Niedra Helvijs, Rogoza Olesja, Saksis Rihards, Peculis Raitis, Halilova Anzela, Gerina Aija, Vilisova Sofija, Senterjakova Natalja, Pukitis Aldis, Ruz-Caracuel Ignacio, Earl Julie, Kolnikova Georgina, Dubovan Peter, Tomas Miroslav, Makovicky Peter, Urbanova Maria, Smolkova Bozena, Koniaris Eythimios, Aggelioudaki Ioanna, Kataki Agapi, Rovite Vita
Latvian Biomedical Research and Study Centre, Ratsupites Str, Riga, Latvia.
Pauls Stradins Clinical University Hospital, Pilsonu Str, Riga, Latvia.
PLoS One. 2025 Jun 16;20(6):e0325672. doi: 10.1371/journal.pone.0325672. eCollection 2025.
The study aimed to identify altered signaling pathways and potential non-invasive biomarkers for pancreatic neuroendocrine tumors (PanNETs) through transcriptomic profiling of tumor tissues. The analysis encompassed samples from non-functional PanNETs (NF-PanNETs), insulinomas, and tumor-adjacent pancreatic tissues (TAPT). In the differential expression analysis comparing PanNETs and TAPTs, we identified 1,210 differentially expressed genes at a false discovery rate significance threshold of < 0.05 and with Log2FoldChange values of > 0.5 and <-0.5. Further pathway enrichment analysis revealed a multitude of overrepresented signaling pathways related to cell proliferation, survival, and tumorigenesis. Significant findings included the Beta-catenin-independent and TCF-dependent WNT signaling pathways, MAPK1/MAPK3 signaling, and terms associated with PI3K/AKT/mTOR signaling. Among the list of DEGs, we also identified 28 upregulated genes encoding cell surface proteins and 24 upregulated genes encoding cancer-associated secretome proteins. Since the proteins of these genes are found in the bloodstream, there is potential for further testing of these markers as biomarkers for liquid biopsy assays. Overall, these findings underscore the promise of transcriptomic landscape analysis in identifying PanNET-specific non-invasive biomarkers and uncovering potential therapeutic targets.
该研究旨在通过肿瘤组织的转录组分析，确定胰腺神经内分泌肿瘤（PanNETs）中改变的信号通路和潜在的非侵入性生物标志物。分析涵盖了来自无功能PanNETs（NF-PanNETs）、胰岛素瘤和肿瘤邻近胰腺组织（TAPT）的样本。在比较PanNETs和TAPT的差异表达分析中，我们在错误发现率显著性阈值<0.05且Log2倍变化值>0.5和<-0.5的情况下，鉴定出1210个差异表达基因。进一步的通路富集分析揭示了许多与细胞增殖、存活和肿瘤发生相关的过度表达的信号通路。重要发现包括β-连环蛋白非依赖性和TCF依赖性WNT信号通路、MAPK1/MAPK3信号通路以及与PI3K/AKT/mTOR信号通路相关的术语。在差异表达基因列表中，我们还鉴定出28个上调的编码细胞表面蛋白的基因和24个上调的编码癌症相关分泌组蛋白的基因。由于这些基因的蛋白质存在于血液中，因此有进一步将这些标志物作为液体活检检测生物标志物进行测试的潜力。总体而言，这些发现强调了转录组图谱分析在识别PanNET特异性非侵入性生物标志物和揭示潜在治疗靶点方面的前景。
