SNORD91B

Osteocytes sense mechanical loads and transduce mechanical signals into a chemical response. They are the most abundant bone cells deeply embedded in mineralized bone matrix, which affects their regulatory activity in the mechanical adaptation of bone. The specific location in the calcified bone matrix hinders studies on osteocytes in the in vivo setting. Recently, we developed a three-dimensional mechanical loading model of human osteocytes in their native matrix, allowing to study osteocyte mechanoresponsive target gene expression in vitro. Here we aimed to identify differentially expressed genes by mapping the response of human primary osteocytes in their native matrix to mechanical loading using RNA sequencing. Human fibular bone was retrieved from 10 donors (age: 32-82 years, 5 female, 5 male). Cortical bone explants (8.0 × 3.0 × 1.5 mm; length × width × height) were either not loaded or mechanically loaded by 2000 or 8000 μɛ for 5 minutes, followed by 0, 6, or 24 hours post-culture without loading. High-quality RNA was isolated, and differential gene expression analysis performed by R2 platform. Real-time PCR was used to confirm differentially expressed genes. Twenty-eight genes were differentially expressed between unloaded and loaded (2000 or 8000 μɛ) bone at 6 hours post-culture, and 19 genes at 24 hours post-culture. Eleven of these genes were related to bone metabolism, ie, EGR1, FAF1, H3F3B, PAN2, RNF213, SAMD4A, and TBC1D24 at 6 hours post-culture, and EGFEM1P, HOXD4, SNORD91B, and SNX9 at 24 hours post-culture. Mechanical loading significantly decreased RNF213 gene expression, which was confirmed by real-time PCR. In conclusion, mechanically loaded osteocytes differentially expressed 47 genes, of which 11 genes were related to bone metabolism. RNF213 might play a role in mechanical adaptation of bone by regulating angiogenesis, which is a prerequisite for successful bone formation. The functional aspects of the differentially expressed genes in bone mechanical adaptation requires future investigation. © 2023 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research.

Previous studies identified microRNAs (miRNAs) and messenger RNAs with significantly different expression between normal pancreas and pancreatic cancer (PDAC) tissues. Due to technological limitations of microarrays and real-time PCR systems these studies focused on a fixed set of targets. Expression of other RNA classes such as long intergenic non-coding RNAs or sno-derived RNAs has rarely been examined in pancreatic cancer. Here, we analysed the coding and non-coding transcriptome of six PDAC and five control tissues using next-generation sequencing.

Besides the confirmation of several deregulated mRNAs and miRNAs, miRNAs without previous implication in PDAC were detected: miR-802, miR-2114 or miR-561. SnoRNA-derived RNAs (e.g. sno-HBII-296B) and piR-017061, a piwi-interacting RNA, were found to be differentially expressed between PDAC and control tissues. In silico target analysis of miR-802 revealed potential binding sites in the 3' UTR of TCF4, encoding a transcription factor that controls Wnt signalling genes. Overexpression of miR-802 in MiaPaCa pancreatic cancer cells reduced TCF4 protein levels. Using Massive Analysis of cDNA Ends (MACE) we identified differential expression of 43 lincRNAs, long intergenic non-coding RNAs, e.g. LINC00261 and LINC00152 as well as several natural antisense transcripts like HNF1A-AS1 and AFAP1-AS1. Differential expression was confirmed by qPCR on the mRNA/miRNA/lincRNA level and by immunohistochemistry on the protein level.

Here, we report a novel lncRNA, sncRNA and mRNA signature of PDAC. In silico prediction of ncRNA targets allowed for assigning potential functions to differentially regulated RNAs.