Unraveling tumor grading and genomic landscape in lung neuroendocrine tumors

A comprehensive analysis of the prognostic value, expression characteristics and immune correlation of MKI67 in cancers

Background

nuclear-associated antigen Ki67 (Ki67) emerges as a clinically practical biomarker for proliferation assessment among many cancer types. However, the definite prognostic value of Ki67 against a specific cancer type has remained vague. This study aims to perform a comprehensive pan-cancer analysis of the prognosis value of Ki67 across various cancer types.

Methods

This study explored the expression, prognostic value, and tumor-infiltrating immune of MKI67 in the TCGA database by pan-cancer, and then performed immunohistochemical, correlation analysis and prognostic analysis using 10028 patients of the top 10 cancer patients in China we collected. The correlation between MKI67 expression and survival outcome, clinical features, MSI, TMB, and tumor-infiltrating immune cells by TCGA database, xCell, and TIMER algorithms.

Results

MKI67 expression was significantly upregulated across varied cancer types verified by datasets. We found MKI67 expression was significantly associated with poor prognosis in LUADLUSC, LIHC, and BRCA patients, but good prognosis in COADREAD and READ patients via Kaplan-Meier survival analysis using 10028 patients collected. These results of our validation were generally consistent with TCGA database except BRCA, COADREAD and READ. Meanwhile, upregulation of MKI67 elevates the degree of immune infiltration of several immune cell subtypes, such as functional T cells, CD4+ T cells, and CD8+ T cells, as well as, MKI67 was related to Cell cycle, Oocyte meiosis, p53 and other pathways.

Conclusion

Our comprehensive analysis may supply useful guidance on MKI67 applicability across various cancer types. These observed results contribute to the promise of MKI67 in a realistic clinical setting and improve the outcomes of cancer patients.

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.

Application of Artificial Intelligence in Neuroendocrine Lung Cancer Diagnosis and Treatment: A Systematic Review

Neuroendocrine tumors (NETs) represent a heterogeneous group of neoplasms with diverse clinical presentations and prognoses. Accurate and timely diagnosis of these tumors is crucial for appropriate management and improved patient outcomes. In recent years, exciting advancements in artificial intelligence (AI) technologies have been revolutionizing medical diagnostics, particularly in the realm of detecting and characterizing pulmonary NETs, offering promising avenues for improved patient care. This article aims to provide a comprehensive overview of the role of AI in diagnosing lung NETs. We discuss the current challenges associated with conventional diagnostic approaches, including histopathological examination and imaging modalities. Despite advancements in these techniques, accurate diagnosis remains challenging due to the overlapping features with other pulmonary lesions and the subjective interpretation of imaging findings. AI-based approaches, including machine learning and deep learning algorithms, have demonstrated remarkable potential in addressing these challenges. By leveraging large datasets of radiological images, histopathological samples, and clinical data, AI models can extract complex patterns and features that may not be readily discernible to human observers. Moreover, AI algorithms can continuously learn and improve from new data, leading to enhanced diagnostic accuracy and efficiency over time. Specific AI applications in the diagnosis of lung NETs include computer-aided detection and classification of pulmonary nodules on CT scans, quantitative analysis of PET imaging for tumor characterization, and integration of multi-modal data for comprehensive diagnostic assessments. These AI-driven tools hold promise for facilitating early detection, risk stratification, and personalized treatment planning in patients with lung NETs.

Incidence and prognostic nomogram for resected non-small cell neuroendocrine tumor: A population-based respective study in China and the SEER database

Background

Pulmonary neuroendocrine tumors, including small cell lung cancer (SCLC) and non-small cell neuroendocrine tumor (NSCLC-NET), have obvious heterogeneity. The comparison between SCLC and NSCLC-NET, and prognostic nomogram of resected NSCLC-NET have not been performed.

Methods

We retrieved data from SEER database. The incidence and prognostic factors were compared between SCLC and NSCLC-NET. By Cox regression, we constructed prognostic nomogram of resected NSCLC-NET. The nomogram was evaluated by ROC, calibration plot and decision curve analysis (DCA) and compared with 8th TNM staging system. A Chinese cohort was used for external validation.

Results

The age-adjusted incidence of SCLC declined after 1991 but the incidence of NSCLC-NET continuously rose. Patients with typical carcinoid had the best prognosis in both overall survival and lung cancer specific survival, followed by atypical carcinoid, large cell neuroendocrine tumor and SCLC after operation. Patients receiving sleeve resection in NSCLC-NET had longer survival but segmental resection was more recommended in SCLC. High-smoking index was associated with worse overall survival in both SCLC and NSCLC-NET. Histological subtype, age, surgery type, N, M stage and chemotherapy were independent prognostic factors and used to construct prognostic nomogram of resected NSCLC-NET. The nomogram performed well with good discrimination, calibration and clinical usefulness, which was validated by a Chinese cohort (1, 3, 5-year AUC: SEER cohort 0.873, 0.901, 0.875; Chinese cohort 0.867, 0.892, 0.874). Compared to the 8th staging system, the nomogram had higher C-index (0.87 vs 0.728, P < 0.001), clinical usefulness, increasing AUC value over time and improved 68%.

Conclusion

The prognostic nomogram of resected NSCLC-NET performed better than the 8th TNM staging system. It may have certain value in risk stratification and survival prediction of patients with resected NSCLC-NET and help clinicians to take measures for high-risk patients in advance.

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.

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.

Clinicopathological and immunohistochemical study of pulmonary neuroendocrine tumors - A single-institute experience

INTRODUCTION

Pulmonary neuroendocrine tumors (NETs) comprise a spectrum of tumors ranging from indolent to highly aggressive neoplasm. This study aims to study the clinicopathological and immunohistochemical features of NETs and assess the sensitivity of various IHC markers.

MATERIALS AND METHODS

All consecutive cases of pulmonary NETs diagnosed from January 2016 to June 2019 were analyzed retrospectively. The routine hematoxylin- and eosin-stained sections along with immunohistochemistry (IHC) slides were reviewed. IHC was done using a panel of markers which included synaptophysin, chromogranin, CD56, thyroid transcription factor-1 (TTF-1), p-40, napsin-A, and ki67.

RESULTS

Of total number of 53 patients, diagnosis was made on biopsy in 40 patients and resection specimen in 13 patients. Small cell lung carcinoma was the most common (31 cases), followed by 16 cases of typical carcinoid, 5 cases of atypical carcinoid, and 1 case of combined SCLC. Both synaptophysin and chromogranin were positive in all the cases of typical carcinoid. Synaptophysin had better sensitivity than chromogranin in atypical carcinoid and small cell carcinoma. CD56 was positive in 8 out of 9 cases done. TTF-1 was negative in all the cases of typical carcinoid. The sensitivity of TTF-1 in small cell carcinoma was 85.19%. The mean Ki67 labeling index was 1.4%, 6.6%, and 65.6% in typical, atypical carcinoid, and small cell carcinomas, respectively.

CONCLUSION

Synaptophysin was more sensitive than chromogranin, especially in atypical carcinoid and small cell carcinoma. TTF-1 along with high Ki67 differentiates small cell carcinoma from carcinoid.

Unravelling actionable biology using transcriptomic data to integrate mitotic index and Ki-67 in the management of lung neuroendocrine tumors

Pulmonary neuroendocrine tumors (NETs) are a heterogeneous family of malignancies whose classification relies on morphology and mitotic rate, unlike extrapulmonary neuroendocrine tumors that require both mitotic rate and Ki-67. As mitotic count is proportional to Ki-67, it is crucial to understand if Ki-67 can complement the existing diagnostic guidelines, as well as discover the benefit of these two markers to unravel the biological heterogeneity. In this study, we investigated the association of mitotic rate and Ki-67 at gene- and pathway-level using transcriptomic data in lung NET malignancies. Lung resection tumor specimens obtained from 28 patients diagnosed with NETs were selected. Mitotic rate, Ki-67 and transcriptomic data were obtained for all samples. The concordance between mitotic rate and Ki-67 was evaluated at gene-level and pathway-level using gene expression data. Our analysis revealed a strong association between mitotic rate and Ki-67 across all samples and cell cycle genes were found to be differentially ranked between them. Pathway analysis indicated that a greater number of pathways overlapped between these markers. Analyses based on lung NET subtypes revealed that mitotic rate in carcinoids and Ki-67 in large cell neuroendocrine carcinomas provided comprehensive characterization of pathways among these malignancies. Among the two subtypes, we found distinct leading-edge gene sets that drive the enrichment signal of commonly enriched pathways between mitotic index and Ki-67. Overall, our findings delineated the degree of benefit of the two proliferation markers, and offers new layer to predict the biological behavior and identify high-risk patients using a more comprehensive diagnostic workup.

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.

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.

Recent Advances in the Management of Typical and Atypical Lung Carcinoids

Neuroendocrine neoplasms of the lung represent about 20% to 30% of all neuroendocrine tumors. On the basis of clinical and pathologic characteristics, 2 different categories of tumors may be defined: poorly differentiated neuroendocrine neoplasms, characterized by a high rate of recurrences and poor prognosis, and well-differentiated neuroendocrine neoplasms (typical carcinoids and atypical carcinoids), which generally display an indolent course. Lung carcinoids represent only 1% to 5% of all lung malignancies, but their incidence has significantly increased over the past 30 years. Surgery is the reference standard of treatment for lung carcinoids with locoregional disease. For advanced or unresectable lung carcinoids, several therapeutic options are available, but the choice should be shared within a multidisciplinary team to ensure optimal therapeutic outcomes. We describe the current management of these rare neoplasms.

Challenges in Ki-67 assessments in pulmonary large-cell neuroendocrine carcinomas

AIMS

To gather the best available evidence regarding Ki-67% values in large-cell neuroendocrine carcinoma (LCNEC) and determine whether certain cut-off values could serve as a prognostic feature in LCNEC.

METHODS AND RESULTS

Aperio ScanScope AT Turbo, eSlide Manager and ImageScope software (Leica Biosystems) were used to measure Ki-67% in 77 resected LCNEC diagnosed by World Health Organisation (WHO) criteria. Cases were stratified into six classes by 10% Ki-67 increments. Using the Kaplan-Meier method, overall (OS) and disease-free survivals (DFS) were compared by AJCC stage, by six Ki-67% classes and with Ki-67% cut-points ≥20% and ≥40%. Tumours were from 0.9 to 11.5 cm and pathological stages 1-3. The system measured Ki-67% positivity using 4072-44 533 tumour nuclei per case (mean 16610 ± 8039). Ki-67% ranged from 1 to 64% (mean = 26%; median = 26%). Only 16 (21%) tumours had Ki-67% ≥40%. OS ranged from 1 to 298 months (median follow-up = 25 months). DFS ranged from 1 to 276 months (median follow-up = 9 months). OS and DFS differed across AJCC stage (overall log-rank P = 0.038 and P = 0.037). However, neither OS nor DFS significantly correlated with Ki-67% when six or two classes were used with either ≥20% Ki-67 or ≥40% Ki-67 as cut-point. A literature review identified 14 reports meeting our inclusion criteria with ≥10 LCNEC. Reported Ki-67% ranged from 2% to 100%. Problems contributing to variability in Ki-67% measurements are discussed.

CONCLUSION

Our findings caution against a blanket use of 20%, 40% or other Ki-67% cut-points for LCNEC diagnosis or prognostication.

EPB41L5 is Associated With the Metastatic Potential of Low-grade Pancreatic Neuroendocrine Tumors

BACKGROUND/AIM

Low-grade pancreatic neuroendocrine tumors (LG-PNETs) behave unpredictably. The aim of the study was to identify biomarkers that predict PNET metastasis to improve treatment selection.

PATIENTS AND METHODS

Five patients with primary non-metastatic LG-PNETs, six with primary LG-PNETs with synchronous or metachronous metastases (M-PNETs), and six metastatic to liver LG-PNETs (ML-PNETs) from the group of six M-PNET patients were selected. RNA data were normalized using iterative rank-order normalization. Student's t-test identified differentially-expressed genes in LG-PNETs versus M-PNETs. A 2-fold difference in expression was considered to be significant. Results were validated with an independent dataset of LG-PNETs and metastatic LG-PNETs.

RESULTS

Overall, 195 genes had a >2-fold change (in either direction). A total of 29 genes were differentially overexpressed in M-PNETs. Erythrocyte membrane protein band 4.1-like 5 (EPB41L5) had a 2.07-fold change increase in M-PNETs and the smallest p-value. EPB41L5 was not statistically different between M-PNETs and ML-PNETs. EPB41L5 differential expression between primary and metastatic LG-PNETs was confirmed by immunohistochemistry.

CONCLUSION

These results support further investigation into whether EPB41L5 is a biomarker of PNETs with high risk for metastases.

Integrative Genomic Characterization Identifies Molecular Subtypes of Lung Carcinoids

Lung carcinoids (LC) are rare and slow growing primary lung neuroendocrine tumors. We performed targeted exome sequencing, mRNA sequencing, and DNA methylation array analysis on macro-dissected LCs. Recurrent mutations were enriched for genes involved in covalent histone modification/chromatin remodeling (34.5%; MEN1, ARID1A, KMT2C, and KMT2A) as well as DNA repair (17.2%) pathways. Unsupervised clustering and principle component analysis on gene expression and DNA methylation profiles showed three robust molecular subtypes (LC1, LC2, LC3) with distinct clinical features. MEN1 gene mutations were found to be exclusively enriched in the LC2 subtype. LC1 and LC3 subtypes were predominately found at peripheral and endobronchial lung, respectively. The LC3 subtype was diagnosed at a younger age than LC1 and LC2 subtypes. IHC staining of two biomarkers, ASCL1 and S100, sufficiently stratified the three subtypes. This molecular classification of LCs into three subtypes may facilitate understanding of their molecular mechanisms and improve diagnosis and clinical management. SIGNIFICANCE: Integrative genomic analysis of lung carcinoids identifies three novel molecular subtypes with distinct clinical features and provides insight into their distinctive molecular signatures of tumorigenesis, diagnosis, and prognosis.

Systemic treatment for lung carcinoids: from bench to bedside

In the huge spectrum of lung neuroendocrine neoplasms, typical and atypical carcinoids should be considered as a separate biological entity from poorly differentiated forms, harboring peculiar molecular alterations. Despite their indolent behavior, lung carcinoids correlate with a worse survival. To date, only limited therapeutic options are available and novel drugs are strongly needed. In this work, we extensively reviewed scientific literature exploring available therapeutic options, new molecular targets and future perspectives in the management of well differentiated neoplasms of bronchopulmonary tree. Systemic therapy represents the main option in advanced and unresectable disease; accepted choices are somatostatin analogs, peptide receptor radionuclide therapy, everolimus and chemotherapy. To date, an univocal treatment strategy has not been identified yet, thus tailored therapeutic algorithms should consider treatment efficacy as well as safety profiles. Several molecular alterations found in carcinoid tumors might act as molecular targets leading to development of new therapeutic options. Further studies are necessary to identify new potential "druggable" molecular targets in the selected subset of low-grade lung carcinoids. Furthermore, evaluating the available therapies in more homogeneous population might improve their efficacy through a perfect tailoring of treatment options.

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.

Lung and Thymic Carcinoids

Carcinoids of the lung and thymus are rare thoracic cancers. In general, lung carcinoid tumors have a favorable prognosis, particularly when diagnosed at an early stage and treated with surgical resection. Thymic neuroendocrine tumors may be associated with multiple endocrine neoplasia-1 syndrome, tend to have a more aggressive natural history, and relatively frequently secrete ectopic adrenocorticotropic hormone.

Comparative evaluation of three proliferation markers, Ki-67, TOP2A, and RacGAP1, in bronchopulmonary neuroendocrine neoplasms: Issues and prospects

The classification of bronchopulmonary neuroendocrine neoplasms (BP-NEN) into four tumor entities (typical carcinoids (TC), atypical carcinoids (AC), small cell lung cancers (SCLC), large cell neuroendocrine lung carcinomas (LCNEC)) is difficult to perform accurately, but important for prognostic statements and therapeutic management decisions. In this regard, we compared the expression of three proliferation markers, Ki-67, Topoisomerase II alpha (TOP2A), and RacGAP1, in a series of tumor samples from 104 BP-NEN patients (24 TC, 21 AC, 52 SCLC, 7 LCNEC) using different evaluation methods (immunohistochemistry (IHC): Average evaluation, Hotspot evaluation, digital image analysis; RT-qPCR).

The results indicated that all three markers had increased protein and mRNA expression with poorer differentiation and correlated well with each other, as well as with grading, staging, and poor survival. Compared with Ki-67 and TOP2A, RacGAP1 allowed for a clearer prognostic statement. The cut-off limits obtained for Ki-67-Average (IHC) were TC-AC 1.5, AC-SCLC 19, and AC-LCNEC 23.5. The Hotspot evaluation generated equal to higher, the digital image analysis generally lower between-entity cut-off limits.

All three markers enabled a clear-cut differentiation between the BP-NEN entities, and all methods evaluated were suitable for marker assessment. However, to define optimal cut-off limits, the Ki-67 evaluation methods should be standardized. RacGAP1 appeared to be a new marker with great potential.

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.

Next-generation sequencing for endocrine cancers: Recent advances and challenges

Contemporary molecular biology research tools have enriched numerous areas of biomedical research that address challenging diseases, including endocrine cancers (pituitary, thyroid, parathyroid, adrenal, testicular, ovarian, and neuroendocrine cancers). These tools have placed several intriguing clues before the scientific community. Endocrine cancers pose a major challenge in health care and research despite considerable attempts by researchers to understand their etiology. Microarray analyses have provided gene signatures from many cells, tissues, and organs that can differentiate healthy states from diseased ones, and even show patterns that correlate with stages of a disease. Microarray data can also elucidate the responses of endocrine tumors to therapeutic treatments. The rapid progress in next-generation sequencing methods has overcome many of the initial challenges of these technologies, and their advantages over microarray techniques have enabled them to emerge as valuable aids for clinical research applications (prognosis, identification of drug targets, etc.). A comprehensive review describing the recent advances in next-generation sequencing methods and their application in the evaluation of endocrine and endocrine-related cancers is lacking. The main purpose of this review is to illustrate the concepts that collectively constitute our current view of the possibilities offered by next-generation sequencing technological platforms, challenges to relevant applications, and perspectives on the future of clinical genetic testing of patients with endocrine tumors. We focus on recent discoveries in the use of next-generation sequencing methods for clinical diagnosis of endocrine tumors in patients and conclude with a discussion on persisting challenges and future objectives.

Prognostic Significance of CD44 and Orthopedia Homeobox Protein (OTP) Expression in Pulmonary Carcinoid Tumours

CD44 and orthopedia homeobox protein (OTP) expressions have shown to be predictive of overall survival in pulmonary carcinoid (PC) tumours. The scope of the present study was to validate their role in PC patients and investigate potential application in clinical practice. Data was collected from patients presenting to a tertiary cancer centre diagnosed with PC between 2003 and 2015. Diagnosis was confirmed by central pathology review. Formalin-fixed paraffin-embedded (FFPE) tissue samples collected at diagnosis were scored using immunohistochemistry (H score) for standard CD44 and nuclear and cytoplasmic OTP protein expression. The study included 108 patients. High CD44/nuclear OTP (nOTP) expression was strongly associated with typical carcinoid (TC) histology (p < 0.001). Eighty-six patients, who underwent radical surgical resection, were selected to assess the impact of patient and tumour parameters on relapse-free survival (RFS). Sixty-nine (80 %) had TC and 17 (20 %) had atypical carcinoid tumours. On multivariate analysis, high CD44 and nOTP expression, TC histology and non-infiltrative tumour growth were associated with superior RFS. Early stage TC (stage pT1aN0) patients (N = 32; 46 %) had excellent prognosis irrespective of CD44/nOTP status. Importantly, TC patients with locally advanced disease (defined as >pT1aN0) and high CD44/nOTP expression (N = 26; 38 %) had excellent RFS (p = 0.005) compared to those with the same stage but low CD44 and/or nOTP (N = 11; 16 %). Additionally, the combination of CD44/nOTP expression and tumour growth pattern led to a more accurate prognostic system compared to the established WHO classification of PC tumours (concordance index = 0.902 vs 0.811, respectively, p < 0.001). Assessment of CD44/nOTP expression combined with tumour growth pattern identifies clear groups with largely different prognosis. These findings provide important information on how patients with these resected cancers should be followed up.

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 Diagnosis and Treatment of Bronchopulmonary Carcinoid

BACKGROUND

The spectrum of primary neuroendocrine tumors of the lungs ranges from typical carcinoid tumors, which are relatively benign, to highly aggressive small-cell carcinoma. In this review, we summarize the treatment of bronchopulmonary carcinoid, a disease with an incidence of 0.5 per 100,000 persons per year in Western countries.

METHOD

We selectively searched the PubMed database for scientific evidence on the treatment of bronchopulmonary carcinoid, considering only articles published up to February 2015. We also performed a survival analysis of 84 patients with this disease who underwent interdisciplinary treatment at the University of Freiburg Medical Center.

RESULTS

Carcinoid tumors account for less than 1% of all lung tumors. They manifest themselves clinically with cough (35%), hemoptysis (25%), and/or bronchial obstruction (40%), depending on their location, size, and pattern of growth. 30% of patients are asymptomatic, and less than 1% have hormone-associated symptoms. Typical and atypical carcinoid tumors are distinguished on a histological basis; the histologic differential diagnosis also includes large-cell neuroendocrine tumors and small-cell carcinoma of the lung. 80% of patients who undergo resection of typical carcinoid tumors survive at least 10 years. Atypical carcinoid tumors recur more commonly than typical ones. If the mediastinal lymph nodes are involved, adjuvant treatment should be considered.

CONCLUSION

Because of their rarity, the treatment of bronchopulmonary carcinoid tumors presents an interdisciplinary challenge. Surgical resection, the treatment of choice for local carcinoid tumors, generally leads to long-term survival. The existing registers should be made more comprehensive so that the treatment of this disease can be better in the future.

Neuroendocrine Tumors of the Lung: Current Challenges and Advances in the Diagnosis and Management of Well-Differentiated Disease

Neuroendocrine tumors (NETs) comprise a heterogeneous group of malignancies that arise from neuroendocrine cells throughout the body, most commonly originating from the lungs and gastrointestinal tract. Lung NETs can be classified as well differentiated (low-grade typical carcinoids [TCs] and intermediate-grade atypical carcinoids [ACs]) and poorly differentiated (high-grade large cell neuroendocrine carcinoma or SCLC). The incidence of these tumors is increasing, but disease awareness remains low among thoracic specialists, who are often involved in the diagnosis and early treatment for these patients. An accurate and timely diagnosis can ensure the implementation of appropriate treatment and have a substantial impact on prognosis. However, lung NET classification and diagnosis, particularly for TCs/ACs, are complicated by several factors, including a variable natural history and nonspecific symptoms. Surgery remains the only curative option for TCs/ACs, but there is a lack of consensus between lung NET management guidelines regarding optimal treatment approaches in the unresectable/metastatic setting on account of the limited availability of high-level clinical evidence. As a result, a multidisciplinary approach to management of lung NETs is required to ensure a consistent and optimal level of care. RADIANT-4 is the first phase III trial involving a large subpopulation of patients with advanced well-differentiated lung NETs to report reductions in the risk for disease progression and death with everolimus over placebo. This led to the recent U.S. approval of everolimus-the first agent approved for advanced lung TCs/ACs. To further improve evidence-based care, additional randomized controlled trials in patients with lung carcinoids are needed.

The impact of immunohistochemistry on the classification of lung tumors

INTRODUCTION

To highlight the role of immunohistochemistry to lung cancer classification on the basis of existing guidelines and future perspectives.

AREAS COVERED

Four orienting key-issues were structured according to an extensive review on the English literature: a) cancer subtyping; b) best biomarkers and rules to follow; c) negative and positive profiling; d) suggestions towards an evidence-based proposal for lung cancer subtyping. A sparing material approach based on a limited number of specific markers is highly desirable. It includes p40 for squamous cell carcinoma ('no p40, no squamous'), TTF1 for adenocarcinoma, synaptophysin for neuroendocrine tumors and vimentin for sarcomatoid carcinoma. A close relationship between genotype and phenotype also supports a diagnostic role for negative profiles. Expert commentary: Highly specific and sensitive IHC markers according to positive and negative diagnostic algorithms seem appropriate for individual patients' lung cancer subtyping.

Diagnosis and management of typical and atypical lung carcinoids

An estimated 20% to 30% of all neuroendocrine tumours originate in the bronchial tree and lungs. According to the 2015 World Health Organization categorization, these tumours are separated into four subtypes characterized by increasing biological aggressiveness: typical carcinoid, atypical carcinoid, large-cell neuroendocrine carcinoma and small-cell carcinoma. Although typical and atypical lung carcinoids account for less than 1-5% of all pulmonary malignancies, the incidence of these neoplasms has risen significantly in recent decades. Surgery is the treatment of choice for loco-regional disease but for advanced lung carcinoids there is no recognized standard of care and successful management requires a multidisciplinary approach. The aim of this review is to provide a useful guide for the clinical management of lung carcinoids.

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.

Somatostatin receptors in bronchopulmonary neuroendocrine neoplasms: new diagnostic, prognostic, and therapeutic markers

CONTEXT AND OBJECTIVES

Gastroenteropancreatic neuroendocrine neoplasms are known for their overexpression of somatostatin receptors (SSTRs), which provide the molecular basis for diagnostic and therapeutic interventions. In contrast, few data on the SSTR expression profile exist for bronchopulmonary neuroendocrine neoplasms (BP-NEN).

DESIGN AND SETTINGS

A total of 240 formalin-fixed, paraffin-embedded specimens from 26 typical carcinoid (TC), 30 atypical carcinoid (AC), and 34 small cell lung cancer (SCLC) patients were examined retrospectively by immunohistochemistry (IHC) using specific rabbit monoclonal antibodies and evaluated by the immunoreactive score. Adjacent slides from 20 samples of each tumor type were subjected to additional RT-quantitative PCR mRNA analysis.

RESULTS

With different expression patterns, SSTRs were present in most of the tumor sections, at both the protein and mRNA levels. The RT-quantitative PCR data correlated with the IHC scores. SSTR1 was detected in approximately 65% of the TC and AC, but hardly in the SCLC, whereas both SSTR2A and SSTR5 were present in approximately 45% of each entity. Furthermore, the SSTR1 expression level was positively correlated with patient survival.

CONCLUSIONS

Our results suggest that SSTRs can be used as novel diagnostic, prognostic, and therapeutic markers of BP-NEN. The differences in the SSTR expression profile between the three types of BP-NEN may help to set a diagnostic cutoff and predict patient prognosis. Similar to TC and AC, our results also revealed a previously unappreciated high level of SSTR2A expression in SCLC within a subgroup of patients. However, in most cases, pan-somatostatin analogs may represent an additional therapeutic option.

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).

Therapeutic biomarkers in lung neuroendocrine neoplasia

The well-known classification of neuroendocrine neoplasms of the lung into four major subtypes (including typical and atypical carcinoids and small- and large-cell neuroendocrine carcinomas) has a proven prognostic validity but only partially helps to predict the response to specific therapies. Therapeutic biomarkers are incompletely known and include morphological, immunophenotypic, and molecular markers. Morphology alone has no specific predictive role, nor has any immunophenotypic marker been proven to bear predictive implications. Ki67 is a relevant prognostic marker and can indirectly predict response to chemotherapy, when levels are extremely high in high-grade neuroendocrine (NE) carcinomas. The expression of somatostatin receptors, especially of the type 2A, has been shown to predict response to somatostatin analog treatments, paralleling the information derived from octreotide scintigraphy. mTOR pathway is targeted by specific inhibitors, but the exact cellular molecules predicting response are still to be defined. It seems that high levels of phosphorylated forms of mTOR and of its downstream factor S6K are associated to a better response to rapalogs in experimental models. Data from gene expression profiling and mutational analyses are currently emerging, providing a more detailed map of different molecular activation pathways, potentially leading to a more accurate molecular classification of lung NE tumors as well as to the discovery of new therapeutic targets. The combination of mutational profiles with those of upregulated or downregulated genes also by gene gains or losses may ultimately provide a better characterization of NE tumor histological types in terms of response to specific chemotherapy or biotherapy.