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ObjectivesKi-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 methodsMedline (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.ResultsOf 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).ConclusionThis 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 numberCRD42018093389.

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., SCOPUS: ar.j, info:eu-repo/semantics/published

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.

Introduction: Neuroendocrine tumours (NETs) are rare tumours with an increasing incidence. While low- and intermediate-grade pancreatic NET (PanNET) and small intestinal NET (siNET) are slow growing, they have a relatively high rate of metastasizing to the liver, leading to substantially worse outcomes. In many solid tumours, the outcome is determined by the quality of the antitumour immune response. However, the quality and significance of antitumour responses in NETs are incompletely understood. This study provides clinico-pathological analyses of the tumour immune microenvironment in PanNET and siNETs. Methods: Formalin-fixed paraffin-embedded tissue from consecutive resected PanNETs (61) and siNETs (131) was used to construct tissue microarrays (TMAs); 1-mm cores were taken from the tumour centre, stroma, tumour edge, and adjacent healthy tissue. TMAs were stained with antibodies against CD8, CD4, CD68, FoxP3, CD20, and NCR1. T-cell counts were compared with counts from lung cancers. Results: For PanNET, median counts were CD8+ 35.4 cells/mm2, CD4+ 7.6 cells/mm2, and CD68+ macrophages 117.7 cells/mm2. For siNET, there were CD8+ 39.2 cells/mm2, CD4+ 24.1 cells/mm2, and CD68+ 139.2 cells/mm2. The CD8+ cell density in the tumour and liver metastases were significantly lower than in the adjacent normal tissues, without evidence of a cell-rich area at the tumour edge that might have suggested immune exclusion. T-cell counts in lung cancer were significantly higher than those in PanNET and siNETs: CD8+ 541 cells/mm2 and CD4+ 861 cells/mm2 (p ≤ 0.0001). Conclusion: PanNETs and siNETs are immune cold with no evidence of T cell exclusion; the low density of immune infiltrates indicates poor antitumour immune responses.

IntroductionThe 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.MethodsThis 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 disseminationEthical 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 numberCRD42018093389