Peripheral Blood tRNA-derived Fragments as Novel Noninvasive Biomarkers for Diagnosis and Prognostic Stratification in Multiple Myeloma

Biyun Yi¹Yan Gao¹Yanzhao Huang²Kaiyun Guo¹Rong Liu¹Mengying Zeng¹Han Xu²Ming Lei^1*

• ¹The First People's Hospital of Changde City, Changde, China
• ²University of South China Hengyang Medical School, Hengyang, China

Transfer RNA-derived small RNAs (tsRNAs) have recently emerged as critical regulators in cancer biology, yet their expression profiles and clinical relevance in multiple myeloma (MM) remain poorly defined. Here, we employed high-throughput sequencing to comprehensively characterize tsRNA expression in peripheral blood mononuclear cells (PBMCs) from 22 newly diagnosed MM patients and 19 healthy controls. This analysis delineated a global tsRNA expression landscape, revealing distinct subtype distributions and length profiles of tRFs and tiRNAs. Following stringent screening and RT-qPCR validation, eight candidate tsRNAs were identified, among which Other-1_19-tRNA-SeC-TCA-1 and Other-13_30-tRNA-Lys-CTT-1-M2 constituted a central regulatory module. Integrative prediction using miRanda and TargetScan uncovered 5,009 shared target genes, enabling construction of a tsRNA–mRNA interaction network comprising 11,141 edges and exhibiting a power-law topology with hub genes such as SRSF10. Functional enrichment analyses (GO and KEGG) indicated significant involvement of target genes in TGF-β, PI3K– Akt, AMPK, cell adhesion, and thyroid hormone signaling pathways. Notably, elevated expression of Other-22_52-tRNA-Gly-GCC-1-M3 correlated strongly with renal impairment in MM, underscoring its potential as a noninvasive biomarker for renal risk assessment. Moreover, Other-36_54-tRNA-Met-CAT-2-M4 and Other-1_19-tRNA-SeC-TCA-1 demonstrated excellent diagnostic performance (AUC > 0.95). Correlation analyses further supported the diagnostic and prognostic relevance of these tsRNAs across multiple clinical parameters. Collectively, our findings reveal a distinct imbalance in tsRNA expression in MM, suggesting that specific tsRNA fragments contribute to disease progression and renal injury through multifaceted signaling networks, thereby providing novel molecular insights for early diagnosis and risk stratification.