biostudies-literatureMatyasovska NCharles University, project GA UKMinistry of Health Czech RepublicMinistry of Health of the Slovak Republicprogram Cooperatio, research area DIAG669https://www.ebi.ac.uk/biostudies/studies/S-EPMC11987397biostudies-literatureUnknown25(1)<h4>Background</h4>Only a limited number of biomarkers guide personalized management of pancreatic neuroendocrine tumors (PanNETs). Transcriptome profiling of microRNA (miRs) and mRNA has shown value in segregating PanNETs and identifying patients more likely to respond to treatment. Because miRs are key regulators of mRNA expression, we sought to integrate expression data from both RNA species into miR-mRNA interaction networks to advance our understanding of PanNET biology.<h4>Methods</h4>We used deep miR/mRNA sequencing on six low-grade/high-risk, well-differentiated PanNETs compared with seven non-diseased tissues to identify differentially expressed miRs/mRNAs. Then we crossed a list of differentially expressed mRNAs with a list of in silico predicted mRNA targets of the most and leasBMC cancerDeep sequencing reveals distinct microRNA-mRNA signatures that differentiate pancreatic neuroendocrine tumor from non-diseased pancreas tissue.PMC11987397SVV UK, LFHK, No. 260657UHHK, 001799062019/69 MXDX-1Abdulhamed AValkova NRenwick NPalicka VBendikova SCekan PPaul EGala MMatyasovska NfalseDeep sequencing reveals distinct microRNA-mRNA signatures that differentiate pancreatic neuroendocrine tumor from non-diseased pancreas tissue.<h4>Background</h4>Only a limited number of biomarkers guide personalized management of pancreatic neuroendocrine tumors (PanNETs). Transcriptome profiling of microRNA (miRs) and mRNA has shown value in segregating PanNETs and identifying patients more likely to respond to treatment. Because miRs are key regulators of mRNA expression, we sought to integrate expression data from both RNA species into miR-mRNA interaction networks to advance our understanding of PanNET biology.<h4>Methods</h4>We used deep miR/mRNA sequencing on six low-grade/high-risk, well-differentiated PanNETs compared with seven non-diseased tissues to identify differentially expressed miRs/mRNAs. Then we crossed a list of differentially expressed mRNAs with a list of in silico predicted mRNA targets of the most and leas2025-01-01T00:00:00Z2025 Apr2026-06-06T17:04:57.55Z2026-06-02T03:12:19.125ZS-EPMC119873974021750210.1186/s12885-025-14043-w