Non-canonical small noncoding RNAs in the plasma extracellular vesicles as novel biomarkers in gastric cancer

Abstract

Identifying robust diagnostic biomarkers for gastric cancer (GC) remains a significant challenge. Emerging studies highlight extracellular vesicle (EV)-derived RNAs in cancer biology, but the diagnostic potential of circulating EV-derived small non-coding RNAs (sncRNAs) in GC is poorly understood. Using panoramic RNA display by overcoming RNA modification aborted sequencing (PANDORA-seq), we mapped non-canonical sncRNAs-specifically ribosomal RNA-derived small RNAs (rsRNAs) and transfer RNA-derived small RNAs (tsRNAs)-in plasma EVs. We identified a three-rs/tsRNA signature that discriminates GC patients from healthy individuals with high sensitivity (80.42%) and specificity (87.43%) (143 GC vs 167 controls). For early-stage GC (stage I), sensitivity and specificity were 81.97% and 81.44%, respectively. Furthermore, the three-rs/tsRNA signature was evaluated in two independent cohorts, resulting in AUC values of 0.97 and 0.91 for distinguishing GC from healthy controls. Functional analyses revealed that these rs/tsRNAs regulate the ErbB/Hippo pathways, suggesting them in the underlying pathogenesis and therapeutic potential. This study establishes a novel EV-derived sncRNA signature for early GC detection.

Keywords: Biomarker; Extracellular vesicles; Gastric cancer; rsRNA; tsRNA.

Fig. 1

Identification of differentially expressed plasma EV non-canonical sncRNAs in gastric cancer. A Read summaries and length distributions of different small RNA categories under PANDORA-seq. B Heatmap displaying the expression profile of plasma EV small RNAs in GC group and healthy controls. C Scatter plot illustrating the changes in expression levels of miRNAs, piRNAs, rsRNAs, tsRNAs, and snoRNAs. D Ranked differential expression of top 10 upregulated (red) and downregulated (blue) sncRNAs (selection criteria: reads per million > 10, fold-change > 10). Parent RNA origins indicated by iconography (rRNA for rsRNAs, tRNA for tsRNAs). E. RT-qPCR validation of candidate sncRNAs in training cohort (24 GC patients vs 24 healthy controls). Data are shown as the mean ± SEMs. Significance determined by unpaired two-tailed Student's t-test. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001

Fig. 2

Multi-cohorts validation and functional characterization of plasma EV-derived rs/tsRNA signature in gastric cancer. A qRT-PCR analysis of six candidate sncRNAs in validation cohort (119 GC patients vs 143 healthy controls). Data are shown as the mean ± SEMs. Significance determined by unpaired two-tailed Student's t-test. ****P < 0.0001. B ROC analyses of the three-rs/tsRNA signature across training and validation cohorts (143 GC patients vs 167 healthy controls). C Feature importance ranking by mean decrease Gini index of three rs/tsRNAs(S2/S7/S10), four clinical protein indices (CA19-9, CA125, CEA, AFP), and their combination, as determined by random forest analysis. D ROC analysis of the performance of three rs/tsRNAs, four clinical protein indices, and all index combinations in the validation set of machine learning model. E Confusion matrix showing the classification accuracy of three rs/tsRNAs, four clinical protein indices, and their combined use in distinguishing GC patients from healthy controls through machine learning. F Validation in two independent test cohorts (Test Cohort 1: 47 GC vs 47 controls; Test Cohort 2: 40 GC vs 43 controls). Data are shown as the mean ± SEMs. Statistical significance was assessed using unpaired two-tailed t tests, ***P < 0.001; ****P < 0.0001.G ROC curves demonstrating diagnostic values of three rs/tsRNAs in two test cohorts. H Functional validation of rs/tsRNA-target interactions via dual-luciferase reporter assay. Data are shown as the mean ± SEMs. Statistical significance was assessed using unpaired two-tailed t tests, *P < 0.05; **P < 0.01; I Western blot verification of ErbB/Hippo pathway modulation in GC cells. MKN-45 and AGS cells transfected with sncRNA mimics and scramble negative control RNA, respectively. GAPDH served as internal control. Quantification represents mean ± SEM from three independent experiments