Table 1_Peripheral blood tRNA-derived fragments as novel noninvasive biomarkers for diagnosis and prognostic stratification in multiple myeloma.docx

BackgroundTransfer 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.
MethodsHigh-throughput sequencing was performed to comprehensively characterize tsRNA expression profiles in peripheral blood mononuclear cells (PBMCs) from 22 newly diagnosed MM patients and 19 healthy controls. Shared target genes were predicted by integrating miRanda and TargetScan, and a tsRNA–mRNA interaction network was constructed; GO and KEGG functional enrichment analyses were also performed. The discriminative performance of candidate biomarkers was evaluated using receiver operating characteristic (ROC) curves, and the associations between candidate tsRNAs and clinical parameters were further examined by correlation analyses.
ResultsA total of 148 significantly upregulated and 63 downregulated tsRNAs were identified. Among them, Other-1_19-tRNA-SeC-TCA-1 and Other-36_54-tRNA-Met-CAT-2-M4 exhibited excellent diagnostic performance, with areas under the ROC curve (AUCs) of 0.9557 and 0.9773, respectively. Functional analyses revealed that differentially expressed tsRNAs were primarily involved in regulating signaling pathways such as TGF-β, PI3K-Akt, and AMPK, and were closely associated with thyroid hormone metabolism. Elevated expression of Other-22_52-tRNA-Gly-GCC-1-M3 was significantly correlated with renal insufficiency (p < 0.05), suggesting its potential as a novel biomarker for assessing renal injury risk. The tsRNA–mRNA regulatory network comprised 11,141 interaction edges and exhibited a power-law topology, with the hub gene SRSF10 mediating coordinated regulation across multiple pathways.
ConclusionsOur findings reveal a distinct imbalance in tsRNA expression in MM, indicating 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.