. For one patient, serial PDX models revealed that cross-resistance was acquired through MYC amplification on extrachromosomal DNA (ecDNA). Genomic and transcriptional profiles of the full PDX panel revealed that MYC paralog amplifications on ecDNAs were recurrent in relapsed cross-resistant SCLC, and this was corroborated in tumor biopsies from relapsed patients. We conclude that ecDNAs with MYC paralogs are recurrent drivers of cross-resistance in SCLC.

SIGNIFICANCE

SCLC is initially chemosensitive, but acquired cross-resistance renders this disease refractory to further treatment and ultimately fatal. The genomic drivers of this transformation are unknown. We use a population of PDX models to discover that amplifications of MYC paralogs on ecDNA are recurrent drivers of acquired cross-resistance in SCLC. This article is featured in Selected Articles from This Issue, p. 695.

Applied models and molecular characteristics of small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive type of cancer frequently diagnosed with metastatic spread, rendering it surgically unresectable for the majority of patients. Although initial responses to platinum-based therapies are often observed, SCLC invariably relapses within months, frequently developing drug-resistance ultimately contributing to short overall survival rates. Recently, SCLC research aimed to elucidate the dynamic changes in the genetic and epigenetic landscape. These have revealed distinct subtypes of SCLC, each characterized by unique molecular signatures. The recent understanding of the molecular heterogeneity of SCLC has opened up potential avenues for precision medicine, enabling the development of targeted therapeutic strategies. In this review, we delve into the applied models and computational approaches that have been instrumental in the identification of promising drug candidates. We also explore the emerging molecular diagnostic tools that hold the potential to transform clinical practice and patient care.

Predicting drug response of small cell lung cancer cell lines based on enrichment analysis of complex gene signatures

Advances in the field of genomics and transcriptomics have enabled researchers to identify gene signatures related to development and treatment of Small Cell Lung Cancer. In most cases, complex gene expression patterns are identified, comprising of genes with differential behavior. Most tools use single-genes as predictors of drug response, with only limited options for multi-gene use. Here we examine the potential of predicting drug response using these complex gene expression signatures by employing clustering and signal enrichment in Small Cell Lung Cancer. Our results demonstrate clustering genes from complex expression patterns helps identify differential activity of gene groups with alternate function which can then be used to predict drug response.

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.

Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs

Combination therapy is a fundamental strategy in cancer chemotherapy. It involves administering two or more anti-cancer agents to increase efficacy and overcome multidrug resistance compared to monotherapy. However, drug combinations can exhibit synergy, additivity, or antagonism. This study presents a machine learning framework to classify and predict cancer drug combinations. The framework utilizes several key steps including data collection and annotation from the O'Neil drug interaction dataset, data preprocessing, stratified splitting into training and test sets, construction and evaluation of classification models to categorize combinations as synergistic, additive, or antagonistic, application of regression models to predict combination sensitivity scores for enhanced predictions compared to prior work, and the last step is examination of drug features and mechanisms of action to understand synergy behaviors for optimal combinations. The models identified combination pairs most likely to synergize against different cancers. Kinase inhibitors combined with mTOR inhibitors, DNA damage-inducing drugs or HDAC inhibitors showed benefit, particularly for ovarian, melanoma, prostate, lung and colorectal carcinomas. Analysis highlighted Gemcitabine, MK-8776 and AZD1775 as frequently synergizing across cancer types. This machine learning framework provides a valuable approach to uncover more effective multi-drug regimens.

Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Circadian gene ARNTL initiates circGUCY1A2 transcription to suppress non-small cell lung cancer progression via miR-200c-3p/PTEN signaling

BACKGROUND

As a subclass of endogenous stable noncoding RNAs, circular RNAs are beginning to be appreciated for their potential as tumor therapeutics. However, the functions and mechanisms by which circRNAs exert protective functions in non-small cell lung cancer (NSCLC) remain largely elusive.

METHODS

The prognostic role of circGUCY1A2 was explored in lung adenocarcinoma specimens. The overexpressed and knockdown plasmids were used to evaluate the effect of circGUCY1A2 on NSCLC cell proliferation and apoptosis efficacy. Luciferase reporter system is used to prove that circGUCY1A2 could bind to miRNA. Chip-PCR was used to prove that circGUCY1A2 could be initiated by transcription factors ARNTL. Subcutaneous tumorigenicity grafts models were established to validate findings in vivo.

RESULTS

The expression of circGUCY1A2 were significantly reduced (P < 0.001) and negatively correlated with tumor size (P < 0.05) in non-small cell lung cancer (NSCLC). CircGUCY1A2 upregulation promoted apoptosis and inhibits cell proliferation and growth of subcutaneous tumorigenicity grafts in nude mice (P < 0.01). In addition, intra-tumor injection of pLCDH-circGUCY1A2 inhibited tumor growth in patient-derived NSCLC xenograft models (PDX). Mechanism studies showed that circGUCY1A2 could act as a sponge to competitively bind miR-200c-3p, promote PTEN expression, and thereby inhibit PI3K/AKT pathway. In addition, we found that the circadian gene ARNTL, which was reduced in NSCLC and prolonged the overall survival of patients, could bind to the promoter of circGUCY1A2, thereby increasing its expression.

CONCLUSIONS

This study is an original demonstration that ARNTL can inhibit the development of lung adenocarcinoma through the circGUCY1A2/miR-200c-3p/PTEN axis, and this finding provides potential targets and therapeutic approaches for the treatment of lung adenocarcinoma.

Predicting potential small molecule-miRNA associations utilizing truncated schatten p-norm

MicroRNAs (miRNAs) have significant implications in diverse human diseases and have proven to be effectively targeted by small molecules (SMs) for therapeutic interventions. However, current SM-miRNA association prediction models do not adequately capture SM/miRNA similarity. Matrix completion is an effective method for association prediction, but existing models use nuclear norm instead of rank function, which has some drawbacks. Therefore, we proposed a new approach for predicting SM-miRNA associations by utilizing the truncated schatten p-norm (TSPN). First, the SM/miRNA similarity was preprocessed by incorporating the Gaussian interaction profile kernel similarity method. This identified more SM/miRNA similarities and significantly improved the SM-miRNA prediction accuracy. Next, we constructed a heterogeneous SM-miRNA network by combining biological information from three matrices and represented the network with its adjacency matrix. Finally, we constructed the prediction model by minimizing the truncated schatten p-norm of this adjacency matrix and we developed an efficient iterative algorithmic framework to solve the model. In this framework, we also used a weighted singular value shrinkage algorithm to avoid the problem of excessive singular value shrinkage. The truncated schatten p-norm approximates the rank function more closely than the nuclear norm, so the predictions are more accurate. We performed four different cross-validation experiments on two separate datasets, and TSPN outperformed various most advanced methods. In addition, public literature confirms a large number of predictive associations of TSPN in four case studies. Therefore, TSPN is a reliable model for SM-miRNA association prediction.

Small Cell Lung Carcinoma: Current Diagnosis, Biomarkers, and Treatment Options with Future Perspectives

Small cell lung cancer (SCLC) is an aggressive malignancy characterized by rapid proliferation, early dissemination, acquired therapy resistance, and poor prognosis. Early diagnosis of SCLC is crucial since most patients present with advanced/metastatic disease, limiting the potential for curative treatment. While SCLC exhibits initial responsiveness to chemotherapy and radiotherapy, treatment resistance commonly emerges, leading to a five-year overall survival rate of up to 10%. New effective biomarkers, early detection, and advancements in therapeutic strategies are crucial for improving survival rates and reducing the impact of this devastating disease. This review aims to comprehensively summarize current knowledge on diagnostic options, well-known and emerging biomarkers, and SCLC treatment strategies and discuss future perspectives on this aggressive malignancy.

Histogenetic and disease-relevant phenotypes in thymic epithelial tumors (TETs): The potential significance for future TET classification

Thymic epithelial tumors (TETs) encompass morphologically various subtypes. Thus, it would be meaningful to explore the expression phenotypes that delineate each TET subtype or overarching multiple subtypes. If these profiles are related to thymic physiology, they will improve our biological understanding of TETs and may contribute to the establishment of a more rational TET classification. Against this background, pathologists have attempted to identify histogenetic features in TETs for a long time. As part of this work, our group has reported several TET expression profiles that are histotype-dependent and related to the nature of thymic epithelial cells (TECs). For example, we found that beta5t, a constituent of thymoproteasome unique to cortical TECs, is expressed mainly in type B thymomas, for which the nomenclature of cortical thymoma was once considered. Another example is the discovery that most thymic carcinomas, especially thymic squamous cell carcinomas, exhibit expression profiles similar to tuft cells, a recently discovered special type of medullary TEC. This review outlines the currently reported histogenetic phenotypes of TETs, including those related to thymoma-associated myasthenia gravis, summarizes their genetic signatures, and provides a perspective for the future direction of TET classification.

Repeatedly next-generation sequencing during treatment follow-up of patients with small cell lung cancer

Somatic alterations in tumors are a frequent occurrence. In small cell lung cancer (SCLC), these include mutations in the tumor suppressors TP53 and retinoblastoma (RB1). We used next generation sequencing (NGS) to study specific genetic variants and compare genetic and clinicopathological features of SCLC with healthy control genome. Ten SCLC patients receiving standard chemotherapy, between 2018 and 2019, from the First Hospital of Jilin University were included in this study. Prior patient treatment, NGS was performed using DNA isolated from blood plasma. New NGS analyses were performed after 2 and 4 treatment cycles. Four patients presented with different metastases at diagnosis. Overall, most genes tested presented missense or frameshift variants. TP53, RB1, CREBBP, FAT1 genes presented gain of stop codons. At the single-gene level, the most frequently altered genes were TP53 (8/10 patients, 80%) and RB1 (4/10 patients, 40%), followed by bromodomain containing 4 (BRD4), CREBBP, FAT1, FMS-like tyrosine kinase 3 (FLT3), KDR, poly ADP-ribose polymerase (PARP1), PIK3R2, ROS1, and splicing factor 3b subunit 1 (SF3B1) (2/10 patients, 20%). We identified 5 genes, which have not been previously reported to bear mutations in the context of SCLC. These genes include BRD4, PARP1, FLT3, KDR, and SF3B1. We observed that among the studied individuals, patients with a high number of genetic events, and in which such mutations were not eradicated after treatment, showed a worse prognosis. There has not yet been given enough attention to the above-mentioned genes in SCLC, which will have great clinical prospects for treatment.

Acquired Cross-resistance in Small Cell Lung Cancer due to Extrachromosomal DNA Amplification of MYC paralogs

Small cell lung cancer (SCLC) presents as a highly chemosensitive malignancy but acquires cross-resistance after relapse. This transformation is nearly inevitable in patients but has been difficult to capture in laboratory models. Here we present a pre-clinical system that recapitulates acquired cross-resistance in SCLC, developed from 51 patient-derived xenografts (PDXs). Each model was tested for in vivo sensitivity to three clinical regimens: cisplatin plus etoposide, olaparib plus temozolomide, and topotecan. These functional profiles captured hallmark clinical features, such as the emergence of treatment-refractory disease after early relapse. Serially derived PDX models from the same patient revealed that cross-resistance was acquired through a MYC amplification on extrachromosomal DNA (ecDNA). Genomic and transcriptional profiles of the full PDX panel revealed that this was not unique to one patient, as MYC paralog amplifications on ecDNAs were recurrent among cross-resistant models derived from patients after relapse. We conclude that ecDNAs with MYC paralogs are recurrent drivers of cross-resistance in SCLC.

SIGNIFICANCE

SCLC is initially chemosensitive, but acquired cross-resistance renders this disease refractory to further treatment and ultimately fatal. The genomic drivers of this transformation are unknown. We use a population of PDX models to discover that amplifications of MYC paralogs on ecDNA are recurrent drivers of acquired cross-resistance in SCLC.

An exploratory study for tuft cells in the breast and their relevance in triple-negative breast cancer: the possible relationship of SOX9

BACKGROUND

Breast cancer is highly heterogeneous, suggesting that small but relevant subsets have been under-recognized. Rare and mainly triple-negative breast cancers (TNBCs) were recently found to exhibit tuft cell-like expression profiles, including POU2F3, the tuft cell master regulator. In addition, immunohistochemistry (IHC) has identified POU2F3-positive cells in the normal human breast, suggesting the presence of tuft cells in this organ.

METHODS

Here, we (i) reviewed previously identified POU2F3-positive invasive breast cancers (n = 4) for POU2F3 expression in intraductal cancer components, (ii) investigated a new cohort of invasive breast cancers (n = 1853) by POU2F3-IHC, (iii) explored POU2F3-expressing cells in non-neoplastic breast tissues obtained from women with or without BRCA1 mutations (n = 15), and (iv) reanalyzed publicly available single-cell RNA sequencing (scRNA-seq) data from normal breast cells.

RESULTS

Two TNBCs of the four previously reported invasive POU2F3-positive breast cancers contained POU2F3-positive ductal carcinoma in situ (DCIS). In the new cohort of invasive breast cancers, IHC revealed four POU2F3-positive cases, two of which were triple-negative, one luminal-type, and one triple-positive. In addition, another new POU2F3-positive tumor with a triple-negative phenotype was found in daily practice. All non-neoplastic breast tissues contained POU2F3-positive cells, irrespective of BRCA1 status. The scRNA-seq reanalysis confirmed POU2F3-expressing epithelial cells (3.3% of all epithelial cells) and the 17% that co-expressed the other two tuft cell-related markers (SOX9/AVIL or SOX9/GFI1B), which suggested they were bona fide tuft cells. Of note, SOX9 is also known as the "master regulator" of TNBCs.

CONCLUSIONS

POU2F3 expression defines small subsets in various breast cancer subtypes, which can be accompanied by DCIS. The mechanistic relationship between POU2F3 and SOX9 in the breast warrants further analysis to enhance our understanding of normal breast physiology and to clarify the significance of the tuft cell-like phenotype for TNBCs.

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.

LINC00312 Inhibits Lung Cancer Progression through the miR-3175/SEMA6A Axis

This study aims to clarify molecular mechanisms and tumor-associated functions of LINC00312 in lung cancer. GEO database was used to acquire lung cancer-related expression microarrays. Then, relevant databases were applied to predict the downstream miRNA for LINC00312 and the target mRNA for the potential miRNA, with their associations deeply confirmed through dual-luciferase and RIP assays. The expression levels of epithelial-mesenchymal transition -related proteins (N-cadherin, Vimentin, MMP-2, and MMP-9) were examined by Western blot. The proliferation, migration, and invasion were evaluated through in vitro experiments including CCK-8 and Transwell assays and further validated by nude mouse xenograft tumor experiment. LINC00312, serving as a tumor suppressor, was down-regulated in lung cancer cells. RIP assay proved that miR-3175 bound LINC00312 and SEMA6A. The dual-luciferase assay showed that miR-3175 specifically targeted SEMA6A, suppressing the expression of SEMA6A. Overexpressing LINC00312 remarkably inhibited the binding between miR-3175 and SEMA6A. Overexpressing miR-3175 or silencing SEMA6A could hamper the effects of LINC00312 on lung cancer cells. LINC00312 inhibits lung cancer occurrence and progression via the miR-3175/SEMA6A axis.

BET Inhibitors Target the SCLC-N Subtype of Small-Cell Lung Cancer by Blocking NEUROD1 Transactivation

Small-cell lung cancer (SCLC) is a recalcitrant malignancy that urgently needs new therapies. Four master transcription factors (ASCL1, NEUROD1, POU2F3, and YAP1) have been identified in SCLC, and each defines the transcriptome landscape of one molecular subtype. However, these master transcription factors have not been found directly druggable. We hypothesized that blocking their transcriptional coactivator(s) could provide an alternative approach to target these master transcription factors. Here, we identify that BET proteins physically interact with NEUROD1 and function as transcriptional coactivators. Using CRISPR knockout and ChIP-seq, we demonstrate that NEUROD1 plays a critical role in defining the landscapes of BET proteins in the SCLC genome. Blocking BET proteins by inhibitors led to broad suppression of the NEUROD1-target genes, especially those associated with superenhancers, resulting in the inhibition of SCLC growth in vitro and in vivo. LSAMP, a membrane protein in the IgLON family, was identified as one of the NEUROD1-target genes mediating BET inhibitor sensitivity in SCLC. Altogether, our study reveals that BET proteins are essential in regulating NEUROD1 transactivation and are promising targets in SCLC-N subtype tumors.

IMPLICATIONS

Our findings suggest that targeting transcriptional coactivators could be a novel approach to blocking the master transcription factors in SCLC for therapeutic purposes.

Pulmonary cancers across different histotypes share hybrid tuft cell/ionocyte-like molecular features and potentially druggable vulnerabilities

Tuft cells are chemosensory epithelial cells in the respiratory tract and several other organs. Recent studies revealed tuft cell-like gene expression signatures in some pulmonary adenocarcinomas, squamous cell carcinomas (SQCC), small cell carcinomas (SCLC), and large cell neuroendocrine carcinomas (LCNEC). Identification of their similarities could inform shared druggable vulnerabilities. Clinicopathological features of tuft cell-like (tcl) subsets in various lung cancer histotypes were studied in two independent tumor cohorts using immunohistochemistry (n = 674 and 70). Findings were confirmed, and additional characteristics were explored using public datasets (RNA seq and immunohistochemical data) (n = 555). Drug susceptibilities of tuft cell-like SCLC cell lines were also investigated. By immunohistochemistry, 10-20% of SCLC and LCNEC, and approximately 2% of SQCC expressed POU2F3, the master regulator of tuft cells. These tuft cell-like tumors exhibited "lineage ambiguity" as they co-expressed NCAM1, a marker for neuroendocrine differentiation, and KRT5, a marker for squamous differentiation. In addition, tuft cell-like tumors co-expressed BCL2 and KIT, and tuft cell-like SCLC and LCNEC, but not SQCC, also highly expressed MYC. Data from public datasets confirmed these features and revealed that tuft cell-like SCLC and LCNEC co-clustered on hierarchical clustering. Furthermore, only tuft cell-like subsets among pulmonary cancers significantly expressed FOXI1, the master regulator of ionocytes, suggesting their bidirectional but immature differentiation status. Clinically, tuft cell-like SCLC and LCNEC had a similar prognosis. Experimentally, tuft cell-like SCLC cell lines were susceptible to PARP and BCL2 co-inhibition, indicating synergistic effects. Taken together, pulmonary tuft cell-like cancers maintain histotype-related clinicopathologic characteristics despite overlapping unique molecular features. From a therapeutic perspective, identification of tuft cell-like LCNECs might be crucial given their close kinship with tuft cell-like SCLC.

Tuft cell-like carcinomas: novel cancer subsets present in multiple organs sharing a unique gene expression signature

BACKGROUND

Tuft cells are chemosensory epithelial cells playing a role in innate immunity. Recent studies revealed cancers with a tuft cell-like gene expression signature in the thorax. We wondered whether this signature might also occur in extrathoracic cancers.

METHODS

We examined mRNA expression of tuft cell markers (POU2F3, GFI1B, TRPM5, SOX9, CHAT, and AVIL) in 19 different types of cancers in multiple extrathoracic organs with The Cancer Genome Atlas (TCGA) (N = 6322). Four different extrathoracic cancers in our local archives (N = 909) were analysed by immunohistochemistry.

RESULTS

Twenty-two (0.35%) extrathoracic tumours with co-expression of POU2F3 and other tuft cell markers were identified in various TCGA datasets. Twelve of the 22 "tuft cell-like tumours" shared poor differentiation and a gene expression pattern, including KIT, anti-apoptotic BCL2, and ionocyte-associated genes. In our archival cases, eleven (1.21%) tumours co-expressing POU2F3, KIT, and BCL2 on immunohistochemistry, i.e., were presumable tuft cell-like cancers. In three among five TCGA cohorts, the tuft cell-like cancer subsets expressed SLFN11, a promising biomarker of PARP inhibitor susceptibility.

CONCLUSIONS

Tuft cell-like carcinomas form distinct subsets in cancers of many organs. It appears warranted to investigate their shared gene expression signature as a predictive biomarker for novel therapeutic strategies.

Targeting the untargetable: RB1-deficient tumours are vulnerable to Skp2 ubiquitin ligase inhibition

Proteins that regulate the cell cycle are accumulated and degraded in a coordinated manner during the transition from one cell cycle phase to the next. The rapid loss of a critical protein, for example, to allow the cell to move from G1/G0 to S phase, is often regulated by its ubiquitination and subsequent proteasomal degradation. Protein ubiquitination is mediated by a series of three ligases, of which the E3 ligases provide the specificity for a particular protein substrate. One such E3 ligase is SCF^Skp1/Cks1, which has a substrate recruiting subunit called S-phase kinase-associated protein 2 (Skp2). Skp2 regulates cell proliferation, apoptosis, and differentiation, can act as an oncogene, and is overexpressed in human cancer. A primary target of Skp2 is the cyclin-dependent kinase inhibitor p27 (CDKN1b) that regulates the cell cycle at several points. The RB1 tumour suppressor gene regulates Skp2 activity by two mechanisms: by controlling its mRNA expression, and by an effect on Skp2's enzymatic activity. For the latter, the RB1 protein (pRb) directly binds to the substrate-binding site on Skp2, preventing protein substrates from being ubiquitinated and degraded. Inactivating mutations in RB1 are common in human cancer, becoming more frequent in aggressive, metastatic, and drug-resistant tumours. Hence, RB1 mutation leads to the loss of pRb, an unrestrained increase in Skp2 activity, the unregulated decrease in p27, and the loss of cell cycle control. Because RB1 mutations lead to the loss of a functional protein, its direct targeting is not possible. This perspective will discuss evidence validating Skp2 as a therapeutic target in RB1-deficient cancer.

cfDNA methylome profiling for detection and subtyping of small cell lung cancers

Small cell lung cancer (SCLC) is characterized by morphologic, epigenetic and transcriptomic heterogeneity. Subtypes based upon predominant transcription factor expression have been defined that, in mouse models and cell lines, exhibit potential differential therapeutic vulnerabilities, with epigenetically distinct SCLC subtypes also described. The clinical relevance of these subtypes is unclear, due in part to challenges in obtaining tumor biopsies for reliable profiling. Here we describe a robust workflow for genome-wide DNA methylation profiling applied to both patient-derived models and to patients' circulating cell-free DNA (cfDNA). Tumor-specific methylation patterns were readily detected in cfDNA samples from patients with SCLC and were correlated with survival outcomes. cfDNA methylation also discriminated between the transcription factor SCLC subtypes, a precedent for a liquid biopsy cfDNA-methylation approach to molecularly subtype SCLC. Our data reveal the potential clinical utility of cfDNA methylation profiling as a universally applicable liquid biopsy approach for the sensitive detection, monitoring and molecular subtyping of patients with SCLC.

Archetype tasks link intratumoral heterogeneity to plasticity and cancer hallmarks in small cell lung cancer

Small cell lung cancer (SCLC) tumors comprise heterogeneous mixtures of cell states, categorized into neuroendocrine (NE) and non-neuroendocrine (non-NE) transcriptional subtypes. NE to non-NE state transitions, fueled by plasticity, likely underlie adaptability to treatment and dismal survival rates. Here, we apply an archetypal analysis to model plasticity by recasting SCLC phenotypic heterogeneity through multi-task evolutionary theory. Cell line and tumor transcriptomics data fit well in a five-dimensional convex polytope whose vertices optimize tasks reminiscent of pulmonary NE cells, the SCLC normal counterparts. These tasks, supported by knowledge and experimental data, include proliferation, slithering, metabolism, secretion, and injury repair, reflecting cancer hallmarks. SCLC subtypes, either at the population or single-cell level, can be positioned in archetypal space by bulk or single-cell transcriptomics, respectively, and characterized as task specialists or multi-task generalists by the distance from archetype vertex signatures. In the archetype space, modeling single-cell plasticity as a Markovian process along an underlying state manifold indicates that task trade-offs, in response to microenvironmental perturbations or treatment, may drive cell plasticity. Stifling phenotypic transitions and plasticity may provide new targets for much-needed translational advances in SCLC. A record of this paper's Transparent Peer Review process is included in the supplemental information.

Novel therapeutic combinations with PARP inhibitors for small cell lung cancer: A bench-to-bedside review

Small cell lung cancer (SCLC) is treated as a monolithic disease despite the evident intra- and intertumoral heterogeneity. Non-specific DNA-damaging agents have remained the first-line treatment for decades. Recently, emerging transcriptomic and genomic profiling of SCLC tumors identified distinct SCLC subtypes and vulnerabilities towards targeted therapeutics, including inhibitors of the nuclear enzyme poly (ADP-ribose) polymerase (PARPi). SCLC cell lines and tumors exhibited an elevated level of PARP1 protein and mRNA compared to healthy lung tissues and other subtypes of lung tumors. Notable responses to PARPi were also observed in preclinical SCLC models. Clinically, PARPi monotherapy exerted variable benefits for SCLC patients. To date, research is being vigorously conducted to examine predictive biomarkers of PARPi response and various PARPi combination strategies to maximize the clinical utility of PARPi. This narrative review summarizes existing preclinical evidence supporting PARPi monotherapy, combination therapy, and respective translation to the clinic. Specifically, we covered the combination of PARPi with DNA-damaging chemotherapy (cisplatin, etoposide, temozolomide), thoracic radiotherapy, immunotherapy (immune checkpoint inhibitors), and many other novel therapeutic agents that target DNA damage response, tumor microenvironment, epigenetic modulation, angiogenesis, the ubiquitin-proteasome system, or autophagy. Putative biomarkers, such as SLFN11 expression, MGMT methylation, E2F1 expression, and platinum sensitivity, which may be predictive of response to distinct therapeutic combinations, were also discussed. The future of SCLC treatment is undergoing rapid change with a focus on tailored and personalized treatment strategies. Further development of cancer therapy with PARPi will immensely benefit at least a subset of biomarker-defined SCLC patients.

ASCL1 regulates super-enhancer-associated miRNAs to define molecular subtypes of small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive neuroendocrine tumor with dismal prognosis. Recently, molecular subtypes of SCLC have been defined by the expression status of ASCL1, NEUROD1, YAP1, and POU2F3 transcription regulators. ASCL1 is essential for neuroendocrine differentiation and is expressed in the majority of SCLC. Although previous studies investigated ASCL1 target genes in SCLC cells, ASCL1‐mediated regulation of miRNAs and its relationship to molecular subtypes remain poorly explored. Here, we performed genome‐wide profiling of chromatin modifications (H3K27me3, H3K4me3, and H3K27ac) by CUT&Tag assay and ASCL1 knockdown followed by RNA sequencing and miRNA array analyses in SCLC cells. ASCL1 could preferentially regulate genes associated with super‐enhancers (SEs) defined by enrichment of H3K27ac marking. Moreover, ASCL1 positively regulated several SE‐associated miRNAs, such as miR‐7, miR‐375, miR‐200b‐3p, and miR‐429, leading to repression of their targets, whereas ASCL1 suppressed miR‐455‐3p, an abundant miRNA in other molecular subtypes. We further elucidated unique patterns of SE‐associated miRNAs in different SCLC molecular subtypes, highlighting subtype‐specific miRNA networks with functional relevance. Notably, we found apparent de‐repression of common target genes of different miRNAs following ASCL1 knockdown, suggesting combinatorial action of multiple miRNAs underlying molecular heterogeneity of SCLC (e.g., co‐targeting of YAP1 by miR‐9 and miR‐375). Our comprehensive analyses provide novel insights into SCLC pathogenesis and a clue to understanding subtype‐dependent phenotypic differences.

Replication stress defines distinct molecular subtypes across cancers

Endogenous replication stress is a major driver of genomic instability. Current assessments of replication stress are low throughput precluding its comprehensive assessment across tumors. Here we develop and validate a transcriptional profile of replication stress by leveraging established cellular characteristics that portend replication stress. The repstress gene signature defines a subset of tumors across lineages characterized by activated oncogenes, aneuploidy, extrachromosomal DNA amplification, immune evasion, high genomic instability, and poor survival, and importantly predicts response to agents targeting replication stress more robustly than previously reported transcriptomic measures of replication stress. Repstress score profiles the dual roles of replication stress during tumorigenesis and in established cancers and defines distinct molecular subtypes within cancers that may be more vulnerable to drugs targeting this dependency. Altogether, our study provides a molecular profile of replication stress, providing novel biological insights of the replication stress phenotype, with clinical implications.

Heterogeneity of neuroendocrine transcriptional states in metastatic small cell lung cancers and patient-derived models

Molecular subtypes of small cell lung cancer (SCLC) defined by the expression of key transcription regulators have recently been proposed in cell lines and limited number of primary tumors. The clinical and biological implications of neuroendocrine (NE) subtypes in metastatic SCLC, and the extent to which they vary within and between patient tumors and in patient-derived models is not known. We integrate histology, transcriptome, exome, and treatment outcomes of SCLC from a range of metastatic sites, revealing complex intra- and intertumoral heterogeneity of NE differentiation. Transcriptomic analysis confirms previously described subtypes based on ASCL1, NEUROD1, POU2F3, YAP1, and ATOH1 expression, and reveal a clinical subtype with hybrid NE and non-NE phenotypes, marked by chemotherapy-resistance and exceedingly poor outcomes. NE tumors are more likely to have RB1, NOTCH, and chromatin modifier gene mutations, upregulation of DNA damage response genes, and are more likely to respond to replication stress targeted therapies. In contrast, patients preferentially benefited from immunotherapy if their tumors were non-NE. Transcriptional phenotypes strongly skew towards the NE state in patient-derived model systems, an observation that was confirmed in paired patient-matched tumors and xenografts. We provide a framework that unifies transcriptomic and genomic dimensions of metastatic SCLC. The marked differences in transcriptional diversity between patient tumors and model systems are likely to have implications in development of novel therapeutic agents.

Lung Cancer Computational Biology and Resources

Comprehensive clinical, pathological, and molecular data, when appropriately integrated with advanced computational approaches, are transforming the way we characterize and study lung cancer. Clinically, cancer registry and publicly available historical clinical trial data enable retrospective analyses to examine how socioeconomic factors, patient demographics, and cancer characteristics affect treatment and outcome. Pathologically, digital pathology and artificial intelligence are revolutionizing histopathological image analyses, not only with improved efficiency and accuracy, but also by extracting additional information for prognostication and tumor microenvironment characterization. Genetically and molecularly, individual patient tumors and preclinical models of lung cancer are profiled by various high-throughput platforms to characterize the molecular properties and functional liabilities. The resulting multi-omics data sets and their interrogation facilitate both basic research mechanistic studies and translation of the findings into the clinic. In this review, we provide a list of resources and tools potentially valuable for lung cancer basic and translational research. Importantly, we point out pitfalls and caveats when performing computational analyses of these data sets and provide a vision of future computational biology developments that will aid lung cancer translational research.

FK228 potentiates topotecan activity against small cell lung cancer cells via induction of SLFN11

The response rate of topotecan, as a second-line chemotherapeutic drug for small cell lung cancer, is ~20%. DNA/RNA helicase SLFN11 (schlafen family member 11), a member of the Schlafen (SLFN) family, is a crucial determinant of response to many DNA damaging agents, expression of SLFN11 tends to augment the antitumor effects of the commonly used DNA-targeting agents. In the present study we investigated how SLFN11 expression regulated the sensitivity of small cell lung cancer to topotecan. We showed that SLFN11 expression levels were positively associated with the sensitivity to topotecan in a panel of seven SCLC cell lines. Topotecan treatment induced different patterns of the DNA response network in SCLC cells: DNA damage response (DDR) was more prominently activated in SLFN11-deficient SCLC cell line H82 than in SLFN11-plentiful SCLC cell line DMS273, whereas topotecan induced significant accumulation of p-Chk1, p-RPA2 and Rad51 in H82 cells, but not in DMS273 cells. We unraveled that SLFN11 expression was highly negatively correlated to the methylation of the SLFN11 promoter. HDAC inhibitors FK228 and SAHA dose-dependently increased SLFN11 expression through suppressing DNA methylation at the SLFN11 promoter, thereby sensitizing SCLC cells to topotecan. Finally, we assessed the methylation status of the SLFN11 promoter in 27 SCLC clinical specimens, and found that most of the clinical samples (24/27) showed DNA methylation at the SLFN11 promoter. In conclusion, it is feasible to combine topotecan with FK228 to improve the response rate of topotecan in SCLC patients.

MiR-200c-3p Modulates Cisplatin Resistance in Biliary Tract Cancer by ZEB1-Independent Mechanisms

Simple Summary

Biliary tract cancer is a rare malignancy with poor overall survival. The majority of patients are faced with advanced disease stage. Cisplatin-based treatment schedules represent the mainstay of first-line therapeutic strategy, yet only a small portion of patients develop a treatment response. One of the main reasons is acquired drug resistance. Previous studies correlated certain microRNAs (miRNAs), including miR-200c-3p, with drug resistance in various cancer types. However, limited knowledge exists about miR-200c-3p expression and cisplatin resistance in biliary tract cancer. Thus, the main aim of this study was to investigate the influence of miR-200c-3p on the cisplatin resistance in this cancer entity. We demonstrated that miR-200c-3p contributes to cisplatin resistance independently of its known influence on ZEB1 expression.

Abstract

Biliary tract cancer is a major global health issue in cancer-related mortality. Therapeutic options are limited, and cisplatin-based treatment schedules represent the mainstay of first-line therapeutic strategies. Although the gain of survival by the addition of cisplatin to gemcitabine is moderate, acquired cisplatin resistance frequently leads to treatment failures with mechanisms that are still poorly understood. Epithelial–mesenchymal transition (EMT) is a dynamic process that changes the shape, function, and gene expression pattern of biliary tract cancer cells. In this study, we explored the influence of the EMT-regulating miR-200c-3p on cisplatin sensitivity in biliary tract cancer cells. Using gain of function experiments, we demonstrated that miR-200c-3p regulates epithelial cell markers through the downregulation of the transcription factor ZEB1. MiR-200c-3p upregulation led to a decreased sensitivity against cisplatin, as observed in transient overexpression models as well as in cell lines stably overexpressing miR-200c-3p. The underlying mechanism seems to be independent of miR-200c-3p’s influence on ZEB1 expression, as ZEB1 knockdown resulted in the opposite effect on cisplatin resistance, which was abolished when ZEB1 knockdown and miR-200c-3p overexpression occurred in parallel. Using a gene panel of 40 genes that were previously associated with cisplatin resistance, two (Dual Specificity Phosphatase 16 (DUSP16) and Stratifin (SFN)) were identified as significantly (>2 fold, p-value < 0.05) up-regulated in miR-200c-3p overexpressing cells. In conclusion, miR-200c-3p might be an important contributor to cisplatin resistance in biliary tract cancer, independently of its interaction with ZEB1.

Notch signaling and efficacy of PD-1/PD-L1 blockade in relapsed small cell lung cancer

Immune checkpoint blockade (ICB) benefits only a small subset of patients with small cell lung cancer (SCLC), yet the mechanisms driving benefit are poorly understood. To identify predictors of clinical benefit to ICB, we performed immunogenomic profiling of tumor samples from patients with relapsed SCLC. Tumors of patients who derive clinical benefit from ICB exhibit cytotoxic T-cell infiltration, high expression of antigen processing and presentation machinery (APM) genes, and low neuroendocrine (NE) differentiation. However, elevated Notch signaling, which positively correlates with low NE differentiation, most significantly predicts clinical benefit to ICB. Activation of Notch signaling in a NE human SCLC cell line induces a low NE phenotype, marked by increased expression of APM genes, demonstrating a mechanistic link between Notch activation, low NE differentiation and increased intrinsic tumor immunity. Our findings suggest Notch signaling as a determinant of response to ICB in SCLC.

Immune checkpoint blockade (ICB) benefits only a small subset of patients with small cell lung cancer (SCLC) and the mechanisms driving benefit are poorly understood. Here, the authors show that elevated Notch signaling predicts clinical benefit in ICB in relapsed SCLC.

Assessing Consistency Across Functional Screening Datasets in Cancer Cells

Motivation

Many high-throughput screening studies have been carried out in cancer cell lines to identify therapeutic agents and targets. Existing consistency assessment studies only examined two datasets at a time, with conclusions based on a subset of carefully selected features rather than considering global consistency of all the data. However, poor concordance can still be observed for a large part of the data even when selected features are highly consistent.

Results

In this study, we assembled nine compound screening datasets and three functional genomics datasets. We derived direct measures of consistency as well as indirect measures of consistency based on association between functional data and copy number-adjusted gene expression data. These results have been integrated into a web application—the Functional Data Consistency Explorer (FDCE), to allow users to make queries and generate interactive visualizations so that functional data consistency can be assessed for individual features of interest.

Availability and implementation

The FDCE web tool and we have developed and the functional data consistency measures we have generated are available at https://lccl.shinyapps.io/FDCE/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Large-scale pharmacogenomic studies and drug response prediction for personalized cancer medicine

The response rate of most anti-cancer drugs is limited because of the high heterogeneity of cancer and the complex mechanism of drug action. Personalized treatment that stratifies patients into subgroups using molecular biomarkers is promising to improve clinical benefit. With the accumulation of preclinical models and advances in computational approaches of drug response prediction, pharmacogenomics has made great success over the last 20 years and is increasingly used in the clinical practice of personalized cancer medicine. In this article, we first summarize FDA-approved pharmacogenomic biomarkers and large-scale pharmacogenomic studies of preclinical cancer models such as patient-derived cell lines, organoids, and xenografts. Furthermore, we comprehensively review the recent developments of computational methods in drug response prediction, covering network, machine learning, and deep learning technologies and strategies to evaluate immunotherapy response. In the end, we discuss challenges and propose possible solutions for further improvement.

Targeting netrin-3 in small cell lung cancer and neuroblastoma

The navigation cue netrin-1 is well-documented for its key role in cancer development and represents a promising therapeutic target currently under clinical investigation. Phase 1 and 2 clinical trials are ongoing with NP137, a humanized monoclonal antibody against netrin-1. Interestingly, the epitope recognized by NP137 in netrin-1 shares 90% homology with its counterpart in netrin-3, the closest member to netrin-1 in humans, for which little is known in the field of cancer. Here, we unveiled that netrin-3 appears to be expressed specifically in human neuroblastoma (NB) and small cell lung cancer (SCLC), two subtypes of neuroectodermal/neuroendocrine lineages. Netrin-3 and netrin-1 expression are mutually exclusive, and the former is driven by the MYCN oncogene in NB, and the ASCL-1 or NeuroD1 transcription factors in SCLC. Netrin-3 expression is correlated with disease stage, aggressiveness, and overall survival in NB. Mechanistically, we confirmed the high affinity of netrin-3 for netrin-1 receptors and we demonstrated that netrin-3 genetic silencing or interference using NP137, delayed tumor engraftment, and reduced tumor growth in animal models. Altogether, these data support the targeting of netrin-3 in NB and SCLC.

Advances in Small-Cell Lung Cancer (SCLC) Translational Research

Over the past several years, we have witnessed a resurgence of interest in the biology and therapeutic vulnerabilities of small-cell lung cancer (SCLC). This has been driven in part through the development of a more extensive array of representative models of disease, including a diverse variety of genetically engineered mouse models and human tumor xenografts. Herein, we review recent progress in SCLC model development, and consider some of the particularly active avenues of translational research in SCLC, including interrogation of intratumoral heterogeneity, insights into the cell of origin and oncogenic drivers, mechanisms of chemoresistance, and new therapeutic opportunities including biomarker-directed targeted therapies and immunotherapies. Whereas SCLC remains a highly lethal disease, these new avenues of translational research, bringing together mechanism-based preclinical and clinical research, offer new hope for patients with SCLC.

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.

Aberrant methylation modifications reflect specific drug responses in small cell lung cancer

In the study, Methylated DNA immunoprecipitation sequencing, RNA sequencing, and whole-exome sequencing were employed to clinical small cell lung cancer (SCLC) patients. Then, we verified the therapeutic predictive effects of differentially methylated genes (DMGs) in 62 SCLC cell lines. Of 4552 DMGs between chemo-sensitive and chemo-insensitive group, coding genes constituted the largest percentage (85.08%), followed by lncRNAs (10.52%) and miRNAs (3.56%). Both two groups demonstrated two methylation peaks near transcription start site and transcription end site. Two lncRNA-miRNA-mRNA networks suggested the extensive genome connection between chemotherapy efficacy-related non-coding RNAs (ncRNAs) and mRNAs. Combing miRNAs and lncRNAs could effectively predict chemotherapy response in SCLC. In addition, we also verified the predictive values of mutated genes in SCLC cell lines. This study was the first to evaluate multiple drugs efficacy-related ncRNAs and mRNAs which were modified by methylation in SCLC. DMGs identified in our research might serve as promising therapeutic targets to reverse drugs-insensitivity by complex lncRNA-miRNA-mRNA mechanisms in SCLC.

Association of expression of epigenetic molecular factors with DNA methylation and sensitivity to chemotherapeutic agents in cancer cell lines

BACKGROUND

Altered DNA methylation patterns play important roles in cancer development and progression. We examined whether expression levels of genes directly or indirectly involved in DNA methylation and demethylation may be associated with response of cancer cell lines to chemotherapy treatment with a variety of antitumor agents.

RESULTS

We analyzed 72 genes encoding epigenetic factors directly or indirectly involved in DNA methylation and demethylation processes. We examined association of their pretreatment expression levels with methylation beta-values of individual DNA methylation probes, DNA methylation averaged within gene regions, and average epigenome-wide methylation levels. We analyzed data from 645 cancer cell lines and 23 cancer types from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer datasets. We observed numerous correlations between expression of genes encoding epigenetic factors and response to chemotherapeutic agents. Expression of genes encoding a variety of epigenetic factors, including KDM2B, DNMT1, EHMT2, SETDB1, EZH2, APOBEC3G, and other genes, was correlated with response to multiple agents. DNA methylation of numerous target probes and gene regions was associated with expression of multiple genes encoding epigenetic factors, underscoring complex regulation of epigenome methylation by multiple intersecting molecular pathways. The genes whose expression was associated with methylation of multiple epigenome targets encode DNA methyltransferases, TET DNA methylcytosine dioxygenases, the methylated DNA-binding protein ZBTB38, KDM2B, SETDB1, and other molecular factors which are involved in diverse epigenetic processes affecting DNA methylation. While baseline DNA methylation of numerous epigenome targets was correlated with cell line response to antitumor agents, the complex relationships between the overlapping effects of each epigenetic factor on methylation of specific targets and the importance of such influences in tumor response to individual agents require further investigation.

CONCLUSIONS

Expression of multiple genes encoding epigenetic factors is associated with drug response and with DNA methylation of numerous epigenome targets that may affect response to therapeutic agents. Our findings suggest complex and interconnected pathways regulating DNA methylation in the epigenome, which may both directly and indirectly affect response to chemotherapy.

New Therapies and Biomarkers: Are We Ready for Personalized Treatment in Small Cell Lung Cancer?

Small cell lung cancer (SCLC) is an aggressive form of lung cancer with a 5-year survival rate of less than 7%. In contrast to non-small cell lung cancer, SCLC has long been treated as a homogeneous disease without personalized treatment options. In recent years, the incorporation of immunotherapy into the treatment paradigm has brought moderate benefit to patients with SCLC; however, more effective therapies are urgently needed. In this article, we describe the current treatment standards and emerging therapeutic approaches for the treatment of SCLC. We also discuss promising biomarkers in SCLC and the recently discovered four subtypes of SCLC, each with its unique therapeutic vulnerability. Lastly, we discuss the advances in radiation therapy for the treatment of SCLC.

PARP Inhibitors in Small-Cell Lung Cancer: Rational Combinations to Improve Responses

Simple Summary

Small-cell lung cancer carries a dismal prognosis with few long-term treatment options. The enzyme poly-(ADP)-ribose polymerase (PARP), which functions to repair DNA breaks, has emerged as a promising therapeutic target, with modest response rates in early clinical trials prompting investigation of predictive biomarkers and therapeutic combinations. This review summarizes the development and testing of PARP inhibitors in small-cell lung cancer with an emphasis on developing treatment combinations. These combinations can be divided into three categories: (1) contributing to DNA damage; (2) inhibiting the DNA damage response; and (3) activating the immune system. An evolving classification of small-cell lung cancer subtypes and gene expression patterns will guide PARP inhibitor biomarker identification to improve treatments for this challenging cancer.

Abstract

Despite recent advances in first-line treatment for small-cell lung cancer (SCLC), durable responses remain rare. The DNA repair enzyme poly-(ADP)-ribose polymerase (PARP) was identified as a therapeutic target in SCLC using unbiased preclinical screens and confirmed in human and mouse models. Early trials of PARP inhibitors, either alone or in combination with chemotherapy, showed promising but limited responses, suggesting that selecting patient subsets and treatment combinations will prove critical to further clinical development. Expression of SLFN11 and other components of the DNA damage response (DDR) pathway appears to select for improved responses. Combining PARP inhibitors with agents that damage DNA and inhibit DDR appears particularly effective in preclinical and early trial data, as well as strategies that enhance antitumor immunity downstream of DNA damage. A robust understanding of the mechanisms of DDR in SCLC, which exhibits intrinsic replication stress, will improve selection of agents and predictive biomarkers. The most effective combinations will target multiple nodes in the DNA damage/DDR/immune activation cascade to minimize toxicity from synthetic lethality.