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

Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project

BACKGROUND

Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers.

PATIENTS AND METHODS

Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value.

RESULTS

The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value.

CONCLUSIONS

This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.

Prognostic Immunohistochemistry for Ki-67 and OTP on Small Biopsies of Pulmonary Carcinoid Tumors: Ki-67 Index Predicts Progression-free Survival and Atypical Histology

Prognostic stratification of pulmonary carcinoids into "typical" and "atypical" categories requires examination of large tissue volume. However, there is a need for tools that provide similar prognostic information on small biopsy samples. Ki-67 and OTP immunohistochemistry have shown promising prognostic value in studies of resected pulmonary carcinoids, but prognostic value when using biopsy/cytology specimens is unclear. Ki-67 immunohistochemistry was performed on small biopsy/cytology specimens from pulmonary carcinoid tumors (n=139), and labeling index was scored via automated image analysis of at least 500 cells. OTP immunohistochemistry was performed on 70 cases with sufficient tissue and scored as positive or negative (<20% tumor nuclei staining). Higher Ki-67 index was associated with worse disease-specific progression-free survival (ds-PFS), with 3% and 4% thresholds having similarly strong associations with ds-PFS ( P <0.001, hazard ratio ≥11). Three-year ds-PFS was 98% for patients with Ki-67 <3% and 89% for patients with Ki-67≥3% ( P =0.0006). The optimal Ki-67 threshold for prediction of typical versus atypical carcinoid histology on subsequent resection was 3.21 (AUC 0.68). Negative OTP staining approached significance with atypical carcinoid histology ( P =0.06) but not with ds-PFS ( P =0.24, hazard ratio=3.45), although sample size was limited. We propose that Ki-67 immunohistochemistry may contribute to risk stratification for carcinoid tumor patients based on small biopsy samples. Identification of a 3% hot-spot Ki-67 threshold as optimal for prediction of ds-PFS is notable as a 3% Ki-67 threshold is currently used for gastrointestinal neuroendocrine tumor stratification, allowing consideration of a unified classification system across organ systems.

Metastatic Neuroendocrine Neoplasms to the Pancreas: Two Unusual Cases and a Review of the Literature

Neuroendocrine tumor metastases to the pancreas are rare, and they share substantial overlap with the significantly more common primary pancreatic neuroendocrine neoplasms, representing a potential diagnostic pitfall. Elucidating whether a neuroendocrine tumor within the pancreas is a primary neoplasm versus a metastasis has significant prognostic and treatment implications. Correlation with clinical history and imaging as well as incorporating an appropriate immunohistochemical panel are essential to establish the correct diagnosis. Herein, we present 2 rare neuroendocrine tumors that metastasized to the pancreas: a medullary thyroid carcinoma and an atypical carcinoid tumor of lung origin. We also provide a brief review of the literature.

Updates on lung neuroendocrine neoplasm classification

Lung neuroendocrine neoplasms (NENs) are a heterogeneous group of pulmonary neoplasms showing different morphological patterns and clinical and biological characteristics. The World Health Organisation (WHO) classification of lung NENs has been recently updated as part of the broader attempt to uniform the classification of NENs. This much-needed update has come at a time when insights from seminal molecular characterisation studies revolutionised our understanding of the biological and pathological architecture of lung NENs, paving the way for the development of novel diagnostic techniques, prognostic factors and therapeutic approaches. In this challenging and rapidly evolving landscape, the relevance of the 2021 WHO classification has been recently questioned, particularly in terms of its morphology-orientated approach and its prognostic implications. Here, we provide a state-of-the-art review on the contemporary understanding of pulmonary NEN morphology and the potential contribution of artificial intelligence, the advances in NEN molecular profiling with their impact on the classification system and, finally, the key current and upcoming prognostic factors.

Recommendations for optimizing the use of cytology in the diagnosis and management of patients with lung cancer

Non-small cell lung cancer (NSCLC) is one of the oncological entities with the greatest evolution in molecular diagnosis due to the large number of diagnostic biomarkers and new treatments approved by international regulatory agencies. An accurate, early diagnosis using the least amount of tissue is the goal for the establishing and developing precision medicine for these patients. Rapid on-site evaluation (ROSE) provides cytological samples of optimal quantity and quality for a complete diagnosis of NSCLC. The usefulness of cytological samples has been demonstrated, not only for massive parallel sequencing but also for the quantification of the expression of programmed death-ligand 1 (PD-L1) and tumour mutational burden (TMB). Pre-analytical, analytical, and post-analytical recommendations are made for the management and appropriate use of cytological samples in order to obtain all the information necessary for the diagnosis and treatment of patients with NSCLC according to current quality parameters.

Comparison Between Manual and Automated Assessment of Ki-67 in Breast Carcinoma: Test of a Simple Method in Daily Practice

BACKGROUND

In the era of "precision medicine," the availability of high-quality tumor biomarker tests is critical and tumor proliferation evaluated by Ki-67 antibody is one of the most important prognostic factors in breast cancer. But the evaluation of Ki-67 index has been shown to suffer from some interobserver variability. The goal of the study is to develop an easy, automated, and reliable Ki-67 assessment approach for invasive breast carcinoma in routine practice.

PATIENTS AND METHODS

A total of 151 biopsies of invasive breast carcinoma were analyzed. The Ki-67 index was evaluated by 2 pathologists with MIB-1 antibody as a global tumor index and also in a hotspot. These 2 areas were also analyzed by digital image analysis (DIA).

RESULTS

For Ki-67 index assessment, in the global and hotspot tumor area, the concordances were very good between DIA and pathologists when DIA focused on the annotations made by pathologist (0.73 and 0.83, respectively). However, this was definitely not the case when DIA was not constrained within the pathologist's annotations and automatically established its global or hotspot area in the whole tissue sample (concordance correlation coefficients between 0.28 and 0.58).

CONCLUSIONS

The DIA technique demonstrated a meaningful concordance with the indices evaluated by pathologists when the tumor area is previously identified by a pathologist. In contrast, basing Ki-67 assessment on automatic tissue detection was not satisfactory and provided bad concordance results. A representative tumoral zone must therefore be manually selected prior to the measurement made by the DIA.

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.

Diagnostic criteria and evolving molecular characterization of pulmonary neuroendocrine carcinomas

Neuroendocrine carcinomas of the lung are currently classified into two categories: small cell lung carcinoma and large cell neuroendocrine carcinoma. Diagnostic criteria for small cell- and large cell neuroendocrine carcinoma are based solely on tumor morphology; however, overlap in histologic and immunophenotypic features between the two types of carcinoma can potentially make their classification challenging. Accurate diagnosis of pulmonary neuroendocrine carcinomas is paramount for patient management, as clinical course and treatment differ between small cell and large cell neuroendocrine carcinoma. Molecular-genetic, transcriptomic, and proteomic data published over the past decade suggest that small cell and large cell neuroendocrine carcinomas are not homogeneous categories but rather comprise multiple groups of distinctive malignancies. Nuances in the susceptibility of small cell lung carcinoma subtypes to different chemotherapeutic regimens and the discovery of targetable mutations in large cell neuroendocrine carcinoma suggest that classification and treatment of neuroendocrine carcinomas may be informed by ancillary molecular and protein expression testing going forward. This review summarizes current diagnostic criteria, prognostic and predictive correlates of classification, and evidence of previously unrecognized subtypes of small cell and large cell neuroendocrine carcinoma.

Utility of KI-67 as a prognostic biomarker in pulmonary neuroendocrine neoplasms: a systematic review and meta-analysis

OBJECTIVES

Ki-67, a marker of cellular proliferation, is associated with prognosis across a wide range of tumours, including gastroenteropancreatic neuroendocrine neoplasms (NENs), lymphoma, urothelial tumours and breast carcinomas. Its omission from the classification system of pulmonary NENs is controversial. This systematic review sought to assess whether Ki-67 is a prognostic biomarker in lung NENs and, if feasible, proceed to a meta-analysis.

RESEARCH DESIGN AND METHODS

Medline (Ovid), Embase, Scopus and the Cochrane library were searched for studies published prior to 28 February 2019 and investigating the role of Ki-67 in lung NENs. Eligible studies were those that included more than 20 patients and provided details of survival outcomes, namely, HRs with CIs according to Ki-67 percentage. Studies not available as a full text or without an English manuscript were excluded. This study was prospectively registered with PROSPERO.

RESULTS

Of 11 814 records identified, seven studies met the inclusion criteria. These retrospective studies provided data for 1268 patients (693 TC, 281 AC, 94 large cell neuroendocrine carcinomas and 190 small cell lung carcinomas) and a meta-analysis was carried out to estimate a pooled effect. Random effects analyses demonstrated an association between a high Ki-67 index and poorer overall survival (HR of 2.02, 95% CI 1.16 to 3.52) and recurrence-free survival (HR 1.42; 95% CI 1.01 to 2.00).

CONCLUSION

This meta-analysis provides evidence that high Ki-67 labelling indices are associated with poor clinical outcomes for patients diagnosed with pulmonary NENs. This study is subject to inherent limitations, but it does provide valuable insights regarding the use of the biomarker Ki-67, in a rare tumour.

PROSPERO REGISTRATION NUMBER

CRD42018093389.

The classification of neuroendocrine neoplasms of the lung and digestive system according to WHO, 5th Edition: similarities, differences, challenges & unmet needs

Neuroendocrine neoplasms (NENs) are a group of disease entities sharing common morphological, ultrastructural and immunophenotypical features, yet with distinct biological behavior and clinical outcome, ranging from benign to frankly malignant. Accordingly, a spectrum of therapeutic options for each single entity is available, including somatostatin analogues (SSA), mTOR-inhibitors, peptide receptor radionuclide therapy (PRRT), non-platinum and platinum chemotherapy. In the last few decades, several attempts have been made in order to (1) better stratify these lesions refining the pathological classifications, so as to obtain an optimal correspondence between the scientific terminology and, the predictive and prognostic features of each disease subtype, and (2) achieve a global Classification encompassing NENs arising at different anatomical sites. Aim of this review is to analyze, compare and discuss the main features and issues of the latest WHO Classifications of NENs of the lung and the digestive system, in order to point out the strengths and limitations of our current understanding of these complex diseases.

Liquid Biopsy as a Prognostic and Theranostic Tool for the Management of Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinomas (PDAC) represent one of the deadliest cancers worldwide. Survival is still low due to diagnosis at an advanced stage and resistance to treatment. Herein, we review the main types of liquid biopsy able to help in both prognosis and adaptation of treatments.

Lung neuroendocrine neoplasms: recent progress and persistent challenges

This review summarizes key recent developments relevant to the pathologic diagnosis of lung neuroendocrine neoplasms, including carcinoids, small cell lung carcinoma (SCLC), and large cell neuroendocrine carcinoma (LCNEC). Covered are recent insights into the biological subtypes within each main tumor type, progress in pathological diagnosis and immunohistochemical markers, and persistent challenging areas. Highlighted topics include highly proliferative carcinoids and their distinction from small cell and large cell neuroendocrine carcinomas (NECs), the evolving role of Ki67, the update on the differential diagnosis of NEC to include thoracic SMARCA4-deficient undifferentiated tumors, the recent data on SCLC transcriptional subtypes with the emergence of POU2F3 as a novel marker for the diagnosis of SCLC with low/negative expression of standard neuroendocrine markers, and the update on the diagnosis of LCNEC, particularly in biopsies. There has been remarkable recent progress in the understanding of the genetic and expression-based profiles within each type of lung neuroendocrine neoplasm, and it is hoped that these insights will enable the development of novel diagnostic, prognostic, and predictive biomarkers to aid in the pathologic assessment of these tumors in the future.

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.

The Ki-67 antigen in the new 2021 World Health Organization classification of lung neuroendocrine neoplasms

Prof. Rosai's work has permeated the surgical pathology in many fields, including the 2017 World Health Organization classification on tumors of endocrine organs and pulmonary neuroendocrine cell pathology, with stimulating contributions which have also anticipated the subsequent evolution of knowledge. Among the many studies authored by Prof. Rosai, we would like to recall one of which whose topic has been encased in the new 2021 World Health Organization classification on lung tumors. This is an eminently practical paper dealing with the use of the proliferation antigen Ki-67 in lung neuroendocrine neoplasms. While these neoplasms are primarily ranked upon histologic features and Ki-67 labeling index does not play any role in classification, diagnostic dilemmas may however arise in severely crushed biopsy or cytology samples where this marker proves helpful to avoid misdiagnoses of carcinoids as small cell carcinoma. Another application of Ki-67 labeling index endorsed by the 2021 World Health Organization classification regards, alongside mitotic count, the emerging recognition of lung atypical carcinoids with increased mitotic or proliferation rates, whose biological boundaries straddle a subset of large cell neuroendocrine carcinoma.

This article focuses on these two practical applications of the proliferation marker Ki-67 in keeping with the 2021 World Health Organization classification, which provides standards for taxonomy, diagnosis and clinical decision making in lung neuroendocrine neoplasm patients.

Automated Analysis of Proliferating Cells Spatial Organisation Predicts Prognosis in Lung Neuroendocrine Neoplasms

Simple Summary

Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome, particularly for the intermediate domains of adenocarcinomas and large-cell neuroendocrine carcinomas. Moreover, subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. The aim of this study was to design and evaluate an objective and reproducible approach to the grading of lung NENs, potentially extendable to other NENs, by exploring a completely new perspective of interpreting the well-recognised proliferation marker Ki-67. We designed an automated pipeline to harvest quantitative information from the spatial distribution of Ki-67-positive cells, analysing its heterogeneity in the entire extent of tumour tissue—which currently represents the main weakness of Ki-67—and employed machine learning techniques to predict prognosis based on this information. Demonstrating the efficacy of the proposed framework would hint at a possible path for the future of grading and classification of NENs.

Abstract

Lung neuroendocrine neoplasms (lung NENs) are categorised by morphology, defining a classification sometimes unable to reflect ultimate clinical outcome. Subjectivity and poor reproducibility characterise diagnosis and prognosis assessment of all NENs. Here, we propose a machine learning framework for tumour prognosis assessment based on a quantitative, automated and repeatable evaluation of the spatial distribution of cells immunohistochemically positive for the proliferation marker Ki-67, performed on the entire extent of high-resolution whole slide images. Combining features from the fields of graph theory, fractality analysis, stochastic geometry and information theory, we describe the topology of replicating cells and predict prognosis in a histology-independent way. We demonstrate how our approach outperforms the well-recognised prognostic role of Ki-67 Labelling Index on a multi-centre dataset comprising the most controversial lung NENs. Moreover, we show that our system identifies arrangement patterns in the cells positive for Ki-67 that appear independently of tumour subtyping. Strikingly, the subset of these features whose presence is also independent of the value of the Labelling Index and the density of Ki-67-positive cells prove to be especially relevant in discerning prognostic classes. These findings disclose a possible path for the future of grading and classification of NENs.

Classification of neuroendocrine neoplasms: lights and shadows

Neuroendocrine neoplasms (NENs) are a heterogeneous group of neoplastic proliferations showing different morphological features, immunophenotype, molecular background, clinical presentation, and outcome. They can virtually originate in every organ of the human body and their classification is not uniform among different sites. Indeed, as they have historically been classified according to the organ in which they primarily arise, the different nomenclature that has resulted have created some confusion among pathologists and clinicians. Although a uniform terminology to classify neuroendocrine neoplasms arising in different systems has recently been proposed by WHO/IARC, some issues remain unsolved or need to be clarified. In this review, we discuss the lights and shadows of the current WHO classifications used to define and characterize NENs of the pituitary gland, lung, breast and those of the head and neck region, and digestive and urogenital systems.

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.

Immunocytochemistry for diagnostic cytopathology-A practical guide

Cytological specimens, which are obtained by minimally invasive methods, are an excellent source of diagnostic material. Sometimes they are the only material available for diagnosis as well as for prognostic/predictive markers. When cytomorphology is not straightforward, ancillary tests may be required for a definitive diagnosis to guide clinical management. Immunocytochemistry (ICC) is the most common and practical ancillary tool used to reach a diagnosis when cytomorphology is equivocal, to differentiate entities with overlapping morphological features, and to determine the cell lineage and the site of origin of a metastatic neoplasm. Numerous immunomarkers are available, and some are expressed in multiple neoplasms. To rule out entities within a differential diagnosis, the use of more than one marker, sometimes panels, is necessary. ICC panels for diagnostic purposes should be customised based on the clinical context and cytomorphology, and the markers should be used judiciously to preserve material for additional tests for targeted therapies in the appropriate setting. This review offers a practical guide for the use of ICC for diagnostic cytopathology, covering the most commonly encountered non-hematolymphoid diagnostic scenarios in various body sites.

Challenges in High-grade Neuroendocrine Neoplasms and Mixed Neuroendocrine/Non-neuroendocrine Neoplasms

The growth in knowledge of the pathogenesis, molecular background, and immunohistochemical profile of neuroendocrine neoplasms (NENs) has led not only to an increased awareness of these diseases but also to several changes of the nomenclature. In particular, the concept and terminology of high-grade (grade 3) NENs and mixed neoplasms have changed considerably over the last 20 years, creating some confusion among pathologists and clinicians. The aim of this review is to elucidate the diagnostic criteria, including the most important differential diagnoses of high-grade NENs and mixed neuroendocrine/non-neuroendocrine neoplasms (MiNENs). The role of the Ki67 labelling index and morphology, used to define grade 3 NENs of the digestive system and lungs, is also discussed. The evolution of the concepts and terminology of MiNENs is revised, including the most important differential diagnoses.

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.

Morphologic and molecular classification of lung neuroendocrine neoplasms

Neuroendocrine neoplasms (NENs) of the lung encompass neuroendocrine tumors (NETs) composed of typical (TC) and atypical (AC) carcinoids and full-fledged carcinomas (NECs) inclusive of large cell neuroendocrine carcinoma (LCNEC) and small cell carcinoma (SCLC). NETs and NECs are thought to represent distinct and separate lesions with neither molecular overlap nor common developmental continuum. Two perspectives were addressed regarding the morphologic and molecular classification of lung NENs: (i) a supervised approach by browsing the traditional classification, the relevant gene alterations, and their clinical implications; and (ii) an unsupervised approach, by reappraising neoplasms according to risk factors and natural history of disease to construct an interpretation model relied on biological data. We herein emphasize lights and shadows of the current classification of lung NENs and provide an alternative outlook on these tumors focused on what we currently know about the biological determinants and the natural history of disease.

Ki-67 Index of 55% Distinguishes Two Groups of Bronchopulmonary Pure and Composite Large Cell Neuroendocrine Carcinomas with Distinct Prognosis

BACKGROUND

Little information is available concerning prognostic factors for bronchopulmonary large cell neuroendocrine carcinomas (BP-LCNECs) and even less is known about combined LCNECs (Co-LCNECs). We investigated whether an integrated morphological, immunohistochemical, and molecular approach could be used for their prognostic evaluation.

METHODS

Morphological (including combined features), proliferative (mitotic count/Ki-67 index), immunohistochemical (napsin A, p40, TTF-1, CD44, OTP, SSTR2A, SSTR5, mASH1, p53, RB1, and MDM2), and genomic (TP53, RB1, ATM, JAK2, KRAS, and STK11) findings were analyzed in BP-LCNECs from 5 Italian centers, and correlated with overall survival (OS). The Ki-67 index was expressed as the percentage of positive cells in hot spots as indicated in the WHO 2019 Digestive System Tumors and, for Co-LCNECs, the Ki-67 index was evaluated only in the LCNEC component.

RESULTS

A total of 111 LCNECs were distinguished into 70 pure LCNECs, 35 Co-LCNECs (27 with adenocarcinoma [ADC] and 8 with squamous cell carcinoma [SqCC]), and 6 LCNECs with only napsin A immunoreactivity. The Ki-67 index cutoff at 55% evaluated in the neuroendocrine component was the most powerful predictor of OS (log-rank p = 0.0001) in all LCNECs; 34 cases had a Ki-67 index <55% (LCNEC-A) and 77 had a Ki-67 index ≥55% (LCNEC-B). Statistically significant differences in OS (log-rank p = 0.0001) were also observed between pure and Co-LCNECs. A significant difference in OS was found between pure LCNECs-A and Co-LCNECs-A (p < 0.05) but not between pure LCNECs-B and Co-LCNECs-B. Co-LCNEC-ADC and LCNEC napsin A+ cases had longer OS than pure LCNEC and Co-LCNEC-SqCC cases (log-rank p = 0.0001). On multivariable analysis, tumor location, pure versus combined features, and napsin A, but no single gene mutation, were significantly associated with OS after adjustment for Ki-67 index and study center (p < 0.05).

CONCLUSIONS

The Ki-67 proliferation index and the morphological characterization of combined features in LCNECs seem to be important tools for predicting clinical outcome in BP-LCNECs.

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.

Preoperative Biopsy Diagnosis in Pulmonary Carcinoids, a Shot in the Dark

INTRODUCTION

The preferred treatment for pulmonary carcinoids (PCs) is lobectomy, and parenchyma-sparing approaches might be considered for typical carcinoids (TCs). Treatment decisions are based on a preoperative biopsy diagnosis. Following the WHO criteria (2015), definitive diagnosis is only feasible postoperatively, thereby hampering preoperative treatment decisions. Here, we determined whether the final carcinoid classification on a resection specimen can be predicted by a preoperative biopsy.

METHODS

We searched all stage I to III patients with a final carcinoid diagnosis who underwent a curative resection and of whom both a preoperative biopsy and paired resection specimen were available (2003-2012) using the Dutch Pathology Registry (PALGA) and the Netherlands Cancer Registry (IKNL). Pathology report conclusions of the biopsy-resection specimen were compared.

RESULTS

Paired biopsy-resection specimens in combination with clinical data were available from 330 patients. 57% (189 of 330) of the patients exhibited discordance between the preoperative biopsy and paired resection diagnosis, including 36% (44 of 121) preoperatively diagnosed TC, 40% (six of 15) atypical carcinoid (AC), and 65% (103 of 158) not-otherwise-specified (NOS) carcinoids. A quarter of preoperatively diagnosed TC and NOS was reclassified as AC on the resection specimen. Preoperatively diagnosed ACs exhibited the highest relapse rates (40%, 6 of 15). Preoperatively diagnosed TC and NOS patients who were reclassified as ACs exhibited higher relapse rates as compared to nonreclassified TCs and NOS (3% versus 1%, and 16% versus 6%).

CONCLUSIONS

We provide evidence that carcinoid classification on preoperative biopsies is imprecise, as is also stated by the current WHO classification. We advise clinicians to interpret the preoperative biopsy diagnosis with caution in deciding the extent of surgery (e.g., parenchyma-sparing versus non-parenchyma-sparing).

Phospho-histone-H3 immunostaining for pulmonary carcinoids: impact on clinical appraisal, interobserver correlation, and diagnostic processing efficiency

Lung carcinoid tumors are classified as either typical or atypical based on the presence of necrosis and the maximum mitotic count per 2 mm² area. Determining the mitotic count, which is manually conducted on slides stained with hematoxylin and eosin (HE), is time-consuming and subject to high interobserver variability. The objective of this study was to test the sensitivity and specificity of a surrogate mitosis marker, phospho-histone-H3 (PHH3) immunostaining, in the processing of pulmonary carcinoids as compared with the standard HE evaluation. Carcinoid tissue blocks that were available from lung resection specimens were analyzed using HE and PHH3 stains. Two thoracic pathologists and two residents determined the mitotic count on HE and PHH3 stains in accordance with the 2015 WHO guidelines and recorded the time required to complete this task. For both methods, the interobserver agreement among raters for the mitotic count/2 mm² was assessed by conducting intraclass correlation analyses. We found that for both pathologists and residents, the time required to determine the mitotic count using the PHH3 method was reduced compared with the traditional HE method. Furthermore, residents detected more mitoses/2 mm² using the PHH3 stain compared with the HE method. More importantly, the PHH3 method yielded better interobserver agreement than the HE method in terms of mitoses/mm² detection. Overall, our data confirmed that histologic assessments of carcinoid tumors using PHH3 staining provides practical benefits in terms of scoring times, mitosis detection, and reproducibility of mitotic counts. In addition, we found that the benefit was even greater for less experienced pathologists.

Automated assessment of Ki-67 in breast cancer: the utility of digital image analysis using virtual triple staining and whole slide imaging

AIMS

Precise evaluation of proliferative activity is essential for the stratified treatment of luminal-type breast cancer (BC). Immunohistochemical staining of Ki-67 has been widely used to determine proliferative activity and is recognised to be a useful prognostic marker. However, there remains discussion concerning the methodology. We aimed to develop an automated and reliable Ki-67 assessment approach for invasive BC.

MATERIALS AND RESULTS

A retrospective study was designed to include two cohorts consisting of 152 and 261 consecutive patients with luminal-type BC. Representative tissue blocks following surgery were collected, and three serial sections were stained automatically with Ki-67, pan-cytokeratin and p63. The whole slides were scanned digitally and aligned using VirtualTripleStaining - an extension to the VirtualDoubleStaining™ technique provided by Visiopharm software. The aligned files underwent automated invasive cancer detection, hot-spot identification and Ki-67 counting. The automated scores showed a significant positive correlation with the pathologists' scores (r = 0.82, P < 0.0001). Among selected patients with curative surgery and standard adjuvant therapies (n = 130), the digitally assessed low Ki-67 group (<20%) demonstrated a significantly better prognosis (breast cancer-specific survival, P = 0.030; hazard ratio = 0.038) than the high Ki-67 group.

CONCLUSIONS

Digital image analysis yielded similar results to the scores determined by experienced pathologists. The prognostic utility was verified in our cohort, and an automated process is expected to have high reproducibility. Although some pitfalls were confirmed and thus need to be monitored by laboratory staff, the application could be utilised for the assessment of BC.

Ki67 index and mitotic count: Correlation and variables affecting the accuracy of the quantification in endocrine/neuroendocrine tumors

Quantification of Ki67 and mitosis is time consuming and subject to inter-observer variabilities. Limited studies explored the impact of those variables on the results and the correlation between mitotic count and Ki67 index in endocrine/neuroendocrine tumors, particularly so since the advent of PHH3 antibody and digital pathology. Using Ki67 and mitosis as examples, this study is intended to reveal variables affecting accurate quantification of biomarkers, and to explore the relationship of Ki67 index and mitotic count/index in endocrine/neuroendocrine tumors. Using both manual and pathologist supervised digital image analysis (PSDIA) methods, we examined the impact of post-analytical variables on the quantification of mitosis and Ki67 index and studied the correlation between them in 41 cases of endocrine/neuroendocrine tumors of variable histological grades/proliferating rates. We found that the selection of hotspots, field size and especially threshold affected the outcome of quantification of mitosis and Ki67 index; that mitotic count/index strongly (p < 0.05) correlated with Ki67 index only in the tumors with peak Ki67 index less than 30% and the correlation was more monotonic (positive, non-linear) than linear. In the hotspots of these tumors, the ratio of mitotic count to proliferating cells defined by Ki67 detection averaged 0.04. We also found that the PHH3 antibody could markedly increase the efficiency and accuracy of mitotic quantification. A consensus among pathologists is needed for the selection of hotspots, field size and threshold for quantification of mitosis and Ki67 index.

Commonwealth Neuroendocrine Tumour Research Collaboration and the North American Neuroendocrine Tumor Society Guidelines for the Diagnosis and Management of Patients With Lung Neuroendocrine Tumors: An International Collaborative Endorsement and Update of the 2015 European Neuroendocrine Tumor Society Expert Consensus Guidelines

Lung neuroendocrine tumors (LNETs) are uncommon cancers, and there is a paucity of randomized evidence to guide practice. As a result, current guidelines from different neuroendocrine tumor societies vary considerably. There is a need to update and harmonize global consensus guidelines. This article reports the best practice guidelines produced by a collaboration between the Commonwealth Neuroendocrine Tumour Research Collaboration and the North American Neuroendocrine Tumor Society. We performed a formal endorsement and updating process of the 2015 European Neuroendocrine Tumor Society expert consensus article on LNET. A systematic review from January 2013 to October 2017 was conducted to procure the most recent evidence. The stepwise endorsement process involved experts from all major subspecialties, patients, and advocates. Guided by discussion of the most recent evidence, each statement from the European Neuroendocrine Tumor Society was either endorsed, modified, or removed. New consensus statements were added if appropriate. The search yielded 1109 new publications, of which 230 met the inclusion criteria. A total of 12 statements were endorsed, 22 statements were modified or updated, one was removed, and two were added. Critical answered questions for each topic in LNET were identified. Through the consensus process, guidelines for the management of patients with local and metastatic neuroendocrine tumors have been updated to include both recent evidence and practice changes relating to technological and definitional advances. The guidelines provide clear, evidence-based statements aimed at harmonizing the global approach to patients with LNETs, on the basis of the principles of person-centered and LNET-specific care. The importance of LNET-directed research and person-centered care throughout the diagnosis, treatment, and follow-up journey is emphasized along with directions for future collaborative research.

Ki-67 Labeling Index in Pulmonary Carcinoid Tumors: Comparison Between Small Biopsy and Resection Using Tumor Tracing and Hot Spot Methods

CONTEXT.—

Pulmonary carcinoids are classified as typical or atypical by assessing necrosis and mitoses, which usually cannot be adequately assessed on small biopsies. Ki-67 is not currently used to grade pulmonary carcinoids, but it may be helpful to determine preliminary grade in biopsies. However, the rate at which Ki-67 could underestimate or overestimate grade on small biopsies has not been well studied.

OBJECTIVE.—

To compare Ki-67 labeling obtained on small biopsies to subsequent resection.

DESIGN.—

Ki-67 was performed on paired biopsy and resection specimens from 55 patients. Slides were scanned using Aperio ScanScope. Labeling index was determined using automated hot spot and tumor tracing methods.

RESULTS.—

The study included 41 typical and 14 atypical carcinoids. Atypical carcinoids were larger and had more distant metastases. Death from disease occurred in 3 patients (all had atypical carcinoids). Median hot spot Ki-67 labeling index was greater in resection compared with biopsy by 0.7% (P = .02). Median tumor tracing Ki-67 was lower in resection compared with biopsy by 0.5% (P < .001). Receiver-operating characteristic analysis showed similar hot spot Ki-67 cutoffs to predict atypical histology (3.5% for biopsy, 3.6% for resection; area under the curve [AUC], 0.75 and 0.74, respectively). Different optimal cutoffs were needed for tracing method based on biopsy (2.1%; AUC, 0.75) compared with resection (1.0%; AUC, 0.67).

CONCLUSIONS.—

Hot spot Ki-67 tends to underestimate grade on small biopsies, whereas grade is overestimated by tumor tracing. Hot spot Ki-67 cutoff of 3.5% predicted atypical histology for both biopsy and resection. Different biopsy and resection cutoffs were necessary for tumor tracing, which would make clinical implementation more difficult.

Classification and Prognostic Stratification of Bronchopulmonary Neuroendocrine Neoplasms

The accuracy and reproducibility of the World Health Organization (WHO) 2015 classification of bronchopulmonary neuroendocrine neoplasms (BP-NENs) is disputed. The aim of this study is to classify and grade BP-NENs using the WHO 2019 classification of digestive system NENs (DiS-NEN-WHO 2019), and to analyze its accuracy and prognostic impact. Two BP-NEN cohorts from Japan and Germany, 393 tumors (88% surgically resected), were reviewed and the clinicopathological data of the resected tumors (n = 301) correlated to patients' disease-free survival (DFS). The DiS-NEN-WHO 2019 stratified the 350 tumors into 91 (26%) neuroendocrine tumors (NET) G1, 52 (15%) NET G2, 15 (4%) NET G3, and 192 (55%) neuroendocrine carcinomas (NEC). NECs, but not NETs, were immunohistochemically characterized by abnormal p53 (100%) and retinoblastoma 1 (83%) expression. The Ki67 index, which was on average 4 times higher than mitotic count (p < 0.0001), was prognostically more accurate than the mitotic count. NET G3 patients had a worse outcome than NET G1 (p < 0.01) and NET G2 patients (p = 0.02), respectively. No prognostic difference was detected between NET G3 and NEC patients after 5 year DFS. It is concluded that stratifying BP-NEN patients according to the DiS-NEN-WHO 2019 classification results in 3 prognostically well-defined NET groups, if grading is solely based on Ki67 index. Mitotic count alone may underestimate malignant potential of NETs.

Pulmonary Neuroendocrine Tumors

Pulmonary neuroendocrine tumors represent a morphologic spectrum of tumors from the well-differentiated typical carcinoid tumor, to the intermediate-grade atypical carcinoid tumor, to the high-grade neuroendocrine carcinomas composed of small-cell carcinoma and large-cell neuroendocrine carcinoma. The addition of immunohistochemistry in diagnostics is helpful and often essential, especially in the classification of large-cell neuroendocrine carcinoma. The importance of the intermediate-grade atypical carcinoid group is underscored by the impact of this diagnosis on therapy. The distinction of pulmonary small-cell carcinoma from large-cell neuroendocrine carcinoma, despite both being in the high-grade group, is of relevance to the therapeutic approach to these tumor types.

A practical guide for ancillary studies in pulmonary cytologic specimens

Although most pulmonary cytologic specimens obtained by either exfoliation or fine needle aspirates can be reliably and accurately diagnosed based on pure morphologic criteria alone, a small proportion of cases require ancillary studies for either refining a diagnosis, for resolving a differential diagnosis or increasingly, for predictive purposes in primary lung carcinomas. This article aims to provide practical guidance on the use of common ancillary studies in pulmonary cytologic specimens. Cancer Cytopathol 2018;000:000-000. © 2018 American Cancer Society.

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.

The utility of Ki-67 as a prognostic biomarker in pulmonary neuroendocrine tumours: protocol for a systematic review and meta-analysis

INTRODUCTION

The omission of the immunohistochemical proliferation marker Ki-67 labelling index (henceforth, simply Ki-67) from the 2015 WHO classification system of pulmonary neuroendocrine tumours (Lung-NETs) as a prognostic and grading criterion remains controversial. This systematic review along with meta-analysis will be conducted to assess the prognostic/grading utility of Ki-67 in Lung-NETs.

METHODS

This systematic review will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. A systematic search of MEDLINE Ovid, Embase, Scopus and the Cochrane Library will be performed from the inception of each database to 28 February 2019 for studies investigating any role of Ki-67 in Lung-NETs. Only full papers published in English detailing survival outcomes and HRs according to Ki-67 will be included. The primary endpoint will be establishing whether Ki-67 is a reliable marker in determining prognosis and thus assessing grade of Lung-NETs patients.

ETHICS AND DISSEMINATION

Ethical approval will not be required as this is an academic review of published literature. Findings will be disseminated through the preparation of a manuscript for publication in a peer-reviewed journal as well as presentation at national and international conferences.

PROSPERO REGISTRATION NUMBER

CRD42018093389.

Stage IV lung carcinoids: spectrum and evolution of proliferation rate, focusing on variants with elevated proliferation indices

The spectrum and evolution of proliferation rates in stage IV lung carcinoids is poorly defined. In particular, there are limited data on the prevalence and characteristics of tumors exceeding the standard upper proliferative criteria-as defined largely based on early-stage carcinoids-in metastatic setting. Sixty-six patients with stage IV lung carcinoids were identified, and all evaluable samples (n = 132; mean 2 samples per patient) were analyzed for mitotic counts and Ki-67 rate. Clinicopathologic and genomic features associated with elevated proliferation rates (>10 mitoses per 2 mm2 and/or >20% hot-spot Ki-67), and evolution of proliferation rates in serial specimens were analyzed. We found that mitoses and/or Ki-67 exceeded the standard criteria in 35 of 132 (27%) samples, primarily (31/35 cases) at  metastatic sites. Although neuroendocrine neoplasms with >10 mitoses per 2 mm2 are currently regarded as de facto neuroendocrine carcinomas, the notion that these cases are part of the spectrum of carcinoids was supported by (1) well-differentiated morphology, (2) conventional proliferation rates in other samples from same patient, (3) genetic characteristics, including the lack of RB1/TP53 alterations in all tested samples (n = 19), and (4) median overall survival of 2.7 years, compared to <1 year survival of stage IV neuroendocrine carcinomas in the historic cohorts. In patients with matched primary/metastatic specimens (48 pairs), escalation of mitoses or Ki-67 by ≥10 points was observed in 35% of metastatic samples; clonal relationship in one pair with marked proliferative progression was confirmed by next-generation sequencing. Notably, escalation of proliferation rate was documented in a subset of metastases arising from resected typical carcinoids, emphasizing that the diagnosis of typical carcinoid in primary tumor does not assure low proliferation rate at metastatic sites. In conclusion, stage IV lung carcinoids frequently exceed the standard proliferative criteria established for primary tumors, and commonly exhibit proliferative escalation at metastatic sites. Despite the overlap of proliferation rates, these tumors show fundamental morphologic, genomic and clinical differences from neuroendocrine carcinomas, and should be classified separately from those tumors. Awareness of the increased proliferative spectrum in metastatic carcinoids is critical for their accurate diagnosis. Further studies are warranted to explore the impact of proliferation indices on prognosis and therapeutic responses of patients with metastatic carcinoids.

Prognostic value of cyclin A2 and B1 expression in lung carcinoids

Carcinoid classification in the lung is still based on morphological criteria. Although there are many studies investigating the role of Ki-67 proliferation index in the classification of lung neuroendocrine tumours, it is still not used in routine diagnostics. Interestingly, cyclins, which have a crucial role in controlling the cell cycle, have not been thoroughly studied in lung neuroendocrine tumours. The aim of our study was to investigate the correlation of cyclin A2 and B1 expression with prognosis, Ki-67 proliferation index, and carcinoid morphology. A cohort of 134 resected typical and atypical carcinoids was stained with antibodies against Ki-67, cyclin A2 and B1. The positive nuclear reaction was assessed in hot spot areas and expressed as the percentage of tumour cells. Univariate analyses found the highest relative hazard between low and high cyclin A2 expression both with respect to overall survival [hazard ratio (HR)=16; 95% confidence interval (CI) 4.8-51; p=0.0000054], and relapse (HR=8; 95% CI 3.1-21; p=0.00002). In multivariate analysis for overall survival cyclin A2 (HR=10; 95% CI 2.5->100; p=0.0082) and B1 (HR=6.5; 95% CI 1.5-35; p=0.02) remained significant when adjusted for other risk factors, whereas Ki-67 was no longer significant (HR=0.64; 95% CI 0.003-5.5; p=0.65). This suggests that Ki-67 is closer to conventional risk factors for survival than cyclin A2 and B1. Furthermore, the analysis revealed 4 mitoses per 2 mm² as a more powerful prognostic cut-off than currently accepted 2 mitoses. We have clearly demonstrated that application of cyclin A2 and cyclin B1 might bring additional value regarding the overall and progression-free survival of patients with carcinoids of the lung.

Automated quantification of Ki-67 index associates with pathologic grade of pulmonary neuroendocrine tumors

Background:

Classification of the pulmonary neuroendocrine tumor (pNET) categories is a step-wise process identified by the presence of necrosis and number of mitoses per 2 mm². In neuroendocrine tumor pathology, Ki-67 was first described as a prognostic factor in the pancreas and incorporated into the grading system of digestive tract neuroendocrine neoplasms in the 2010 WHO classification. However, the significance of Ki-67 in pNETs was still a controversial issue. This study was to investigate the potentially diagnostic value of Ki-67 in pNETs.

Methods:

We retrieved 159 surgical specimens of pNETs, including 35 typical carcinoids (TCs), 2 atypical carcinoid (ACs), 28 large-cell neuroendocrine carcinomas (LCNECs), 94 small-cell lung cancers (SCLCs). Manual conventional method (MCM) and computer-assisted image analysis method (CIAM) were used to calculate the Ki-67 proliferative index. In CIAM, 6 equivalent fields (500 × 500 μm) at 10× magnification were manually annotated for digital image analysis.

Results:

The Ki-67 index among the 4 groups with ranges of 0.38% to 12.66% for TC, 4.34% to 29.48% for AC, 30.67% to 93.74% for LCNEC, and 40.71% to 96.87% for SCLC. The cutoff value of Ki-67 index to distinguish low grade with high grade was 30.07%. For the univariate survival analyses in pNETs, both the overall survival and progression-free survival correlated with Ki-67 index. In addition, the Ki-67 index performed by CIAM was proved to be of great positive correlation with MCM.

Conclusions:

Ki-67 index counted by CIAM is a reliable method and can be a useful adjunct to classify the low- and high-grade NETs.

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.

Role of Immunocytochemistry in the Cytological Diagnosis of Pulmonary Tumors

Pulmonary cytology is a challenging diagnostic tool, and it is usually evaluated considering medical history and radiological findings in order to reach an accurate diagnosis. Since the majority of lung cancer patients have an advanced stage at diagnosis, a cytological specimen is frequently the only material available for diagnosis and further prognostic/predictive marker determination. Several types of specimens can be obtained from the respiratory system (including sputum, bronchoalveolar lavage, bronchial brushing, fine needle aspiration, and pleural fluid) with different technical preclinical management protocols and different diagnostic yields. Immunocytochemistry (ICC) has a pivotal role in the determination of diagnostic, prognostic, and predictive markers. Therefore, limited cytology samples are to be used with a cell-sparing approach, to allow both diagnostic ICC evaluation as well as predictive marker assessment by ICC or specific molecular assays. In this review, we describe the most common ICC markers used for the diagnosis and prognostic/predictive characterization of thoracic tumors in different cytological specimens.

Ki-67 Evaluation for Clinical Decision in Metastatic Lung Carcinoids: A Proof of Concept

Accrual of metastatic pulmonary carcinoid patients for therapy is usually relied on clinical and histologic characterization, with no role for the proliferation activity as defined by Ki-67 labelling index (LI). A total of 14 carcinoid patients with tumour primaries (TP) and 19 corresponding tumour metastases (TM) were blindly reviewed by 2 different pathologists for necrosis, mitotic count, and Ki-67 LI. Ki-67 LI outperformed histologic subtyping, mitotic count, and necrosis with good to almost excellent (0.40-0.75) inter-observer agreement. About 10% cut-off Ki-67 LI predicted survival better than histology for TP and TM for both observers. The TM patients survived differently according to diverse treatments (somatostatin analogues [SSAs], analogues plus additional treatments except for platinum; platinum-based chemotherapy) in close correlation with <10%, 10% to 20%, and >20% cut-off thresholds of Ki-67 LI, respectively. There was also a trend for an increase in Ki-67 LI in TM as compared with TP. This is the first proof of concept in which a clinical potential is preliminarily suggested for Ki-67 LI to better stratify pulmonary metastatic carcinoid patients for treatment according to a criterion of histology-independent biological aggressiveness.

Is the sum of positive neuroendocrine immunohistochemical stains useful for diagnosis of large cell neuroendocrine carcinoma (LCNEC) on biopsy specimens?

Aims

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is underdiagnosed on biopsy specimens. We evaluated if routine neuroendocrine immunohistochemical (IHC) stains are helpful in the diagnosis of LCNEC on biopsy specimens.

Methods and results

Using the Dutch pathology registry (PALGA), surgically resected LCNEC with matching pre‐operative biopsy specimens were identified and haematoxylin and IHC slides (CD56, chromogranin‐A, synaptophysin) requested. Subsequently, three pathologists assigned (1) the presence or absence of the WHO 2015 criteria and (2) cumulative size of all (biopsy) specimens. For validation, a tissue microarray (TMA) of non‐small‐cell lung cancer (NSCLC) (n = 77) and LCNEC (n = 19) was used. LCNEC was confirmed on the resection specimens in 32 of 48 re‐reviewed cases. In 47% (n = 15 of 32) LCNEC was also confirmed in the paired biopsy specimens. Neuroendocrine morphology was absent in 53% (n = 17 of 32) of paired biopsy specimens, more often when smaller amounts of tissue were available for evaluation [29% < 5 mm (n = 14) versus 67% ≥5 mm (n = 18) P = 0.04]. Combined with current WHO criteria, positive staining for greater than or equal to two of three neuroendocrine IHC markers increased the sensitivity for LCNEC from 47% to 93% on paired biopsy specimens, and further validated using an independent TMA of LCNEC and NSCLC with sensitivity and specificity of 80% and 99%, respectively.

Conclusions

LCNEC is difficult to diagnose because neuroendocrine morphology is frequently absent in biopsy specimens. In NSCLC devoid of obvious morphological squamous or adenocarcinoma features, positive staining in greater than or equal to two of three neuroendocrine IHC stains supports the diagnosis of LCNEC.

The use of Ki-67 labeling index to grade pulmonary well-differentiated neuroendocrine neoplasms: current best evidence

Although Ki-67 labeling index (Ki-67%) is not a diagnostic or grading criterion in the World Health Organization classification of pulmonary carcinoid tumor, oncologists often request this test. A survey was administered at a North American Society for Neuroendocrine Tumors meeting to understand how Ki-67% is used in oncologic practices. A systematic literature review was performed to gather best evidence regarding the use of Ki-67%. Consecutive pulmonary carcinoids were stratified into pulmonary typical carcinoids with Ki-67% <5% (group A, n = 187), typical carcinoids with Ki-67% ≥5% (group B, n = 38) and atypical carcinoids irrespective of Ki-67% (group C, n = 31). Overall survival, progression-free survival, recurrence proportions and time to recurrence were compared, by group, using the log-rank test, chi-square statistics and ANOVA, respectively. Our survey confirmed that Ki-67% is frequently used by specialists caring for these patients. Ki-67% of 1-7% significantly correlated with overall survival in the literature but we found no information about Ki-67% cut-off values that would accurately distinguish pulmonary typical from atypical carcinoids or estimate the prognosis of patients stratified by World Health Organization diagnosis and Ki-67% cut-off. Overall survival was significantly different in our 3 patient groups (p < 0.001), with survival probabilities decreasing from groups A to C. Progression-free survival was significantly longer in group A than B (p < 0.007). Our results support the concept that by combining World Health Organization diagnosis and Ki-67%, pulmonary carcinoids can be stratified into 3 grades: G1 (typical carcinoids with Ki-67% <5), G2 (typical carcinoids with Ki-67% ≥5%) and G3 (atypical carcinoids) with different prognoses.

Insights into Novel Prognostic and Possible Predictive Biomarkers of Lung Neuroendocrine Tumors

Primary lung neuroendocrine tumors (NETs) consist of typical and atypical carcinoids, large-cell neuroendocrine carcinomas and small-cell lung carcinomas. NETs are highly heterogeneous in histological characteristics, clinical presentation and natural history. While there are morphological and immunohistochemical criteria to establish diagnosis, there is a lack of universal consensus for prognostic factors or therapeutic targets for personalized treatment of the disease. Thus, identifying potential markers of neuroendocrine differentiation and prognostic factors remains of high importance. This review provides an insight into promising molecules and genes that are implicated in NET carcinogenesis, cell-cycle regulation, chromatin remodeling, apoptosis, intracellular cascades and cell-cell interactions. Additionally it supports a basis for classifying these tumors into categories that distinct molecular characteristics and disease natural history, which may have a direct impact on treatment options. In light of the recent approval of everolimus, mammalian target of rapamycin pathway inhibition and related biomarkers may play a central role in the treatment of pulmonary NETs. Future clinical trials that integrate molecular profiling are deemed necessary in order to treat patients with NET on a personalized basis.

Augmented expression of Ki-67 is correlated with clinicopathological characteristics and prognosis for lung cancer patients: an up-dated systematic review and meta-analysis with 108 studies and 14,732 patients

Background

Lung cancer ranks as the leading cause of cancer-related deaths worldwide and we performed this meta-analysis to investigate eligible studies and determine the prognostic effect of Ki-67.

Methods

In total, 108 studies in 95 articles with 14,732 patients were found to be eligible, of which 96 studies reported on overall survival (OS) and 19 studies reported on disease-free survival (DFS) with relation to Ki-67 expression in lung cancer patients.

Results

The pooled hazard ratio (HR) indicated that a high Ki-67 level could be a valuable prognostic factor for lung cancer (HR = 1.122 for OS, P < 0.001 and HR = 1.894 for DFS, P < 0.001). Subsequently, the results revealed that a high Ki-67 level was significantly associated with clinical parameters of lung cancer including age (odd ratio, OR = 1.246 for older patients, P = 0.018), gender (OR = 1.874 for males, P < 0.001) and smoking status (OR = 3.087 for smokers, P < 0.001). Additionally, significant positive correlations were found between Ki-67 overexpression and poorer differentiation (OR = 1.993, P = 0.003), larger tumor size (OR = 1.436, P = 0.003), and higher pathologic stages (OR = 1.867 for III-IV, P < 0.001). Furthermore, high expression of Ki-67 was found to be a valuable predictive factor for lymph node metastasis positive (OR = 1.653, P < 0.001) and advanced TNM stages (OR = 1.497 for stage III-IV, P = 0.024). Finally, no publication bias was detected in any of the analyses.

Conclusions

This study highlights that the high expression of Ki-67 is clinically relevant in terms of the prognostic and clinicopathological characteristics for lung cancer. Nevertheless, more prospective well-designed studies are warranted to validate these findings.

Electronic supplementary material

The online version of this article (10.1186/s12931-018-0843-7) contains supplementary material, which is available to authorized users.

Pathologic Grading of Malignant Pleural Mesothelioma: An Evidence-Based Proposal

INTRODUCTION

A pathologic grading system (PGS) for malignant pleural mesothelioma (MPM) is warranted to better identify different risk categories of patients, plan therapeutic options, and activate clinical trials.

METHODS

A series of 940 patients with MPM (328 in a training set and 612 in a validation set) that was diagnosed between October 1980 and June 2015 at the participant institutions was retrospectively assembled. A PGS was constructed by attributing to each histologic parameter, independent at multivariate analysis with excellent reproducibility (κ > 0.75), different scores based on the increase in corresponding hazard ratios. The relevant PGS score thus ranged from 0 to 8 points for individual patients with MPM.

CONCLUSIONS

The PGS was constructed by taking into consideration the histological subtyping of MPM (epithelioid/biphasic = 0 points; sarcomatoid = 2 points), necrosis (absent = 0 points versus present = 1 point), mitotic count per 1 mm² (cutoffs as follows: 1-2 = 0 points, 3-5 = 1 point, 6-9 = 2 points, or ≥10 = 4 points), and Ki-67 labeling index based on 2000 cells (<30% = 0 points versus ≥30 = 1 point), all of which are independent factors in both patient sets after adjustment for stage and age at diagnosis. No heterogeneity was seen across the validation centers (p = 0.19). Epithelioid/biphasic MPM patterning and biopsy versus resection did not affect survival, whereas the PGS outperformed mitotic count and Ki-67 LI in both the training (area under the curve receiver operating characteristic = 0.76) and validation sets (area under the curve receiver operating characteristic = 0.73) (p < 0.01). Patient survival progressively deteriorated from a score of 0 (median times of 26.3 and 26.9 months) to a score 1 to 3 (median times of 12.8 and 14.4 months) and a score of 4 to 8 (median times of 3.7 and 7.7 months) in both sets of patients, with the hazard ratio for a 1-point increase in score being 1.46 (95% confidence interval: 1.36-1.56) in the training set and 1.28 (95% confidence interval: 1.22-1.34) in the validation set (after adjustment for age and [when available] tumor stage). The PGS was effective even in subgroup analysis (epithelioid, biphasic, and sarcomatoid tumors).

DISCUSSION

A simple and reproducible multiparametric PGS effectively predicted survival in patients with MPM.

Immunohistochemical Biomarkers of Gastrointestinal, Pancreatic, Pulmonary, and Thymic Neuroendocrine Neoplasms

Neuroendocrine neoplasms (NENs) are a heterogeneous group of epithelial neoplastic proliferations that irrespective of their primary site share features of neural and endocrine differentiation including the presence of secretory granules, synaptic-like vesicles, and the ability to produce amine and/or peptide hormones. NENs encompass a wide spectrum of neoplasms ranging from well-differentiated indolent tumors to highly aggressive poorly differentiated neuroendocrine carcinomas. Most cases arise in the digestive system and in thoracic organs, i.e., the lung and thymus. A correct diagnostic approach is crucial for the management of patients with both digestive and thoracic NENs, because their high clinical and biological heterogeneity is related to their prognosis and response to therapy. In this context, immunohistochemistry represents an indispensable diagnostic tool that pathologists need to use for the correct diagnosis and classification of such neoplasms. In addition, immunohistochemistry is also useful in identifying prognostic and theranostic markers. In the present article, the authors will review the role of immunohistochemistry in the routine workup of digestive and thoracic NENs.