Morphometry confirms the presence of considerable nuclear size overlap between "small cells" and "large cells" in high-grade pulmonary neuroendocrine neoplasms

Head-to-head: Should Ki67 proliferation index be included in the formal classification of pulmonary neuroendocrine neoplasms?

The reporting of lung neuroendocrine neoplasms (NENs) according to the 2021 World Health Organisation (WHO) is based on mitotic count per 2 mm2, necrosis assessment and a constellation of cytological and immunohistochemical details. Accordingly, typical carcinoid and atypical carcinoid are low- to intermediate-grade neuroendocrine tumours (NETs), while large-cell neuroendocrine carcinoma (NEC) and small-cell lung carcinoma are high-grade NECs. In small-sized diagnostic material (cytology and biopsy), the noncommittal term of carcinoid tumour/NET not otherwise specified (NOS) and metastatic carcinoid NOS have been introduced with regard to primary and metastatic diagnostic settings, respectively. Ki-67 antigen, a well-known marker of cell proliferation, has been included in the WHO classification as a non-essential but desirable criterion, especially to distinguish NETs from high-grade NECs and to delineate the provisional category of carcinoid tumours/NETs with elevated mitotic counts (> 10 mitoses per mm2) and/or Ki-67 proliferation index (≥ 30%). However, a wider use of this marker in the spectrum of lung NENs continues to be highly reported and debated, thus witnessing a never-subsided attention. Therefore, the arguments for and against incorporating Ki-67 in the classification and clinical practice of these neoplasms are discussed herein in detail.

Molecular subtypes of neuroendocrine carcinomas: A cross-tissue classification framework based on five transcriptional regulators

Neuroendocrine carcinomas (NECs) are extremely lethal malignancies that can arise at almost any anatomic site. Characterization of NECs is hindered by their rarity and significant inter- and intra-tissue heterogeneity. Herein, through an integrative analysis of over 1,000 NECs originating from 31 various tissues, we reveal their tissue-independent convergence and further unveil molecular divergence driven by distinct transcriptional regulators. Pan-tissue NECs are therefore categorized into five intrinsic subtypes defined by ASCL1, NEUROD1, HNF4A, POU2F3, and YAP1. A comprehensive portrait of these subtypes is depicted, highlighting subtype-specific transcriptional programs, genomic alterations, evolution trajectories, therapeutic vulnerabilities, and clinicopathological presentations. Notably, the newly discovered HNF4A-dominated subtype-H exhibits a gastrointestinal-like signature, wild-type RB1, unique neuroendocrine differentiation, poor chemotherapeutic response, and prevalent large-cell morphology. The proposal of uniform classification paradigm illuminates transcriptional basis of NEC heterogeneity and bridges the gap across different lineages and cytomorphological variants, in which context-dependent prevalence of subtypes underlies their phenotypic disparities.

POU2F3-Expressing Small Cell Lung Carcinoma and Large Cell Neuroendocrine Carcinoma Show Morphologic and Phenotypic Overlap

Considering the differences in protein expression in small cell lung carcinoma (SCLC) by molecular classification, it is likely that there are differences in morphology, but the relationship between molecular classification and morphology has not been examined. Furthermore, there are limited reports concerning this molecular classification for large cell neuroendocrine carcinoma (LCNEC) and SCLC simultaneously. Therefore, we investigated the relationship between immunohistochemistry-based molecular classification and morphology, protein expression, and clinical features of 146 consecutive resection specimens of pulmonary neuroendocrine carcinoma (NEC), focusing mainly on POU2F3, the master transcription factor involved in tuft cell generation. POU2F3-dominant SCLC (n=24) and LCNEC (n=14) showed overlap in cytomorphology, while non-POU2F3-dominant SCLC (n=71) and LCNEC (n=37) showed distinct differences in cytomorphology. In addition, POU2F3-dominant NEC exhibited significantly more abundant tumor stroma, more prominent nest formation, more frequent bronchial intraepithelial involvement, and less frequent background fibrosis than non-POU2F3-dominant NEC. Immunohistochemically, POU2F3-dominant SCLC and LCNEC were characterized by lower expression of TTF-1, CEA, and neuroendocrine markers and higher expression of bcl-2, c-Myc, and c-kit. Clinically, POU2F3-dominant NEC had a significantly better prognosis than non-POU2F3-dominant NEC for recurrence-free survival. POU2F3-dominant NEC had a higher smoking index than non-POU2F3-dominant NEC. POU2F3-dominant NEC forms a unique population, exhibiting intermediate morphologic features between SCLC and LCNEC, with distinct protein expression as tuft cell-like carcinoma. Recognition of this unique subtype may provide clues for solving the long-standing issues of NEC and appropriate therapeutic stratification. It is important to accurately identify POU2F3-expressing carcinomas by immunohistochemistry and to analyze their clinicopathological features.

Proposing Specific Neuronal Epithelial-to-Mesenchymal Transition Genes as an Ancillary Tool for Differential Diagnosis among Pulmonary Neuroendocrine Neoplasms

Pulmonary neuroendocrine neoplasms (PNENs) are currently classified into four major histotypes, including typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC), and small cell lung carcinoma (SCLC). This classification was designed to be applied to surgical specimens mostly anchored in morphological parameters, resulting in considerable overlapping among PNENs, which may result in important challenges for clinicians' decisions in the case of small biopsies. Since PNENs originate from the neuroectodermic cells, epithelial-to-mesenchymal transition (EMT) gene expression shows promise as biomarkers involved in the genotypic transformation of neuroectodermic cells, including mutation burden with the involvement of chromatin remodeling genes, apoptosis, and mitosis rate, leading to modification in final cellular phenotype. In this situation, additional markers also applicable to biopsy specimens, which correlate PNENs subtypes with systemic treatment response, are much needed, and current potential candidates are neurogenic EMT genes. This study investigated EMT genes expression and its association with PNENs histotypes in tumor tissues from 24 patients with PNENs. PCR Array System for 84 EMT-related genes selected 15 differentially expressed genes among the PNENs, allowing to discriminate TC from AC, LCNEC from AC, and SCLC from AC. Functional enrichment analysis of the EMT genes differentially expressed among PNENs subtypes showed that they are involved in cellular proliferation, extracellular matrix degradation, regulation of cell apoptosis, oncogenesis, and tumor cell invasion. Interestingly, four EMT genes (MAP1B, SNAI2, MMP2, WNT5A) are also involved in neurological diseases, in brain metastasis, and interact with platinum-based chemotherapy and tyrosine-kinase inhibitors. Collectively, these findings emerge as an important ancillary tool to improve the strategies of histologic diagnosis in PNENs and unveil the four EMT genes that can play an important role in driving chemical response in PNENs.

Role of surgery in high-grade neuroendocrine tumors of the lung

Background

This study aims to evaluate the surgical results for high-grade neuroendocrine carcinomas and to identify factors that influence prognosis.

Methods

Between January 2009 and December 2017, a total of 71 patients (58 males, 13 females; mean age: 62±9.6 years; range, 38 to 78 years) with a high-grade neuroendocrine carcinoma of the lung were retrospectively analyzed. Overall survival and five-year overall survival rates were evaluated.

Results

The mean overall survival was 60.7±6.9 months with a five-year survival rate of 44.3%. The mean overall survival and five-year overall survival rates according to disease stage were as follows: Stage 1, 67±10.8 months (46%); Stage 2, 61.4±10.8 months (45%); and Stage 3, 33.2±8.6 months (32%) (p=0.02). The mean overall survival and five-year overall survival rate according to histological types were as follows: in large cell neuroendocrine carcinoma, 59.4±9.2 months (45%); in small cell neuroendocrine carcinoma, 68.6±12.2 months (43%); and in combined-type neuroendocrine carcinoma, 40.9±10.1 months (35%) (p=0.34).

Conclusion

Thoracic surgeons should be very selective in performing pulmonary resection in patients with Stage 3 high-grade neuroendocrine carcinomas and combined cell subtype tumors.

Small-Cell Carcinoma of the Lung: What We Learned about It?

Small-cell lung carcinoma (SCLC) is a high-grade aggressive disease that belongs to the neuroendocrine (NE) group of lung tumors that also includes typical carcinoid, atypical carcinoid, and large-cell NE carcinoma. SCLC has specific histological diagnostic criteria that are sometimes troublesome to be assessed in cytological samples that indeed represent the most frequent source of diagnostic material due to the typical advanced presentation at the onset of SCLC. However, cytological preparations could be in some instances more reliable than histology due to the better preservation of nuclear details. Cytological criteria for diagnosis of SCLC include high cellularity, small cell size, scant cytoplasm, coarsely granulated chromatin with "salt-and-pepper" appearance, inconspicuous or absent nucleoli, Azzopardi crush effect, and necrotic debris in the background. Despite being distinctive, these features could be incomplete to differentiate SCLC with other small-cell neoplasia. Therefore, immunocytochemical determination of diagnostic biomarkers is crucial to achieve a confident diagnosis. Furthermore, recent findings on molecular and transcriptomic studies of SCLC revealed the potential rise of new predictive and prognostic biomarkers that, whenever validated by immunocytochemistry, may potentially assist to tailor the best therapy, including immune checkpoint inhibition.

Urinary Large Cell Neuroendocrine Carcinoma: A Clinicopathologic Analysis of 22 Cases

Large cell neuroendocrine carcinoma (LCNEC) of the urinary tract is a rare disease. We present a relatively large retrospective cohort of urinary LCNEC, 20 from the urinary bladder, and 2 from the ureter, from a single institution. The patients included 16 men and 6 women with a median age of 74.5 years. Most LCNEC presented at an advanced stage with tumors invading the muscularis propria and beyond (21/22). Eight cases were pure LCNEC, while 14 cases were mixed with other histologic types, including conventional urothelial carcinoma (n=9), carcinoma in situ (n=7), small cell carcinoma (n=6), and urothelial carcinoma with glandular (n=3) features. Most LCNEC expressed neuroendocrine markers synaptophysin (22/22), chromogranin (13/16), CD56 (7/7), TTF1 (8/8), and INSM1 (2/3). They were negative for common urothelial markers including HMWCK (0/3), p40/p63 (0/6), CK20 (0/10), and had variable GATA3 staining (4/8). Ki-67 stained 25% to nearly 100% tumor cell nuclei. Patient survival was associated with cancer stage, and pure LCNEC showed worse survival than mixed LCNEC. Compared with small cell carcinoma at similar stages from a prior study, LCNEC had a worse prognosis only when patients developed metastatic disease. For organ-confined LCNEC, neoadjuvant chemotherapy followed by radical resection is the treatment option to achieve long-term survival.

Clinical Behavior of Combined Versus Pure High-Grade Neuroendocrine Carcinoma

BACKGROUND

The aim of this study was to investigate and compare the clinical behaviors of combined and pure high-grade neuroendocrine carcinoma (large-cell neuroendocrine carcinoma [LCNEC] and small-cell lung carcinoma [SCLC]).

PATIENTS AND METHODS

Data of 132 patients who underwent complete resection for combined or pure high-grade neuroendocrine carcinoma (combined group, 67; pure group, 65) between January 2001 and December 2015 were retrospectively reviewed. The clinicopathological features were analyzed and compared, and the prognoses were assessed by performing the Kaplan-Meier method and Cox regression analysis.

RESULTS

The combined and pure groups had nearly equivalent clinicopathological characteristics, specifically, older males with smoking history, almost the same percentage of pleural/lymphatic/vascular invasion, and nearly the same recurrence rates and relapse patterns. The combined group had prognosis equivalent to that of the pure group (5-year overall survival [OS] rates: 61.8% vs. 52.2%, respectively; P = .82 and 5-year recurrence-free survival [RFS] rates: 42.4% vs. 43.9%, respectively; P = .96), and this trend was identified in sub-analyses only for patients with LCNEC, SCLC, and the same pathological stage. Multivariable Cox regression analysis in patients with high-grade neuroendocrine carcinoma revealed that vascular invasion and pathological stage were independent prognostic factors for OS; more importantly, combined and pure histologies were proven to have nearly equivalent associations with prognosis (hazard ratio, 0.96; 95% confidence interval, 0.22to 1.66; P = .96).

RESULTS

Combined high-grade neuroendocrine carcinoma had clinical behavior equivalent to those of pure high-grade neuroendocrine carcinoma, with similar clinicopathological characteristics.

Clinical-Pathologic Challenges in the Classification of Pulmonary Neuroendocrine Neoplasms and Targets on the Horizon for Future Clinical Practice

Diagnosing a pulmonary neuroendocrine neoplasm (NEN) may be difficult, challenging clinical decision making. In this review, the following key clinical and pathologic issues and informative molecular markers are being discussed: (1) What is the preferred outcome parameter for curatively resected low-grade NENs (carcinoid), for example, overall survival or recurrence-free interval? (2) Does the WHO classification combined with a Ki-67 proliferation index and molecular markers, such as OTP and CD44, offer improved prognostication in low-grade NENs? (3) What is the value of a typical versus atypical carcinoid diagnosis on a biopsy specimen in local and metastatic disease? Diagnosis is difficult in biopsy specimens and recent observations of an increased mitotic rate in metastatic carcinoid from typical to atypical and high-grade NEN can further complicate diagnosis. (4) What is the (ir)relevance of morphologically separating large cell neuroendocrine carcinoma (LCNEC) SCLC and the value of molecular markers (RB1 gene and pRb protein or transcription factors NEUROD1, ASCL1, POU2F3, or YAP1 [NAPY]) to predict systemic treatment outcome? (5) Are additional diagnostic criteria required to accurately separate LCNEC from NSCLC in biopsy specimens? Neuroendocrine morphology can be absent owing to limited sample size leading to missed LCNEC diagnoses. Evaluation of genomic studies on LCNEC and marker studies have identified that a combination of napsin A and neuroendocrine markers could be helpful. Hence, to improve clinical practice, we should consider to adjust our NEN classification incorporating prognostic and predictive markers applicable on biopsy specimens to inform a treatment outcome-driven classification.

Large Cell Neuro-Endocrine Carcinoma of the Lung: Current Treatment Options and Potential Future Opportunities

Large-cell neuroendocrine carcinomas of the lung (LCNECs) are rare tumors representing 1-3% of all primary lung cancers. Patients with LCNEC are predominantly male, older, and heavy smokers. Histologically, these tumors are characterized by large cells with abundant cytoplasm, high mitotic rate, and neuroendocrine immunohistochemistry-detected markers (chromogranin-A, synaptophysin, and CD56). In 2015 the World Health Organization classified LCNEC as a distinct subtype of pulmonary large-cell carcinoma and, therefore, as a subtype of non-small cell lung carcinoma (NSCLC). Because of the small-sized tissue samples and the likeness to other neuroendocrine tumors, the histological diagnosis of LCNEC remains difficult. Clinically, the prognosis of metastatic LCNECs is poor, with high rates of recurrence after surgery alone and overall survival of approximately 35% at 5 years, even for patients with early stage disease that is dramatically shorter compared with other NSCLC subtypes. First-line treatment options have been largely discussed but with limited data based on phase II studies with small sample sizes, and there are no second-line well defined treatments. To date, no standard treatment regimen has been developed, and how to treat LCNEC is still on debate. In the immunotherapy and targeted therapy era, in which NSCLC treatment strategies have been radically reshaped, a few data are available regarding these opportunities in LCNEC. Due to lack of knowledge in this field, many efforts have been done for a deeper understanding of the biological and molecular characteristics of LCNEC. Next generation sequencing analyses have identified subtypes of LCNEC that may be relevant for prognosis and response to therapy, but further studies are needed to better define the clinical impact of these results. Moreover, scarce data exist about PD-L1 expression in LCNEC and its predictive value in this histotype with regard to immunotherapy efficacy. In the literature some cases are reported concerning LCNEC metastatic patients carrying driver mutations, especially EGFR alterations, showing targeted therapy efficacy in this setting of disease. Due to the rarity and the challenging understanding of LCNEC, in this review we aim to summarize the management options currently available for treatment of LCNEC.

Recent advances and current controversies in lung neuroendocrine neoplasms✰

In the lung, neuroendocrine tumors (NETs), namely typical and atypical carcinoids, and neuroendocrine carcinomas (NECs), grouping small cell carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC), make up for distinct tumor entities according to epidemiological, genetic, pathologic and clinical data. The proper classification is essential in clinical practice for diagnosis, prognosis and therapy purposes. Through an extensive literature survey, three perspectives on lung NENs have been revised: i) criteria and terminology on biopsy or cytology samples of primaries or metastases; ii) carcinoids with elevated mitotic counts and/or Ki-67 proliferation rates; iii) relevance of molecular landscape to identify new tumor entities and therapeutic targets. Furthermore, a dispute about lung NEN development has been raised according to emerging molecular models. We herein provide a pathology update on practical topics in the setting of lung NENs according to the current classification (recent advances). We have also reappraised the development of these tumors by modeling risk factors and natural history of disease (recent controversies). Combining recent advances and controversies may help clarify our biological understanding of lung NENs and give practical information for the clinical decision-making process.

Identification of novel transcription factor-microRNA-mRNA co-regulatory networks in pulmonary large-cell neuroendocrine carcinoma

Background

Large cell neuroendocrine carcinoma (LCNEC) of the lung is a rare neuroendocrine neoplasm. Previous studies have shown that microRNAs (miRNAs) are widely involved in tumor regulation through targeting critical genes. However, it is unclear which miRNAs play vital roles in the pathogenesis of LCNEC, and how they interact with transcription factors (TFs) to regulate cancer-related genes.

Methods

To determine the novel TF-miRNA-target gene feed-forward loop (FFL) model of LCNEC, we integrated multi-omics data from Gene Expression Omnibus (GEO), Transcriptional Regulatory Relationships Unraveled by Sentence-Based Text Mining (TRRUST), Transcriptional Regulatory Element Database (TRED), and The experimentally validated microRNA-target interactions database (miRTarBase database). First, expression profile datasets for mRNAs (GSE1037) and miRNAs (GSE19945) were downloaded from the GEO database. Overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified through integrative analysis. The target genes of the FFL were obtained from the miRTarBase database, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed on the target genes. Then, we screened for key miRNAs in the FFL and performed gene regulatory network analysis based on key miRNAs. Finally, the TF-miRNA-target gene FFLs were constructed by the hypergeometric test.

Results

A total of 343 DEGs and 60 DEMs were identified in LCNEC tissues compared to normal tissues, including 210 down-regulated and 133 up-regulated genes, and 29 down-regulated and 31 up-regulated miRNAs. Finally, the regulatory network of TF-miRNA-target gene was established. The key regulatory network modules included ETS1-miR195-CD36, TAOK1-miR7-1-3P-GRIA1, E2F3-miR195-CD36, and TEAD1-miR30A-CTHRC1.

Conclusions

We constructed the TF-miRNA-target gene regulatory network, which is helpful for understanding the complex LCNEC regulatory mechanisms.

Clinical implications of lung neuroendocrine neoplasm classification

INTRODUCTION

Neuroendocrine neoplasms of the lung (Lung NENs) encompass NE tumors (NETs), which are in turn split into typical and atypical carcinoids, and NE carcinomas (NECs), which group together small-cell carcinoma and large-cell NE carcinoma. This classification is the current basis for orienting the daily practice of these patients, with diagnostic, prognostic, and predictive inferences.

AREAS COVERED

The clinical implications of lung NEN classification are addressed according to three converging perspectives, which were dissected through an extensive literature overview: (1) how to put intratumor heterogeneity into the context of the current classification; (2) how to contextualize immunohistochemistry markers to improve diagnosis, prognosis, and therapy prediction; and (3) how to use immuno-oncology strategies for life-threatening NECs, which still account for 90% or more of lung NENs.

EXPERT OPINION

We provide practical insights to account for intratumor heterogeneity, practice the choice of immunohistochemistry markers, and emphasize once again the added value of immuno-oncology in the setting of personalized medicine of lung NENs.

New molecular classification of large cell neuroendocrine carcinoma and small cell lung carcinoma with potential therapeutic impacts

Large cell neuroendocrine carcinoma (LCNECs) and small cell lung carcinomas (SCLCs) are high-grade neuroendocrine carcinomas of the lung with very aggressive behavior and poor prognosis. Their histological classification as well as their therapeutic management has not changed much in recent years, but genomic and transcriptomic analyses have revealed different molecular subtypes raising hopes for more personalized treatment. Indeed, four subtypes of SCLCs have been recently described, SCLC-A driven by the master gene ASCL1, SCLC-N driven by NEUROD1, SCLC-Y by YAP1 and SCLC-P by POU2F3. Whereas SCLC standard of care is based on concurrent chemoradiation for limited stages and on chemotherapy alone or chemotherapy combined with anti-PD-L1 checkpoint inhibitors for extensive stage SCLC, SCLC-A variants could benefit from DLL3 or BCL2 inhibitors, and SCLC-N variants from Aurora kinase inhibitors combined with chemotherapy, or PI3K/mTOR or HSP90 inhibitors. In addition, a new SCLC variant (SCLC-IM) with high-expression of immune checkpoints has been also reported, which could benefit from immunotherapies. PARP inhibitors also gave promising results in combination with chemotherapy in a subset of SCLCs. Regarding LCNECs, they represent a heterogeneous group of tumors, some of them exhibiting mutations also found in SCLC but with a pattern of expression of NSCLC, while others harbor mutations also found in NSCLC but with a pattern of expression of SCLC, questioning their clinical management as NSCLCs or SCLCs. Overall, we are probably entering a new area, which, if personalized treatments are effective, will also lead to the implementation in practice of molecular testing or biomarkers detection for the selection of patients who can benefit from them.

Classifying Lung Neuroendocrine Neoplasms through MicroRNA Sequence Data Mining

Lung neuroendocrine neoplasms (NENs) can be challenging to classify due to subtle histologic differences between pathological types. MicroRNAs (miRNAs) are small RNA molecules that are valuable markers in many neoplastic diseases. To evaluate miRNAs as classificatory markers for lung NENs, we generated comprehensive miRNA expression profiles from 14 typical carcinoid (TC), 15 atypical carcinoid (AC), 11 small cell lung carcinoma (SCLC), and 15 large cell neuroendocrine carcinoma (LCNEC) samples, through barcoded small RNA sequencing. Following sequence annotation and data preprocessing, we randomly assigned these profiles to discovery and validation sets. Through high expression analyses, we found that miR-21 and -375 are abundant in all lung NENs, and that miR-21/miR-375 expression ratios are significantly lower in carcinoids (TC and AC) than in neuroendocrine carcinomas (NECs; SCLC and LCNEC). Subsequently, we ranked and selected miRNAs for use in miRNA-based classification, to discriminate carcinoids from NECs. Using miR-18a and -155 expression, our classifier discriminated these groups in discovery and validation sets, with 93% and 100% accuracy. We also identified miR-17, -103, and -127, and miR-301a, -106b, and -25, as candidate markers for discriminating TC from AC, and SCLC from LCNEC, respectively. However, these promising findings require external validation due to sample size.

Retinoblastoma co-repressor 1 (RB) and cyclin-dependent kinase inhibitor (CDKN) as a multi-gene panel for differentiating pulmonary from non-pulmonary origin in metastatic neuroendocrine carcinomas

BACKGROUND

Neuroendocrine carcinomas (NECs) arise from neuroendocrine cells present throughout the body, and often present with metastases even with small and undetectable primary tumors. Additionally, neuroendocrine differentiation can be seen in carcinomas of non-neuroendocrine origin further complicating the landscape of metastatic NECs. Organ specific immunohistochemical markers such as TTF1, CDX2 and PAX8 are often lost in high grade tumors and may be non-contributory in localizing the primary site. Though NECs share a common cellular origin, they exhibit great variability in biologic behavior, prognosis and treatment based on the primary organ of origin.

DESIGN

Twenty one cases of metastatic NECs were retrieved from our archives and were classified based on location of the primary tumor derived from clinical and radiological findings. Next generation sequencing data was retrieved and analyzed for recurrent genetic abnormalities in these cases. Statistical analysis was performed using IBM SPSS25 software.

RESULTS

RB1 mutations were exclusive to NECs metastasizing from lung primary and were detected in 5 of 12 (41.6 %) cases (p = 0.04). CDKN gene family (CDKN1B and 2 A) mutations were limited to metatstatic NECs of non-pulmonary origin and were detected in 4 of 9 (44.4 %) cases (p = 0.02).

CONCLUSION

The location of the primary tumor in metastatic NECs appears to have significant prognostic and therapeutic implications. But due to the morphological homogeneity, higher grade of tumor, variable sensitivity of immunohistochemical markers, and small, often undetectable primary tumors, the localization of the primary tumor in cases of metastatic NECs is a challenge. In this study, RB1 and CDKN gene family mutations are identified as possible markers for differentiating pulmonary and non-pulmonary origin in metatstatic NECs.

Multiple faces of pulmonary large cell neuroendocrine carcinoma: update with a focus on practical approach to diagnosis

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is a rare and aggressive malignancy that is strongly linked to smoking and notoriously difficult to diagnose and treat. Recent molecular data reveal that it represents a biologically heterogeneous group of tumors, characterized by morphologic and genomic diversity that straddles small cell and non-small cell lung carcinomas (NSCLCs), and in a minority of cases atypical carcinoids. This review provides an update on recent molecular and clinical developments in LCNEC with the main focus on practical approach to pathologic diagnosis using illustrative examples of the main differential diagnostic considerations.

Feasibility of a deep learning algorithm to distinguish large cell neuroendocrine from small cell lung carcinoma in cytology specimens

INTRODUCTION

Distinguishing small cell lung carcinoma (SCLC) from large cell neuroendocrine carcinoma (LCNEC) in cytology is challenging. Our aim was to design a deep learning algorithm for classifying high-grade neuroendocrine carcinomas in fine needle aspirations.

METHODS

Archival cytology cases of high-grade neuroendocrine carcinoma (17 small cell, 13 large cell, 10 mixed/unclassifiable) were retrieved. Each case included smears (Diff-Quik® and Papanicolaou stains) and cell block or concomitant core biopsies (haematoxylin and eosin [H&E] stain). All slides (n = 114) were scanned at 40× magnification, randomised and split into training (11 large, nine small) and test (two large, eight small, 10 mixed) groups. Tumour was annotated using QuPath and exported as JPEG image tiles. Three distinct deep learning convolutional neural networks, one for each preparation/stain, were designed to classify each tile and provide an overall diagnosis for each slide.

RESULTS

The H&E-trained algorithm correctly classified 7/8 (87.5%) SCLC cases and 2/2 (100%) LCNEC cases. The Papanicolaou stain algorithm correctly classified 6/7 (85.7%) SCLC. and 1/1 (100%) LCNEC cases. The algorithm trained on Diff-Quik® stained images correctly classified 7/8 (87.5%) SCLC and 1/1 (100%) LCNEC cases.

CONCLUSION

Using open source software, it was feasible to design a deep learning algorithm to distinguish between SCLC and LCNEC. The algorithm showed high precision in distinguishing between these two categories on H&E sectioned material and direct smears. Although the dataset was limited, our deep learning models show promising results in the classification of LCNEC and SCLC. Additional work using a larger dataset is necessary to improve the algorithm's performance.

High Expression of CARM1 Inhibits Lung Cancer Progression by Targeting TP53 by Regulating CTNNB1

OBJECTIVE

To explore the role of CARM1 in lung cancer (LC) and its relationship with TP53 and CTNNB1.

METHODS

Lung cells H1299 and PC14 were randomly divided into six groups: ov-H1299, si-H1299, ov-PC14, si-PC14, Con-H1299, and Con-PC14. Transwell assay, plate clone formation assay, and flow cytometry were used to determine the migration, clone formation capacity, and apoptosis situation of LC cells in the six groups, respectively. Western blot assay was used to determine the protein expression of CARM1, TP53, and CTNNB1 in the six groups. CHIP assay was applied to analyze the combined characteristics of JUN and TP53 promoter. Co-immunoprecipitation was used to analyze the interaction between TP53 and CARM1/CTNNB1. Cox proportional hazard regression model was used to analyze the relevance between the expression of CARM1 and clinicopathological information of the patient. Kaplan-Meier plot was used to determine the relevance between CARM1 and patient survival.

RESULTS

High expression of CARM1 inhibits the migration and proliferation of LC cells and promoted the apoptosis of LC cell. Overexpression of CARM1 promotes the expression of CARM1 and TP53, while decreases CTNNB1 expression. CARM1 supplementation of H1299 cells induced JUN aggregation on the TP53 promoter. TP53 and CARM1 protein/TP53 and CTNNB1 protein in H1299 cells were immunoprecipitated together. High expression of CARM1was negatively correlated with the degree of tumor metastasis. The survival period of patients with high expression CARM1 was greater than that of low expression.

CONCLUSION

Overexpression of CARM1 may inhibit the progression of LC by targeting TP53 via regulation CTNNB1.

Disparity in clinical outcomes between pure and combined pulmonary large-cell neuroendocrine carcinoma: A multi-center retrospective study

OBJECTIVES

The 2015 World Health Organization classification defines pulmonary large-cell neuroendocrine carcinoma (LCNEC) as a high-grade neuroendocrine carcinoma. However, the clinical characteristics and prognostic factors of pure LCNEC and combined LCNEC remain unclear. Hence, we performed a multi-center retrospective study to compare the clinical outcomes of pure versus combined LCNEC.

MATERIALS AND METHODS

Data from 381 patients with pulmonary LCNEC admitted to 17 Chinese institutes between 2009 and 2016 were collected retrospectively. Clinical characteristics and prognosis were analyzed among patients receiving adjuvant (adjuvant group; n = 56) and first-line (first-line group; n = 146) chemotherapy, as well as among patients receiving small cell lung cancer (SCLC) and non-SCLC (NSCLC) chemotherapy regimens. The Kaplan-Meier method and multivariable Cox regression were used to identify clinicopathological variables that might influence patient outcomes.

RESULTS

Expression levels of neuroendocrine markers (synaptophysin, chromogranin-A, CD56) were associated with patients' prognosis in the total study cohort. In the adjuvant group, median disease-free survival was non-significantly longer for SCLC-based regimens than for NSCLC-based regimens (P = 0.112). In the first-line group, median progression-free survival was significantly longer for SCLC-based regimens than for NSCLC-based regimens (11.5 vs. 7.2 months, P = 0.003). Among patients with combined LCNEC, adenocarcinoma was the most common combined component, accounting for 70.0 % of cases. Additionally, median overall survival was non-significantly shorter for combined LCNEC than for pure LCNEC (P = 0.083).

CONCLUSION

The SCLC regimen is a more effective choice, as either first-line or adjuvant chemotherapy, when compared to the NSCLC regimen for LCNEC treatment. Further studies are needed to clarify the survival differences between patients with pure-, and combined LCNEC.

Neuroendocrine Tumors of the Lung: Updates and Diagnostic Pitfalls

Neuroendocrine tumors of the lung constitute approximately 20% of all primary lung tumors and include typical carcinoid, atypical carcinoid, small cell carcinoma, and large cell neuroendocrine carcinoma. Given their morphologic overlap with diverse mimics, neuroendocrine tumors of the lung can be diagnostically challenging. This review discusses the clinical, histologic, immunophenotypic, and molecular features of pulmonary neuroendocrine tumors, along with common diagnostic pitfalls and strategies for avoidance.

Two cases of lung neuroendocrine carcinoma with carcinoid morphology

BACKGROUND

The category of grade 3 neuroendocrine tumor (NET G3) was newly introduced in the 2017 World Health Organization (WHO 2017) classification of neuroendocrine neoplasms of the pancreas. Pancreatic NET G3 shows a carcinoid-like morphology with high proliferative activity and the prognosis is intermediate between NET G2 and neuroendocrine carcinoma. There is no category corresponding to NET G3 in the current WHO 2015 classification of lung tumors. Herein, we report two cases of lung neuroendocrine carcinoma with carcinoid morphology that correspond to NET G3.

CASE PRESENTATION

Case 1: An abnormal chest shadow was detected in a 78-year-old female never-smoker during a routine medical examination. She was asymptomatic. The radiological assessment revealed a mass in the peripheral S4 segment of the right lung. She underwent right middle lobectomy for the mass preoperatively diagnosed as non-small cell lung carcinoma. Postoperative histological examination revealed a neuroendocrine tumor with carcinoid morphology and a mitotic count of 15/2 mm2. Case 2: An abnormal chest shadow was detected in a 74-year-old female never-smoker undergoing follow-up for another disease. She was asymptomatic. The radiological assessment revealed a mass in the peripheral S3 segment of the right lung. She underwent right upper lobectomy for the mass suspected to be lung carcinoma. Postoperative histological examination revealed a neuroendocrine tumor with carcinoid morphology with mitotic count of 13/2 mm2. Both of these tumors showed carcinoid morphology but with a mitotic count exceeding 10/2 mm2; thus, we diagnosed them as small cell lung carcinomas according to the current WHO 2015 classification.

CONCLUSIONS

Our tumors occurred in female never-smokers and their histology showed carcinoid morphology without extensive necrosis. Moreover, proliferative abilities of them were extremely low compared to small cell lung carcinoma. The clinical and pathological features of our tumors appeared to be different from those of small cell lung carcinoma. Although there is no category corresponding to NET G3 in the current classification of lung tumors, we consider that our tumors may correspond to NET G3 and identification of this subset is relevant for therapeutic management.

Recent advances in the molecular landscape of lung neuroendocrine tumors

INTRODUCTION

Neuroendocrine tumors of the lung (Lung-NETs) make up a heterogenous family of neoplasms showing neuroendocrine differentiation and encompass carcinoids and neuroendocrine carcinomas. On molecular grounds, they considered two completely distinct and separate tumor groups with no overlap of molecular alterations nor common developmental mechanisms. Areas covered: Two perspectives were evaluated based on an extensive review and rethinking of literature: (1) the current classification as an instrument to obtaining clinical and molecular insights into the context of Lung-NETs; and (2) an alternative and innovative interpretation of these tumors, proposing a tripartite separation into early aggressive primary high-grade neuroendocrine tumors (HGNET), differentiating or secondary HGNET, and indolent NET. Expert opinion: We herein provide an alternative outlook on Lung-NETs, which is a paradigm shift to current pathogenesis models and expands the understanding of these tumors.

Large Cell Neuroendocrine Carcinoma of the Mediastinum Successfully Treated with Systemic Chemotherapy after Palliative Radiotherapy

Large cell neuroendocrine carcinoma (LCNEC) is a highly malignant cancer originally found in lung in 1991. In extremely rare occasions, primary LCNEC is found in the mediastinum; approximately 40 of such cases have been reported. Due to the limited number of reported cases, a standardized treatment protocol has yet to be established. We report a case of a 66-year-old woman with primary mediastinal LCNEC who presented with superior vena cava syndrome. Emergent radiotherapy was performed, followed by systemic chemotherapy with cisplatin and etoposide, which resulted in a dramatic tumor reduction. This is the first report describing the achievement of a complete response after systemic chemotherapy in a patient with primary LCNEC.

A New Possible Lung Cancer Marker: VGF Detection from the Conditioned Medium of Pulmonary Large Cell Neuroendocrine Carcinoma–Derived Cells using Secretome Analysis

The prognosis of malignant neuroendocrine tumors of the lung is known to be very poor. Aiming to identify new markers of pulmonary neuroendocrine tumors in early stages and also differential diagnostic markers between large cell neuroendocrine carcinoma and small cell lung cancer, we comprehensively analyzed peptides which were secreted into conditioned medium by LCN1, a large cell neuroendocrine carcinoma cell line. Specific peaks in conditioned medium but not in used medium alone were detected using matrix-associated laser desorption/ionization time of flight mass spectrometry. Two peptide fragments of 40 and 19 amino acid residues were identified by matrix-associated laser desorption/ionization time of flight mass spectrometry. These two fragments were demonstrated to be parts of VGF nerve growth factor inducible (VGF), which is usually expressed in nerve cells or neuroendocrine cells. RT-PCR analysis of lung cancer cell lines showed that VGF mRNA was expressed only in neuroendocrine carcinoma–derived cells. Our data suggest that VGF can be used as a novel serological diagnostic marker of pulmonary neuroendocrine tumors.

Molecular Subtypes of Pulmonary Large-cell Neuroendocrine Carcinoma Predict Chemotherapy Treatment Outcome

Purpose: Previous genomic studies have identified two mutually exclusive molecular subtypes of large-cell neuroendocrine carcinoma (LCNEC): the RB1 mutated (mostly comutated with TP53) and the RB1 wild-type groups. We assessed whether these subtypes have a predictive value on chemotherapy outcome.Experimental Design: Clinical data and tumor specimens were retrospectively obtained from the Netherlands Cancer Registry and Pathology Registry. Panel-consensus pathology revision confirmed the diagnosis of LCNEC in 148 of 232 cases. Next-generation sequencing (NGS) for TP53, RB1, STK11, and KEAP1 genes, as well as IHC for RB1 and P16 was performed on 79 and 109 cases, respectively, and correlated with overall survival (OS) and progression-free survival (PFS), stratifying for non-small cell lung cancer type chemotherapy including platinum + gemcitabine or taxanes (NSCLC-GEM/TAX) and platinum-etoposide (SCLC-PE).Results:RB1 mutation and protein loss were detected in 47% (n = 37) and 72% (n = 78) of the cases, respectively. Patients with RB1 wild-type LCNEC treated with NSCLC-GEM/TAX had a significantly longer OS [9.6; 95% confidence interval (CI), 7.7-11.6 months] than those treated with SCLC-PE [5.8 (5.5-6.1); P = 0.026]. Similar results were obtained for patients expressing RB1 in their tumors (P = 0.001). RB1 staining or P16 loss showed similar results. The same outcome for chemotherapy treatment was observed in LCNEC tumors harboring an RB1 mutation or lost RB1 protein.Conclusions: Patients with LCNEC tumors that carry a wild-type RB1 gene or express the RB1 protein do better with NSCLC-GEM/TAX treatment than with SCLC-PE chemotherapy. However, no difference was observed for RB1 mutated or with lost protein expression. Clin Cancer Res; 24(1); 33-42. ©2017 AACR.

Update on large cell neuroendocrine carcinoma

High-grade neuroendocrine carcinomas of the lung are classified into two categories: large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC). While typical cases of LCNEC are morphologically distinct from SCLC, the differentiation between LCNEC and SCLC can be challenging in some cases. In fact, there are borderline high-grade neuroendocrine carcinomas that morphologically fall between LCNEC and SCLC. Growing evidence suggests that LCNEC is a histologically and biologically heterogeneous group of tumors. Molecular profiling with next-generation sequencing (NGS) has revealed a few biologically distinct subsets of LCNEC. Of those, the SCLC-like subset is characterized by concurrent inactivating mutations in TP53 and loss of RB1 that are typically seen in SCLC, whereas the non-small cell lung cancer (NSCLC)-like subset frequently harbors molecular alterations that are usually seen in NSCLC. Furthermore, the SCLC-like subset exhibits morphologic features of SCLC, and NSCLC-like morphology predominates in the NSCLC-like subset, although there was a substantial overlap in morphologic features between these subsets. As for the treatment of LCNEC, surgery is advocated for early stage tumors, but surgery alone does not appear to be sufficient and adjuvant chemotherapy, consisting of platinum/etoposide, likely prevents recurrence in patients with completely resected LCNEC. For advanced disease, there have been conflicting reports as to whether LCNEC responds to chemotherapeutic regimens in the similar manner to SCLC rather than NSCLC, and the heterogeneous biology of LCNEC may contribute in part to the discrepant results. A further understanding of the biology of LCNEC will lead to novel approaches to clinical managements of patients with LCNEC.

Classification of pulmonary neuroendocrine tumors: new insights

Neuroendocrine tumors of the lung (Lu-NETs) embrace a heterogeneous family of neoplasms classified into four histological variants, namely typical carcinoid (TC), atypical carcinoid (AC), large cell neuroendocrine carcinoma (LCNEC) and small cell lung carcinoma (SCLC). Defining criteria on resection specimens include mitotic count in 2 mm2 and the presence or absence of necrosis, alongside a constellation of cytological and histological traits including cell size and shape, nuclear features and overall architecture. Clinically, TC are low-grade malignant tumors, AC intermediate-grade malignant tumors and SCLC/LCNEC high-grade malignant full-blown carcinomas with no significant differences in survival between them. Homologous tumors arise in the thymus that occasionally have some difficulties in differentiating from the lung counterparts when presented with large unresectable or metastatic lesions. Immunohistochemistry (IHC) helps refine NE diagnosis at various anatomical sites, particularly on small-sized tissue material, in which only TC and small cell carcinoma categories can be recognized easily on hematoxylin & eosin stain, while AC and LCNEC can only be suggested on such material. The Ki-67 labeling index effectively separates carcinoids from small cell carcinoma and may prove useful for the clinical management of a metastatic disease to help the therapeutic decision-making process. Although carcinoids and high-grade neuroendocrine carcinomas in the lung and elsewhere make up separate tumor categories on molecular grounds, emerging data supports the concept of secondary high-grade NETs arising in the preexisting carcinoids, whose clinical and biological relevance will have to be placed into the proper context for the optimal management of these patients. In this review, we will discuss the selected, recent literature with a focus on current issues regarding Lu-NET nosology, i.e., classification, derivation and tumor evolution.

Large-Cell Neuroendocrine Carcinoma of the Lung

BACKGROUND

Large-cell neuroendocrine carcinoma (LCNEC) of the lung displays morphologic and immunohistochemical characteristics common to neuroendocrine tumors and morphologic features of large-cell carcinomas. Because surgical resection of LCNEC in many series has been described with 5-year actuarial survival that is far worse than that reported for other histologic variants of non-small-cell lung cancer (NSCLC), considerable debate has emerged as to whether these tumors should be classified and treated as NSCLC or small-cell lung cancer.

METHODS

The initial evaluation and diagnosis, tumor classification, surgical treatment, results of therapy, and long-term prognosis of patients with LCNEC based on our experience are discussed, and a review of the literature is presented.

RESULTS

Patients with LCNEC are more likely to develop recurrent lung cancer and have shorter actuarial survival than patients with other histologic types of NSCLC, even in those with stage I disease.

CONCLUSIONS

Accurate differentiation of LCNEC from other types of NSCLC is important because it identifies those patients at highest risk for developing recurrent disease. Efforts to identify effective adjuvant therapies are needed to improve treatment outcomes with this aggressive type of lung cancer.

New quantitative features for the morphological differentiation of abnormal lymphoid cell images from peripheral blood

AIMS

This work aims to propose a set of quantitative features through digital image analysis for significant morphological qualitative features of different cells for an objective discrimination among reactive, abnormal and blast lymphoid cells.

METHODS

Abnormal lymphoid cells circulating in peripheral blood in chronic lymphocytic leukaemia, B-prolymphocytic leukaemia, hairy cell leukaemia, splenic marginal zone lymphoma, mantle cell lymphoma, follicular lymphoma, T-prolymphocytic leukaemia, T large granular lymphocytic leukaemia and Sézary syndrome, normal, reactive and blast lymphoid cells were included. From 325 patients, 12 574 cell images were obtained and 2676 features (27 geometric and 2649 related to colour and texture) were extracted and analysed.

RESULTS

We analysed the 20 most relevant features for the morphological differentiation of the 12 lymphoid cell groups under study. Most of them showed significant differences: 19 comparing follicular and mantle cells, 18 for blast and reactive cells, 17 for Sézary cells and T prolymphocytes and 16 for B and T prolymphocytes and 16 for villous lymphocytes. Moreover, a total of five quantitative features were significant for the discrimination among reactive and the set of abnormal lymphoid cells included.

CONCLUSIONS

Image analysis may assist in quantifying cell morphology turning qualitative data into quantitative values. New cytological variables were established based on geometric and colour/texture features to contribute to a more accurate and objective morphological assessment of lymphoid cells and their association with flow cytometry methods may be interesting to explore in the next future.

Ki-67 labeling index of neuroendocrine tumors of the lung has a high level of correspondence between biopsy samples and surgical specimens when strict counting guidelines are applied

Optimal histopathological analysis of biopsies from metastases of neuroendocrine tumor (NET) of the lung requires more than morphology only. Additional parameters such as Ki-67 labeling index are required for adequate diagnosis, but few studies have compared reproducibility of different counting protocols and modalities of reporting on biopsies of lung NET. We compared the results of four different manual counting techniques to establish Ki-67 LI. On 47 paired biopsies and surgical specimens from 22 typical carcinoids (TCs), 14 atypical carcinoids (ACs), six large cell neuroendocrine carcinomas (LCNECs), and five small cell carcinomas (SCCs) immunohistochemical staining of Ki-67 antigen was performed. We counted, in regions of highest nuclear staining (HSR), a full ×40-high-power field (diameter = 0.55 mm), 500 or 2000 cells, or 2 mm² surface area, including the HSR or the entire biopsy fragment(s). Mitoses and necrosis were evaluated in an area of 2 mm² or the entire biopsy fragment(s). Between the four counting methods, no differences in Ki-67 LI were observed. However, a Ki-67 LI higher than 5% was found in only four cases when in an HSR, 500 cells were counted (18%), five (23%) when in an HSR 2000 cells were counted, four (18%) when 2 mm² were counted, and one (5%) TC case when the entire biopsy was counted. A 20% cutoff distinguished TC and AC from LCNEC and SCC with 100% specificity and sensitivity, while mitoses and necrosis failed to a large extent. Ki-67 LI in biopsy samples was concordant with that in resection specimens when 2000 cells, 2 mm², or the entire biopsy fragment(s) were counted. Our results are important for clinical management of patients with metastases of a lung NET.

The Use of Immunohistochemistry Improves the Diagnosis of Small Cell Lung Cancer and Its Differential Diagnosis. An International Reproducibility Study in a Demanding Set of Cases

INTRODUCTION

The current WHO classification of lung cancer states that a diagnosis of SCLC can be reliably made on routine histological and cytological grounds but immunohistochemistry (IHC) may be required, particularly (1) in cases in which histologic features are equivocal and (2) in cases in which the pathologist wants to increase confidence in diagnosis. However, reproducibility studies based on hematoxylin and eosin-stained slides alone for SCLC versus large cell neuroendocrine carcinoma (LCNEC) have shown pairwise κ scores ranging from 0.35 to 0.81. This study examines whether judicious use of IHC improves diagnostic reproducibility for SCLC.

METHODS

Nineteen lung pathologists studied interactive digital images of 79 tumors, predominantly neuroendocrine lung tumors. Images of resection and biopsy specimens were used to make diagnoses solely on the basis of morphologic features (level 1), morphologic features along with requested IHC staining results (level 2), and all available IHC staining results (level 3).

RESULTS

For the 19 pathologists reading all 79 cases, the rate of agreement for level 1 was 64.7%, and it increased to 73.2% and 77.5% in levels 2 and 3, respectively. With IHC, κ scores for four tumor categories (SCLC, LCNEC, carcinoid tumors, and other) increased in resection samples from 0.43 to 0.60 and in biopsy specimens from 0.43 to 0.64.

CONCLUSIONS

Diagnosis using hematoxylin and eosin staining alone showeds moderate agreement among pathologists in tumors with neuroendocrine morphology, but agreement improved to good in most cases with the judicious use of IHC, especially in the diagnosis of SCLC. An approach for IHC in the differential diagnosis of SCLC is provided.

Neuroendocrine Tumors of the Urinary Bladder According to the 2016 World Health Organization Classification: Molecular and Clinical Characteristics

Neuroendocrine neoplasms of the urinary bladder are a rare type of tumor that account for a small percentage of urinary bladder neoplasms. These tumors of the urinary bladder range from well-differentiated neuroendocrine neoplasms (carcinoids) to the more aggressive subtypes such as small cell carcinoma. Despite the rarity of the neuroendocrine tumors of the bladder, there has been substantial investigation into the underlying genomic, molecular, and the cellular alterations within this group of neoplasms. Accordingly, these findings are increasingly incorporated into the understanding of clinical aspects of these neoplasms. In this review, we provide an overview of recent literature related to the 2016 World Health Organization Classification of Neuroendocrine Tumors of the Urinary Bladder. Particular emphasis is placed on molecular alterations and recently described gene expression. The neuroendocrine tumors of the urinary bladder are subdivided into four subtypes. Similar to their pulmonary and other extrapulmonary site counterparts, these have different degrees of neuroendocrine differentiation and morphological features. The clinical aspects of four subtypes of neuroendocrine tumor are discussed with emphasis of the most recent developments in diagnosis, treatment, and prognosis. An understanding of molecular basis of neuroendocrine tumors will provide a base of knowledge for future investigations into this group of unusual bladder neoplasms.

Classification of lung neuroendocrine tumors: lights and shadows

Neuroendocrine tumors of the lung are classified into low-grade typical and intermediate-grade atypical carcinoids, and high-grade poorly differentiated neuroendocrine carcinomas of the large and small cell types. This scheme is strongly predictive of patients' prognosis but relies on few and scarcely reproducible pathological parameters (namely mitotic count and assessment of the presence of necrosis), which have been demonstrated to affect the inter-observer agreement of the classification. Moreover, tumor and nodal staging schemes are not specific for lung carcinoids, at variance with neuroendocrine tumors of the gastro-entero-pancreatic system, despite these tumors have specific features that strongly differ from conventional lung cancer. Finally, there is no grading for lung neuroendocrine neoplasms and prognostication, as well as the definition of treatment modalities and clinical strategies, which are based on tumor histotypes, only. However, literature data indicate that the evaluation of Ki-67 proliferation index may be a reliable and useful tool to determine the biological and clinical behavior of neuroendocrine tumors, with special reference to carcinoids, both in pre-operative and surgical samples.

What clinicians are asking pathologists when dealing with lung neuroendocrine neoplasms?

Lung neuroendocrine tumors (NET) are currently classified in resection specimens according to four histological categories, namely typical carcinoid (TC), atypical carcinoid (AC), large-cell neuroendocrine carcinoma (LCNEC) and small cell carcinoma (SCC). Diagnostic criteria have remained unchanged in the 2015 WHO classification, which has ratified the wide acceptance and popularity of such terminology in the pathologists׳ and clinicians׳ community. A unifying umbrella of NE morphology and differentiation has been recognized in lung NET, which has pushed to enter an unique box of invasive tumors along with diffuse idiopathic pulmonary NE cell hyperplasia (DIPNECH) as a pre-invasive lesion with a potential toward the development of carcinoids. However, uncertainties remain in the terminology of lung NET upon small samples, where Ki-67 antigen could play some role to avoid misdiagnosing carcinoids as high-grade NE tumors. Epidemiologic, clinical and genetic traits support a biological three-tier over a pathology four-tier model, according to which TC are low malignancy tumors, AC intermediate malignancy tumors and LCNEC/SCC high malignancy tumors with no significant differences in survival among them. Inconsistencies in diagnostic reproducibility, troubles in the therapy of AC and LCNEC, and limitations to histology within the same tumor category argue in favor of a global re-thinking of lung NET where a grading system could play a role. This review outlines three main key questions in the field of lung NET: (A) unbiased diagnoses, (B) the role of Ki-67 and tumor grading, and (C) management of predictive markers. Answers are still inconclusive, thus additional research is required to improve our understanding on lung NET.

Large cell carcinoma of the lung: a tumor in search of an author. A clinically oriented critical reappraisal

Large cell carcinoma (LCC) is a merely descriptive term indicating a subtype of lung cancer with no specific features of small-cell lung cancer (SCLC), adenocarcinoma (ADC) or squamous cell carcinoma (SQC). This diagnosis is allowed on surgical specimens only, whereas its counterpart in biopsy/cytology samples is non-small-cell lung carcinoma (NSCLC), not otherwise specified (NOS). Although these two terms do not fulfill the same concept, they can be interchangeable synonyms at the clinical level, reflecting, in different ways, the inability to define a specific subtype. Immunohistochemistry (IHC), next generation sequencing (NGS) analysis and, historically, electron microscopy have been unveiling diverse cell differentiation lineages in LCC, resulting in LCC-favor ADC, LCC-favor SQC and LCC-favor large-cell neuroendocrine carcinoma (LCNEC), the latter hopefully to be included into the neuroendocrine tumor (NET) group in the future. Paradoxically, however, the interpretation issues of LCC/NSCLC-NOS are not diminishing, but even increasing albeight an accurate diagnosis is oncologically required and crucial. Also, rare LCC/NSCLC-NOS cases exhibiting null/unclear phenotype, are difficult to classify, and this terminology could be maintained for the sake of classification (basically these tumors are serendipitous ADC, as also confirmed by the lack of p40). In this review article, seven relevant issues to LCC have been addressed by using a question-answer methodology, with final key points discussing major interpretation issues. In conclusion, most LCC/NSCLC-NOS may be eventually re-classified and addressed by exploiting IHC and/or molecular testing to satisfy the criteria of precision medicine (the right drug, to the right patient, at the right time).

MicroRNA-34a inhibits the proliferation and promotes the apoptosis of non-small cell lung cancer H1299 cell line by targeting TGFβR2

MicroRNAs (MiRNAs) are small non-coding RNA molecules which act as important regulators of post-transcriptional gene expression by binding 3'-untranslated region (3'-UTR) of target messenger RNA (mRNA). In this study, we analyzed miRNA-34a (miR-34a) as a tumor suppressor in non-small cell lung cancer (NSCLC) H1299 cell line. The expression level of miR-34a in four different NSCLC cell lines, H1299, A549, SPCA-1, and HCC827, was significantly lower than that in the non-tumorigenic bronchial epithelium cell line BEAS-2B. In human NSCLC tissues, miR-34a expression level was also significantly decreased in pT2-4 compared with the pT1 group. Moreover, miR-34a mimic could inhibit the proliferation and triggered apoptosis in H1299 cells. Luciferase assays revealed that miR-34a inhibited TGFβR2 expression by targeting one binding site in the 3'-UTR of TGFβR2 mRNA. Quantitative real-time PCR (qRT-PCR) and Western blot assays verified that miR-34a reduced TGFβR2 expression at both mRNA and protein levels. Furthermore, downregulation of TGFβR2 by siRNA showed the same effects on the proliferation and apoptosis as miR-34a mimic in H1299 cells. Our results demonstrated that miR-34a could inhibit the proliferation and promote the apoptosis of H1299 cells partially through the downregulation of its target gene TGFβR2.

Ki-67 antigen in lung neuroendocrine tumors: unraveling a role in clinical practice

Classification of lung neuroendocrine (NE) tumors is a step-wise process with four tumor categories being identified by morphology, namely typical carcinoid (TC), atypical carcinoid, large-cell NE carcinoma, and small-cell lung carcinoma (SCLC). Ki-67 antigen or protein (henceforth simply Ki-67) has been largely studied in these tumors, but the clinical implications are so far not clear. A well-defined role has regarded the diagnostic use in the separation of TC and AC from SCLC in nonsurgical specimens, with monoclonal antibody MIB-1 resulting in the most used reagent after antigen retrieval procedures. Uncertainties, however, have arisen in its assessment, usually expressed as Ki-67 labeling index, because of some variability in obtaining either value of the fraction. A diagnostic role is currently lacking, even though there are significant differences in most cases between TC and AC, less so between large-cell NE carcinoma and SCLC. In addition, the prognostic role of Ki-67 is debated, likely due to methodological and biological reasons. The last challenge would be to identify an effective lung-specific grading system based on Ki-67 labeling index. In this review article, five relevant issues to Ki-67 have been addressed by using a question-answer methodology, with relevant key points discussing major interpretation issues. The conclusion is that Ki-67 is a feasible and potentially meaningful marker in lung NE tumors, but more data are needed to determine its ideal function in this setting of tumors.

Unraveling tumor grading and genomic landscape in lung neuroendocrine tumors

Currently, grading in lung neuroendocrine tumors (NETs) is inherently defined by the histological classification based on cell features, mitosis count, and necrosis, for which typical carcinoids (TC) are low-grade malignant tumors with long life expectation, atypical carcinoids (AC) intermediate-grade malignant tumors with more aggressive clinical behavior, and large cell NE carcinomas (LCNEC) and small cell lung carcinomas (SCLC) high-grade malignant tumors with dismal prognosis. While Ki-67 antigen labeling index, highlighting the proportion of proliferating tumor cells, has largely been used in digestive NETs for assessing prognosis and assisting therapy decisions, the same marker does not play an established role in the diagnosis, grading, and prognosis of lung NETs. Next generation sequencing techniques (NGS), thanks to their astonishing ability to process in a shorter timeframe up to billions of DNA strands, are radically revolutionizing our approach to diagnosis and therapy of tumors, including lung cancer. When applied to single genes, panels of genes, exome, or the whole genome by using either frozen or paraffin tissues, NGS techniques increase our understanding of cancer, thus realizing the bases of precision medicine. Data are emerging that TC and AC are mainly altered in chromatin remodeling genes, whereas LCNEC and SCLC are also mutated in cell cycle checkpoint and cell differentiation regulators. A common denominator to all lung NETs is a deregulation of cell proliferation, which represents a biological rationale for morphologic (mitoses and necrosis) and molecular (Ki-67 antigen) parameters to successfully serve as predictors of tumor behavior (i.e., identification of pathological entities with clinical correlation). It is envisaged that a novel grading system in lung NETs based on the combined assessment of mitoses, necrosis, and Ki-67 LI may offer a better stratification of prognostic classes, realizing a bridge between molecular alterations, morphological features, and clinical behavior.

Grading the neuroendocrine tumors of the lung: an evidence-based proposal

Lung neuroendocrine tumors are catalogued in four categories by the World Health Organization (WHO 2004) classification. Its reproducibility and prognostic efficacy was disputed. The WHO 2010 classification of digestive neuroendocrine neoplasms is based on Ki67 proliferation assessment and proved prognostically effective. This study aims at comparing these two classifications and at defining a prognostic grading system for lung neuroendocrine tumors. The study included 399 patients who underwent surgery and with at least 1 year follow-up between 1989 and 2011. Data on 21 variables were collected, and performance of grading systems and their components was compared by Cox regression and multivariable analyses. All statistical tests were two-sided. At Cox analysis, WHO 2004 stratified patients into three major groups with statistically significant survival difference (typical carcinoid vs atypical carcinoid (AC), P=0.021; AC vs large-cell/small-cell lung neuroendocrine carcinomas, P<0.001). Optimal discrimination in three groups was observed by Ki67% (Ki67% cutoffs: G1 <4, G2 4-<25, G3 ≥25; G1 vs G2, P=0.021; and G2 vs G3, P≤0.001), mitotic count (G1 ≤2, G2 >2-47, G3 >47; G1 vs G2, P≤0.001; and G2 vs G3, P≤0.001), and presence of necrosis (G1 absent, G2 <10% of sample, G3 >10% of sample; G1 vs G2, P≤0.001; and G2 vs G3, P≤0.001) at uni and multivariable analyses. The combination of these three variables resulted in a simple and effective grading system. A three-tiers grading system based on Ki67 index, mitotic count, and necrosis with cutoffs specifically generated for lung neuroendocrine tumors is prognostically effective and accurate.

Combination chemotherapy with irinotecan and cisplatin for large-cell neuroendocrine carcinoma of the lung: a multicenter phase II study

INTRODUCTION

We conducted a phase II study of combination chemotherapy with irinotecan (CPT) and cisplatin (CDDP) in patients with advanced large-cell neuroendocrine carcinoma (LCNEC) of the lung.

METHODS

Patients received irinotecan (60 mg/m², days 1, 8, and 15) and cisplatin (60 mg/m², day 1) every 4 weeks for up to four cycles. The primary endpoint was the response rate. Expected and threshold values for the primary endpoint were 50% and 30%.

RESULTS

Forty-four patients were enrolled between January 2005 and November 2011. The response rate (RR) was 54.5% (95% confidence interval [CI], 38.8-69.6%). The median progression-free survival time was 5.9 months (95% CI, 5.5-6.3), and the median survival time was 15.1 months (95% CI, 11.2-19.0). A central pathological review of specimens from 41 patients demonstrated that 30 patients had LCNEC but that 10 patients had small-cell lung cancer (SCLC) and one had non-small-cell lung cancer with a neuroendocrine structure. The RR was 46.7% (95% CI, 28.3-65.7%) in the LCNEC group and 80% (95% CI, 44.4-97.5%) in the SCLC group (p = 0.0823). The median survival time was 12.6 months (95% CI, 9.3-16.0) in the LCNEC group and 17.3 months (95% CI, 11.2-23.3) in the SCLC group (p = 0.047).

CONCLUSIONS

Combination chemotherapy with irinotecan and cisplatin was active in patients with LCNEC, but the RR and the overall survival period among the patients with LCNEC seemed to be inferior to those among the patients with SCLC. Small numbers of patients were a major limitation in this study.

BAI3, CDX2 and VIL1: a panel of three antibodies to distinguish small cell from large cell neuroendocrine lung carcinomas

AIMS

Discriminating small-cell lung carcinoma (SCLC) from large-cell neuroendocrine carcinoma (LCNEC) rests on morphological criteria, and reproducibility has been shown to be poor. We aimed to identify immunohistochemical markers to assist this diagnosis.

METHODS AND RESULTS

Gene expression profiling on laser captured frozen tumour samples from eight SCLC and eight LCNEC tumours identified a total of 888 differentially expressed genes (DEGs), 23 of which were validated by qRT-PCR. Antibodies to four selected gene products were then evaluated as immunohistochemical markers on a cohort of 173 formalin-fixed paraffin-embedded (FFPE) SCLC/LCNEC tumour samples, including 26 indeterminate tumours without a consensus diagnosis. Three markers, CDX2, VIL1 and BAI3, gave significantly different results in the two tumour types (P < 0.0001): CDX2 and VIL1 in combination (either marker positive) showed sensitivity and specificity of 81% for LCNEC while BAI3 showed 89% sensitivity and 75% specificity for SCLC. Of the 26 indeterminate tumours 15 (58%) showed an immunophenotype suggesting either SCLC or LCNEC, eight (31%) showed staining of both tumour types, and three (11%) were negative for all markers.

CONCLUSION

A panel of three markers, BAI3, CDX2 and VIL1, is a useful adjunct in the diagnosis of these tumour types.

Neuroendocrine tumours--challenges in the diagnosis and classification of pulmonary neuroendocrine tumours

Pulmonary neuroendocrine (NE) proliferations are a diverse group of disorders which share distinct cytological, architectural and biosynthetic features. Tumours composed of NE cells are dispersed among different tumour categories in the WHO classification of tumours and as such do not conform to a singular group with regards to treatment and prognosis. This is reflected by the highly variable behaviour of NE proliferations, ranging from asymptomatic, for instance in diffuse idiopathic pulmonary NE cell hyperplasia and tumourlets, to highly malignant cancers such as small cell lung cancer and large cell NE carcinoma. In this review NE proliferations are described as distinct entities ranging from low grade lesions to high grade cancers. The differential diagnoses are considered with each of the entries. Finally, mention is made of tumours which may show some NE features.