ArticleComputational and structural biotechnology journal2023
A novel method to identify and characterize personalized functional driver lncRNAs in cancer samples.
Article in Computational and structural biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Deciphering the Transcription Factor-Dominated Ecosystem During Esophageal Squamous Cell Carcinoma Progression at the Single-Cell Level.International journal of molecular sciences · 2026Article
- POCALI: Prediction and Insight on CAncer LncRNAs by Integrating Multi-Omics Data with Machine Learning.Small methods · 2025Article
- Symptom and functional networks of patients with cancer in different latent risk subgroups based on patient-reported outcomes.BMC cancer · 2025Article
- Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer.International journal of molecular sciences · 2023Review
Corrections and comments
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Authors and funding
13 authors at 1 institution in 1 country.
Funding
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Abstract
Cancer is a highly heterogeneous disease, and different individuals of the same cancer type can display different therapeutic effects and prognosis. Genetic variation of long non-coding RNA is the key factor driving tumor development, and plays an important role in genetic and biological heterogeneity. Therefore, it is of great significance to identify lncRNA as a driving factor in the non-coding region and explain its function in tumors for revealing the pathogenesis of cancer. In this study, we developed an integrated method to identify Personalized Functional Driver lncRNAs (PFD-lncRNAs) by integrating the DNA copy number data, gene expression data, and the biological subpathways information. Then, we applied the method to identify 2695 PFD-lncRNAs in 5334 samples across 19 cancer types. We performed an analysis of the association between PFD-lncRNAs and drug sensitivity, which provides medication guidance in disease therapy and drug discovery in the individual. Our research is of great significance for elucidating the biological roles of lncRNA genetic variation in cancer, revealing the related mechanism of cancer, and providing novel insights for individualized medicine.
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Registered trials
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