Purpose: Autophagy is a major catabolic system by which eukaryotic cells undergo self-degradation of damaged, defective, or unwanted intracellular components. An abnormal autophagic level is implicated in the pathogenesis of multiple diseases, including cancers. The aim of this study is to explore the prognostic value of autophagy in bladder cancer (BC), which is a major cause of cancer-related death globally. Patients and methods: First, 27 differentially expressed autophagy-related genes (ARGs) were identified in BC patients based on The Cancer Genome Atlas (TCGA) database. Functional enrichment analyses hinted that autophagy may act in a tumor-suppressive role in the initiation of BC. Then, the Cox proportional hazard regression model were employed to identify three key prognostic ARGs (JUN, MYC, and ITGA3), which were related with overall survival (OS) significantly in BC. The three genes represented important clinical significance and prognostic value in BC. Then a prognostic index (PI) was constructed. Results: The PI was constructed based on the three genes, and significantly stratified BC patients into high- and low-risk groups in terms of OS (HR=1.610, 95% CI=1.200–2.160, P =0.002). PI remained as an independent prognostic factor in multivariate analyses (HR=2.355, 95% CI=1.483–3.739, P <0.001). When integrated with clinical characteristics of age and stage, an autophagy-clinical prognostic index (ACPI) was finally validated, which had improved performance in predicting OS of BC patients (HR=2.669, 95% CI=1.986–3.587, P <0.001). The ACPI was confirmed in datasets of GSE13507 (HR=7.389, 95% CI=3.645–14.980, P <0.001) and GSE31684 (HR=1.665, 95% CI=0.872–3.179, P =0.122). Conclusion: This study provides a potential prognostic signature for predicting prognosis of BC patients and molecular insights of autophagy in BC.

Background Hepatocellular carcinoma (HCC) is the second-highest cause of malignancy-related death worldwide, and many physiological and pathological processes, including cancer, are regulated by microRNAs (miRNAs). miR-193a-3p is an anti-oncogene that plays an important part in health and disease biology by interacting with specific targets and signals. Methods In vitro assays were performed to explore the influences of miR-193a-3p on the propagation and apoptosis of HCC cells. The sequencing data for HCC were obtained from The Cancer Genome Atlas (TCGA), and the expression levels of miR-193a-3p in HCC and non-HCC tissues were calculated. The differential expression of miR-193a-3p in HCC was presented as standardized mean difference (SMD) with 95% confidence intervals (CIs) in Stata SE. The impact of miR-193a-3p on the prognoses of HCC patients was determined by survival analysis. The potential targets of miR-193a-3p were then predicted using miRWalk 2.0 and subjected to enrichment analyses, including Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Protein-Protein Interaction (PPI) network analysis. The interaction between miR-193a-3p and one predicted target, Cyclin D1 (CCND1), was verified by dual luciferase reporter assays and Pearson correlation analysis. Results MiR-193a-3p inhibited the propagation and facilitated the apoptosis of HCC cells in vitro. The pooled SMD indicated that miR-193a-3p had a low level of expression in HCC (SMD: −0.88, 95% CI [−2.36 −0.59]). Also, HCC patients with a higher level of miR-193a-3p expression tended to have a favorable overall survival (OS: HR = 0.7, 95% CI [0.43–1.13], P = 0.14). For the KEGG pathway analysis, the most related pathway was “proteoglycans in cancer”, while the most enriched GO term was “protein binding”. The dual luciferase reporter assays demonstrated the direct interaction between miR-193a-3p and CCND1, and the Pearson correlation analysis suggested that miR-193a-3p was negatively correlated with CCND1 in HCC tissues (R =  − 0.154, P = 0.002). Conclusion miR-193a-3p could suppress proliferation and promote apoptosis by targeting CCND1 in HCC cells. Further, miR-193a-3p can be used as a promising biomarker for the diagnosis and treatment of HCC in the future.

Lung adenocarcinoma (LUAD), the main subtype of non-small cell lung cancer, is known to be regulated by various microRNAs (miRs/miRNAs); however, the role of miR-198-5p in LUAD has not been clarified. In the present study, the clinical value of miR-198-5p in LUAD and its potential molecular mechanism was evaluated. miR-198-5p expression was examined by reverse transcription-quantitative PCR (RT-qPCR) in 101 paired LUAD and adjacent normal lung tissues. Subsequently, the miR-198-5p expression level was determined from microarray data from the Gene Expression Omnibus, ArrayExpress and by meta-analyses. Furthermore, the target mRNAs of miR-198-5p from 12 miRNA-mRNA predictive tools were intersected with The Cancer Genome Atlas (TCGA)-based differentially expressed genes. In addition, Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to determine the possible mechanism of miR-198-5p in LUAD. The Search Tool for the Retrieval of Interacting Genes/Proteins database was employed to construct a protein-protein interaction network among the potential target genes of miR-198-5p. The results showed that miR-198-5p expression was lower in LUAD tissues than in adjacent non-cancerous lung tissues (4.469±2.495 vs. 5.301±2.502; P=0.015). Meta-analyses, including the data from the present study and online microarray data, also verified the downregulation of miR-198-5p in 584 cases of LUAD. The expression of miR-198-5p was associated with the age, blood vessel invasion, Tumor-Node-Metastasis stage, and lymph node metastasis of patients with LUAD and served as an independent prognostic factor for survival. The hub genes of miR-198-5p were upregulated in LUAD, according to TCGA and The Human Protein Atlas. For the KEGG pathway analysis, the most enriched KEGG pathway was the p53 signaling pathway (P=1.42×10 −6 ). These findings indicated that the downregulation of miR-198-5p may play a pivotal role in the development of LUAD by targeting various signaling pathways.