Combination of Urine Exosomal mRNAs and lncRNAs as Novel Diagnostic Biomarkers for Bladder Cancer.

2021 
Background The recent discovery of miRNAs and lncRNAs in urine exosomes has emerged as promising diagnostic biomarkers for bladder cancer (BCa). However, mRNAs as the direct products of transcription has not been well evaluated in exosomes as biomarkers for BCa diagnosis. The purpose of this study was to identify tumor progression-related mRNAs and lncRNAs in urine exosomes that could be used for detection of BCa. Methods RNA-sequencing was performed to identify tumor progression-related biomarkers in three matched superficial tumor and deep infiltrating tumor regions of muscle-invasive bladder cancer (MIBC) specimens, differently expressed mRNAs and lncRNAs were validated in TCGA dataset (n = 391) in the discovery stage. Then candidate RNAs were chosen for evaluation in urine exosomes of a training cohort (10 BCa and 10 healthy controls) and a validation cohort (80 BCa and 80 healthy controls) using RT-qPCR. The diagnostic potential of the candidates were evaluated by receiver operating characteristic (ROC) curves. Results RNA sequencing revealed 8 mRNAs and 32 lncRNAs that were significantly upregulated in deep infiltrating tumor region. After validation in TCGA database, 10 markedly dysregulated RNAs were selected for further investigation in urine exosomes, of which five (mRNAs: KLHDC7B, CASP14, and PRSS1; lncRNAs: MIR205HG and GAS5) were verified to be significantly dysregulated. The combination of the five RNAs had the highest AUC to disguising the BCa (0.924, 95% CI, 0.875-0.974) or early stage BCa patients (0.910, 95% CI, 0.850 to 0.971) from HCs. The expression levels of these five RNAs were correlated with tumor stage, grade, and hematuria degrees. Conclusions These findings highlight the potential of urine exosomal mRNAs and lncRNAs profiling in the early diagnosis and provide new insights into the molecular mechanisms involved in BCa.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    32
    References
    4
    Citations
    NaN
    KQI
    []