← BioTransfer GEO Dataset Finder
GEO series

NICO Myriad system Improves sample quality for molecular pathology assays

GSE298049 Homo sapiens Expression profiling by high throughput sequencing 29 samples 2026/06/30 GPL18460
Summary
Meningiomas are commonly treated through surgery, radiation, or chemotherapy, based. These decisions are guided by pathological interpretation which traditionally uses the WHO classification schema. Current diagnostic methods based on FFPE samples often fall short of providing precise treatment, and hence multiple revisions have been generated such as cImpact8. However, emerging molecular techniques, such as circular RNA (circRNA) profiling show potential to enhance diagnostic accuracy but are limited by degradation caused by FFPE process. To overcome this challenge, we tested the extent to which the NICO Myriad system enhances tissue preservation. The NICO Myriad system extracts fresh tissue in situ using a refrigerated chamber and Ringer’s Lactate fluid. This study aims to compare the efficiency of Traditional and NICO tissue extraction protocols for meningioma resection, focusing on circRNA profiles as clinical biomarkers. We performed circRNA sequencing in 20 patients, collected under identical tumor resection conditions. We performed T-test to compare RNA extraction and sequencing quality, circRNA detection and profile between protocols. DEseq analysis was applied to circRNAs Differential Expression, and Weighted Gene Co-expression Network Analysis (WGCNA) correlated with clinical features followed by GO enrichment. NICO protocol enhances RNA integrity (p=0.0023), yielding a high-quality data (>Q30 median=95%) which reduced variation of circRNA detection. WGCNA identified two modules differentiating the protocols, while two modules were related with WHO Grade 2 associated with cellular metabolism, and epitranscriptomic regulation. We conclude that the NICO protocol, which offers a homeostatic environment, significantly improves the precision of circRNA detection.
Download
NCBI GEO page ↗ Paper (PMID 42475233) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.