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

Molecular Classification of Gastrointestinal and Pancreatic Neuroendocrine Neoplasms: Are We Ready for That?

In the last two decades, the increasing availability of technologies for molecular analyses has allowed an insight in the genomic alterations of neuroendocrine neoplasms (NEN) of the gastrointestinal tract and pancreas. This knowledge has confirmed, supported, and informed the pathological classification of NEN, clarifying the differences between neuroendocrine carcinomas (NEC) and neuroendocrine tumors (NET) and helping to define the G3 NET category. At the same time, the identification genomic alterations, in terms of gene mutation, structural abnormalities, and epigenetic changes differentially involved in the pathogenesis of NEC and NET has identified potential molecular targets for precision therapy. This review critically recapitulates the available molecular features of digestive NEC and NET, highlighting their correlates with pathological aspects and clinical characteristics of these neoplasms and revising their role as predictive biomarkers for targeted therapy. In this context, the feasibility and applicability of a molecular classification of gastrointestinal and pancreatic NEN will be explored.

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 Thresholds of Mitotic Count and Ki-67 Labeling Index for Recurrence and Survival in Lung Atypical Carcinoids

Atypical carcinoid (AC) is a rare neuroendocrine neoplasm of the lung, which exhibits a varying malignant potential. In this study, we aimed to identify the prognostic thresholds of the mitotic count and Ki-67 labeling index for recurrence and survival in AC. We retrospectively reviewed 78 patients who had been radically resected for AC and calculated said thresholds using time-dependent receiver operating characteristic curves and the Youden index. We then dichotomized the patients into groups of above or below these thresholds and estimated the cumulative incidences of the groups using the Aalen-Johansen estimator. We compared the groups using univariable and multivariable Fine-Gray subdistribution hazard models. Our findings show that more patients recurred and died from this disease if their mitotic count exceeded three and four mitoses per 2 mm2, respectively, or if their Ki-67 labeling index exceeded 14% and 11%, respectively. Both thresholds independently predicted survival (p < 0.001 and p = 0.015, respectively). These thresholds may serve as a valuable tool for clinicians and researchers in making treatment plans and predicting outcomes for patients with AC.

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.

Diagnostic Approaches to Neuroendocrine Neoplasms of Unknown Primary Site

ABSTRACT

Neuroendocrine tumors (NETs) are relatively uncommon heterogeneous neoplasms arising from endocrine and neuronal origin cells showing highly variable clinical behavior. By the time these tumors are discovered, up to 14% of patients with histologically proven NETs have metastasis, with the liver as the most frequently affected organ. Sometimes, no known primary site can be identified via routine imaging. Neuroendocrine tumors of unknown origin carry a poorer prognosis (compared with metastatic NETs with a known primary site) because of a lack of tailored surgical intervention and appropriate medical therapy (eg, chemotherapy or targeted therapy). A multimethod approach is frequently used in the trial to accurately determine the primary site for NETs of unknown primary sites and may include clinical, laboratory, radiological, histopathological, and surgical data. New molecular techniques using the genomic approach to identify the molecular signature have shown promising results. Various imaging modalities include ultrasound, computed tomography (CT), dual-energy CT, magnetic resonance imaging, and functional and hybrid imaging (positron emission tomography/CT, positron emission tomography/magnetic resonance imaging); somatostatin receptor imaging with new tracers is frequently used in an attempt for localization of the primary site.

Distribution of gastrointestinal neuroendocrine tumors in Europe: results from a retrospective cross-sectional study

BACKGROUND

Gastrointestinal (non-pancreatic) neuroendocrine tumors (GI-NETs) represent a rare but increasingly common tumor entity. Prognosis and biological behavior of these tumors is extremely heterogenous and largely dependent on the specific tumor site, stage and differentiation. However, systematic data on the epidemiology of GI-NET, especially in terms of geographic distributions are missing.

METHODS

We used the Oncology Dynamics database (IQVIA) to identify a total of 1354 patients with GI-NET from four European countries (Germany, France, Spain, UK) and compared them with regard to major patient and tumor related characteristics including patients' age, sex, tumor stage, tumor grading and differentiation.

RESULTS

Out of the analyzed 1354 NET patients, 535 were found in the UK (39.5%), 289 in Germany (21.3%), 283 in Spain (20.9%) and 247 in France (18.2%). More patients were male than female (53.8% vs. 46.2%) with no significant differences between the analyzed countries. In contrast, the age distribution varied between the different countries, with the highest number of patients identified in the age groups of 61-70 years (31.0%) and 71-80 years (30.7%). The vast majority of patients showed a tumor origin in the small intestine, in German patients NET of the large intestine were slightly overrepresented and NET of the stomach underrepresented compared to all other countries. More than 80% of patients had stage IV disease at the time of diagnosis. Regarding tumor histology, most tumors showed a G2 tumor; interestingly, a G3 grading was found in 40.9% of patients in Germany (Ki-67 > 20%).

CONCLUSION

The distribution of important patient- and tumor-specific characteristics of neuroendocrine tumors shows regional differences in four major European countries. These data may help to better understand the specific epidemiology of GI-NET in Europe.

Diagnostic, Prognostic, and Predictive Role of Ki67 Proliferative Index in Neuroendocrine and Endocrine Neoplasms: Past, Present, and Future

The introduction of Ki67 immunohistochemistry in the work-up of neuroendocrine neoplasms (NENs) has opened a new approach for their diagnosis and prognostic evaluation. Since the first demonstration of the prognostic role of Ki67 proliferative index in pancreatic NENs in 1996, several studies have been performed to explore its prognostic, diagnostic, and predictive role in other neuroendocrine and endocrine neoplasms. A large amount of information is now available and published results globally indicate that Ki67 proliferative index is useful to this scope, although some differences exist in relation to tumor site and type. In gut and pancreatic NENs, the Ki67 proliferative index has a well-documented and accepted diagnostic and prognostic role and its evaluation is mandatory in their diagnostic work-up. In the lung, the Ki67 index is recommended for the diagnosis of NENs on biopsy specimens, but its diagnostic role in surgical specimens still remains to be officially accepted, although its prognostic role is now well documented. In other organs, such as the pituitary, parathyroid, thyroid (follicular cell-derived neoplasms), and adrenal medulla, the Ki67 index does not play a diagnostic role and its prognostic value still remains a controversial issue. In medullary thyroid carcinoma, the Ki67 labelling index is used to define the tumor grade together with other morphological parameters, while in the adrenal cortical carcinoma, it is useful to select patients to treated with mitotane therapy. In the present review, the most important information on the diagnostic, prognostic, and predictive role of Ki67 proliferative index is presented discussing the current knowledge. In addition, technical issues related to the evaluation of Ki67 proliferative index and the future perspectives of the application of Ki67 immunostaining in endocrine and neuroendocrine neoplasms is discussed.

Lung carcinoid tumours: histology and Ki-67, the eternal rivalry

WHO classification of Thoracic Tumours defines lung carcinoid tumours (LCTs) as well-differentiated neuroendocrine neoplasms (NENs) classified in low grade typical (TC) and intermediate grade atypical carcinoids (AC). Limited data exist concerning protein expression and morphologic factors able to predict disease aggressiveness. Though Ki-67 has proved to be a powerful diagnostic and prognostic factor for Gastro-entero-pancreatic NENs, its role in lung NENs is still debated. A retrospective series of 370 LCT from two oncology centers was centrally reviewed. Morphology and immunohistochemical markers (Ki-67, TTF-1, CD44, OTP, SSTR-2A, Ascl1, and p53) were studied and correlated with Overall Survival (OS), Cancer-specific survival (CSS) and Disease-free survival (DFS). Carcinoid histology was confirmed in 355 patients: 297 (83.7%) TC and 58 (16.3%) AC. Ki-67 at 3% was the best value in predicting DFS. Ki-67 ≥ 3% tumours were significantly associated with AC histology, stage III-IV, smoking, vascular invasion, tumour spread through air spaces OTP negativity, and TTF-1, Ascl1 and p53 positivity. After adjustment for center and period of diagnosis, both Ki-67 (≥3 versus <3) and histology (AC versus TC) alone significantly added prognostic information to OS and CSS multivariable model with age, stage and OTP; addition of both variables did not provide further prognostic information. Conversely, an improved significance of the DFS prediction model at multivariate analysis was seen by adding Ki-67 (≥3 versus <3, P adj = 0.01) to TC and AC histological distinction, age, lymph node involvement, residual tumour and OTP. Ki-67 ≥ 3% plays a potentially pivotal role in LCT prognosis, irrespective of histological grade.

Rarest of rare cases within the one thousand faces of atypical carcinoid: Pseudomesotheliomatous manifestation in a pregnant woman

Carcinoid tumors in pregnant women are rare, and there have been no previous studies of atypical carcinoid tumor reported in pregnancy. Also, pseudomesotheliomatous manifestation in atypical carcinoid is an extremely rare finding, there being only two cases reported. Here, we present the first case of pseudomesotheliomatous manifestation of atypical carcinoid in a pregnant woman. Upon image analysis, we found that atypical carcinoids with multiple metastatic lesions can exhibit variability in vascularity and metabolism, resulting in heterogeneous image characteristics among metastatic lesions, even those with identical histology. In addition, even with extensive metastasis, patients can exhibit good performance explained by long-standing presentation of indolent cancer.