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OncotRF: an online resource for exploration of tRNA-derived fragments in human cancers
Dongxia Yao1, Xiwei Sun2, Liyuan Zhou2
1Center for Uterine Cancer Diagnosis & Therapy Research of Zhejiang Province, Women's Reproductive Health Key Laboratory of Zhejiang Province, Department of Gynecologic Oncology, Women's Hospital and Institute of Translational Medicine, School of Medicine, Zhejiang University , Hangzhou, Zhejiang, China.
Abstract:
Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs whose biological roles in cancers are not well understood. Emerging evidence suggests that tRFs are involved in gene regulation at multiple levels. In this study, we constructed an integrative database, OncotRF (http://bioinformatics.zju.edu.cn/OncotRF), for in silico exploration of tRF functions, and identification of diagnostic and prognostic biomarkers in cancers. The database contains an analysis pipeline for tRF identification and characterization, analysis results of 11,211 small RNA sequencing samples and 8,776 RNA sequencing samples, and clinicopathologic annotation data from The Cancer Genome Atlas (TCGA). The results include: tRF identification and quantification across 33 cancers, abnormally expressed tRFs and genes, tRF-gene correlations, tRF-gene networks, survival analyses, and tRF-related functional enrichment analyses. Users are also able to identify differentially expressed tRFs, predict their functions, and assess the relevance of the tRF expression levels to the clinical outcome according to user-defined groups. Additionally, an online Kaplan-Meier plotter is available in OncotRF for plotting survival curves according to user-defined groups. OncotRF will be a valuable online database and functional annotation tool for researchers studying the roles, functions, and mechanisms of tRFs in human cancers.
Insights
Transfer RNA-derived fragments (tRFs) are small RNAs with unknown roles in cancer. The OncotRF database aids in exploring tRF functions and identifying cancer biomarkers.
Area of Science:
- Molecular Biology
- Genomics
- Bioinformatics
Background:
- Transfer RNA-derived fragments (tRFs) are novel small non-coding RNAs implicated in gene regulation.
- The biological functions and significance of tRFs in human cancers remain largely unexplored.
Purpose of the Study:
- To develop OncotRF, an integrated online database for exploring tRF functions in cancer.
- To facilitate the identification of tRFs as potential diagnostic and prognostic biomarkers in various cancers.
Main Methods:
- Construction of the OncotRF database integrating tRF identification pipeline, sequencing data (11,211 small RNA-seq, 8,776 RNA-seq), and TCGA clinical data.
- Analysis of tRFs across 33 cancer types, including expression profiling, correlation analysis with genes, network construction, and survival analysis.
- Implementation of user-friendly tools for differential tRF expression analysis, functional prediction, and clinical outcome assessment.
Main Results:
- Comprehensive tRF profiling and quantification across 33 cancer types.
- Identification of abnormally expressed tRFs and associated genes, revealing potential regulatory relationships and networks.
- Demonstration of tRFs' relevance to patient survival through integrated survival analyses and an online Kaplan-Meier plotter.
Conclusions:
- OncotRF provides a valuable resource for investigating tRF roles and mechanisms in human cancers.
- The database empowers researchers to identify and validate tRFs as potential cancer biomarkers and therapeutic targets.
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