A functional role for tumor cell heterogeneity in a mouse model of small cell lung cancer

Intersection between lung cancer and neuroscience: Opportunities and challenges

Lung cancer, which has the highest morbidity and mortality rates worldwide, involves intricate interactions with the nervous system. Research indicates that the nervous system not only plays a role in the origin of lung cancer, but also engages in complex interactions with cancer cells through neurons, neurotransmitters, and various neuroactive molecules during tumor proliferation, invasion, and metastasis, especially in brain metastases. Cancer and its therapies can remodel the nervous system. Despite advancements in immunotherapy and targeted therapies in recent years, drug resistance of lung cancer cells after treatment limits improvements in patient survival and prognosis. The emergence of neuroscience has created new opportunities for the treatment of lung cancer. However, it also presents challenges. This review emphasizes that a deeper understanding of the interactions between the nervous system and lung cancer, along with the identification of new therapeutic targets, may lead to significant advancements or even a revolution in treatment strategies for patients with lung cancer.

Challenges of small cell lung cancer heterogeneity and phenotypic plasticity

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy with ~7% 5-year overall survival reflecting early metastasis and rapid acquired chemoresistance. Immunotherapy briefly extends overall survival in ~15% cases, yet predictive biomarkers are lacking. Targeted therapies are beginning to show promise, with a recently approved delta-like ligand 3 (DLL3)-targeted therapy impacting the treatment landscape. The increased availability of patient-faithful models, accumulating human tumour biobanks and numerous comprehensive molecular profiling studies have collectively facilitated the mapping and understanding of substantial intertumoural and intratumoural heterogeneity. Beyond the almost ubiquitous loss of wild-type p53 and RB1, SCLC is characterized by heterogeneously mis-regulated expression of MYC family members, yes-associated protein 1 (YAP1), NOTCH pathway signalling, anti-apoptotic BCL2 and epigenetic regulators. Molecular subtypes are based on the neurogenic transcription factors achaete-scute homologue 1 (ASCL1) and neurogenic differentiation factor 1 (NEUROD1), the rarer non-neuroendocrine transcription factor POU class 2 homeobox 3 (POU2F3), and immune- and inflammation-related signatures. Furthermore, SCLC shows phenotypic plasticity, including neuroendocrine-to-non-neuroendocrine transition driven by NOTCH signalling, which is associated with disease progression, chemoresistance and immune modulation and, in mouse models, with metastasis. Although these features pose substantial challenges, understanding the molecular vulnerabilities of transcription factor subtypes, the functional relevance of plasticity and cell cooperation offer opportunities for personalized therapies informed by liquid and tissue biomarkers.

Deciphering pre-existing and induced 3D genome architecture changes involved in constricted melanoma migration

Metastatic cancer cells traverse constricted spaces that exert forces on their nucleus and the genomic contents within. Cancerous tumors are highly heterogeneous and not all cells within them can achieve such a feat. Here, we investigated what initial genome architecture characteristics favor the constricted migratory ability of cancer cells and which arise only after passage through multiple constrictions. We identified a cell surface protein (ITGB4) whose expression correlates with increased initial constricted migration ability in human melanoma A375 cells. Sorting out this subpopulation allowed us to identify cellular and nuclear features that pre-exist and favor migration, as well as alterations that only appear after cells have passed through constrictions. We identified specific genomic regions that experienced altered genome spatial compartment profiles only after constricted migration. Our study reveals 3D genome structure contributions to both selection and induction mechanisms of cell fate change during cancer metastasis.

Cancer immune evasion, immunoediting and intratumour heterogeneity

Cancers can avoid immune-mediated elimination by acquiring traits that disrupt antitumour immunity. These mechanisms of immune evasion are selected and reinforced during tumour evolution under immune pressure. Some immunogenic subclones are effectively eliminated by antitumour T cell responses (a process known as immunoediting), which results in a clonally selected tumour. Other cancer cells arise to resist immunoediting, which leads to a tumour that includes several distinct cancer cell populations (referred to as intratumour heterogeneity (ITH)). Tumours with high ITH are associated with poor patient outcomes and a lack of responsiveness to immune checkpoint blockade therapy. In this Review, we discuss the different ways that cancer cells evade the immune system and how these mechanisms impact immunoediting and tumour evolution. We also describe how subclonal antigen presentation in tumours with high ITH can result in immune evasion.

Primary de novo Epidermal Growth Factor Receptor Mutant Small Cell Lung Carcinomas: Clinicopathological Study of a Rare Entity Presenting in Treatment-Naïve Setting with Review of Literature

Introduction: Small cell lung carcinomas (SCLC) are characterized by loss of function mutations in genes encoding for p53 (tumor protein p53-TP53) and retinoblastoma transcriptional corepressor 1 (RB1) proteins in the majority of tumors. They are aggressive, usually present with metastatic disease, and are treated with platinum-based chemotherapy with overall poor outcomes. Epidermal growth factor receptor (EGFR) mutations, classically associated with primary lung adenocarcinomas, have been reported in rare de novo SCLC outside the context of the relatively more common transformed SCLC that arise with emergence of tyrosine kinase inhibitor resistance in EGFR-mutant adenocarcinomas. Aim: To analyze the clinicopathological features of EGFR-mutant de novo SCLC. Methods: EGFR-mutant de novo SCLCs were retrieved over 5 years and reviewed for clinicopathological parameters. Results: Five patients were identified harboring either exon 19 deletion (n = 4) or exon 21 L858R mutation (n = 1) in EGFR. Median age at diagnosis was 48 years (30-58 years). Four patients were never-smokers of whom three were tobacco chewers. Three biopsies showed pure small cell carcinoma while others showed composite adenocarcinoma. Diffuse loss of RB1 (5/5) and mutant type p53 staining pattern (3/3) were noted in all tested samples. Among two patient samples subjected to sequencing, additional pathogenic mutations in TP53 (2/2), RB1 (1/2), PTEN (1/2), neurofibromatosis type 1 (1/2), and CREBB1 (1/2) were identified. Conclusion: EGFR-mutant de novo SCLCs are extremely rare and show frequent inactivation of p53 and RB1, like the more common transformed SCLCs. Given the lack of tyrosine kinase inhibitor exposure, these tumors highlight the inherent lineage plasticity of EGFR/TP53/RB1 triple mutant lung carcinomas.

Lactate controls cancer stemness and plasticity through epigenetic regulation

Tumors arise from uncontrolled cell proliferation driven by mutations in genes that regulate stem cell renewal and differentiation. Intestinal tumors, however, retain some hierarchical organization, maintaining both cancer stem cells (CSCs) and cancer differentiated cells (CDCs). This heterogeneity, coupled with cellular plasticity enabling CDCs to revert to CSCs, contributes to therapy resistance and relapse. Using genetically encoded fluorescent reporters in human tumor organoids, combined with our machine-learning-based cell tracker, CellPhenTracker, we simultaneously traced cell-type specification, metabolic changes, and reconstructed cell lineage trajectories during tumor organoid development. Our findings reveal distinctive metabolic phenotypes in CSCs and CDCs. We find that lactate regulates tumor dynamics, suppressing CSC differentiation and inducing dedifferentiation into a proliferative CSC state. Mechanistically, lactate increases histone acetylation, epigenetically activating MYC. Given that lactate's regulation of MYC depends on the bromodomain-containing protein 4 (BRD4), targeting cancer metabolism and BRD4 inhibitors emerge as a promising strategy to prevent tumor relapse.

Tumor Heterogeneity and the Immune Response in Non-Small Cell Lung Cancer: Emerging Insights and Implications for Immunotherapy

Resistance to immune checkpoint inhibitors (ICIs) represents a major challenge for the effective treatment of non-small cell lung cancer (NSCLC). Tumor heterogeneity has been identified as an important mechanism of treatment resistance in cancer and has been increasingly implicated in ICI resistance. The diversity and clonality of tumor neoantigens, which represent the target epitopes for tumor-specific immune cells, have been shown to impact the efficacy of immunotherapy. Advances in genomic techniques have further enhanced our understanding of clonal landscapes within NSCLC and their evolution in response to therapy. In this review, we examine the role of tumor heterogeneity during immune surveillance in NSCLC and highlight its spatial and temporal evolution as revealed by modern technologies. We explore additional sources of heterogeneity, including epigenetic and metabolic factors, that have come under greater scrutiny as potential mediators of the immune response. We finally discuss the implications of tumor heterogeneity on the efficacy of ICIs and highlight potential strategies for overcoming therapeutic resistance.

Combination therapy with expanded natural killer cells and atezolizumab exerts potent antitumor immunity in small cell lung cancer

Despite an initial response to platinum-based chemotherapy, most patients with extensive stage of small cell lung cancer (SCLC) have a poor prognosis due to recurrence. Additionally, the benefit of immune checkpoint inhibitors is more modest than non-small cell lung cancer. Natural killer (NK) cells can directly eliminate cancer cells without prior sensitization; this is largely governed by inflammatory cytokines, which serve as killing signals to cancer cells. Here, we investigated whether the combination of NK cells plus atezolizumab, a fully humanized monoclonal antibody that specifically targets the protein programmed death-ligand 1 (PD-L1), has a synergistic effect against SCLC. NK cells were expanded and activated using irradiated K562 feeder cells in the presence of interleukin (IL)-2/IL-15/IL-21/41BB ligand for 14 days. Expanded and activated NK cells (eNK) were combined with atezolizumab and used to treat SCLC cells in both in vitro and in vivo studies. The results revealed increased PD-L1 expression in SCLC cells after the eNK challenge. eNK cells plus atezolizumab demonstrated increased cytotoxicity toward target SCLC cells, as evidenced by increased interferon-γ and tumor necrosis factor-α production, and higher levels of SCLC stem cell (CD44+CD90+) suppression. Combined treatment with eNK and atezolizumab more effectively inhibited SCLC tumor growth and significantly prolonged the survival of treated mice. Our findings revealed that combining eNK with atezolizumab strongly increased cytotoxicity, significantly inhibited SCLC tumor growth, and prolonged the survival of treated mice. These results provide a framework for developing a more advanced immunotherapeutic modality for future clinical trials for patients with SCLC.

A highly resolved integrated single-cell atlas of HPV-negative head and neck cancer

Head and Neck Squamous Cell Carcinomas (HNSCC) are the seventh most prevalent form of cancer and are associated with human papilloma virus infection (HPV-positive) or with tobacco and alcohol use (HPV-negative). HPV-negative HNSCCs have a high recurrence rate, and individual patients' responses to treatment vary greatly due to the high level of cellular heterogeneity of the tumor and its microenvironment. Here, we describe a HNSCC single cell atlas, which we created by integrating six publicly available datasets encompassing over 230,000 cells across 54 patients. We contextualized the relationships between existing signatures and cell populations, identified new subpopulations, and show the power of this large-scale resource to robustly identify associations between transcriptional signatures and clinical phenotypes that would not be possible to discover using fewer patients. We reveal a previously undefined myeloid population, sex-associated changes in cell type proportions, and novel interactions between CXCL8-positive fibroblasts and vascular endothelial cells. Beyond our findings, the atlas will serve as a public resource for the high-resolution characterization of tumor heterogeneity of HPV-negative HNSCC.

Intrinsic electrical activity drives small-cell lung cancer progression

Elevated or ectopic expression of neuronal receptors promotes tumour progression in many cancer types1,2; neuroendocrine (NE) transformation of adenocarcinomas has also been associated with increased aggressiveness3. Whether the defining neuronal feature, namely electrical excitability, exists in cancer cells and impacts cancer progression remains mostly unexplored. Small-cell lung cancer (SCLC) is an archetypal example of a highly aggressive NE cancer and comprises two major distinct subpopulations: NE cells and non-NE cells4,5. Here we show that NE cells, but not non-NE cells, are excitable, and their action potential firing directly promotes SCLC malignancy. However, the resultant high ATP demand leads to an unusual dependency on oxidative phosphorylation in NE cells. This finding contrasts with the properties of most cancer cells reported in the literature, which are non-excitable and rely heavily on aerobic glycolysis. Additionally, we found that non-NE cells metabolically support NE cells, a process akin to the astrocyte-neuron metabolite shuttle6. Finally, we observed drastic changes in the innervation landscape during SCLC progression, which coincided with increased intratumoural heterogeneity and elevated neuronal features in SCLC cells, suggesting an induction of a tumour-autonomous vicious cycle, driven by cancer cell-intrinsic electrical activity, which confers long-term tumorigenic capability and metastatic potential.

Sociobiology meets oncology: unraveling altruistic cooperation in cancer cells and its implications

Altruism, an act of benefiting others at a cost to the self, challenges our understanding of evolution. This Perspective delves into the importance of altruism in cancer cells and its implications for therapy. Against the backdrop of existing knowledge on various social organisms found in nature, we explore the mechanisms underlying the manifestation of altruism within breast tumors, revealing a complex interplay of seemingly counteracting cancer signaling pathways and processes that orchestrate the delicate balance between cost and benefit underlying altruistic cooperation. We also discuss how evolutionary game theory, coupled with contemporary molecular tools, may shed light on understudied mechanisms governing the dynamics of altruistic cooperation in cancer cells. Finally, we discuss how molecular insights gleaned from these mechanistic dissections may fuel advancements in our comprehension of altruism among cancer cells, with implications across multiple disciplines, offering innovative prospects for therapeutic strategies, molecular discoveries, and evolutionary investigations.

Autophagic flux modulates tumor heterogeneity and lineage plasticity in SCLC

Introduction

Small cell lung cancer (SCLC) is characterized by significant heterogeneity and plasticity, contributing to its aggressive progression and therapy resistance. Autophagy, a conserved cellular process, is implicated in many cancers, but its role in SCLC remains unclear.

Methods

Using a genetically engineered mouse model (Rb1fl/fl ; Trp53fl/fl ; GFP-LC3-RFP-LC3△G), we tracked autophagic flux in vivo to investigate its effects on SCLC biology. Additional in vitro experiments were conducted to modulate autophagic flux in NE and non-NE SCLC cell lines.

Results

Tumor subpopulations with high autophagic flux displayed increased proliferation, enhanced metastatic potential, and neuroendocrine (NE) characteristics. Conversely, low-autophagic flux subpopulations exhibited immune-related signals and non-NE traits. In vitro, increasing autophagy induced NE features in non-NE cell lines, while autophagy inhibition in NE cell lines promoted non-NE characteristics.

Discussion

This study provides a novel model for investigating autophagy in vivo and underscores its critical role in driving SCLC heterogeneity and plasticity, offering potential therapeutic insights.

Comparison of molecular subtype composition between independent sets of primary and brain metastatic small cell lung carcinoma and matched samples

INTRODUCTION

Recent advances in the subclassification of small cell lung carcinomas (SCLCs) may help to overcome the unmet need for targeted therapies and improve survival. However, limited information is available on how the expression of the subtype markers changes during tumour progression. Our study aimed to compare the expression of these markers in primary and brain metastatic SCLCs.

MATERIALS AND METHODS

Immunohistochemical analysis of the subtype markers was performed on 120 SCLCs (including 10 matched samples) and SCLC xenografts.

RESULTS

Compared to primary SCLCs, there was a significant increase in the proportion of mixed subtypes in brain metastases, with a rate of ASCL1high/NeuroD1high and ASCL1high/NeuroD1high/YAP1high subtypes increasing to 48 % and 18 %, respectively. The subtype of the paired samples matched in only one-third of the cases. Although we did not observe a significant change after chemotherapy, a continuous decrease in ASCL1 expression coupled with an increase in the NeuroD1 expression was detected in the xenografts in a long-term experiment.

DISCUSSION

Our results indicate that the expression of subtype markers frequently changes during disease progression, and subtype analysis of the primary SCLC may not provide accurate information about the characteristics of the recurrent or metastatic tumour. Therefore, repeated sampling and subtyping may be necessary for subtype-specific targeted therapy.

Small cell lung cancer with liver metastases: from underlying mechanisms to treatment strategies

Small cell lung cancer (SCLC) represents an aggressive neuroendocrine (NE) tumor within the pulmonary region, characterized by very poor prognoses. Druggable targets for SCLC remain limited, thereby constraining treatment options available to patients. Immuno-chemotherapy has emerged as a pivotal therapeutic strategy for extensive-stage SCLC (ES-SCLC), yet it fails to confer significant efficacy in cases involving liver metastases (LMs) originating from SCLC. Therefore, our attention is directed towards the challenging subset of SCLC patients with LMs. Disease progression of LM-SCLC patients is affected by various factors in the tumor microenvironment (TME), including immune cells, blood vessels, inflammatory mediators, metabolites, and NE substances. Beyond standard immuno-chemotherapy, ongoing efforts to manage LMs in SCLC encompass anti-angiogenic therapy, radiotherapy, microwave ablation (MWA) / radiofrequency ablation (RFA), trans-arterial chemoembolization (TACE), and systemic therapies in conjunction with local interventions. Prospective experimental and clinical investigations into SCLC should prioritize precise and individualized approaches to enhance the prognosis across distinct patient cohorts.

Small cell lung cancer profiling: an updated synthesis of subtypes, vulnerabilities, and plasticity

Small cell lung cancer (SCLC) is a devastating disease with high proliferative and metastatic capacity. SCLC has been classified into molecular subtypes based on differential expression of lineage-defining transcription factors. Recent studies have proposed new subtypes that are based on both tumor-intrinsic and -extrinsic factors. SCLC demonstrates substantial intratumoral subtype heterogeneity characterized by highly plastic transcriptional states, indicating that the initially dominant subtype can shift during disease progression and in association with resistance to therapy. Strategies to promote or constrain plasticity and cell fate transitions have nominated novel targets that could prompt the development of more durably effective therapies for patients with SCLC. In this review, we describe the latest advances in SCLC subtype classification and their biological and clinical implications.

Small Cell Lung Cancer Neuronal Features and Their Implications for Tumor Progression, Metastasis, and Therapy

Small cell lung cancer (SCLC) is an epithelial neuroendocrine form of lung cancer for which survival rates remain dismal and new therapeutic approaches are greatly needed. Key biological features of SCLC tumors include fast growth and widespread metastasis, as well as rapid resistance to treatment. Similar to pulmonary neuroendocrine cells, SCLC cells have traits of both hormone-producing cells and neurons. In this study, we specifically discuss the neuronal features of SCLC. We consider how neuronal G protein-coupled receptors and other neuronal molecules on the surface of SCLC cells can contribute to the growth of SCLC tumors and serve as therapeutic targets in SCLC. We also review recent evidence for the role of neuronal programs expressed by SCLC cells in the fast proliferation, migration, and metastasis of these cells. We further highlight how these neuronal programs may be particularly relevant for the development of brain metastases and how they can assist SCLC cells to functionally interact with neurons and astrocytes. A greater understanding of the molecular and cellular neuronal features of SCLC is likely to uncover new vulnerabilities in SCLC cells, which may help develop novel therapeutic approaches. More generally, the epithelial-to-neuronal transition observed during tumor progression in SCLC and other cancer types can contribute significantly to tumor development and response to therapy.

Deciphering Pre-existing and Induced 3D Genome Architecture Changes involved in Constricted Melanoma Migration

Metastatic cancer cells traverse constricted spaces that exert forces on their nucleus and the genomic contents within. Cancerous tumors are highly heterogeneous and not all cells within them can achieve such a feat. Here, we investigated what initial genome architecture characteristics favor the constricted migratory ability of cancer cells and which arise only after passage through multiple constrictions. We identified a cell surface protein (ITGB4) whose expression correlates with increased initial constricted migration ability in human melanoma A375 cells. Sorting out this subpopulation allowed us to identify cellular and nuclear features that pre-exist and favor migration, as well as alterations that only appear after cells have passed through constrictions. We identified specific genomic regions that experienced altered genome spatial compartment profiles only after constricted migration. Our study reveals 3D genome structure contributions to both selection and induction mechanisms of cell fate change during cancer metastasis.

Small Cell Lung Cancer-An Update on Chemotherapy Resistance

OPINION STATEMENT

Compared to other types of lung cancer, small cell lung cancer (SCLC) exhibits aggressive characteristics that promote drug resistance. Despite platinum-etoposide chemotherapy combined with immunotherapy being the current standard treatment, the rapid development of drug resistance has led to unsatisfactory clinical outcomes. This review focuses on the mechanisms contributing to the chemotherapy resistance phenotype in SCLC, such as increased intra-tumoral heterogeneity, alterations in the tumor microenvironment, changes in cellular metabolism, and dysregulation of apoptotic pathways. A comprehensive understanding of these drug resistance mechanisms in SCLC is imperative for ushering in a new era in cancer research, which will promise revolutionary advancements in cancer diagnosis and treatment methodologies.

SMARCA4 controls state plasticity in small cell lung cancer through regulation of neuroendocrine transcription factors and REST splicing

INTRODUCTION

Small Cell Lung Cancer (SCLC) can be classified into transcriptional subtypes with distinct degrees of neuroendocrine (NE) differentiation. Recent evidence supports plasticity among subtypes with a bias toward adoption of low-NE states during disease progression or upon acquired chemotherapy resistance. Here, we identify a role for SMARCA4, the catalytic subunit of the SWI/SNF complex, as a regulator of subtype shift in SCLC.

METHODS

ATACseq and RNAseq experiments were performed in SCLC cells after pharmacological inhibition of SMARCA4. DNA binding of SMARCA4 was characterized by ChIPseq in high-NE SCLC patient derived xenografts (PDXs). Enrichment analyses were applied to transcriptomic data. Combination of FHD-286 and afatinib was tested in vitro and in a set of chemo-resistant SCLC PDXs in vivo.

RESULTS

SMARCA4 expression positively correlates with that of NE genes in both SCLC cell lines and patient tumors. Pharmacological inhibition of SMARCA4 with FHD-286 induces the loss of NE features and downregulates neuroendocrine and neuronal signaling pathways while activating non-NE factors. SMARCA4 binds to gene loci encoding NE-lineage transcription factors ASCL1 and NEUROD1 and alters chromatin accessibility, enhancing NE programs. Enrichment analysis applied to high-confidence SMARCA4 targets confirmed neuron related pathways as the top GO Biological processes regulated by SMARCA4 in SCLC. In parallel, SMARCA4 also controls REST, a known suppressor of the NE phenotype, by regulating SRRM4-dependent REST transcript splicing. Furthermore, SMARCA4 inhibition drives ERBB pathway activation in SCLC, rendering SCLC tumors sensitive to afatinib.

CONCLUSIONS

This study nominates SMARCA4 as a key regulator of the NE state plasticity and defines a novel therapeutic strategy for SCLC.

Microenvironment shapes small-cell lung cancer neuroendocrine states and presents therapeutic opportunities

Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC's adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.

Gastrointestinal stromal tumor with small cell carcinoma infiltration: a case report

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors of the digestive system. They usually occur in the gastrointestinal tract. However, we discovered a rare phenomenon in which small cell carcinoma infiltrated the GIST of a patient. The patient came to the hospital and presented with chest tightness and shortness of breath for 2 months and a dry cough for half a month. As the ancillary tests were refined, it was discovered that he also had a lesion in the pelvic cavity. After pathological examination of the core needle biopsy (CNB) samples from the pelvic cavity lesion, the patient was diagnosed with GIST with small cell carcinoma infiltration. The patient is currently receiving a chemotherapy regimen of etoposide combined with cisplatin.

Extracellular vesicles from non-neuroendocrine SCLC cells promote adhesion and survival of neuroendocrine SCLC cells

Small cell lung cancer (SCLC) tumors are made up of distinct cell subpopulations, including neuroendocrine (NE) and non-neuroendocrine (non-NE) cells. While secreted factors from non-NE SCLC cells have been shown to support the growth of the NE cells, the underlying molecular factors are not well understood. Here, we show that exosome-type small extracellular vesicles (SEVs) secreted from non-NE SCLC cells promote adhesion and survival of NE SCLC cells. Proteomic analysis of purified SEVs revealed that extracellular matrix (ECM) proteins and integrins are highly enriched in SEVs of non-NE cells whereas nucleic acid-binding proteins are enriched in SEVs purified from NE cells. Addition of select purified ECM proteins identified in purified extracellular vesicles (EVs), specifically fibronectin, laminin 411, and laminin 511, were able to substitute for the role of non-NE-derived SEVs in promoting adhesion and survival of NE SCLC cells. Those same proteins were differentially expressed by human SCLC subtypes. These data suggest that ECM-carrying SEVs secreted by non-NE cells play a key role in supporting the growth and survival of NE SCLC cells.

Landscape and Treatment Options of Shapeshifting Small Cell Lung Cancer

Small cell lung cancer (SCLC) is a deadly neuroendocrine malignancy, notorious for its rapid tumor growth, early metastasis, and relatively "cold" immune environment. Only standard chemotherapies and a few immune checkpoint inhibitors have been approved for SCLC treatment, revealing an urgent need for novel therapeutic approaches. Moreover, SCLC has been recently recognized as a malignancy with high intratumoral and intertumoral heterogeneity, which explains the modest response rate in some patients and the early relapse. Molecular subtypes defined by the expression of lineage-specific transcription factors (ASCL1, NEUROD1, POU2F3, and, in some studies, YAP1) or immune-related genes display different degrees of neuroendocrine differentiation, immune cell infiltration, and response to treatment. Despite the complexity of this malignancy, a few biomarkers and targets have been identified and many promising drugs are currently undergoing clinical trials. In this review, we integrate the current progress on the genomic landscape of this shapeshifting malignancy, the characteristics and treatment vulnerabilities of each subtype, and promising drugs in clinical phases.

Small cells - big issues: biological implications and preclinical advancements in small cell lung cancer

Current treatment guidelines refer to small cell lung cancer (SCLC), one of the deadliest human malignancies, as a homogeneous disease. Accordingly, SCLC therapy comprises chemoradiation with or without immunotherapy. Meanwhile, recent studies have made significant advances in subclassifying SCLC based on the elevated expression of the transcription factors ASCL1, NEUROD1, and POU2F3, as well as on certain inflammatory characteristics. The role of the transcription regulator YAP1 in defining a unique SCLC subset remains to be established. Although preclinical analyses have described numerous subtype-specific characteristics and vulnerabilities, the so far non-existing clinical subtype distinction may be a contributor to negative clinical trial outcomes. This comprehensive review aims to provide a framework for the development of novel personalized therapeutic approaches by compiling the most recent discoveries achieved by preclinical SCLC research. We highlight the challenges faced due to limited access to patient material as well as the advances accomplished by implementing state-of-the-art models and methodologies.

Transforming lung cancer types

Lung cancer cells can escape targeted therapy by switching oncogenic drivers and cell identity.

Dynamic phenotypic reprogramming and chemoresistance induced by lung fibroblasts in small cell lung cancer

Small cell lung cancer (SCLC) is heterogenous in phenotype and microenvironment. Dynamic phenotypic reprogramming, leading to heterogeneity, is prevalent in SCLC, while the mechanisms remain incompletely understood. Cancer-associated fibroblasts (CAFs) possess comprehensive roles in cancer progression, while their function in phenotypic reprogramming of SCLC remain elusive. Here, we obtained transcriptome data of SCLC tissues from publicly available databases, subsequently estimated abundance of CAFs. We found CAF-abundant SCLC exhibited non-neuroendocrine (Non-NE) characteristics. Supporting this, the positive correlation of expression level of α-SMA, the CAF marker, and expression level of REST, protein typically expressed in Non-NE type SCLC, was identified in SCLC tissue arrays. Moreover, we revealed that fibroblasts inhibited NE markers expression and cell proliferation of SCLC cells in the co-culture system comprising lung fibroblasts and SCLC cells, indicating a phenotypic reprogramming from NE to Non-NE. During this process, fibroblast-derived IL-6 activated the JAK2/STAT3 signaling, upregulated c-MYC expression, and subsequently activated the NOTCH pathway, driving phenotypic reprogramming. Moreover, CAF-enriched SCLC exhibited increased immune cell infiltration, elevated expression of immune activation-related signatures, and checkpoint molecules. Our data also highlighted the chemoresistance induced by fibroblasts in SCLC cells, which was effectively reversed by JAK inhibitor. In conclusion, fibroblasts induced phenotypic reprogramming of SCLC cells from NE to Non-NE, likely contributes to inflamed immune microenvironment and chemoresistance. These findings provide novel insights into the clinical implications of CAFs in SCLC.

Genetically-engineered mouse models of small cell lung cancer: the next generation

Small cell lung cancer (SCLC) remains the most fatal form of lung cancer, with patients in dire need of new and effective therapeutic approaches. Modeling SCLC in an immunocompetent host is essential for understanding SCLC pathogenesis and ultimately discovering and testing new experimental therapeutic strategies. Human SCLC is characterized by near universal genetic loss of the RB1 and TP53 tumor suppressor genes. Twenty years ago, the first genetically-engineered mouse model (GEMM) of SCLC was generated using conditional deletion of both Rb1 and Trp53 in the lungs of adult mice. Since then, several other GEMMs of SCLC have been developed coupling genomic alterations found in human SCLC with Rb1 and Trp53 deletion. Here we summarize how GEMMs of SCLC have contributed significantly to our understanding of the disease in the past two decades. We also review recent advances in modeling SCLC in mice that allow investigators to bypass limitations of the previous generation of GEMMs while studying new genes of interest in SCLC. In particular, CRISPR/Cas9-mediated somatic gene editing can accelerate how new genes of interest are functionally interrogated in SCLC tumorigenesis. Notably, the development of allograft models and precancerous precursor models from SCLC GEMMs provides complementary approaches to GEMMs to study tumor cell-immune microenvironment interactions and test new therapeutic strategies to enhance response to immunotherapy. Ultimately, the new generation of SCLC models can accelerate research and help develop new therapeutic strategies for SCLC.

Dynamic altruistic cooperation within breast tumors

BACKGROUND

Social behaviors such as altruism, where one self-sacrifices for collective benefits, critically influence an organism's survival and responses to the environment. Such behaviors are widely exemplified in nature but have been underexplored in cancer cells which are conventionally seen as selfish competitive players. This multidisciplinary study explores altruism and its mechanism in breast cancer cells and its contribution to chemoresistance.

METHODS

MicroRNA profiling was performed on circulating tumor cells collected from the blood of treated breast cancer patients. Cancer cell lines ectopically expressing candidate miRNA were used in co-culture experiments and treated with docetaxel. Ecological parameters like relative survival and relative fitness were assessed using flow cytometry. Functional studies and characterization performed in vitro and in vivo include proliferation, iTRAQ-mass spectrometry, RNA sequencing, inhibition by small molecules and antibodies, siRNA knockdown, CRISPR/dCas9 inhibition and fluorescence imaging of promoter reporter-expressing cells. Mathematical modeling based on evolutionary game theory was performed to simulate spatial organization of cancer cells.

RESULTS

Opposing cancer processes underlie altruism: an oncogenic process involving secretion of IGFBP2 and CCL28 by the altruists to induce survival benefits in neighboring cells under taxane exposure, and a self-sacrificial tumor suppressive process impeding proliferation of altruists via cell cycle arrest. Both processes are regulated concurrently in the altruists by miR-125b, via differential NF-κB signaling specifically through IKKβ. Altruistic cells persist in the tumor despite their self-sacrifice, as they can regenerate epigenetically from non-altruists via a KLF2/PCAF-mediated mechanism. The altruists maintain a sparse spatial organization by inhibiting surrounding cells from adopting the altruistic fate via a lateral inhibition mechanism involving a GAB1-PI3K-AKT-miR-125b signaling circuit.

CONCLUSIONS

Our data reveal molecular mechanisms underlying manifestation, persistence and spatial spread of cancer cell altruism. A minor population behave altruistically at a cost to itself producing a collective benefit for the tumor, suggesting tumors to be dynamic social systems governed by the same rules of cooperation in social organisms. Understanding cancer cell altruism may lead to more holistic models of tumor evolution and drug response, as well as therapeutic paradigms that account for social interactions. Cancer cells constitute tractable experimental models for fields beyond oncology, like evolutionary ecology and game theory.

Biomarkers and experimental models for cancer immunology investigation

The rapid advancement of tumor immunotherapies poses challenges for the tools used in cancer immunology research, highlighting the need for highly effective biomarkers and reproducible experimental models. Current immunotherapy biomarkers encompass surface protein markers such as PD-L1, genetic features such as microsatellite instability, tumor-infiltrating lymphocytes, and biomarkers in liquid biopsy such as circulating tumor DNAs. Experimental models, ranging from 3D in vitro cultures (spheroids, submerged models, air-liquid interface models, organ-on-a-chips) to advanced 3D bioprinting techniques, have emerged as valuable platforms for cancer immunology investigations and immunotherapy biomarker research. By preserving native immune components or coculturing with exogenous immune cells, these models replicate the tumor microenvironment in vitro. Animal models like syngeneic models, genetically engineered models, and patient-derived xenografts provide opportunities to study in vivo tumor-immune interactions. Humanized animal models further enable the simulation of the human-specific tumor microenvironment. Here, we provide a comprehensive overview of the advantages, limitations, and prospects of different biomarkers and experimental models, specifically focusing on the role of biomarkers in predicting immunotherapy outcomes and the ability of experimental models to replicate the tumor microenvironment. By integrating cutting-edge biomarkers and experimental models, this review serves as a valuable resource for accessing the forefront of cancer immunology investigation.

Data-driven structural analysis of small cell lung cancer transcription factor network suggests potential subtype regulators and transition pathways

Small cell lung cancer (SCLC) is an aggressive disease and challenging to treat due to its mixture of transcriptional subtypes and subtype transitions. Transcription factor (TF) networks have been the focus of studies to identify SCLC subtype regulators via systems approaches. Yet, their structures, which can provide clues on subtype drivers and transitions, are barely investigated. Here, we analyze the structure of an SCLC TF network by using graph theory concepts and identify its structurally important components responsible for complex signal processing, called hubs. We show that the hubs of the network are regulators of different SCLC subtypes by analyzing first the unbiased network structure and then integrating RNA-seq data as weights assigned to each interaction. Data-driven analysis emphasizes MYC as a hub, consistent with recent reports. Furthermore, we hypothesize that the pathways connecting functionally distinct hubs may control subtype transitions and test this hypothesis via network simulations on a candidate pathway and observe subtype transition. Overall, structural analyses of complex networks can identify their functionally important components and pathways driving the network dynamics. Such analyses can be an initial step for generating hypotheses and can guide the discovery of target pathways whose perturbation may change the network dynamics phenotypically.

Novel Mouse Cell Lines and In Vivo Models for Human High-Grade Neuroendocrine Lung Carcinoma, Small Cell Lung Carcinoma (SCLC), and Large Cell Neuroendocrine Carcinoma (LCNEC)

There is a clear need to expand the toolkit of adequate mouse models and cell lines available for preclinical studies of high-grade neuroendocrine lung carcinoma (small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC)). SCLC and LCNEC are two highly aggressive tumor types with dismal prognoses and few therapeutic options. Currently, there is an extreme paucity of material, particularly in the case of LCNEC. Given the lack of murine cell lines and transplant models of LCNEC, the need is imperative. In this study, we generated and examined new models of LCNEC and SCLC transplantable cell lines derived from our previously developed primary mouse LCNEC and SCLC tumors. RNA-seq analysis demonstrated that our cell lines and syngeneic tumors maintained the transcriptome program from the original transgenic primary tumor and displayed strong similarities to human SCLC or LCNEC. Importantly, the SCLC transplanted cell lines showed the ability to metastasize and mimic this characteristic of the human condition. In summary, we generated mouse cell line tools that allow further basic and translational research as well as preclinical testing of new treatment strategies for SCLC and LCNEC. These tools retain important features of their human counterparts and address the lack of LCNEC disease models.

Crosstalk between small-cell lung cancer cells and astrocytes mimics brain development to promote brain metastasis

Brain metastases represent an important clinical problem for patients with small-cell lung cancer (SCLC). However, the mechanisms underlying SCLC growth in the brain remain poorly understood. Here, using intracranial injections in mice and assembloids between SCLC aggregates and human cortical organoids in culture, we found that SCLC cells recruit reactive astrocytes to the tumour microenvironment. This crosstalk between SCLC cells and astrocytes drives the induction of gene expression programmes that are similar to those found during early brain development in neurons and astrocytes. Mechanistically, the brain development factor Reelin, secreted by SCLC cells, recruits astrocytes to brain metastases. These astrocytes in turn promote SCLC growth by secreting neuronal pro-survival factors such as SERPINE1. Thus, SCLC brain metastases grow by co-opting mechanisms involved in reciprocal neuron-astrocyte interactions during brain development. Targeting such developmental programmes activated in this cancer ecosystem may help prevent and treat brain metastases.

Lineage Plasticity in SCLC Generates Non-Neuroendocrine Cells Primed for Vasculogenic Mimicry

INTRODUCTION

Vasculogenic mimicry (VM), the process of tumor cell transdifferentiation to endow endothelial-like characteristics supporting de novo vessel formation, is associated with poor prognosis in several tumor types, including SCLC. In genetically engineered mouse models (GEMMs) of SCLC, NOTCH, and MYC co-operate to drive a neuroendocrine (NE) to non-NE phenotypic switch, and co-operation between NE and non-NE cells is required for metastasis. Here, we define the phenotype of VM-competent cells and molecular mechanisms underpinning SCLC VM using circulating tumor cell-derived explant (CDX) models and GEMMs.

METHODS

We analyzed perfusion within VM vessels and their association with NE and non-NE phenotypes using multiplex immunohistochemistry in CDX, GEMMs, and patient biopsies. We evaluated their three-dimensional structure and defined collagen-integrin interactions.

RESULTS

We found that VM vessels are present in 23/25 CDX models, 2 GEMMs, and in 20 patient biopsies of SCLC. Perfused VM vessels support tumor growth and only NOTCH-active non-NE cells are VM-competent in vivo and ex vivo, expressing pseudohypoxia, blood vessel development, and extracellular matrix organization signatures. On Matrigel, VM-primed non-NE cells remodel extracellular matrix into hollow tubules in an integrin β1-dependent process.

CONCLUSIONS

We identified VM as an exemplar of functional heterogeneity and plasticity in SCLC and these findings take considerable steps toward understanding the molecular events that enable VM. These results support therapeutic co-targeting of both NE and non-NE cells to curtail SCLC progression and to improve the outcomes of patients with SCLC in the future.

Clonal cooperation through soluble metabolite exchange facilitates metastatic outgrowth by modulating Allee effect

Cancers feature substantial intratumoral heterogeneity of genetic and phenotypically distinct lineages. Although interactions between coexisting lineages are emerging as a potential contributor to tumor evolution, the extent and nature of these interactions remain largely unknown. We postulated that tumors develop ecological interactions that sustain diversity and facilitate metastasis. Using a combination of fluorescent barcoding, mathematical modeling, metabolic analysis, and in vivo models, we show that the Allee effect, i.e., growth dependency on population size, is a feature of tumor lineages and that cooperative ecological interactions between lineages alleviate the Allee barriers to growth in a model of triple-negative breast cancer. Soluble metabolite exchange formed the basis for these cooperative interactions and catalyzed the establishment of a polyclonal community that displayed enhanced metastatic dissemination and outgrowth in xenograft models. Our results highlight interclonal metabolite exchange as a key modulator of tumor ecology and a contributing factor to overcoming Allee effect-associated growth barriers to metastasis.

Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics

Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.

A Comparative Study of Neuroendocrine Heterogeneity in Small Cell Lung Cancer and Neuroblastoma

Lineage plasticity has long been documented in both small cell lung cancer (SCLC) and neuroblastoma, two clinically distinct neuroendocrine (NE) cancers. In this study, we quantified the NE features of cancer as NE scores and performed a systematic comparison of SCLC and neuroblastoma. We found neuroblastoma and SCLC cell lines have highly similar molecular profiles and shared therapeutic sensitivity. In addition, NE heterogeneity was observed at both the inter- and intra-cell line levels. Surprisingly, we did not find a significant association between NE scores and overall survival in SCLC or neuroblastoma. We described many shared and unique NE score-associated features between SCLC and neuroblastoma, including dysregulation of Myc oncogenes, alterations in protein expression, metabolism, drug resistance, and selective gene dependencies.

IMPLICATIONS

Our work establishes a reference for molecular changes and vulnerabilities associated with NE to non-NE transdifferentiation through mutual validation of SCLC and neuroblastoma samples.

Transcription factor networks link B-lymphocyte development and malignant transformation in leukemia

Rapid advances in genomics have opened unprecedented possibilities to explore the mutational landscapes in malignant diseases, such as B-cell acute lymphoblastic leukemia (B-ALL). This disease is manifested as a severe defect in the production of normal blood cells due to the uncontrolled expansion of transformed B-lymphocyte progenitors in the bone marrow. Even though classical genetics identified translocations of transcription factor-coding genes in B-ALL, the extent of the targeting of regulatory networks in malignant transformation was not evident until the emergence of large-scale genomic analyses. There is now evidence that many B-ALL cases present with mutations in genes that encode transcription factors with critical roles in normal B-lymphocyte development. These include PAX5, IKZF1, EBF1, and TCF3, all of which are targeted by translocations or, more commonly, partial inactivation in cases of B-ALL. Even though there is support for the notion that germline polymorphisms in the PAX5 and IKZF1 genes predispose for B-ALL, the majority of leukemias present with somatic mutations in transcription factor-encoding genes. These genetic aberrations are often found in combination with mutations in genes that encode components of the pre-B-cell receptor or the IL-7/TSLP signaling pathways, all of which are important for early B-cell development. This review provides an overview of our current understanding of the molecular interplay that occurs between transcription factors and signaling events during normal and malignant B-lymphocyte development.

Unified tumor growth mechanisms from multimodel inference and dataset integration

Mechanistic models of biological processes can explain observed phenomena and predict responses to a perturbation. A mathematical model is typically constructed using expert knowledge and informal reasoning to generate a mechanistic explanation for a given observation. Although this approach works well for simple systems with abundant data and well-established principles, quantitative biology is often faced with a dearth of both data and knowledge about a process, thus making it challenging to identify and validate all possible mechanistic hypothesis underlying a system behavior. To overcome these limitations, we introduce a Bayesian multimodel inference (Bayes-MMI) methodology, which quantifies how mechanistic hypotheses can explain a given experimental datasets, and concurrently, how each dataset informs a given model hypothesis, thus enabling hypothesis space exploration in the context of available data. We demonstrate this approach to probe standing questions about heterogeneity, lineage plasticity, and cell-cell interactions in tumor growth mechanisms of small cell lung cancer (SCLC). We integrate three datasets that each formulated different explanations for tumor growth mechanisms in SCLC, apply Bayes-MMI and find that the data supports model predictions for tumor evolution promoted by high lineage plasticity, rather than through expanding rare stem-like populations. In addition, the models predict that in the presence of cells associated with the SCLC-N or SCLC-A2 subtypes, the transition from the SCLC-A subtype to the SCLC-Y subtype through an intermediate is decelerated. Together, these predictions provide a testable hypothesis for observed juxtaposed results in SCLC growth and a mechanistic interpretation for tumor treatment resistance.

The paradox of cooperation among selfish cancer cells

It is traditionally assumed that during cancer development, tumor cells abort their initially cooperative behavior (i.e., cheat) in favor of evolutionary strategies designed solely to enhance their own fitness (i.e., a "selfish" life style) at the expense of that of the multicellular organism. However, the growth and progress of solid tumors can also involve cooperation among these presumed selfish cells (which, by definition, should be noncooperative) and with stromal cells. The ultimate and proximate reasons behind this paradox are not fully understood. Here, in the light of current theories on the evolution of cooperation, we discuss the possible evolutionary mechanisms that could explain the apparent cooperative behaviors among selfish malignant cells. In addition to the most classical explanations for cooperation in cancer and in general (by-product mutualism, kin selection, direct reciprocity, indirect reciprocity, network reciprocity, group selection), we propose the idea that "greenbeard" effects are relevant to explaining some cooperative behaviors in cancer. Also, we discuss the possibility that malignant cooperative cells express or co-opt cooperative traits normally expressed by healthy cells. We provide examples where considerations of these processes could help understand tumorigenesis and metastasis and argue that this framework provides novel insights into cancer biology and potential strategies for cancer prevention and treatment.

Clonal interactions in cancer: integrating quantitative models with experimental and clinical data

Tumors consist of different genotypically distinct subpopulations-or subclones-of cells. These subclones can influence neighboring clones in a process called "clonal interaction." Conventionally, research on driver mutations in cancer has focused on their cell-autonomous effects that lead to an increase in fitness of the cells containing the driver. Recently, with the advent of improved experimental and computational technologies for investigating tumor heterogeneity and clonal dynamics, new studies have shown the importance of clonal interactions in cancer initiation, progression, and metastasis. In this review we provide an overview of clonal interactions in cancer, discussing key discoveries from a diverse range of approaches to cancer biology research. We discuss common types of clonal interactions, such as cooperation and competition, its mechanisms, and the overall effect on tumorigenesis, with important implications for tumor heterogeneity, resistance to treatment, and tumor suppression. Quantitative models-in coordination with cell culture and animal model experiments-have played a vital role in investigating the nature of clonal interactions and the complex clonal dynamics they generate. We present mathematical and computational models that can be used to represent clonal interactions and provide examples of the roles they have played in identifying and quantifying the strength of clonal interactions in experimental systems. Clonal interactions have proved difficult to observe in clinical data; however, several very recent quantitative approaches enable their detection. We conclude by discussing ways in which researchers can further integrate quantitative methods with experimental and clinical data to elucidate the critical-and often surprising-roles of clonal interactions in human cancers.

Data-driven structural analysis of Small Cell Lung Cancer transcription factor network suggests potential subtype regulators and transition pathways

Small Cell Lung Cancer (SCLC) is an aggressive disease and challenging to treat due to its mixture of transcriptional subtypes and subtype transitions. Transcription factor (TF) networks have been the focus of studies to identify SCLC subtype regulators via systems approaches. Yet, their structures, which can provide clues on subtype drivers and transitions, are barely investigated. Here, we analyze the structure of an SCLC TF network by using graph theory concepts and identify its structurally important components responsible for complex signal processing, called hubs. We show that the hubs of the network are regulators of different SCLC subtypes by analyzing first the unbiased network structure and then integrating RNA-seq data as weights assigned to each interaction. Data-driven analysis emphasizes MYC as a hub, consistent with recent reports. Furthermore, we hypothesize that the pathways connecting functionally distinct hubs may control subtype transitions and test this hypothesis via network simulations on a candidate pathway and observe subtype transition. Overall, structural analyses of complex networks can identify their functionally important components and pathways driving the network dynamics. Such analyses can be an initial step for generating hypotheses and can guide the discovery of target pathways whose perturbation may change the network dynamics phenotypically.

Targeting the Notch signaling pathway and the Notch ligand, DLL3, in small cell lung cancer

Small cell lung cancer (SCLC) is a highly aggressive and poorly differentiated cancer with high-grade neuroendocrine (NE) features, accounting for approximately 15 % of all lung cancers. For decades, chemotherapy and radiotherapy have predominated the treatment strategy for SCLC, but relapses ensue quickly and result in poor survival of patients. Immunotherapy has brought novel insights, yet the efficacy is still restricted to a limited population with SCLC. Notch signaling is identified to play a key role in the initiation and development of SCLC, and the Notch ligand, Delta-like ligand 3 (DLL3) is found broadly and specifically expressed in SCLC cells. Thus, Notch signaling is under active exploration as a potential therapeutic target in SCLC. Herein, we summarized and updated the functional relevance of Notch signaling in SCLC, discussed Notch signaling-targeted therapy for SCLC and the correspondent preclinical and clinical trials, and investigated the promising synergy effects of Notch signaling targeted therapy and immune checkpoint inhibitors (ICIs) treatment.

Molecular features and evolutionary trajectory of ASCL1+ and NEUROD1+ SCLC cells

BACKGROUND

Small cell lung cancer (SCLC) is the most aggressive subtype of lung cancer without recognised morphologic or genetic heterogeneity. Based on the expression of four transcription factors, ASCL1, NEUROD1, POU2F3, and YAP1, SCLCs are classified into four subtypes. However, biological functions of these different subtypes are largely uncharacterised.

METHODS

We studied intratumoural heterogeneity of resected human primary SCLC tissues using single-cell RNA-Seq. In addition, we undertook a series of in vitro and in vivo functional studies to reveal the distinct features of SCLC subtypes.

RESULTS

We identify the coexistence of ASCL1⁺ and NEUROD1⁺ SCLC cells within the same human primary SCLC tissue. Compared with ASCL1⁺ SCLC cells, NEUROD1⁺ SCLC cells show reduced epithelial features and lack EPCAM expression. Thus, EPCAM can be considered as a cell surface marker to distinguish ASCL1⁺ SCLC cells from NEUROD1⁺ SCLC cells. We further demonstrate that NEUROD1⁺ SCLC cells exhibit higher metastatic capability than ASCL1⁺ SCLC cells and can be derived from ASCL1⁺ SCLC cells.

CONCLUSIONS

Our studies unveil the biology and evolutionary trajectory of ASCL1⁺ and NEUROD1⁺ SCLC cells, shedding light on SCLC tumourigenesis and progression.

Involvement of Epithelial-Mesenchymal Transition Genes in Small Cell Lung Cancer Phenotypic Plasticity

Small cell lung cancer (SCLC) is an aggressive cancer recalcitrant to treatment, arising predominantly from epithelial pulmonary neuroendocrine (NE) cells. Intratumor heterogeneity plays critical roles in SCLC disease progression, metastasis, and treatment resistance. At least five transcriptional SCLC NE and non-NE cell subtypes were recently defined by gene expression signatures. Transition from NE to non-NE cell states and cooperation between subtypes within a tumor likely contribute to SCLC progression by mechanisms of adaptation to perturbations. Therefore, gene regulatory programs distinguishing SCLC subtypes or promoting transitions are of great interest. Here, we systematically analyze the relationship between SCLC NE/non-NE transition and epithelial to mesenchymal transition (EMT)-a well-studied cellular process contributing to cancer invasiveness and resistance-using multiple transcriptome datasets from SCLC mouse tumor models, human cancer cell lines, and tumor samples. The NE SCLC-A2 subtype maps to the epithelial state. In contrast, SCLC-A and SCLC-N (NE) map to a partial mesenchymal state (M1) that is distinct from the non-NE, partial mesenchymal state (M2). The correspondence between SCLC subtypes and the EMT program paves the way for further work to understand gene regulatory mechanisms of SCLC tumor plasticity with applicability to other cancer types.

A multiplexed in vivo approach to identify driver genes in small cell lung cancer

Small cell lung cancer (SCLC) is a lethal form of lung cancer. Here, we develop a quantitative multiplexed approach on the basis of lentiviral barcoding with somatic CRISPR-Cas9-mediated genome editing to functionally investigate candidate regulators of tumor initiation and growth in genetically engineered mouse models of SCLC. We found that naphthalene pre-treatment enhances lentiviral vector-mediated SCLC initiation, enabling high multiplicity of tumor clones for analysis through high-throughput sequencing methods. Candidate drivers of SCLC identified from a meta-analysis across multiple human SCLC genomic datasets were tested using this approach, which defines both positive and detrimental impacts of inactivating 40 genes across candidate pathways on SCLC development. This analysis and subsequent validation in human SCLC cells establish TSC1 in the PI3K-AKT-mTOR pathway as a robust tumor suppressor in SCLC. This approach should illuminate drivers of SCLC, facilitate the development of precision therapies for defined SCLC genotypes, and identify therapeutic targets.

Orchestration of Collective Migration and Metastasis by Tumor Cell Clusters

Metastatic dissemination has lethal consequences for cancer patients. Accruing evidence supports the hypothesis that tumor cells can migrate and metastasize as clusters of cells while maintaining contacts with one another. Collective metastasis enables tumor cells to colonize secondary sites more efficiently, resist cell death, and evade the immune system. On the other hand, tumor cell clusters face unique challenges for dissemination particularly during systemic dissemination. Here, we review recent progress toward understanding how tumor cell clusters overcome these disadvantages as well as mechanisms they utilize to gain advantages throughout the metastatic process. We consider useful models for studying collective metastasis and reflect on how the study of collective metastasis suggests new opportunities for eradicating and preventing metastatic disease.

Neuroendocrine neoplasms of the lung and gastrointestinal system: convergent biology and a path to better therapies

Neuroendocrine neoplasms (NENs) can develop in almost any organ and span a spectrum from well-differentiated and indolent neuroendocrine tumours (NETs) to poorly differentiated and highly aggressive neuroendocrine carcinomas (NECs), including small-cell lung cancer (SCLC). These neoplasms are thought to primarily derive from neuroendocrine precursor cells located throughout the body and can also arise through neuroendocrine transdifferentiation of organ-specific epithelial cell types. Hence, NENs constitute a group of tumour types that share key genomic and phenotypic characteristics irrespective of their site of origin, albeit with some organ-specific differences. The establishment of representative preclinical models for several of these disease entities together with analyses of human tumour specimens has provided important insights into crucial aspects of their biology with therapeutic implications. In this Review, we provide a comprehensive overview of the current understanding of NENs of the gastrointestinal system and lung from clinical and biological perspectives. Research on NENs has typically been siloed by the tumour site of origin, and a cross-cutting view might enable advances in one area to accelerate research in others. Therefore, we aim to emphasize that a better understanding of the commonalities and differences of NENs arising in different organs might more effectively inform clinical research to define therapeutic targets and ultimately optimize patient care.

DLL3 regulates Notch signaling in small cell lung cancer

Tumor heterogeneity plays a critical role in tumor development and response to treatment. In small-cell lung cancer (SCLC), intratumoral heterogeneity is driven in part by the Notch signaling pathway, which reprograms neuroendocrine cancer cells to a less/non-neuroendocrine state. Here we investigated the atypical Notch ligand DLL3 as a biomarker of the neuroendocrine state and a regulator of cell-cell interactions in SCLC. We first built a mathematical model to predict the impact of DLL3 expression on SCLC cell populations. We next tested this model using a single-chain variable fragment (scFv) to track DLL3 expression in vivo and a new mouse model of SCLC with inducible expression of DLL3 in SCLC tumors. We found that high levels of DLL3 promote the expansion of a SCLC cell population with lower expression levels of both neuroendocrine and non-neuroendocrine markers. This work may influence how DLL3-targeting therapies are used in SCLC patients.

Multivalent state transitions shape the intratumoral composition of small cell lung carcinoma

Studies to date have not resolved how diverse transcriptional programs contribute to the intratumoral heterogeneity of small cell lung carcinoma (SCLC), an aggressive tumor associated with a dismal prognosis. Here, we identify distinct and commutable transcriptional states that confer discrete functional attributes in individual SCLC tumors. We combine an integrative approach comprising the transcriptomes of 52,975 single cells, high-resolution measurement of cell state dynamics at the single-cell level, and functional and correlative studies using treatment naïve xenografts with associated clinical outcomes. We show that individual SCLC tumors contain distinctive proportions of stable cellular states that are governed by bidirectional cell state transitions. Using drugs that target the epigenome, we reconfigure tumor state composition in part by altering individual state transition rates. Our results reveal new insights into how single-cell transition behaviors promote cell state equilibrium in SCLC and suggest that facile plasticity underlies its resistance to therapy and lethality.