神经内分泌肿瘤（NETs）的早期诊断是一个临床挑战，需要对这一异质性肿瘤群体的分子和遗传特征有深入的了解。然而，很少有生物标志物可用于辅助诊断，并预测预后和治疗反应。在肿瘤学领域，肿瘤教育血小板（TEPs）被认为是对肿瘤生长的全身和局部反应中的核心参与者，从而改变肿瘤特异性RNA谱。尽管发现TEPs富含RNA，但很少有研究调查了一种RNA类型，即循环RNA（circRNA），作为癌症的血小板衍生生物标志物的潜力。在这项概念验证研究中，我们旨在证明是否可以将肿瘤教育血小板的circRNA特征作为液体活检生物标志物用于胃肠胰（GEP）-NETs的检测和早期治疗反应的预测。我们进行了一项为期24个月的前瞻性概念验证研究，纳入了年龄在18-80岁之间且有组织学证实的良性分化G1-G2 GEP-NET患者，未接受过治疗。我们对10名GEP-NET患者的基线样本和治疗后3个月（生长抑素类似物或手术）的血小板教育血小板样本进行了circRNA的RNA测序分析，并对5名患有非恶性内分泌疾病的患者作为对照组。基于p < 0.05的统计分析结果表明，鉴定出252个circRNA在GEP-NET和对照组之间差异表达，其中109个在NET患者中上调，143个下调。基于FDR值≤0.05的进一步分析选择了5个circRNA，均高度显著下调。对5名患者的GEP-NET在基线和治疗后进行同样的分析，发现了平均4983个差异显著的circRNA，其中2648个上调，2334个下调。应用p≤0.05和FDR≤0.05的筛选条件，只有3/5个比较给出了统计学显著的结果。我们的研究首次发现了TEPs的circRNA特征作为GEP-NETs的潜在诊断和预测生物标志物。 © 2023. 生物医学中央有限公司，施普林格自然出版集团的一部分。

Neuroendocrine tumors (NETs) early diagnosis is a clinical challenge that require a deep understanding of molecular and genetic features of this heterogeneous group of neoplasms. However, few biomarkers exist to aid diagnosis and to predict prognosis and treatment response. In the oncological field, tumor-educated platelets (TEPs) have been implicated as central players in the systemic and local responses to tumor growth, thereby altering tumor specific RNA profile. Although TEPs have been found to be enriched in RNAs, few studies have investigated the potential of a type of RNA, circular RNAs (circRNA), as platelet-derived biomarkers for cancer. In this proof-of-concept study, we aim to demonstrate whether the circRNAs signature of tumor educated platelets can be used as a liquid biopsy biomarker for the detection of gastroenteropancreatic (GEP)-NETs and the prediction of the early response to treatment.We performed a 24-months, prospective proof-of-concept study in men and women with histologically proven well-differentiated G1-G2 GEP-NET, aged 18-80 years, naïve to treatment. We performed a RNAseq analysis of circRNAs obtained from TEPs samples of 10 GEP-NETs patients at baseline and after 3 months from therapy (somatostatin analogs or surgery) and from 5 patients affected by non-malignant endocrinological diseases enrolled as a control group.Statistical analysis based on p < 0.05 resulted in the identification of 252 circRNAs differentially expressed between GEP-NET and controls of which 109 were up-regulated and 143 were down-regulated in NET patients. Further analysis based on an FDR value ≤ 0.05 resulted in the selection of 5 circRNAs all highly significant downregulated. The same analysis on GEP-NETs at baseline and after therapy in 5 patients revealed an average of 4983 remarkably differentially expressed circRNAs between follow-up and baseline samples of which 2648 up-regulated and 2334 down-regulated, respectively. Applying p ≤ 0.05 and FDR ≤ 0.05 filters, only 3/5 comparisons gave statistically significant results.Our findings identified for the first time a circRNAs signature from TEPs as potential diagnostic and predictive biomarkers for GEP-NETs.© 2023. BioMed Central Ltd., part of Springer Nature.