Clinical significance of miR-33b in glioma and its regulatory role in tumor cell proliferation, invasion and migration

miR-33b in human cancer: Mechanistic and clinical perspectives

The microRNAs (miRNAs), an extensive class of small noncoding RNAs (∼22 nucleotides), have been shown to have critical functions in various biological processes during development. miR-33b (or hsa-miR-33b) is down-regulated in cancer of multiple systems. Notably, at least 27 protein-coding genes can be targeted by miR-33b. miR-33b regulates the cell cycle, cell proliferation, various metabolism pathways, epithelial-mesenchymal transition (EMT), cancer cell invasion and migration, etc. In prostate cancer, Cullin 4B (CUL4B) can be recruited to the promoter to inhibit the expression of miR-33b. In gastric cancer, the hypermethylation of the CpG island regulated the expression of miR-33b. Besides, miR-33b could be negatively regulated by 7 competing-endogenous RNAs (ceRNAs), which are all long non-coding RNAs (lncRNAs). There are at least 4 signaling pathways, including NF-κB, MAP8, Notch1, and Wnt/β-catenin signaling pathways, which could be regulated partially by miR-33b. Additionally, low expression of miR-33b was associated with clinicopathology and prognosis in cancer patients. In addition, the aberrant expression of miR-33b was connected with the resistance of cancer cells to 5 anticancer drugs (cisplatin, docetaxel, bortezomib, paclitaxel, and daunorubicin). Importantly, our work systematically summarizes the aberrant expression of miR-33b in various neoplastic diseases and the effect of its downregulation on the biological behavior of cancer cells. Furthermore, this review focuses on recent advances in understanding the molecular regulation mechanisms of miR-33b. Moreso, the relationship between the miR-33b expression levels and the clinicopathological data and prognosis of tumor patients was summarized for the first time. Overall, we suggest that the current studies of miR-33b are insufficient but provide potential hints and direction for future miR-33b-related research.

DANCR promotes glioma cell autophagy and proliferation via the miR‑33b/DLX6/ATG7 axis

Long non‑coding RNAs (lncRNAs) are common in the human body. Misregulated lncRNA expression can cause a variety of diseases in the human body. The present study aimed to investigate the effect of lncRNA differentiation antagonizing non‑protein‑coding RNA (DANCR) on glioma proliferation and autophagy through the microRNA (miR)‑33b/distal‑less homeobox 6 (DLX6)/autophagy‑related 7 (ATG7) axis. Reverse transcription‑quantitative PCR was used to detect DANCR and miR‑33b expression. Cell Counting Kit‑8 assay and flow cytometry were used to detect cell proliferation and apoptosis, respectively. Transmission electron microscopy was used to determine the autophagy level by observing intracellular autophagosomes. A western blot assay was used to detect protein expression levels and determine the level of autophagy in different cells. The binding sites of miR‑33b and DANCR or DLX6 were detected using a dual‑luciferase reporter assay. A chromatin immunoprecipitation assay confirmed DLX6 as a transcript of ATG7. In vivo tumorigenesis of glioma cells was validated in nude mice. DANCR and DLX6 were highly expressed in glioma cells, while miR‑33b showed low expression in glioma cells. DANCR reduced the targeted binding of miR‑33b to DLX6 by sponging miR‑33b. The result verified that DANCR could promote ATG7 protein expression through miR‑33b/DLX6, promote intracellular autophagy and proliferation and reduce apoptosis. The present study identified the role of the DANCR/miR‑33b/DLX6/ATG7 axis in regulating autophagy, proliferation, and apoptosis in glioma cells, providing new ideas for glioma treatment.

MethylSPWNet and MethylCapsNet: Biologically Motivated Organization of DNAm Neural Networks, Inspired by Capsule Networks

DNA methylation (DNAm) alterations have been heavily implicated in carcinogenesis and the pathophysiology of diseases through upstream regulation of gene expression. DNAm deep-learning approaches are able to capture features associated with aging, cell type, and disease progression, but lack incorporation of prior biological knowledge. Here, we present modular, user-friendly deep-learning methodology and software, MethylCapsNet and MethylSPWNet, that group CpGs into biologically relevant capsules-such as gene promoter context, CpG island relationship, or user-defined groupings-and relate them to diagnostic and prognostic outcomes. We demonstrate these models' utility on 3,897 individuals in the classification of central nervous system (CNS) tumors. MethylCapsNet and MethylSPWNet provide an opportunity to increase DNAm deep-learning analyses' interpretability by enabling a flexible organization of DNAm data into biologically relevant capsules.

Circulating MicroRNAs as Promising Diagnostic Biomarkers for Patients With Glioma: A Meta-Analysis

Backgrounds and Purpose: Currently, circulating microRNAs (miRNAs) are considered to be non-invasive diagnostic biomarkers in a broad range of tumors. Nevertheless, so far, miRNAs have not been fully applied to the clinic for routine screening in glioma patients. Thus, our goal is to evaluate the diagnostic performance of circulating miRNAs for gliomas via a meta-analysis. The present study is registered on the PROSPERO website, with the number CRD42020195883. Methods: Literature retrieval was implemented in the PubMed, Embase, and Web of Science databases using the established search strategy. We pooled the sensitivity, specificity, and its 95% confidence intervals (CIs) for the included studies using the Stata 14.0 software. In addition, the heterogeneity between studies was assessed via the Q statistics and I ² values calculated by a Chi-square test. A bivariate random effects model was selected due to significant heterogeneity. Specifically, for exploring the factors influencing the heterogeneity, we implemented subgroup and meta-regression analyses. Ultimately, a Deek's funnel plot asymmetry test was used to estimate the potential publication bias. Results: A total of 18 articles covering 24 studies were included, containing 2,170 glioma patients and 1,456 healthy participants. The overall pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were 0.84 (95%CI: 0.79-0.87), 0.84 (95%CI: 0.80-0.88), 5.3 (95%CI: 4.1-6.8), 0.19 (95%CI: 0.15-0.25), 27 (95%CI: 18-41), and 0.91 (95%CI: 0.88-0.93), respectively. Additionally, the findings revealed that serum miRNAs and miRNA panels presented superior diagnostic performance. Conclusion: Thus, circulating miRNAs have the potential to serve as diagnostic biomarkers for gliomas, but need to be verified via a large pool of prospective studies. Additionally, specific miRNAs still need to be elucidated in the diagnosis of a glioma, especially in the early screening stage. The findings may provide diagnostic and therapeutic strategies for the glioma population.