MicroRNA‑718 serves a tumor‑suppressive role in non‑small cell lung cancer by directly targeting CCNB1

EMCMDA: predicting miRNA-disease associations via efficient matrix completion

Abundant researches have consistently illustrated the crucial role of microRNAs (miRNAs) in a wide array of essential biological processes. Furthermore, miRNAs have been validated as promising therapeutic targets for addressing complex diseases. Given the costly and time-consuming nature of traditional biological experimental validation methods, it is imperative to develop computational methods. In the work, we developed a novel approach named efficient matrix completion (EMCMDA) for predicting miRNA-disease associations. First, we calculated the similarities across multiple sources for miRNA/disease pairs and combined this information to create a holistic miRNA/disease similarity measure. Second, we utilized this biological information to create a heterogeneous network and established a target matrix derived from this network. Lastly, we framed the miRNA-disease association prediction issue as a low-rank matrix-complete issue that was addressed via minimizing matrix truncated schatten p-norm. Notably, we improved the conventional singular value contraction algorithm through using a weighted singular value contraction technique. This technique dynamically adjusts the degree of contraction based on the significance of each singular value, ensuring that the physical meaning of these singular values is fully considered. We evaluated the performance of EMCMDA by applying two distinct cross-validation experiments on two diverse databases, and the outcomes were statistically significant. In addition, we executed comprehensive case studies on two prevalent human diseases, namely lung cancer and breast cancer. Following prediction and multiple validations, it was evident that EMCMDA proficiently forecasts previously undisclosed disease-related miRNAs. These results underscore the robustness and efficacy of EMCMDA in miRNA-disease association prediction.

Bioinformatics Research and qRT-PCR Verify Hub Genes and a Transcription Factor-MicroRNA Feedback Network in Intervertebral Disc Degeneration

The present study explores the potentials of bioinformatics analysis to identify hub genes linked to intervertebral disc degeneration (IDD) and explored the potential molecular mechanism of transcription factor-microRNA regulatory network. Furthermore, the hub genes were identified through quantitative reverse transcriptase PCR (qRT-PCR). GEO database expression profile datasets for candidate genes (GSE124272) were downloaded. Genes that were differentially expressed (DEGs) were detected utilizing limma technique in the R programming language. Search Tool for the Retrieval of Interacting Genes/Proteins and NetworkAnalyst software identified hub genes. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis as well as Gene Ontology annotation of the DEGs were performed using Metascape. Using Bioinformatics data from the TRRUST, StarBase, and TransmiR databases, a TF-miRNA-hub genes network was constructed. qRT-PCR was utilized to confirm the result. As compared to healthy persons, 521 DEGs, comprising 203 down-regulated and 318 up-regulated genes, as well as 7 core genes, were found in people with IDD. Analysis revealed that all seven essential genes were under-expressed. qRT-PCR further confirmed the low expression of these seven important genes. Based on the TRRUST database, 16 TFs that could target five junction genes were then predicted. According to the StarBase database, four miRNAs were linked to crucial genes, while the TransmiR database predicted regulatory connections between four miRNAs and five TFs. The expression of the TP53-(hsa-miR-183-5p)-CCNB1 TF-miRNA-mRNA interaction network was discovered to be correlated with IDD. Throughout this investigation, a network of TF-miRNA-mRNA connections was built for investigation of the probable molecular mechanisms responsible for IDD. The identification of hub genes associated with IDD may reveal promising IDD treatment strategies.

Role of CCNB1, CENPF, and neutrophils in lung cancer diagnosis and prognosis

This study aimed to investigate CCNB1, CENPF, and Neutrophils as diagnostic predictors of lung cancer and to explore their association with clinical prognosis. Clinical data were obtained for a total of 52 patients. In addition, we downloaded 555 lung cancer-related samples from the cancer genome atlas (TCGA) database. Differentially expressed genes were further screened. Immune cell infiltration and survival analysis were performed. Immunohistochemistry was used to confirm gene expression. Peripheral blood analysis showed that neutrophil percentages were significantly reduced in patients with lung cancer. The least absolute shrinkage and selection operator and multivariate regression analysis revealed that CCNB1 and CENPF were lung cancer risk factors. Both CCNB1 and CENPF are overexpressed in lung cancer. The clinical diagnostic model constructed using CCNB1, CENPF, and neutrophils had a C-index of 0.994. This model area under the curve (AUC) and internal validation C-index values were 0.994 and 0.993, respectively. The elevated expression of CCNB1 and CENPF showed that the survival rate of lung cancer patients was reduced. CCNB1 and CENPF expression was positively correlated with the clinical stage of lung cancer. Further studies confirmed that CCNB1 and CENPF are overexpressed in lung cancer tissues. The clinically constructed model with high accuracy based on CCNB1, CENPF, and neutrophils demonstrated that these are crucial indicators for lung cancer diagnosis. High expression of CCNB1 and CENPF indicates a poor prognosis in patients with lung cancer.

Regulation and therapeutic potentials of microRNAs to non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, accounting for 80%-85% of total cases and leading to millions of deaths worldwide. Drug resistance is the primary cause of treatment failure in NSCLC, which urges scientists to develop advanced approaches for NSCLC treatment. Among novel approaches, the miRNA-based method has emerged as a potential approach as it allows researchers to modulate target gene expression. Subsequently, cell behaviors are altered, which leads to the death and the depletion of cancer cells. It has been reported that miRNAs possess the capacity to regulate multiple genes that are involved in various signaling pathways, including the phosphoinositide 3-kinase, receptor tyrosine kinase/rat sarcoma virus/mitogen-activated protein kinase, wingless/integrated, retinoblastoma, p53, transforming growth factor β, and nuclear factor-kappa B pathways. Dysregulation of these signaling pathways in NSCLC results in abnormal cell proliferation, tissue invasion, and drug resistance while inhibiting apoptosis. Thus, understanding the roles of miRNAs in regulating these signaling pathways may enable the development of novel NSCLC treatment therapies. However, a comprehensive review of potential miRNAs in NSCLC treatment has been lacking. Therefore, this review aims to fill the gap by summarizing the up-to-date information on miRNAs regarding their targets, impact on cancer-associated pathways, and prospective outcomes in treating NSCLC. We also discuss current technologies for delivering miRNAs to the target cells, including virus-based, non-viral, and emerging extracellular vesicle-based delivery systems. This knowledge will support future studies to develop an innovative miRNA-based therapy and select a suitable carrier to treat NSCLC effectively.

CTHRC1 promotes anaplastic thyroid cancer progression by upregulating the proliferation, migration, and invasion of tumor cells

Anaplastic thyroid carcinoma (ATC) is an extremely aggressive tumor with a high mortality rate and poor prognosis. However, the pathogenesis of ATC is complex and poorly understood, and the effective treatment options are limited. Analysis of data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases showed that collagen triple helix repeat containing-1 (CTHRC1) was specifically upregulated in ATC tissues and was negatively correlated with overall survival (OS) in thyroid carcinoma patients. In vitro knockdown of CTHRC1 dramatically decreased the proliferation, migration, and invasion abilities of ATC cells, and in vivo studies in BALB/c nude mice confirmed that CTHRC1 knockdown significantly inhibited tumor growth. Mechanistically, CTHRC1 knockdown was found to suppress the Wnt/β-catenin pathway and epithelial-mesenchymal transition (EMT) at the protein level. These findings suggest that CTHRC1 promotes the progression of ATC via upregulating tumor cell proliferation, migration, and invasion, which may be achieved by activating the Wnt/β-catenin pathway and EMT.

Screening for MicroRNA combination with engineered exosomes as a new tool against osteosarcoma in elderly patients

The most common primary malignant bone sarcoma is Osteogenic sarcoma (OS) which has a bimodal age distribution. Unfortunately, the treatment of OS was less effective for elderly patients than for younger ones. The study aimed to explore a new microRNA (miRNA) which can bind to combining engineered exosomes for treatment of older OS patients. Based on GSE65071 and miRNet 2.0, two up-regulated miRNAs (miR-328, miR-107) and seven down-regulated miRNAs (miR-133b, miR-206, miR-1-3p, miR-133a, miR-449a, miR-181daysay, miR-134) were selected. Next, we used FunRich software to predict the up-stream transcription factors (TFs) of differentially expressed miRNAs (DE-miRNAs). By comparing target genes predicted from DE-miRNAs with differentially expressed genes, we identified 12 down-regulated and 310 up-regulated mRNAs. For KEGG analysis, the most enriched KEGG pathway was Cell cycle, Spliceosome, and Protein digestion and absorption. By using protein-protein interactions network, topological analysis algorithm and GEPIA database, miR-449a /CCNB1 axis was identified. Experiments in vitro were conducted to confirm the results too. MiRNA-449a is down-regulated in osteosarcoma and suppresses cell proliferation by targeting CCNB1. Our findings not only reveal a novel mechanism of miR-449a /CCNB1 in OS but also had laid the groundwork for further investigation and analysis in the field of exosome engineering.

Regulation of apoptosis, autophagy and ferroptosis by non‑coding RNAs in metastatic non‑small cell lung cancer (Review)

Non-small cell lung cancer (NSCLC), a common type of cancer worldwide, is normally associated with a poor prognosis. It is difficult to treat successfully as it often metastasizes into brain or bone. Methods to facilitate the induction of effective programmed cell death (PCD) in NSCLC cells to reverse drug resistance, or to inhibit the invasion and migration of NSCLC cells, are currently under investigation. The present study summarized the regulatory functions of PCD, including apoptosis, autophagy and ferroptosis, in the context of NSCLC metastasis. It further summarized how regulatory agents, including long non-coding RNAs, circular RNAs and microRNAs, regulate PCD during the metastasis of NSCLC and characterized new potential diagnostic biomarkers of NSCLC metastasis.

CCNB1, Negatively Regulated by miR-559, Promotes the Proliferation, Migration, and Invasion of Ovarian Carcinoma Cells

Cyclin B1 (CCNB1) is regarded as an oncogene in multiple tumors. This work aims to investigate the expression, function, and related mechanisms of CCNB1 in ovarian carcinoma (OC). Three microarray datasets (GSE14407, GSE18520, and GSE54388) were obtained from the Gene Expression Omnibus (GEO) database and screened for differentially expressed genes (DEGs) of OC tissues and normal ovarian tissues. CCNB1 expression in OC tissues and paracancerous tissues was detected by immunohistochemistry. Kaplan-Meier plotter database was utilized to analyze the correlation between CCNB1 expression and the prognosis of OC patients. After the loss-of-function and gain-of-function cell models were established, cell counting kit-8 (CCK-8), bromo-deoxyuridine (BrdU), and transwell experiments were employed to examine the proliferation, migration, and invasion of OC cells, respectively. The targeting relationship between miR-559 and CCNB1 was verified using the dual-luciferase reporter gene experiment. The expressions of CCNB1 mRNA and miR-559 were detected by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Western blot was used to quantify the protein expression of CCNB1. In addition, xenograft nude mouse models were established to examine the effects of CCNB1 on lung metastasis in vivo. CCNB1 expression was markedly increased in OC tissues and cell lines. The overall survival, progression-free survival, and post-progression survival of OC patients with high CCNB1 expression were significantly shorter. OC cell proliferation, migration, and invasion were enhanced by CCNB1 overexpression while CCNB1 knockdown led to opposite effects. MiR-559 expression was remarkably reduced in OC tissues and cell lines, and miR-559 markedly suppressed the malignant characteristics of OC cells. Besides, miR-559 directly targeted the 3' UTR of CCNB1 mRNA and reduced CCNB1 expression at both the mRNA and protein levels. Overexpression of CCNB1 accelerated lung metastasis of OC cells in vivo. CCNB1, of which expression is modulated by miR-559, facilitates proliferation, migration, and invasion of OC cells, therefore, working as a potential therapeutic target of OC. This work provides new insights into the clinical diagnosis and treatment of OC.

A functional screen with metformin identifies microRNAs that regulate metabolism in colorectal cancer cells

Metformin inhibits oxidative phosphorylation and can be used to dissect metabolic pathways in colorectal cancer (CRC) cells. CRC cell proliferation is inhibited by metformin in a dose dependent manner. MicroRNAs that regulate metabolism could be identified by their ability to alter the effect of metformin on CRC cell proliferation. An unbiased high throughput functional screen of a synthetic micoRNA (miRNA) library was used to identify miRNAs that impact the metformin response in CRC cells. Experimental validation of selected hits identified miRNAs that sensitize CRC cells to metformin through modulation of proliferation, apoptosis, cell-cycle and direct metabolic disruption. Among eight metformin sensitizing miRNAs identified by functional screening, miR-676-3p had both pro-apoptotic and cell cycle arrest activity in combination with metformin, whereas other miRNAs (miR-18b-5p, miR-145-3p miR-376b-5p, and miR-718) resulted primarily in cell cycle arrest when combined with metformin. Investigation of the combined effect of miRNAs and metformin on CRC cell metabolism showed that miR-18b-5p, miR-145-3p, miR-376b-5p, miR-676-3p and miR-718 affected glycolysis only, while miR-1181 only regulated CRC respiration. MicroRNAs can sensitize CRC cells to the anti-proliferative effects of metformin. Identifying relevant miRNA targets may enable the design of innovative therapeutic strategies.

MiR-139-5p Targeting CCNB1 Modulates Proliferation, Migration, Invasion and Cell Cycle in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most frequent histological subtype of non-small cell lung cancer. Cyclin B1 (CCNB1) is the vital initiator and controller of mitosis. Studies have indicated that CCNB1 overexpression is closely associated with cell proliferation and tumorigenesis in many cancers. Thus, discovery of molecular mechanism of CCNB1 in LUAD is conducive to developing new diagnostic or therapeutic targets for LUAD. We acquired mature miRNA and mRNA expression information of LUAD from TCGA database, as well as related clinical data. CCNB1 expression in normal and LUAD tissue was analyzed. Relationship between CCNB1 and patient's survival and clinical stage was analyzed. Upstream regulatory gene miRNA of CCNB1 was predicted. qRT-PCR and western blot examined expression levels of CCNB1 and miR-139-5p in cells. CCK-8 tested cell proliferation. Scratch healing and Transwell determined cell migration and invasion. Flow cytometry analyzed the cell cycle. Dual-luciferase verified targeting relationship between the two genes. Compared to controls, CCNB1 expression was prominently high in LUAD patient samples, and associated with advanced tumor stages and shorter overall survival. MiR-139-5p expressed an evidently negative correlation with CCNB1 and was predicted to target CCNB1. MiR-139-5p mimics reduced CCNB1 mRNA and protein expression, and suppressed luciferase activity in a target-specific manner, as confirmed by a control construct with a mutated miR-139-5p binding site. CCNB1 overexpression fostered progression of LUAD cells. Mechanistically, miR-139-5p might negatively regulate CCNB1 in LUAD, thereby suppressing cell proliferation, migration, invasion and cell cycle.

Prediction of Genes Involved in Lung Cancer with a Systems Biology Approach Based on Comprehensive Gene Information

Over the past few years, hundreds of genes have been reported in relation to lung cancer. Systems biology studies can help validate this association and find the most valid genes to use in the diagnosis and treatment. We reviewed the candidate genes for lung cancer in 120 published articles from September 1, 1993, to September 1, 2020. We obtained 134 up- and 36 downregulated genes for lung cancer in this article. The genes extracted from the articles were imported to Search Tool for the Retrieval of Interacting genes/proteins (STRING) to construct the protein-protein interaction (PPI) Network and pathway enrichment. GO ontology and Reactome databases were used for describing the genes, average length of survival, and constructing networks. Then, the ClusterONE plugin of Cytoscape software was used to analyze and cluster networks. Hubs and bottleneck nodes were defined based on their degree and betweenness. Common genes between the ClusterONE plugin and network analysis consisted of seven genes (BRCA1-TP53-CASP3-PLK1-VEGFA-MDM2-CCNB1 and PLK1), and two genes (PLK1 and TYMS) were selected as survival factors. Our drug-gene network showed that CASP3, BRCA1, TP53, VEGFA, and MDM2 are common genes that are involved in this network. Also, among the drugs recognized in the drug-gene network, five drugs such as paclitaxel, oxaliplatin, carboplatin, irinotecan, and cisplatin were examined in different studies. It seems that these seven genes, with further studies and confirmatory tests, could be potential markers for lung cancer, especially PLK1 that has a significant effect on the survival of patients. We provide the novel genes into the pathogenesis of lung cancer, and we introduced new potential biomarkers for this malignancy.

Systematic identification of key functional modules and genes in esophageal cancer

BACKGROUND

Esophageal cancer is associated with high incidence and mortality worldwide. Differential expression genes (DEGs) and weighted gene co-expression network analysis (WGCNA) are important methods to screen the core genes as bioinformatics methods.

METHODS

The DEGs and WGCNA were combined to screen the hub genes, and pathway enrichment analyses were performed on the hub module in the WGCNA. The CCNB1 was identified as the hub gene based on the intersection between DEGs and the greenyellow module in WGCNA. Expression levels and prognostic values of CCNB1 were verified in UALCAN, GEPIA2, HCMDB, Kaplan-Meier plotter, and TIMER databases.

RESULTS

We identified 1,044 DEGs from dataset GSE20347, 1,904 from GSE29001, and 2,722 from GSE111044, and 32 modules were revealed by WGCNA. The greenyellow module was identified as the hub module in the WGCNA. CCNB1 gene was identified as the hub gene, which was upregulated in tumour tissues. Moreover, esophageal cancer patients with higher expression of CCNB1 showed a worse prognosis. However, CCNB1 'might not play an important role in immune cell infiltration.

CONCLUSIONS

Based on DEGs and key modules related to esophageal cancer, CCNB1 was identified as the hub gene, which offered novel insights into the development and treatment of esophageal cancer.