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.

The Surgical Management of Lung Neuroendocrine Neoplasms.

This review summarizes key recent developments relevant to the surgical management of lung neuroendocrine neoplasms (L-NENs), including typical and atypical carcinoids, large cell neuroendocrine carcinoma, and small cell lung carcinoma. This review includes recent insights into the classification, clinical presentation, diagnostic workup, treatment options, and follow-up. Highlighted topics include general principles of surgery in localized or locally advanced or metastatic L-NENs, lung-sparing surgery for small, peripheral typical carcinoids, adjuvant and systemic therapies for typical and atypical carcinoids, and surgery and adjuvant therapies for large cell neuroendocrine carcinoma and small cell lung carcinoma.

Neuroendocrine tumor G3 of bronchopulmonary origin and its classification.

Neuroendocrine tumors (NET) with high proliferative activity (Ki-67 index >20% and/or mitotic counts >2 mm2 ) are defined as NET G3 in the 2019 World Health Organization (WHO) classification of digestive system neuroendocrine neoplasms (NENs). NETs G3 occur mostly in the pancreas, colon, rectum, and stomach and only rarely in the small intestine and the appendix. In the bronchopulmonary system, similar tumors have also been recognized and were mostly classified as atypical carcinoid (AC) or large cell neuroendocrine carcinoma. Bronchopulmonary NENs that were classified as NETs G3 are characterized by histological and immunohistochemical similarities with carcinoids/NETs, and a clinical course that is more aggressive than with ACs and similar to that of neuroendocrine carcinomas. The morphomolecular and clinical features of bronchopulmonary neoplasms with a high proliferative activity were reviewed and a future classification system that is applicable for both digestive and bronchopulmonary NETs is proposed.

Epidemiological analysis of lung and mediastinal neuroendocrine neoplasms in Japan based on the national database.

BACKGROUND: Neuroendocrine neoplasms (NENs) are rare and can originate from any body part. However, there are only few epidemiological studies, especially on lung and mediastinal NENs. This study investigated the epidemiological trends and differences between lung and mediastinal NENs in Japan. METHODS: Patients with lung and mediastinal NENs were identified in a national hospital-based cancer registry between 2009 and 2015 in Japan. NENs were subclassified into neuroendocrine tumors (NETs) and neuroendocrine carcinomas (NECs). NECs were further subdivided into large neuroendocrine carcinomas (LCNECs) and small cell carcinomas (SCCs). We examined the patient characteristics: sex, age, histology, year of diagnosis, diagnostic opportunity, and initial treatment. RESULTS: We identified 48,433 patients with 47,888 lung (98.9%) and 545 mediastinal (1.1%) NENs. The commonest subtype of lung NENs was SCCs (87%), followed by LCNECs (10%) and NETs (3%). In the mediastinum, SCCs were also the commonest (48%), followed by NETs (38%) and LCNECs (14%). The number of lung NEN annually increased; however, that of mediastinal NENs did not change over time. The mean age of patients with lung NETs was lower than that of patients with lung LCNECs and SCCs (NETs, 62 ± 14 years; LCNECs, 70 ± 9 years; SCCs, 71 ± 9 years; p < .001). The lung and mediastinal NENs were mainly detected based on symptoms, except for lung NETs. Surgical intervention, including multimodal therapy, was performed for 89.3% of lung NETs (surgery alone: 83.6%), while only 15.6% of lung NECs were treated with surgery. For the mediastinum, 75.9% of NETs were treated with surgery, with 27.1% of cases treated with surgery plus multimodal therapy. Surgery was performed more frequently for mediastinal NECs (37%) than for lung NECs (15.6%). CONCLUSIONS: This study highlights differences in trends of lung and mediastinal NENs. This study's findings support the importance of epidemiological evaluations based on the primary sites and histological subtypes.

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

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.

Preclinical evaluation of [225Ac]Ac-DOTA-TATE for treatment of lung neuroendocrine neoplasms.

PURPOSE: There is significant interest in the development of targeted alpha-particle therapies (TATs) for treatment of solid tumors. The metal chelator-peptide conjugate, DOTA-TATE, loaded with the ß-particle emitting radionuclide 177Lu ([177Lu]Lu-DOTA-TATE) is now standard care for neuroendocrine tumors that express the somatostatin receptor 2 (SSTR2) target. A recent clinical study demonstrated efficacy of the corresponding [225Ac]Ac-DOTA-TATE in patients that were refractory to [177Lu]Lu-DOTA-TATE. Herein, we report the radiosynthesis, toxicity, biodistribution (BD), radiation dosimetry (RD), and efficacy of [225Ac]Ac-DOTA-TATE in small animal models of lung neuroendocrine neoplasms (NENs). METHODS: [225Ac]Ac-DOTA-TATE was synthesized and characterized for radiochemical yield, purity and stability. Non-tumor-bearing BALB/c mice were tested for toxicity and BD. Efficacy was determined by single intravenous injection of [225Ac]Ac-DOTA-TATE into SCID mice-bearing human SSTR2 positive H727 and H69 lung NENs. RD was calculated using the BD data. RESULTS: [225Ac]Ac-DOTA-TATE was synthesized with 98% yield, 99.8% purity, and displayed 97% stability after 2 days incubation in human serum at 37 °C. All animals in the toxicity study appeared healthy 5 months post injection with no indications of toxicity, except that animals that received ≥111 kBq of [225Ac]Ac-DOTA-TATE had chronic progressive nephropathy. BD studies revealed that the primary route of elimination is by the renal route. RD calculations determined pharmacokinetics parameters and absorbed α-emission dosages from 225Ac and its daughters. For both tumor models, a significant tumor growth delay and time to experimental endpoint were observed following a single administration of [225Ac]Ac-DOTA-TATE relative to controls. CONCLUSIONS: These results suggest significant potential for the clinical translation of [225Ac]Ac-DOTA-TATE for lung NENs.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) with confirmed liver metastases negative on 18F-FDG and 68Ga-DOTATATE PET.

Lung neuroendocrine neoplasms (NENs) encompass the low-, intermediate-, and high-grade entities. Differentiated NENs overexpress somatostatin receptors, which are targeted by 68Ga-DOTA-conjugated peptides in molecular imaging with positron emission tomography. Less differentiated NENs may have lost their expression of somatostatin receptors and thus show lower uptake of 68Ga-DOTA-peptides; however, these tumors express GLUT-1 and can be imaged with (18)F-fluordeoxyglucose (FDG). We report the case of a 72-year-old patient with a poorly differentiated, high grade lung NEN, which was 18F-FDG-positive at initial diagnosis. After treatment and remission, the patient had histologically confirmed relapse in the liver. Interestingly, these hepatic metastases did not demonstrated radiopharmaceutical uptake at neither 18F-FDG nor 68Ga-DOTATATE positron emission tomography/computed tomography.

Classifying Lung Neuroendocrine Neoplasms through MicroRNA Sequence Data Mining.

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

Advances on systemic treatment for lung neuroendocrine neoplasms.

Lung well-to-moderately differentiated neuroendocrine tumors (also known as carcinoids) and large cell neuroendocrine lung carcinoma (poorly differentiated neuroendocrine tumor) are rare neuroendocrine neoplasms, which account for less than 4% of all lung neoplasms. Due to their low incidence, their systemic treatment is greatly influenced by therapeutic evidence derived from the more frequent gastroenteropancreatic neuroendocrine neoplasms and/or small cell lung carcinoma leading to significant bias. Currently, employed systemic therapies for lung carcinoids, aiming at controlling tumor growth include long acting somatostatin analogues (SSAs), peptide receptor radionuclide therapy, chemotherapy and molecular-targeted therapy. In this review, each of those treatments is presented based upon available clinical evidence from retrospective and prospective studies particularly focused on the role of everolimus in the advanced setting and on ongoing clinical trials reflecting our expectations in the near future. In addition, we critically analyse currently employed treatment of large cell neuroendocrine carcinoma where the appropriate chemotherapeutic regimen is still a matter of debate.

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.