Differential development of large-cell neuroendocrine or small-cell lung carcinoma upon inactivation of 4 tumor suppressor genes

Investigation into the Spatial Heterogeneity of Lung Composite Large-Cell Neuroendocrine Carcinoma Spatial Transcriptomic Analysis of Combined Large-Cell Neuroendocrine Carcinoma

Background: Lung combined large-cell neuroendocrine carcinoma (CoLCNEC) refers to lung regions exhibiting both the features of large-cell neuroendocrine carcinoma (LCNEC) and the defined components of nonsmall cell lung cancer (NSCLC), with a relatively high mitotic rate. Diagnosing and predicting the prognosis of CoLCNEC are challenging. This study aimed to explore spatial transcriptomic expression patterns and identify crucial genes. Methods: We utilized a sample from a CoLCNEC patient containing three distinct components, namely, LCNEC, adenocarcinoma, and squamous cell carcinoma, with the former being predominant. Spatial transcriptomics (ST) technology, which employs the 10× Genomics Visium formalin-fixed paraffin-embedded ST kit, was applied along with high-throughput sequencing to obtain gene expression information and spatial locations for each spot. Subsequent analysis included differentially gene expression and functional enrichment. Finally, immunohistochemistry was employed to validate the marker protein structural maintenance of chromosomes 1A (SMC1A). Then, SMC1A was overexpressed and silenced in NCI-H661 and LTEP-a-2 cells, and the migration and invasion ability of the cells were detected by scratch assay and Transwell, respectively. The role of SMC1A in cancer cell cycle was detected by Real-time Reverse Transcription-PCR(RT-qPCR), Western blot, and flow cytometry, the apoptosis was detected by flow cytometry. Results: The results revealed that tumor tissue regions had higher unique molecular identifiers and gene counts than nontumor regions did. Unsupervised clustering identified four clusters, revealing the uniform distribution of unique transcripts, which were mapped onto slices to display apparent spatial separation. Differentially gene expression analysis revealed genes highly expressed in cancer cells. Further analysis of different regions revealed distinct cellular subgroups enriched through differentially gene expression analysis in various pathways, such as the cell cycle and DNA replication. Finally, SMC1A was chosen as a candidate gene, and immunohistochemistry confirmed its elevated expression in tumor regions. In addition, compared with oe-NC, oe-SMC1A can significantly promote the migration, invasion and G1/S phase transition of lung cancer cells, and promote the inhibition of apoptosis of cancer cells, while sh-SMC1A is completely opposite. Conclusions: In the tumor region of CoLCNEC, SMC1A is significantly upregulated. Moreover, silencing SMC1A effectively inhibits lung cancer cell invasion, migration, and G1/S phase transition, while promoting apoptosis. These findings indicate that SMC1A has the potential to be a new therapeutic target for CoLCNEC treatment.

Basic science and translational implications of current knowledge on neuroendocrine tumors

Neuroendocrine tumors (NETs) are a diverse group of malignancies that can occur in various organs, with a notable prevalence in the lungs and gastrointestinal tract, which are the focus of this Review. Although NETs are rare in individual organs, their incidence has increased over recent decades, highlighting the urgent need for current classification systems to evolve by incorporating recent advances in the understanding of NET biology. Several omics studies have revealed molecular subtypes, which, when integrated into existing classification frameworks, may provide more clinically relevant insights for patients with NETs. This Review examines recent progress in elucidating the biology of NETs, with a particular emphasis on the tumor microenvironment and cells of origin. The existence of different cells of origin, which may contribute to distinct molecular groups, along with profiles of immune infiltration - despite being generally low - could explain the emergence of more aggressive cases and the potential for metastatic progression. Given the molecular heterogeneity of NETs and the diversity of their microenvironments and different cells of origin, there is an urgent need to develop morphomolecular classification systems. Such systems would make it possible to better characterize tumor progression, identify new therapeutic targets, and, ultimately, guide the development of personalized therapies.

Spontaneous Transformation from Lung Adenocarcinoma to MYC-amplified Large Cell Neuroendocrine Carcinoma

Recent studies suggest that lung adenocarcinoma cells are closely associated with the tumorigenesis of large-cell neuroendocrine carcinoma via cellular transformation. However, morphological evidence, along with genetic abnormalities before, during, and after transformation, is quite limited. We present here a case of combined large-cell neuroendocrine carcinoma and adenocarcinoma exhibiting acinar and solid patterns. Adenocarcinoma cells with abundant mucin, exhibiting positivity for both napsin-A and neuroendocrine markers, were partially found in the acinar adenocarcinoma component and extensively observed in the solid adenocarcinoma component. Next-generation sequencing using extracted genomic DNA from the three components revealed homozygous TP53 (missense) and STK11 (nonsense) mutations in all three components, suggesting monoclonal origin. Furthermore, MYC gene amplification, recently presumed to be a pivotal driver in neuroendocrine transformation, was observed in both the solid adenocarcinoma and large-cell neuroendocrine carcinoma components. These genetic findings corresponded to pre- and post-transformation morphology, providing compelling evidence that some kinds of adenocarcinomas may serve as a precursor of large-cell neuroendocrine carcinoma.

Clinical characteristics and treatment management of combined large cell neuroendocrine carcinoma, a subtype of large cell neuroendocrine carcinoma

Combined large cell neuroendocrine carcinoma (CLCNEC) is a rare neuroendocrine carcinoma, accounting for approximately 10% of large cell neuroendocrine carcinoma (LCNEC). Mainly composed of coexisting adenocarcinoma components, with strong invasiveness and poor prognosis. The treatment regimen for CLCNEC mainly refers to complete surgical resection as the first choice in the early stage, while patients with stage II or higher require adjuvant treatment. At present, research on CLCNEC is mostly small sample and retrospective, and there is no consensus on whether molecular typing and treatment should be carried out. There is considerable controversy over whether it should be managed as small-cell lung cancer (SCLC) or non-small-cell lung cancer (NSCLC). Therefore, in order to solve the problem of confusion in the selection of treatment regimens for CLCNEC, while also considering the therapeutic effects, this article summarizes and analyzes previous studies, fully seeks evidence, and boldly proposes new therapeutic insights: the etoposide-platinum (EP) regimen serves as the basis for adjuvant therapy; In addition, SCLC/NSCLC-CLCNEC can be distinguished based on presence of RB1 and TP53 co-mutation, and targeted therapy or NSCLC type chemotherapy including platinum + gemcitabine or taxanes (NSCLC-GEM/TAX) can be used in combination or sequentially for NSCLC-CLCNEC.

Neuroendocrine transdifferentiation in human cancer: molecular mechanisms and therapeutic targets

Neuroendocrine transdifferentiation (NEtD), also commonly referred to as lineage plasticity, emerges as an acquired resistance mechanism to molecular targeted therapies in multiple cancer types, predominately occurs in metastatic epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer treated with EGFR tyrosine kinase inhibitors and metastatic castration-resistant prostate cancer treated with androgen receptor targeting therapies. NEtD tumors are the lethal cancer histologic subtype with unfavorable prognosis and limited treatment. A comprehensive understanding of molecular mechanism underlying targeted-induced plasticity could greatly facilitate the development of novel therapies. In the past few years, increasingly elegant studies indicated that NEtD tumors share key the convergent genomic and phenotypic characteristics irrespective of their site of origin, but also embrace distinct change and function of molecular mechanisms. In this review, we provide a comprehensive overview of the current understanding of molecular mechanism in regulating the NEtD, including genetic alterations, DNA methylation, histone modifications, dysregulated noncoding RNA, lineage-specific transcription factors regulation, and other proteomic alterations. We also provide the current management of targeted therapies in clinical and preclinical practice.

Nonviral CRISPR/Cas9 mutagenesis for streamlined generation of mouse lung cancer models

Functional analysis in mouse models is necessary to establish the involvement of a set of genetic variations in tumor development. A modeling platform to facilitate and cost-effectively analyze the role of multiple genes in carcinogenesis would be valuable. Here, we present an innovative strategy for lung mutagenesis using CRISPR/Cas9 ribonucleoproteins delivered via cationic polymers. This approach allows the simultaneous inactivation of multiple genes. We validate the effectiveness of this system by targeting a group of tumor suppressor genes, specifically Rb1, Rbl1, Pten, and Trp53, which were chosen for their potential to cause lung tumors, namely small cell lung carcinoma (SCLC). Tumors with histologic and transcriptomic features of human SCLC emerged after intratracheal administration of CRISPR/polymer nanoparticles. These tumors carried loss-of-function mutations in all four tumor suppressor genes at the targeted positions. These findings were reproduced in two different pure genetic backgrounds. We provide a proof of principle for simplified modeling of lung tumorigenesis to facilitate functional testing of potential cancer-related genes.

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.

Lineage-specific intolerance to oncogenic drivers restricts histological transformation

Lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) are thought to originate from different epithelial cell types in the lung. Intriguingly, LUAD can histologically transform into SCLC after treatment with targeted therapies. In this study, we designed models to follow the conversion of LUAD to SCLC and found that the barrier to histological transformation converges on tolerance to Myc, which we implicate as a lineage-specific driver of the pulmonary neuroendocrine cell. Histological transformations are frequently accompanied by activation of the Akt pathway. Manipulating this pathway permitted tolerance to Myc as an oncogenic driver, producing rare, stem-like cells that transcriptionally resemble the pulmonary basal lineage. These findings suggest that histological transformation may require the plasticity inherent to the basal stem cell, enabling tolerance to previously incompatible oncogenic driver programs.

Establishment and Validation of Prognostic Nomograms for Patients with Metastatic Pulmonary Large Cell Neuroendocrine Carcinoma

PURPOSE

Metastatic pulmonary large cell neuroendocrine carcinoma (LCNEC) is an aggressive cancer with generally poor outcomes. Effective methods for predicting survival in patients with metastatic LCNEC are needed. This study aimed to identify independent survival predictors and develop nomograms for predicting survival in patients with metastatic LCNEC.

PATIENTS AND METHODS

We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, identifying patients with metastatic LCNEC diagnosed between 2010 and 2017. To find independent predictors of cancer-specific survival (CSS), we performed Cox regression analysis. A nomogram was developed to predict the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC. The concordance index (C-index), area under the receiver operating characteristic (ROC) curves (AUC), and calibration curves were adopted with the aim of assessing whether the model can be discriminative and reliable. Decision curve analyses (DCAs) were used to assess the model's utility and benefits from a clinical perspective.

RESULTS

This study enrolled a total of 616 patients, of whom 432 were allocated to the training cohort and 184 to the validation cohort. Age, T staging, N staging, metastatic sites, radiotherapy, and chemotherapy were identified as independent prognostic factors for patients with metastatic LCNEC based on multivariable Cox regression analysis results. The nomogram showed strong performance with C-index values of 0.733 and 0.728 for the training and validation cohorts, respectively. ROC curves indicated good predictive performance of the model, with AUC values of 0.796, 0.735, and 0.736 for predicting the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC in the training cohort, and 0.795, 0.801, and 0.780 in the validation cohort, respectively. Calibration curves and DCAs confirmed the nomogram's reliability and clinical utility.

CONCLUSION

The new nomogram was developed for predicting CSS in patients with metastatic LCNEC, providing personalized risk evaluation and aiding clinical decision-making.

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.

IGF2BP1 induces neuroblastoma via a druggable feedforward loop with MYCN promoting 17q oncogene expression

BACKGROUND

Neuroblastoma is the most common solid tumor in infants accounting for approximately 15% of all cancer-related deaths. Over 50% of high-risk neuroblastoma relapse, emphasizing the need of novel drug targets and therapeutic strategies. In neuroblastoma, chromosomal gains at chromosome 17q, including IGF2BP1, and MYCN amplification at chromosome 2p are associated with adverse outcome. Recent, pre-clinical evidence indicates the feasibility of direct and indirect targeting of IGF2BP1 and MYCN in cancer treatment.

METHODS

Candidate oncogenes on 17q were identified by profiling the transcriptomic/genomic landscape of 100 human neuroblastoma samples and public gene essentiality data. Molecular mechanisms and gene expression profiles underlying the oncogenic and therapeutic target potential of the 17q oncogene IGF2BP1 and its cross-talk with MYCN were characterized and validated in human neuroblastoma cells, xenografts and PDX as well as novel IGF2BP1/MYCN transgene mouse models.

RESULTS

We reveal a novel, druggable feedforward loop of IGF2BP1 (17q) and MYCN (2p) in high-risk neuroblastoma. This promotes 2p/17q chromosomal gains and unleashes an oncogene storm resulting in fostered expression of 17q oncogenes like BIRC5 (survivin). Conditional, sympatho-adrenal transgene expression of IGF2BP1 induces neuroblastoma at a 100% incidence. IGF2BP1-driven malignancies are reminiscent to human high-risk neuroblastoma, including 2p/17q-syntenic chromosomal gains and upregulation of Mycn, Birc5, as well as key neuroblastoma circuit factors like Phox2b. Co-expression of IGF2BP1/MYCN reduces disease latency and survival probability by fostering oncogene expression. Combined inhibition of IGF2BP1 by BTYNB, MYCN by BRD inhibitors or BIRC5 by YM-155 is beneficial in vitro and, for BTYNB, also.

CONCLUSION

We reveal a novel, druggable neuroblastoma oncogene circuit settling on strong, transcriptional/post-transcriptional synergy of MYCN and IGF2BP1. MYCN/IGF2BP1 feedforward regulation promotes an oncogene storm harboring high therapeutic potential for combined, targeted inhibition of IGF2BP1, MYCN expression and MYCN/IGF2BP1-effectors like BIRC5.

Risk factors and prognostic factors for pulmonary large cell neuroendocrine carcinoma with brain metastasis

BACKGROUND

As the studies regarding the brain metastasis (BM) of pulmonary large cell neuroendocrine carcinoma (LCNEC) are insufficient, the present research aims to describe the risk factors and prognostic factors that are related to cancer-specific survival (CSS) for LCNEC patients with BM.

METHODS

The data of LCNEC patients between January 2010 and October 2018 were obtained from the SEER database. Binary logistic regression analyses were utilized to screen the possible risk factors related to BM. Prognostic factors for LCNEC patients with BM were indentified by Cox regression analyses. Moreover, a nomogram was established to predict the 6-, 12-, and 18-month CSS rates. The concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves were utilized to assess the discrimination and reliability of the model. Clinical decision curves (DCAs) were used to evaluate the clinical benefits and utility of our model.

RESULTS

Totally, 1875 patients were enrolled, with 294 (15.7%) of them having BM at diagnosis. Multivariate logistic regression analyses revealed that patients with age < 65 (odds ratio, OR = 1.564) and N2 staging (OR = 1.775) had a greater chance of developing BM. Age (≥ 65 vs. < 65: hazard ratio, HR = 1.409), T staging (T1 vs. T0: HR = 4.580; T2 vs. T0: HR = 6.008; T3 vs. T0: HR = 7.065; T4 vs. T0: HR = 6.821), N staging (N2 vs. N0: HR = 1.592; N3 vs. N0: HR = 1.654), liver metastasis (HR = 1.410), primary site surgery (HR = 0.581) and chemotherapy (HR = 0.452) were independent prognostic factors for LCNEC patients with BM. A nomogram prediction model was constructed by incorporating these factors. Using the C-index, calibration curves, ROC curves, and DCAs, we found that the clinical prediction model performed well.

CONCLUSION

We described the risk factors and prognostic factors that were associated with CSS for LCNEC patients with BM. The related nomogram was established and validated to help clinicians formulate more rational and effective treatment strategies.

The prognosis analysis of organ metastatic patterns in lung large cell neuroendocrine carcinoma: A population-based study

Lung large cell neuroendocrine carcinoma (LCNEC) is a rare and highly aggressive malignancy with a dismal prognosis. This study was designed to depict patterns of distant organ metastatic and to analyze prognosis of LCNEC patients. We gathered data from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. We conducted the Kaplan-Meier method to calculate overall survival (OS) and compare different variables. Cox proportional hazards regression models in univariate and multivariate analyses were employed to further explore prognostic factors. A total of 1335 LCNEC patients were eventually selected from the SEER database, of which 348 patients (26.0%) had single organ metastasis and 197 patients (14.8%) had multiple metastases. Our study indicates that patients with single organ metastasis generally have a poor prognosis, with a median OS of 8 months for both lung and brain metastasis with 1-year survival rates of 33% and 29% respectively. Patients with multiple metastases exhibited the worst prognosis, with a median OS of only 4 months and a 1-year OS of 8%. Multivariate analysis revealed that age, T stage, N stage, chemotherapy and radiation in metastatic patients were independently associated with OS. In conclusion, LCNEC exhibits a high metastatic rate when diagnosed. The most common metastatic organ is the brain in single-site metastatic patients. Patients with single or multiple metastases exhibit a significantly worse prognosis than those with non-organ metastases. In the group of single organ metastases, patients with brain and lung metastases had a better prognosis than those with bone and liver metastases.

Treatment outcome and prognostic analysis of advanced large cell neuroendocrine carcinoma of the lung

The optimal systemic treatment of advanced large cell neuroendocrine carcinoma (LCNEC) is still controversial. We intend to explore advanced LCNEC through SEER database, construct nomogram model of advanced LCNEC, and understand the effect of different treatment regimens on LCNEC. We collected 909 patients, divided them into a training set validation set, constructed nomograms using Cox proportional hazards regression models, and evaluated nomogram discrimination and calibration by C-index and calibration curves. Kaplan–Meier will also be used to compare OS in different groups of patients and to explore the impact of different treatment regimens on advanced LCNEC. On the nomogram plotted, the nomogram predicted AUC values over time were always greater than 0.7, the C-index was 0.681 (95% CI 0.656–0.706) and 0.663 (95% CI 0.628–0.698) in the training and validation sets, respectively, and patients were divided into two groups according to risk, and a significant difference in OS was observed between the high-risk and low-risk groups in the training and validation cohorts. Different treatment analyses showed that chemotherapy is still the best treatment for advanced LCNEC. This nomogram provides a convenient and reliable tool for individual assessment and clinical decision-making of patients with advanced LCNEC.

Pten and p53 Loss in the Mouse Lung Causes Adenocarcinoma and Sarcomatoid Carcinoma

Simple Summary

Lung cancer is the world leading cause of cancer death. Therefore, a better understanding of the disease is needed to improve patient survival. In this work, we have deleted the tumor suppressor genes Pten and Trp53 in adult mouse lungs to analyze its impact on tumor formation. Double mutant mice develop Adenocarcinoma and Pulmonary Sarcomatoid Carcinoma, two different types of Non-Small Cell Carcinoma whose biological relationships are a matter of debate. The former is very common, with various models described and some therapeutic options. The latter is very rare with very poor prognosis, no effective treatment and lack of models reported so far. Interestingly, this study reports the first mouse model of pulmonary sarcomatoid carcinoma available for preclinical research.

Abstract

Lung cancer remains the leading cause of cancer deaths worldwide. Among the Non-Small Cell Carcinoma (NSCLC) category, Adenocarcinoma (ADC) represents the most common type, with different reported driver mutations, a bunch of models described and therapeutic options. Meanwhile, Pulmonary Sarcomatoid Carcinoma (PSC) is one of the rarest, with very poor outcomes, scarce availability of patient material, no effective therapies and no models available for preclinical research. Here, we describe that the combined deletion of Pten and Trp53 in the lungs of adult conditional mice leads to the development of both ADC and PSC irrespective of the lung targeted cell type after naphthalene induced airway epithelial regeneration. Although this model shows long latency periods and incomplete penetrance for tumor development, it is the first PSC mouse model reported so far, and sheds light on the relationships between ADC and PSC and their cells of origin. Moreover, human ADC show strong transcriptomic similarities to the mouse PSC, providing a link between both tumor types and the human ADC.

In-depth molecular analysis of combined and co-primary pulmonary large cell neuroendocrine carcinoma and adenocarcinoma

Up to 14% of large cell neuroendocrine carcinomas (LCNECs) are diagnosed in continuity with nonsmall cell lung carcinoma. In addition to these combined lesions, 1% to 7% of lung tumors present as co-primary tumors with multiple synchronous lesions. We evaluated molecular and clinicopathological characteristics of combined and co-primary LCNEC-adenocarcinoma (ADC) tumors. Ten patients with LCNEC-ADC (combined) and five patients with multiple synchronous ipsilateral LCNEC and ADC tumors (co-primary) were included. DNA was isolated from distinct tumor parts, and 65 cancer genes were analyzed by next generation sequencing. Immunohistochemistry was performed including neuroendocrine markers, pRb, Ascl1 and Rest. Pure ADC (N = 37) and LCNEC (N = 17) cases were used for reference. At least 1 shared mutation, indicating tumor clonality, was found in LCNEC- and ADC-parts of 10/10 combined tumors but only in 1/5 co-primary tumors. A range of identical mutations was observed in both parts of combined tumors: 8/10 contained ADC-related (EGFR/KRAS/STK11 and/or KEAP1), 4/10 RB1 and 9/10 TP53 mutations. Loss of pRb IHC was observed in 6/10 LCNEC- and 4/10 ADC-parts. The number and intensity of expression of Ascl1 and neuroendocrine markers increased from pure ADC (low) to combined ADC (intermediate) and combined and pure LCNEC (high). The opposite was true for Rest expression. In conclusion, all combined LCNEC-ADC tumors were clonally related indicating a common origin. A relatively high frequency of pRb inactivation was observed in both LCNEC- and ADC-parts, suggesting an underlying role in LCNEC-ADC development. Furthermore, neuroendocrine differentiation might be modulated by Ascl1(+) and Rest(-) expression.

A Clinical Nomogram for Predicting Cancer-Specific Survival in Pulmonary Large-Cell Neuroendocrine Carcinoma Patients: A Population-Based Study

Purpose

This study was designed to construct and validate a nomogram that was available for predicting cancer-specific survival (CSS) in patients with pulmonary large-cell neuroendocrine carcinoma (LCNEC).

Patients and Methods

Using the US Surveillance, Epidemiology, and End Results (SEER) database, we identified patients pathologically diagnosed as LCNEC from 1975 to 2016. Univariate and multivariate Cox regression was conducted to assess prognostic factors of CSS. A novel nomogram model was constructed and validated by the concordance index (C-index), calibration curves and decision curve analysis (DCA).

Results

A total of 624 LCNEC patients were enrolled. Five prognostic factors for CSS were identified and merged to establish nomograms. In the training and validation cohorts, calibration curves displayed the nomogram predictions are in a good agreement with the actual survival. The C-Index of the training and validation cohorts were both higher than 0.8, and the DCA results showed that the nomogram has clinical validity and utility.

Conclusion

The proposed nomogram resulted in accurate CSS prognostic prediction for patients with LCNEC.

RBL1/p107 Expression Levels Are Modulated by Multiple Signaling Pathways

The members of the retinoblastoma (RB) protein family, RB1/p105, retinoblastoma-like (RBL)1/p107 and RBL2/p130 are critical modulators of the cell cycle and their dysregulation has been associated with tumor initiation and progression. The activity of RB proteins is regulated by numerous pathways including oncogenic signaling, but the molecular mechanisms of these functional interactions are not fully defined. We previously demonstrated that RBL2/p130 is a direct target of AKT and it is a key mediator of the apoptotic process induced by AKT inhibition. Here we demonstrated that RBL1/p107 levels are only minorly modulated by the AKT signaling pathway. In contrast, we discovered that RBL1/p107 levels are regulated by multiple pathways linked directly or indirectly to Ca²⁺-dependent signaling. Inhibition of the multifunctional calcium/calmodulin-dependent kinases (CaMKs) significantly reduced RBL1/p107 expression levels and phosphorylation, increased RBL1/p107 nuclear localization and led to cell cycle arrest in G0/G1. Targeting the Ca²⁺-dependent endopeptidase calpain stabilized RBL1/p107 levels and counteracted the reduction of RBL1/p107 levels associated with CaMKs inhibition. Thus, these novel observations suggest a complex regulation of RBL1/p107 expression involving different components of signaling pathways controlled by Ca²⁺ levels, including CaMKs and calpain, pointing out a significant difference with the mechanisms modulating the close family member RBL2/p130.

Binary pan-cancer classes with distinct vulnerabilities defined by pro- or anti-cancer YAP/TEAD activity

Cancer heterogeneity impacts therapeutic response, driving efforts to discover over-arching rules that supersede variability. Here, we define pan-cancer binary classes based on distinct expression of YAP and YAP-responsive adhesion regulators. Combining informatics with in vivo and in vitro gain- and loss-of-function studies across multiple murine and human tumor types, we show that opposite pro- or anti-cancer YAP activity functionally defines binary YAP^on or YAP^off cancer classes that express or silence YAP, respectively. YAP^off solid cancers are neural/neuroendocrine and frequently RB1^-/-, such as retinoblastoma, small cell lung cancer, and neuroendocrine prostate cancer. YAP silencing is intrinsic to the cell of origin, or acquired with lineage switching and drug resistance. The binary cancer groups exhibit distinct YAP-dependent adhesive behavior and pharmaceutical vulnerabilities, underscoring clinical relevance. Mechanistically, distinct YAP/TEAD enhancers in YAP^off or YAP^on cancers deploy anti-cancer integrin or pro-cancer proliferative programs, respectively. YAP is thus pivotal across cancer, but in opposite ways, with therapeutic implications.

Diagnosis and Molecular Profiles of Large Cell Neuroendocrine Carcinoma With Potential Targets for Therapy

Large cell neuroendocrine carcinoma (LCNEC) together with small cell carcinoma (SCLC) and typical and atypical carcinoids form the group of pulmonary neuroendocrine tumors. LCNEC and SCLC are high-grade carcinomas. Although both can be found outside the thoracic cavity, they are most common in the lung. LCNEC differs from SCLC by morphologic pattern, and by cytological features such as nuclear size, nucleoli, chromatin pattern, but also by genetic differences. Originally thought to represent a single entity, it became evident, that three subgroups of LCNEC can be identified at the molecular level: a SCLC-like type with loss of retinoblastoma 1 gene (RB1) and TP53 mutations; a non-small cell lung carcinoma (NSCLC)-like type with wildtype RB1, TP53 mutation, and activating mutations of the phosphoinositol-3 kinase (PI3K-CA), or loss of PTEN; and a carcinoid-like type with MEN1 gene mutation. These subtypes can be identified by immunohistochemical staining for RB1, p53, and molecular analysis for PI3K and MEN1 mutations. These subtypes might also respond differently to chemotherapy. Immuno-oncologic treatment has also been applied to LCNEC, however, in addition to the evaluation of tumor cells the stroma evaluation seems to be important. Based on personal experiences with these tumors and available references this review will try to encompass our present knowledge in this rare entity and provoke new studies for better treatment of this carcinoma.

Biomarkers of Response to Etoposide-Platinum Chemotherapy in Patients with Grade 3 Neuroendocrine Neoplasms

Etoposide-platinum (EP) chemotherapy has long been the reference treatment for grade 3 neuroendocrine neoplasms (G3 NEN). However, G3 NEN are heterogeneous, including well-differentiated tumors (NET) and poorly differentiated large (LCNEC) or small (SCNEC) cell carcinomas, whose response to EP chemotherapy varies considerably. Our aim was to evaluate predictive biomarkers for the response to EP chemotherapy in G3 NEN. We retrospectively studied 89 patients with lung (42%) and digestive (58%) G3 NEN treated by EP chemotherapy between 2006 and 2020. All cases were centrally reviewed for cytomorphology/Ki-67 and immunohistochemistry of retinoblastoma protein (Rb)/p53/p16, analyzed using a semi-quantitative score. The absence of Rb staining (Rbinap) or the absence of very intense p53 staining (p53inap) were considered inappropriate. Rb staining was also studied as a quantitative marker, the best threshold being determined by ROC curve. Intense p16 staining (p16high) also suggested cell cycle dysregulation. Our primary endpoint was the objective response rate (ORR). We included 10 G3 NET, 31 LCNEC and 48 SCNEC, which showed ORR of 20%, 32% and 75%, respectively (NET vs. NEC, p = 0.040; LCNEC vs. SCNEC, p < 0.001). The ORR was significantly higher in NEN presenting with Rbinap (63% vs. 42%, p = 0.025) and p16high (66% vs. 35%, p = 0.006). Rb < 150 optimally identified responders (AUC = 0.657, p < 0.001). The ORR was 67% in Rb < 150 (vs. 25%, p = 0.005). On multivariate analysis, only Rb < 150 was independently associated with ORR (OR 4.16, 95% CI 1.11-15.53, p = 0.034). We confirm the heterogeneity of the response to EP treatment in G3 NEN. Rb < 150 was the best predictive biomarker for the response to EP, and p53 immunostaining had no additional value.

Small-cell lung cancer

Small-cell lung cancer (SCLC) represents about 15% of all lung cancers and is marked by an exceptionally high proliferative rate, strong predilection for early metastasis and poor prognosis. SCLC is strongly associated with exposure to tobacco carcinogens. Most patients have metastatic disease at diagnosis, with only one-third having earlier-stage disease that is amenable to potentially curative multimodality therapy. Genomic profiling of SCLC reveals extensive chromosomal rearrangements and a high mutation burden, almost always including functional inactivation of the tumour suppressor genes TP53 and RB1. Analyses of both human SCLC and murine models have defined subtypes of disease based on the relative expression of dominant transcriptional regulators and have also revealed substantial intratumoural heterogeneity. Aspects of this heterogeneity have been implicated in tumour evolution, metastasis and acquired therapeutic resistance. Although clinical progress in SCLC treatment has been notoriously slow, a better understanding of the biology of disease has uncovered novel vulnerabilities that might be amenable to targeted therapeutic approaches. The recent introduction of immune checkpoint blockade into the treatment of patients with SCLC is offering new hope, with a small subset of patients deriving prolonged benefit. Strategies to direct targeted therapies to those patients who are most likely to respond and to extend the durable benefit of effective antitumour immunity to a greater fraction of patients are urgently needed and are now being actively explored.

Neuroendocrine Lung Cancer Mouse Models: An Overview

Simple Summary

Neuroendocrine lung tumors are a heterogeneous group of malignancies that share a common neuroendocrine nature. They range from low- and intermediate-grade typical and atypical carcinoma, to the highly malignant large cell neuroendocrine lung carcinoma and small cell carcinoma, with marked differences in incidences and prognosis. This review delineates the current knowledge of the genetic landscape of the human tumors, its influence in the development of genetically engineered mouse models (GEMMs) and the molecular imaging tools available to detect and monitor these diseases. While small cell lung carcinoma is one of the diseases best represented by GEMMs, there is a worrying lack of animal models for the other members of the group, these being understudied diseases. Regardless of the incidence and material available, they all are in urgent need of effective therapies.

Abstract

Neuroendocrine lung tumors comprise a range of malignancies that extend from benign tumorlets to the most prevalent and aggressive Small Cell Lung Carcinoma (SCLC). They also include low-grade Typical Carcinoids (TC), intermediate-grade Atypical Carcinoids (AC) and high-grade Large Cell Neuroendocrine Carcinoma (LCNEC). Optimal treatment options have not been adequately established: surgical resection when possible is the choice for AC and TC, and for SCLC chemotherapy and very recently, immune checkpoint inhibitors. Some mouse models have been generated based on the molecular alterations identified in genomic analyses of human tumors. With the exception of SCLC, there is a limited availability of (preclinical) models making their development an unmet need for the understanding of the molecular mechanisms underlying these diseases. For SCLC, these models are crucial for translational research and novel drug testing, given the paucity of human material from surgery. The lack of early detection systems for lung cancer point them out as suitable frameworks for the identification of biomarkers at the initial stages of tumor development and for testing molecular imaging methods based on somatostatin receptors. Here, we review the relevant models reported to date, their impact on the understanding of the biology of the tumor subtypes and their relationships, as well as the effect of the analyses of the genetic landscape of the human tumors and molecular imaging tools in their development.

Cells of origin of lung cancers: lessons from mouse studies

As one of the most common forms of cancer, lung cancers present as a collection of different histological subtypes. These subtypes are characterized by distinct sets of driver mutations and phenotypic appearance, and they often show varying degrees of heterogenicity, aggressiveness, and response/resistance to therapy. Intriguingly, lung cancers are also capable of showing features of multiple subtypes or converting from one subtype to another. The intertumoral and intratumoral heterogeneity of lung cancers as well as incidences of subtype transdifferentiation raise the question of to what extent the tumor characteristics are dictated by the cell of origin rather than the acquired driver lesions. We provide here an overview of the studies in experimental mouse models that try to address this question. These studies convincingly show that both the cell of origin and the genetic driver lesions play a critical role in shaping the phenotypes of lung tumors. However, they also illustrate that there is far from a direct one-to-one relationship between the cell of origin and the cancer subtype, as most epithelial cells can be reprogrammed toward diverse lung cancer fates when exposed to the appropriate set of driver mutations.

Development and long-term evaluation of a new 68Ge/68Ga generator based on nano-SnO2 for PET imaging

Radionuclide generator systems can routinely provide radionuclides on demand such as ⁶⁸Ga produced by a ⁶⁸Ge/⁶⁸Ga generator without the availability of an on-site accelerator or a research reactor. Thus, in this work nano-SnO₂ was used to develop a new ⁶⁸Ge/⁶⁸Ga generator which was evaluated over a period of 17 months and 305 elution cycles. The elution yield was 91.1 ± 1.8% in the first 7 mL (1 M HCl as eluent) when the generator was new and then it decreased with time and use to 73.8 ± 1.9%. Around 80% of the elutable ⁶⁸Ga activity was obtained in 1 mL and the ⁶⁸Ge content in the eluate did not exceed 1 × 10^–4% over the investigation period when it was eluted regularly. The described generator provided adequate results for radiolabelling of DOTA-TOC with direct use of eluate. In addition, [⁶⁸Ga]Ga-DOTA-TOC was tested satisfactorily for in vivo tumor detection by microPET/CT imaging in a lung cancer mouse model.

New models of large-cell neuroendocrine carcinoma and small-cell lung carcinoma

High-grade neuroendocrine lung carcinomas (LCNEC, SCLC) are recalcitrant cancers for which no optimal management has been achieved. We have recently described two models of LCNEC and SCLC developed upon inactivation of 4 tumor suppressors genes (Rb1 (RB transcriptional corepressor 1), Rbl1 (RB transcriptional corepressor like 1), Pten (phosphatase and tensin homolog), Trp53 (transformation-related protein 53), which provide a suitable frame for preclinical intervention. A defined model for LCNEC had not been previously reported.