Nanopore direct RNA sequencing reveals the 2′-O-methylation landscape and SNORD88B-guided FN1 modification in hepatocellular carcinoma

Objective To systematically map the internal 2′-O-methylation (Nm) landscape on messenger RNA (mRNA) in hepatocellular carcinoma (HCC), characterize its distribution features and biological functions, and identify key C/D box small nucleolar RNAs (snoRNAs) that regulate Nm modification along with their target genes, thereby providing a molecular basis for elucidating post-transcriptional regulatory mechanisms in HCC. Methods Based on Nanopore direct RNA sequencing data from the HepG2 cell line, we employed the NanoNm machine learning algorithm to systematically identify internal Nm modification sites on mRNA and analyzed their sequence preferences, genomic distribution, and methylation ratio characteristics. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to explore the biological functions of the modified genes. Using snoRNA expression profiles from the GSE233521 dataset derived from liver cancer stem cells, we conducted differential expression analysis to screen for significantly differentially expressed C/D box snoRNAs. Based on the principle of sequence complementarity, we predicted their guided Nm-modified target genes. Subsequently, hepatocellular carcinoma single-cell RNA sequencing (scRNA-seq) data were used to characterize the cell-type-specific expression of the target genes. Results A total of 10,450 high-confidence consensus Nm modification sites were identified, spanning 1515 genes. These modification sites exhibited a significant sequence preference for AGmA and UCmU trinucleotide motifs (where “m” denotes 2′-O-methylation). Genes bearing Nm modifications were significantly enriched in pathways associated with energy metabolism and protein synthesis, including oxidative phosphorylation, ribosome assembly, and cytoplasmic translation. SNORD88B was significantly upregulated in liver cancer stem cells, its guide sequence displayed perfect base-pairing complementarity with the Nm-modified region of fibronectin 1 (FN1) mRNA. Furthermore, single-cell RNA sequencing analysis revealed that FN1 was specifically expressed in hepatocellular carcinoma tumor cell clusters. Conclusion This study systematically mapped the global landscape of internal Nm modifications on HCC mRNA at single-base resolution. Nm modification may participate in the development and progression of HCC by modulating the expression and function of target genes. The high expression of SNORD88B in liver cancer stem cells may promote the malignant progression of HCC by guiding Nm modification on FN1 mRNA, thereby providing new research directions for an in-depth understanding of the regulatory mechanisms of snoRNA-mediated Nm modification in HCC.

Authors

Institutions

Publication Details

Journal
Non-coding RNA Research
Published
2026-11-06
DOI
https://doi.org/10.1016/j.ncrna.2026.10.002
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Nanopore direct RNA sequencing reveals the 2′-O-methylation landscape and SNORD88B-guided FN1 modification in hepatocellular carcinoma

Xuan Liu, Jingxiang Xu, Chenzhi Xiahou
2 links
Non-coding RNA Research
RNA modifications and cancer
article

Nanopore direct RNA sequencing reveals the 2′-O-methylation landscape and SNORD88B-guided FN1 modification in hepatocellular carcinoma

Xuan Liu, Jingxiang Xu, Chenzhi Xiahou
article en

Abstract

Objective To systematically map the internal 2′-O-methylation (Nm) landscape on messenger RNA (mRNA) in hepatocellular carcinoma (HCC), characterize its distribution features and biological functions, and identify key C/D box small nucleolar RNAs (snoRNAs) that regulate Nm modification along with their target genes, thereby providing a molecular basis for elucidating post-transcriptional regulatory mechanisms in HCC. Methods Based on Nanopore direct RNA sequencing data from the HepG2 cell line, we employed the NanoNm machine learning algorithm to systematically identify internal Nm modification sites on mRNA and analyzed their sequence preferences, genomic distribution, and methylation ratio characteristics. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to explore the biological functions of the modified genes. Using snoRNA expression profiles from the GSE233521 dataset derived from liver cancer stem cells, we conducted differential expression analysis to screen for significantly differentially expressed C/D box snoRNAs. Based on the principle of sequence complementarity, we predicted their guided Nm-modified target genes. Subsequently, hepatocellular carcinoma single-cell RNA sequencing (scRNA-seq) data were used to characterize the cell-type-specific expression of the target genes. Results A total of 10,450 high-confidence consensus Nm modification sites were identified, spanning 1515 genes. These modification sites exhibited a significant sequence preference for AGmA and UCmU trinucleotide motifs (where “m” denotes 2′-O-methylation). Genes bearing Nm modifications were significantly enriched in pathways associated with energy metabolism and protein synthesis, including oxidative phosphorylation, ribosome assembly, and cytoplasmic translation. SNORD88B was significantly upregulated in liver cancer stem cells, its guide sequence displayed perfect base-pairing complementarity with the Nm-modified region of fibronectin 1 (FN1) mRNA. Furthermore, single-cell RNA sequencing analysis revealed that FN1 was specifically expressed in hepatocellular carcinoma tumor cell clusters. Conclusion This study systematically mapped the global landscape of internal Nm modifications on HCC mRNA at single-base resolution. Nm modification may participate in the development and progression of HCC by modulating the expression and function of target genes. The high expression of SNORD88B in liver cancer stem cells may promote the malignant progression of HCC by guiding Nm modification on FN1 mRNA, thereby providing new research directions for an in-depth understanding of the regulatory mechanisms of snoRNA-mediated Nm modification in HCC.

Non-coding RNA ResearchVol. 21
Gannan Medical University (CN), Third Affiliated Hospital of Sun Yat-sen University (CN)
National Natural Science Foundation of China, Gannan Medical University
Good health and well-being
Openalex Percentile: Top 27%
RNA modifications and cancer
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon