Plasma exosomal lncRNA SLC16A1-AS1 as an early diagnostic biomarker for renal cell carcinoma

Abstract

Purpose Advanced renal cell carcinoma (RCC) has a poor prognosis due to metastasis, delayed diagnosis and drug resistance. Therefore, the early diagnosis of the disease is of vital importance, but currently there are no validated circulating blood biomarkers available for the prediction of early-stage renal cell carcinoma. This study aimed to identify plasma exosomal long non-coding RNAs (lncRNAs) as novel diagnostic biomarkers to support early RCC diagnosis. Methods We obtained 5 mL plasma from every individual among 6 RCC patients and 6 healthy controls, alongside other 36 paired RCC tumor and adjacent non-tumor tissues. Plasma exosomes were isolated by ultracentrifugation and characterized via transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA) and western blotting (WB). Differentially expressed exosomal lncRNAs were screened by next‐generation sequencing (NGS). Candidate lncRNAs were validated by qPCR in RCC cell lines and clinical tissues. Receiver operating characteristic (ROC) and the area under curve (AUC) analysis were used to evaluate the diagnostic efficacy. Kaplan–Meier analysis was applied to explore the prognostic value. Results We successfully isolated and identified exosomes. By applying NGS, we successfully screened out five plasma exosomal lncRNAs—ENSG00000261253, FRRS1L, LINC02035, DNAJC7 and SLC16A1-AS1. Meanwhile, sequencing results further confirmed that these lncRNAs are significantly upregulated in plasma exosomes from RCC patients. QPCR was performed to detect the expression levels of five candidate lncRNAs in renal cell carcinoma cell lines as well as paired carcinoma and adjacent non-tumor tissues. Among these lncRNAs, only SLC16A1-AS1 was markedly upregulated in both cellular and tissue specimens. Based on 36 pairs of renal cell cancer tissue samples, the ROC curve was calculated, which revealed its AUC = 0.901, indicating excellent diagnostic efficacy and potential for early diagnosis of renal cell cancer. Kaplan–Meier analysis based on the TCGA database further demonstrated that both overall survival (OS) and disease-free survival (DFS) were significantly decreased in the high-expression group, suggesting its high expression predicts unfavorable patient prognosis. Conclusions This study identifies plasma exosomal lncRNA SLC16A1-AS1 may serve as a preliminary potential non-invasive biomarker for RCC early diagnosis and prognostic monitoring. Future in vivo/vitro experiments will explore its functional mechanisms, providing theoretical basis for RCC treatment.