Purpose: to collect data from real-life experiences of the management of type 3 g-NETs and identify possible prognostic factors that may impact the decision-making process. Methods: We performed a systematic review of the literature on type 3 g-NET management using the PubMed, MEDLINE, and Embase databases. We included cohort studies, case series, and case reports written in the English language. Results: We selected 31 out of 556 articles from between 2001 and 2022. In 2 out of the 31 studies, a 10 mm and 20 mm cut-off size were respectively associated with a higher risk of gastric wall infiltration and/or lymph node and distant metastasis at diagnosis. The selected studies reported a higher risk of lymph node or distant metastasis at diagnosis in the case of muscularis propria infiltration or beyond, irrespective of the dimensions or grading. From these findings, size, grading, and gastric wall infiltration seem to be the most relevant factors in management staff making choices and prognoses of type 3 g-NET patients. We produced a hypothetical flowchart for a standardized approach to these rare diseases. Conclusion: Further prospective analyses are needed to validate the prognostic impact of the use of size, grading, and gastric wall infiltration as prognostic factors in the management of type 3 g-NETs.

Carcinoid syndrome (CS), mostly associated with small intestinal neuroendocrine tumors (SI-NETs) or lung-related NETs, is characterized by symptoms related to hormonal secretion and long-term complications, including carcinoid heart disease (CHD), which is potentially life-threatening. In the early stages of the disease, symptoms are non-specific, which leads to delayed diagnoses. The availability of reliable tumor markers is crucial for a prompt diagnosis and proper management. This review summarizes available evidence on the role of 24 h urinary 5-hydroxyindolacetic acid (24u5HIAA), which is the urinary breakdown metabolite of serotonin, in the diagnosis/follow-up of NET-related CS, with a focus on its potential prognostic role, while eventually attempting to suggest a timeline for its measurement during the follow-up of NET patients. The use of 24u5HIAA is an established biomarker for the diagnosis of NETs with CS since it shows a sensibility and specificity of 100% and 85–90%, respectively. The downside of 24u5-HIAA is represented by the need for 24 h urine collection and the risk of confounding factors (foods and medication), which might lead to false positive/negative results. Moreover, 24u5HIAA is useful in the follow-up of NETs with CS since a shorter double time correlates to a higher risk of disease progression/disease-specific mortality. Furthermore, an elevation in 24u5-HIAA is correlated with a dismal prognosis because it is associated with an increased likelihood of CHD development and disease progression/mortality. Other potentially interesting biochemical markers have been proposed, including plasmatic 5HIAA, although further standardization and prospective studies are required to define their role in the management of NETs. Meanwhile, 24u5HIAA remains the most accurate CS biomarker.

Background: The success of targeted therapies in the treatment of pancreatic neuroendocrine tumors has emphasized the strategy of targeting angiogenesis and the PI3K/AKT/mTOR pathway. However, the major challenge in the targeted era remains the early identification of resistant tumors especially when the efficacy is rarely associated to a clear tumor shrinkage at by imaging assessment. Methods: In this prospective study (NCT02305810) we investigated the predictive and prognostic role of soluble biomarkers of angiogenesis turnover (VEGF, bFGF, VEGFR2, TSP-1) circulating endothelial cells and progenitors, in 43 patients with metastatic panNET receiving everolimus. Results: Among all tested biomarkers, we found a specific subpopulation of circulating cells, CD31+CD140b-, with a significantly increased tumor progression hazard for values less or equal to the first quartile. Conclusion: Our study suggested the evidence that circulating cells might be surrogate biomarkers of angiogenesis activity in patients treated with everolimus and their baseline levels can be correlated with survival. However, further studies are now needed to validate the role of these cells as surrogate markers for the selection of patients to be candidates for antiangiogenic treatments.

Merkel cell carcinoma (MCC) is a very rare and aggressive neuroendocrine carcinoma originating from Merkel cells, typically with a skin nodule; however, it exceptionally presents with only a basin lymph node localization, with neither a cutaneous primary site nor distant metastases. From 1996 to 2020, among patients with histologically confirmed MCC managed at a neuroendocrine neoplasm-referral center, we selected those with an exclusive nodal basin, no distant metastasis, and an unknown primary site defined by cross-sectional and physical examination. A total of 55 out of 310 patients fulfilled the selection criteria. The median age was 64 years and the majority were males. Inguinal lymph-nodes were the most common anatomic site. With a median follow-up of 4.3 years, the 5-year relapse-free survival (RFS) rate was 56.6 (95% CI 42.0–68.8%) and the 5-year cancer specific survival (CSS) rate was 68.5 (95% CI 52.8–79.9%) for the whole population. The 36 patients (65.5%) undergoing lymphadenectomy (LND) + radiotherapy (RT) ± chemotherapy had a 5-year RFS rate of 87.2% (95% CI 65.5–95.7%) and a 5-year CSS rate of 90.5% (95% CI 67.0–97.5), which were better than those receiving LND alone. In a multivariable analysis, the survival benefit for LND + RT remained significant. Results from one of the largest single-center series of nMCC-UP suggest that a curative approach including RT can be effective, similar to what is observed for stage IIIB MCC. Multicentric studies with homogenous populations should be carried out in this controversial clinical entity, to minimize the risk of biases and provide robust data.

Mesenchymal tumors originate from mesenchymal cells and can be either benign or malignant, such as bone, soft tissue, and visceral sarcomas. Surgery is a cornerstone treatment in the management of mesenchymal tumors, often requiring complex procedures performed in high-volume referral centers. However, the COVID-19 pandemic has highlighted this need for alternative non-surgical approaches due to limited access to surgical resources. This review explores the role of non-surgical treatments in different clinical scenarios: for improving surgical outcomes, as a bridge to surgery, as better alternatives to surgery, and for non-curative treatment when surgery is not feasible. We discuss the effectiveness of active surveillance, cryoablation, high-intensity focused ultrasound, and other ablative techniques in managing these tumors. Additionally, we examine the use of tyrosine kinase inhibitors in gastrointestinal stromal tumors and hypofractionated radiotherapy in soft tissue sarcomas. The Sarculator tool is highlighted for its role in stratifying high-risk sarcoma patients and personalizing treatment plans. While surgery remains the mainstay of treatment, integrating advanced non-surgical strategies can enhance therapeutic possibilities and patient care, especially in specific clinical settings with limitations. A multidisciplinary approach in referral centers is vital to determine the optimal treatment course for each patient.

The application of machine learning (ML) techniques could facilitate the identification of predictive biomarkers of somatostatin analog (SSA) efficacy in patients with neuroendocrine tumors (NETs). We collected data from 74 patients with a pancreatic or gastrointestinal NET who received SSA as first-line therapy. We developed three classification models to predict whether the patient would experience a progressive disease (PD) after 12 or 18 months based on clinic-pathological factors at the baseline. The dataset included 70 samples and 15 features. We initially developed three classification models with accuracy ranging from 55% to 70%. We then compared ten different ML algorithms. In all but one case, the performance of the Multinomial Naïve Bayes algorithm (80%) was the highest. The support vector machine classifier (SVC) had a higher performance for the recall metric of the progression-free outcome (97% vs. 94%). Overall, for the first time, we documented that the factors that mainly influenced progression-free survival (PFS) included age, the number of metastatic sites and the primary site. In addition, the following factors were also isolated as important: adverse events G3–G4, sex, Ki67, metastatic site (liver), functioning NET, the primary site and the stage. In patients with advanced NETs, ML provides a predictive model that could potentially be used to differentiate prognostic groups and to identify patients for whom SSA therapy as a single agent may not be sufficient to achieve a long-lasting PFS.