Exosomal long noncoding RNA (lncRNA) has been found to be associated with the development of cancers. However, the expression characteristics and the biological roles of exosomal lncRNAs in hepatocellular carcinoma (HCC) remain unknown. Here, by RNA sequencing, we found 9440 mRNAs and 8572 lncRNAs were differentially expressed (DE‐) in plasma exosomes between HCC patients and healthy controls. Exosomal DE‐lncRNAs displayed higher expression levels and tissue specificity, lower expression variability and splicing efficiency than DE‐mRNAs. Six candidate DE‐lncRNAs (fold change 6 or more, P ≤ .01) were high in HCC cells and cell exosomes. The knockdown of these candidate DE‐lncRNAs significantly affected the migration, proliferation, and apoptosis in HCC cells. In particular, a novel DE‐lncRNA, RP11‐85G21.1 (lnc85), promoted HCC cellular proliferation and migration by targeted binding and regulating of miR‐324‐5p. More importantly, the level of serum lnc85 was highly expressed in both Alpha‐fetoprotein (AFP)‐positive and AFP‐negative HCC patients and allowed distinguishing AFP‐negative HCC from healthy control and liver cirrhosis (area under the receiver operating characteristic curve, 0.869; sensitivity, 80.0%; specificity, 76.5%) with high accuracy. Our finding offers a new insight into the association between the dysregulation of exosomal lncRNA and HCC, suggesting that lnc85 could be a potential biomarker of HCC.

Aim: The aim was to systematically evaluate whether exosomal miRNAs could be regarded as potential minimally invasive biomarkers of diagnosis for gastrointestinal cancer. Methods: A systematic review and meta analysis of exosomal miRNA expression in gastrointestinal cancer were performed. Results: A total of 370 articles were retrieved from PubMed and EMBASE. The summary receiver operating characteristic curves of three miRNAs (miR-21, miR-1246 and miR-4644) were drawn, miR-21, miR-1246 and miR-4644 exhibited sensitivities of 0.66, 0.920 and 0.750, respectively; specificities were 0.87, 0.958 and 0.769, respectively; and areas under the curve for discriminating gastrointestinal cancer patients from control subjects were 0.876, 0.969 and 0.827, respectively. Conclusion: Exosome miR-1246 had the highest level of diagnostic efficiency, which indicated that miR-1246 could be a biomarker.

Background There are no proven tumor biomarkers for the early diagnosis of clear cell renal cell carcinoma (ccRCC) thus far. This study aimed to identify novel biomarkers of ccRCC based on exosomal mRNA (emRNA) profiling and develop emRNA-based signatures for the early detection of ccRCC. Methods Four hundred eighty-eight participants, including 226 localized ccRCCs, 73 patients with benign renal masses, and 189 healthy controls, were recruited. Circulating emRNA sequencing was performed in 12 ccRCCs and 22 healthy controls in the discovery phase. The candidate emRNAs were evaluated with 108 ccRCCs and 70 healthy controls in the test and training phases. The emRNA-based signatures were developed by logistic regression analysis and validated with additional cohorts of 106 ccRCCs, 97 healthy controls, and 73 benign individuals. Results Five emRNAs, CUL9, KMT2D, PBRM1, PREX2, and SETD2, were identified as novel potential biomarkers of ccRCC. We further developed an early diagnostic signature that comprised KMT2D and PREX2 and a differential diagnostic signature that comprised CUL9, KMT2D, and PREX2 for RCC detection. The early diagnostic signature displayed high accuracy in distinguishing ccRCCs from healthy controls, with areas under the receiver operating characteristic curve (AUCs) of 0.836 and 0.830 in the training and validation cohorts, respectively. The differential diagnostic signature also showed great performance in distinguishing ccRCCs from benign renal masses (AUC = 0.816), including solid masses (AUC = 0.810) and cystic masses (AUC = 0.832). Conclusions We established and validated novel emRNA-based signatures for the early detection of ccRCC and differential diagnosis of uncertain renal masses. These signatures could be promising and noninvasive biomarkers for ccRCC detection and thus improve the prognosis of ccRCC patients.

Aim: The aim was to systematically investigate the miRNA biomarkers for early diagnosis of hepatocellular carcinoma (HCC). Materials & methods: A systematic review and meta-analysis of miRNA expression in HCC were performed. Results: A total of 4903 cases from 30 original studies were comprehensively analyzed. The sensitivity and specificity of miR-224 in discriminating early-stage HCC patients from benign lesion patients were 0.868 and 0.792, which were superior to α-fetoprotein. Combined miR-224 with α-fetoprotein, the sensitivity and specificity were increased to 0.882 and 0.808. Prognostic survival analysis showed low expression of miR-125b and high expression of miR-224 were associated with poor prognosis. Conclusion: miR-224 had a prominent diagnostic efficiency in early-stage HCC, with miR-224 and miR-125b being valuable in the prognostic diagnosis.

Bladder urothelial carcinoma (BLCA) is a common malignant tumor of the human urinary system, and a large proportion of BLCA patients have a poor prognosis. Therefore, there is an urgent need to find more efficient and sensitive biomarkers for the prognosis of BLCA patients in clinical practice. RNA sequencing (RNA‐seq) data and clinical information were obtained from The Cancer Genome Atlas, and 584 energy metabolism‐related genes (EMRGs) were obtained from the Reactome pathway database. Cox regression analysis and least absolute shrinkage and selection operator analysis were applied to assess prognostic genes and build a risk score model. The estimate and cibersort algorithms were used to explore the immune microenvironment, immune infiltration, and checkpoints in BLCA patients. Furthermore, we used the Human Protein Atlas database and our single‐cell RNA‐seq datasets of BLCA patients to verify the expression of 13 EMRGs at the protein and single‐cell levels. We constructed a risk score model; the area under the curve of the model at 5 years was 0.792. The risk score was significantly correlated with the immune markers M0 macrophages, M2 macrophages, CD8 T cells, follicular helper T cells, regulatory T cells, and dendritic activating cells. Furthermore, eight immune checkpoint genes were significantly upregulated in the high‐risk group. The risk score model can accurately predict the prognosis of BLCA patients and has clinical application value. In addition, according to the differences in immune infiltration and checkpoints, BLCA patients with the most significant benefit can be selected for immune checkpoint inhibitor therapy.