LnCeVar 2.0: an updated resource and web tools for genomic variations disrupting ceRNA networks from single-cell/spatial transcriptomics data

LnCeVar 2.0 (available at http://bio-bigdata.hrbmu.edu.cn/LnCeVar or http://www.bio-bigdata.net/LnCeVar) is an updated database investigating genomic variations that disrupt competing endogenous RNA (ceRNA) networks via single-cell and spatial transcriptomics. Enhancements include expanded data and improved features: (i) 16 937 experimentally supported cancer biomarkers as well as 5785 validated ceRNA interactions and single nucleotide variant (SNV)-ceRNA events, manually curated and linked to key cancer pathogenic processes; (ii) 812 single-cell RNA sequencing/spatial transcriptomics RNA sequencing datasets covering 102 diseases, clinical treatments (e.g. chemotherapy, immunotherapy), and normal tissues; (iii) 5 218 062 single-cell- and spatial-specific SNV-ceRNA events across 2 673 603 cells/spots, with cellular functional perturbation networks; (iv) 5 comprehensive and 12 mini tools for multilevel cross talk analysis and 3D visualization; and (v) novel inference of SNV effects on cell types, states, and functions at single-cell and spatial levels. LnCeVar 2.0 features a user-friendly interface for searching, browsing, and analyzing data. For instance, the CeVarState interface illustrates how SNV-ceRNA events influence cell states during developmental processes, revealing interactions that determine cell fate. The CeVarSC3D and CeVarST3D tools perform multilevel cross talk analyses of SNVs, ceRNA networks, and cell states in disease pathology, providing interactive 3D visualizations. Overall, we anticipate that the updated database will facilitate the high-resolution investigation of SNV-ceRNA networks and advance our understanding of the regulatory mechanisms in complex disease ecosystems.

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Publication Details

Journal
Nucleic Acids Research
Published
2025-09-19
DOI
https://doi.org/10.1093/nar/gkaf1009
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.00

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article

LnCeVar 2.0: an updated resource and web tools for genomic variations disrupting ceRNA networks from single-cell/spatial transcriptomics data

Shangwei Ning, Yifan Dai, Jiatong Li, Mengyu Xin et al.
Nucleic Acids Research
Cancer-related molecular mechanisms research
article

LnCeVar 2.0: an updated resource and web tools for genomic variations disrupting ceRNA networks from single-cell/spatial transcriptomics data

Shangwei Ning, Yifan Dai, Jiatong Li, Mengyu Xin, Xinxin Shan, Hui Zhi, Bochao Xu, Houxing Li, Qian Liu, Yue Gao, Rui Sun, Yuting He, Qiuyan Guo, Peng Wang, Yujie Zhang
article en

Abstract

LnCeVar 2.0 (available at http://bio-bigdata.hrbmu.edu.cn/LnCeVar or http://www.bio-bigdata.net/LnCeVar) is an updated database investigating genomic variations that disrupt competing endogenous RNA (ceRNA) networks via single-cell and spatial transcriptomics. Enhancements include expanded data and improved features: (i) 16 937 experimentally supported cancer biomarkers as well as 5785 validated ceRNA interactions and single nucleotide variant (SNV)-ceRNA events, manually curated and linked to key cancer pathogenic processes; (ii) 812 single-cell RNA sequencing/spatial transcriptomics RNA sequencing datasets covering 102 diseases, clinical treatments (e.g. chemotherapy, immunotherapy), and normal tissues; (iii) 5 218 062 single-cell- and spatial-specific SNV-ceRNA events across 2 673 603 cells/spots, with cellular functional perturbation networks; (iv) 5 comprehensive and 12 mini tools for multilevel cross talk analysis and 3D visualization; and (v) novel inference of SNV effects on cell types, states, and functions at single-cell and spatial levels. LnCeVar 2.0 features a user-friendly interface for searching, browsing, and analyzing data. For instance, the CeVarState interface illustrates how SNV-ceRNA events influence cell states during developmental processes, revealing interactions that determine cell fate. The CeVarSC3D and CeVarST3D tools perform multilevel cross talk analyses of SNVs, ceRNA networks, and cell states in disease pathology, providing interactive 3D visualizations. Overall, we anticipate that the updated database will facilitate the high-resolution investigation of SNV-ceRNA networks and advance our understanding of the regulatory mechanisms in complex disease ecosystems.

Nucleic Acids ResearchVol. 54(D1)
Harbin Medical University (CN), First Affiliated Hospital of Harbin Medical University (CN)
Harbin Medical University, National Natural Science Foundation of China
Openalex Percentile: Top 64%
Cancer-related molecular mechanisms research
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