Ciobanu Oana A, Herlea Vlad, Milanesi Elena, Dobre Maria, Fica Simona
Department of Endocrinology and Diabetes, Elias Hospital, Bucharest, Romania.
Department of Endocrinology and Diabetes, Nutrition and Metabolic Diseases, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Sci Prog. 2025 Jan-Mar;108(1):368504251326864. doi: 10.1177/00368504251326864. Epub 2025 Mar 28.
Our understanding of the pathophysiology of pancreatic neuroendocrine tumors (PanNETs) remains incomplete, largely due to their historically underestimated incidence and the perception of these tumors as rare and slow-growing cancers. Additionally, conventional reliance on histological examination alone is gradually being supplemented by the exploration and introduction of molecular biomarkers, such as microRNAs (miRNAs). As miRNAs modulate the expression of multiple genes and pathways involved in the tumorigenesis of PanNETs, these biomarkers hold considerable promise for diagnosis and prognosis applications. In this study, we aimed to identify miRNAs as tissue markers associated with the diagnosis of PanNETs.
We conducted a case-control study including: 7 PanNETs and 19 nontumoral pancreatic tissues obtained from Romanian patients. The samples underwent miRNA profiling via quantitative RT-PCR to assess the expression of 84 miRNAs. Our results were compared with those obtained by reanalyzing a public dataset. Furthermore, we structured our miRNA expression data according to their targeted mRNAs and their roles in signaling pathways.
Fourteen miRNAs (miR-1, miR-133a-3p, miR-210-3p, miR-7-5p, miR-10a-5p, miR-92b-3p, miR-132-3p, miR-221-3p, miR-29b-3p, miR-107, miR-103a-3p, let-7b-5p, miR-148a-3p, and miR-202-3p) were identified as differentially expressed by comparing PanNETs with pancreatic nontumoral tissues, with six miRNAs (miR-7-5p, miR-92b-3p, miR-29b-3p, miR-107, miR-103a-3p, and miR-148a-3p) also found in the public dataset analyzed. Bioinformatic analysis revealed that the 14 identified miRNAs target 17 genes. Reanalyzing two public gene expression datasets, five of these genes have been found differentially expressed in PanNET compared to controls.
Our preliminary results, albeit limited by a small sample size, highlighted a specific miRNA expression pattern able to distinguish tumoral from normal pancreatic tissue. The diagnostic performance of these miRNAs, matching with circulating miRNAs and validated in more homogeneous and large cohorts, could represent a starting point for improving the diagnostic accuracy of PanNETs.
我们对胰腺神经内分泌肿瘤（PanNETs）病理生理学的理解仍不完整，这主要是由于其发病率在历史上被低估，以及这些肿瘤被视为罕见且生长缓慢的癌症。此外，传统上仅依赖组织学检查正逐渐被分子生物标志物（如微小RNA（miRNA））的探索和引入所补充。由于miRNA调节参与PanNETs肿瘤发生的多个基因和通路的表达，这些生物标志物在诊断和预后应用方面具有很大的潜力。在本研究中，我们旨在鉴定作为与PanNETs诊断相关的组织标志物的miRNA。
我们进行了一项病例对照研究，包括：从罗马尼亚患者获得的7个PanNETs和19个非肿瘤性胰腺组织。通过定量RT-PCR对样本进行miRNA谱分析，以评估84种miRNA的表达。我们的结果与通过重新分析一个公共数据集获得的结果进行比较。此外，我们根据其靶向的mRNA及其在信号通路中的作用对miRNA表达数据进行了整理。
通过将PanNETs与胰腺非肿瘤组织进行比较，鉴定出14种miRNA（miR-1、miR-133a-3p、miR-210-3p、miR-7-5p、miR-10a-5p、miR-92b-3p、miR-132-3p、miR-221-3p、miR-29b-3p、miR-107、miR-103a-3p、let-7b-5p、miR-148a-3p和miR-202-3p）差异表达，在分析的公共数据集中也发现了6种miRNA（miR-7-5p、miR-92b-3p、miR-29b-3p、miR-107、miR-103a-3p和miR-148a-3p）。生物信息学分析显示，鉴定出的14种miRNA靶向17个基因。重新分析两个公共基因表达数据集，发现其中5个基因在PanNETs中与对照相比差异表达。
我们的初步结果虽然受样本量小的限制，但突出了一种能够区分肿瘤性和正常胰腺组织的特定miRNA表达模式。这些miRNA的诊断性能，与循环miRNA相匹配并在更同质和更大的队列中得到验证，可能代表提高PanNETs诊断准确性的一个起点。
