Global identification and characterization of tRNA-derived RNA fragment landscapes across human cancers

Area of Science:

• Genomics
• Molecular Biology
• Cancer Research

Background:

• Transfer RNA-derived RNA fragments (tRFs) are small non-coding RNAs with largely unexplored roles in cancer.
• Their functional genomic landscape across diverse cancer types remains to be fully elucidated.

Purpose of the Study:

• To comprehensively map the functional genomic landscape of tRFs in 15 cancer types using The Cancer Genome Atlas (TCGA) data.
• To identify cancer-specific tRF expression patterns, driver tRFs, and their clinical relevance.
• To validate the oncogenic role of a specific tRF in lung cancer.

Main Methods:

• Analysis of tRF expression across 8118 cancer specimens from TCGA.
• Cross-tumor analysis of tRF expression subtypes and associated signaling pathways.
• Bioinformatic identification of cancer driver tRFs.
• In vitro and in vivo functional assays for a selected tRF (5'-IleAAT-8-1-L20).

Main Results:

• tRFs exhibit widespread expression, sequence conservation, and cytoplasmic localization across cancer types.
• Common tRF expression subtypes characterized by upregulated tRFs and activated cancer signaling (Ras/MAPK, RTK, TSC/mTOR) were identified.
• tRF-based subgrouping improved cancer outcome prediction.
• Eleven cancer driver tRFs were discovered, and 5'-IleAAT-8-1-L20 was validated as an oncogenic driver in lung cancer.

Conclusions:

• tRFs represent a significant functional genomic landscape in cancer with conserved patterns across tumor types.
• tRFs can serve as clinically relevant biomarkers for cancer stratification and outcome prediction.
• This study provides a valuable resource for tRF-based cancer diagnostics, therapeutics, and pathogenesis research.