Prognostic values and prospective pathway signaling of MicroRNA-182 in ovarian cancer: a study based on gene expression omnibus (GEO) and bioinformatics analysis

Cancer pharmacoinformatics: Databases and analytical tools

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

Identification of RTP4 facilitating ovarian cancer by bioinformatics analysis and experimental validation

Ovarian cancer (OV) is the most malignant gynecological tumor in women, with poor prognosis and high mortality rate. This study aims to identify hub genes in OV and explore the role of Receptor transporter 4 (RTP4) in OV progression. Common differentially expressed genes (DEGs) were screened from two microarray datasets. GO and KEGG enrichment analysis were performed. Protein-protein interaction (PPI) network was constructed by STING. Kaplan-Meier plotter was used to analyze prognosis. The effect of target gene on immune infiltration was analyzed by TIMER. The proliferation, migration, and invasion of OV cells were measured by CCK-8, wound healing assay, and trans-well assay, respectively. A total of 293 common DEGs were selected from GSE12470 and GSE16709 datasets. Hub genes, EPCAM, KIFC1, RTP4, TAGLN, and ZFP36 were selected by PPI network. Kaplan-Meier plotter demonstrated that high expression of RTP4 was related to low overall survival in OV patients. The TIMER result showed that high expression of RTP4 promoted immune infiltration of CD8+ T cells, B cells, neutrophils, and dendritic cells in OV. Moreover, silencing RTP4 significantly inhibited the proliferation, migration, and invasion of OV cells. RTP4 was associated with the poor prognosis in OV. In summary, silencing RTP4 inhibited the proliferation, migration, and invasion of OV cells, having the potential to be a novel therapeutic target for OV.

Targeting tumour markers in ovarian cancer treatment

Ovarian cancers (OC) are the most common, lethal, and stage-dependent cancers at the global level, specifically in female patients. Targeted therapies involve the administration of drugs that specifically target the alterations in tumour cells responsible for their growth, proliferation, and metastasis, with the aim of treating particular patients. Presently, within the realm of gynaecological malignancies, specifically in breast and OCs, there exist various prospective therapeutic targets encompassing tumour-intrinsic signalling pathways, angiogenesis, homologous-recombination deficit, hormone receptors, and immunologic components. Breast cancers are often detected in advanced stages, primarily due to the lack of a reliable screening method. However, various tumour markers have been extensively researched and employed to evaluate the condition, progression, and effectiveness of medication treatments for this ailment. The emergence of recent technological advancements in the domains of bioinformatics, genomics, proteomics, and metabolomics has facilitated the exploration and identification of hitherto unknown biomarkers. The primary objective of this comprehensive review is to meticulously investigate and analyze both established and emerging methodologies employed in the identification of tumour markers associated with OC.

Cerebrospinal fluid exosomal microRNAs as biomarkers for diagnosing or monitoring the progression of non-small cell lung cancer with leptomeningeal metastases

Non-small-cell lung cancer (NSCLC) has a terrible consequence called leptomeningeal metastases (LM). It is crucial to look for novel biomarkers because none of the known biomarkers could effectively reflect the oncogenesis, progression and therapeutic responses of LM. Exosomal miRNAs from plasma have a critical function in lung cancer, according to growing data. However, unique biomarkers of cerebrospinal fluid (CSF) are more representative for patients with LM, which have not been reported. Here, we explore the possibility of using CSF-derived exosomal microRNAs as potential biomarkers for NSCLC-LM. Nine NSCLC-LM patients who received regular intrathecal chemotherapy with permetexed were divided into a partial response (PR) group and a progressive disease (PD) group. CSF samples were taken from all patients before and after intrathecal treatment and five non-cancerous controls. Using the size exclusion chromatography (SEC) method, the exosome microRNAs were isolated and profiled. Between LM patients and controls, 56 differentially expressed genes (DEGs) were found, of which three highly elevated diagnostic biomarkers (hsa-miR-183-5p, hsa-miR-96-5p and hsa-miR-182-5p) were ruled out. The two most significant DEGs between the untreated PR group and the PD group were determined to be upregulated hsa-miR-509-3p and downregulated hsa-miR-449a, and they may serve as potential indicators of intrathecal anti-pemetrexed treatment. Hsa-miR-1-3p increased gradually with the intrathecal chemotherapy in the PR group, which might offer a new approach to screen optimal patients and estimate the efficacy. This study revealed specific CSF exosomal miRNAs profile and dynamic changes of patients with NSCLC-LM for the first time and identified several potential exosomal miRNA biomarkers in diagnosis, drug resistance and prognosis.

Smart carbon-based sensors for the detection of non-coding RNAs associated with exposure to micro(nano)plastics: an artificial intelligence perspective

Micro(nano)plastics (MNPs) are pervasive environmental pollutants that individuals eventually consume. Despite this, little is known about MNP's impact on public health. In this article, we assess the evidence for potentially harmful consequences of MNPs in the human body, concentrating on molecular toxicity and exposure routes. Since MNPs are present in various consumer products, foodstuffs, and the air we breathe, exposure can occur through ingestion, inhalation, and skin contact. MNPs exposure can cause mitochondrial oxidative stress, inflammatory lesions, and epigenetic modifications, releasing specific non-coding RNAs in circulation, which can be detected to diagnose non-communicable diseases. This article examines the most fascinating smart carbon-based nanobiosensors for detecting circulating non-coding RNAs (lncRNAs and microRNAs). Carbon-based smart nanomaterials offer many advantages over traditional methods, such as ease of use, sensitivity, specificity, and efficiency, for capturing non-coding RNAs. In particular, the synthetic methods, conjugation chemistries, doping, and in silico approach for the characterization of synthesized carbon nanodots and their adaptability to identify and measure non-coding RNAs associated with MNPs exposure is discussed. Furthermore, the article provides insights into the use of artificial intelligence tools for designing smart carbon nanomaterials.

Exosomal miRNA-profiling of pleural effusion in lung adenocarcinoma and tuberculosis

Background

Pleural effusion (PE) caused by lung cancer is prevalent, and it is difficult to differentiate it from PE caused by tuberculosis. Exosome-based liquid biopsy offers a non-invasive technique to diagnose benign and malignant PE. Exosomal miRNAs are potential diagnostic markers and play an essential role in signal transduction and biological processes in tumor development. We hypothesized that exosomal miRNA expression profiles in PE would contribute to identifying its diagnostic markers and elucidating the molecular basis of PE formation in lung cancer.

Methods

The exosomes from PE caused by lung adenocarcinoma (LUAD) and pulmonary tuberculosis were isolated and verified by transmission electron microscopy. The exosomal miRNA profiles were identified using deep sequencing and validated with quantitative real-time PCR (qRT-PCR). We performed bioinformatic analysis for differentially expressed miRNAs to explore how exosomal miRNAs regulate pleural effusion.

Results

We identified 99 upregulated and 91 downregulated miRNAs in malignant pleural effusion (MPE) compared to tuberculous pleural effusion (TPE). Seven differentially expressed miRNAs (DEmiRNAs) were validated by qRT-PCR, out of which 5 (71.4%) were confirmed through sequencing. Gene Ontology (GO) analysis revealed that most exosomal miRNAs target genes were involved in regulating cellular processes and nitrogen compound metabolism. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, the exosomal miRNAs target genes were mainly involved in Fc gamma R-mediated phagocytosis, Rap1 signaling pathway, and breast cancer. The hub genes, including ITGAM, FOXO1, MAPK14, YWHAB, GRIN1, and PRF1, were screened through plug-in cytoHubba. The PFR1 was identified as a critical gene in MPE formation using single-cell sequencing analysis. Additionally, we hypothesized that tumor cells affected natural killer cells and promoted the generation of PE in LUAD via the exosomal hsa-miR-3120-5p-PRF1 axis.

Conclusions

We identified exosomal miRNA profiles in LUAD-MPE and TPE, which may help in the differential diagnosis of MPE and TPE. Bioinformatic analysis revealed that these miRNAs might affect PE generation through tumor immune response in LUAD. Our results provided a new theoretical basis for understanding the function of exosomal miRNAs in LUAD-MPE.

Effect of Bone Marrow Mesenchymal Stem Cells (BMSCs) with High miR-183-5p Expression on Ovarian Cancer Cells by Regulating Signal Transducer and Activator of Transcription 3 (STAT3)

Currently, the treatment for ovarian cancer (OC) is not satisfactory. The microRNAs may have an important function in tumor pathogenesis. miR-183-5p involves in several tumors. However, its effect on OC cells is unclear. The BMSCs could regulate the micro-environment of tumor and participate in tumor procession. In this study, effect of BMSCs with highly-expressed miR-183-5p on OC cells was assessed. The BMSCs with highly-expressed miR-183-5p was established and co-cultivated with OC cell line SKOV3 followed by measuring miR-183-5p level by PCR, STAT3 and ADAM9 expression by western blot. miR-183-5p level in OC cells was reduced and further decreased after co-culture with BMSCs along with enhance cell proliferation and upregulated STAT3 expression (P < 0.05). In addition, miR-183-5p level was increased in BMSCs with highly-expressed miR-183-5p and STAT3 expression was reduced along with restrained cell proliferation (P < 0.05). In conclusion, miR-183-5p in OC cells is downregulated and malignant biological behaviors of OC cells are restrained by BMSCs with highly-expressed miR-183-5p possibly through regulating the expression of STAT3.

Recent advances of non-coding RNAs in ovarian cancer prognosis and therapeutics

Ovarian cancer (OC) is the third most common gynecological malignancy with the highest mortality worldwide. OC is usually diagnosed at an advanced stage, and the standard treatment is surgery combined with platinum or paclitaxel chemotherapy. However, chemoresistance inevitably appears coupled with the easy recurrence and poor prognosis. Thus, early diagnosis, predicting prognosis, and reducing chemoresistance are of great significance for controlling the progression and improving treatment effects of OC. Recently, much insight has been gained into the non-coding RNA (ncRNA) that is employed for RNAs but does not encode a protein, and many types of ncRNAs have been characterized including long-chain non-coding RNAs, microRNAs, and circular RNAs. Accumulating evidence indicates these ncRNAs play very active roles in OC progression and metastasis. In this review, we briefly discuss the ncRNAs as biomarkers for OC prognosis. We focus on the recent advances of ncRNAs as therapeutic targets in preventing OC metastasis, chemoresistance, immune escape, and metabolism. The novel strategies for ncRNAs-targeted therapy are also exploited for improving the survival of OC patients.

Identification of Hub Genes and Key Pathways Associated with Follicular Lymphoma

Follicular lymphoma (FL) is the second most prevalent form of non-Hodgkin lymphoma (NHL) and accounts for almost 20% of all NHL cases. Although FL patients' overall survival rates have steadily increased, there is still no accepted standard of care for individuals who experience recurrence or resistance to treatment. Hence, it is needed to evaluate the precise molecular cascades underlying FL to develop efficient diagnostic and treatment approaches. Herein, we aimed to evaluate variations in gene expression profiles, explore the underlying mechanisms, and find new FL targets. In the present study, Gene Expression Omnibus (GEO) database was employed to evaluate microarray datasets including GSE32018 and GSE55267. R software was employed to evaluate differentially expressed genes (DEGs) between FL and noncancer samples. The DEGs were evaluated using GO, KEGG pathway enrichment analysis, and PPI network to evaluate hub genes, which were then, examined using gene function enrichment analysis. According to the obtained results, a total of 190 upregulated and 162 downregulated DEGs were evaluated. Following the generation of PPI networks, 15 hub genes in highly connected upregulated DEGs were selected including FN1, MMP9, CCL2, CD8A, POSTN, CCR5, COL3A1, CXCL12, VCAM1, COL1A2, CCL5, SPARC, TIMP1, CXCL9, and IL18. The GO enrichment evaluation of the underlined hub genes indicated that the immunological response was the most considerably enriched term. Twelve significant cascades were found using the KEGG pathway analysis, most of which were linked to cellular structure and immunity. Our findings suggested that FN1, SPARC, POSTN, MMP9, and VCAM1 genes are potential biomarkers of FL, and cellular immunity contributes to the pathogenesis of FL. Moreover, the unique DEGs and cascades found in the present study may present new perspectives on the molecular basis of FL's underlying mechanisms as well as a new understanding of FL's future precise management.

Epigenetic Mechanisms and Therapeutic Targets in Chemoresistant High-Grade Serous Ovarian Cancer

High-grade serous ovarian cancer (HGSOC) is the most common ovarian cancer subtype, and the overall survival rate has not improved in the last three decades. Currently, most patients develop recurrent disease within 3 years and succumb to the disease within 5 years. This is an important area of research, as the major obstacle to the treatment of HGSOC is the development of resistance to platinum chemotherapy. The cause of chemoresistance is still largely unknown and may be due to epigenetics modifications that are driving HGSOC metastasis and treatment resistance. The identification of epigenetic changes in chemoresistant HGSOC enables the development of epigenetic modulating drugs that may be used to improve outcomes. Several epigenetic modulating drugs have displayed promise as drug targets for HGSOC, such as demethylating agents azacitidine and decitabine. Others, such as histone deacetylase inhibitors and miRNA-targeting therapies, demonstrated promising preclinical results but resulted in off-target side effects in clinical trials. This article reviews the epigenetic modifications identified in chemoresistant HGSOC and clinical trials utilizing epigenetic therapies in HGSOC.

Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer

Background

Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer.

Methods

One mRNA dataset (GSE28739) and one miRNA dataset (GSE25202) were acquired from Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) between platinum-resistant and platinum-sensitive ovarian cancer patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed using the DAVID to present the most visibly enriched pathways. Protein–protein interaction (PPI) of these DEGs was constructed based on the information of the STRING database. Hub genes related to platinum resistance were visualized by Cytoscape software. Then, we chose seven interested hub genes to further validate using qRT-PCR in A2780 ovarian cancer cell lines. And, at last, the TF-miRNA-target genes regulatory network was predicted and constructed using miRNet software.

Results

A total of 63 upregulated DEGs, 124 downregulated DEGs, four upregulated miRNAs and six downregulated miRNAs were identified. From the PPI network, the top 10 hub genes were identified, which were associated with platinum resistance. Our further qRT-PCR showed that seven hub genes (BUB1, KIF2C, NUP43, NDC80, NUF2, CCNB2 and CENPN) were differentially expressed in platinum-resistant ovarian cancer cells. Furthermore, the upstream transcription factors (TF) for upregulated DE-miRNAs were SMAD4, NFKB1, SMAD3, TP53 and HNF4A. Three overlapping downstream target genes (KIF2C, STAT3 and BUB1) were identified by miRNet, which was regulated by hsa-miR-494.

Conclusions

The TF-miRNA–mRNA regulatory pairs, that is TF (SMAD4, NFKB1 and SMAD3)-miR-494-target genes (KIF2C, STAT3 and BUB1), were established. In conclusion, the present study is of great significance to find the key genes of platinum resistance in ovarian cancer. Further study is needed to identify the mechanism of these genes in ovarian cancer.

Risk Scores Based on Six Survival-Related RNAs in a Competing Endogenous Network Composed of Differentially Expressed RNAs Between Clear Cell Renal Cell Carcinoma Patients Carrying Wild-Type or Mutant Von Hippel-Lindau Serve Well to Predict Malignancy and Prognosis

Clear cell renal cell carcinoma (ccRCC) carrying wild-type Von Hippel–Lindau (VHL) tumor suppressor are more invasive and of high morbidity. Concurrently, competing endogenous RNA (ceRNA) network has been suggested to play an important role in ccRCC malignancy. In order to understand why the patients carrying wild-type VHL gene have high degrees of invasion and morbidity, we applied bioinformatics approaches to identify 861 differentially expressed RNAs (DE-RNAs) between patients carrying wild-type and patients carrying mutant VHL from The Cancer Genome Atlas (TCGA) database, established a ceRNA network including 122 RNAs, and elected six survival-related DE-RNAs including Linc00942, Linc00858, RP13_392I16.1, hsa-miR-182-5p, hsa-miR-183-5p, and PAX3. Examining clinical samples from our hospital revealed that patients carrying wild-type VHL had significantly higher levels of all six RNAs than those carrying mutant VHL. Patients carrying wild-type VHL had significantly higher risk scores, which were calculated based on expression levels of all six RNAs, than those carrying mutant VHL. Patients with higher risk scores had significantly shorter survival times than those with lower risk scores. Therefore, the risk scores serve well to predict malignancy and prognosis.

MicroRNAs as Biomarkers for Early Diagnosis, Prognosis, and Therapeutic Targeting of Ovarian Cancer

Ovarian cancer is the major cause of gynecologic cancer-related mortality. Regardless of outstanding advances, which have been made for improving the prognosis, diagnosis, and treatment of ovarian cancer, the majority of the patients will die of the disease. Late-stage diagnosis and the occurrence of recurrent cancer after treatment are the most important causes of the high mortality rate observed in ovarian cancer patients. Unraveling the molecular mechanisms involved in the pathogenesis of ovarian cancer may help find new biomarkers and therapeutic targets for ovarian cancer. MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression, mostly at the posttranscriptional stage, through binding to mRNA targets and inducing translational repression or degradation of target via the RNA-induced silencing complex. Over the last two decades, the role of miRNAs in the pathogenesis of various human cancers, including ovarian cancer, has been documented in multiple studies. Consequently, these small RNAs could be considered as reliable markers for prognosis and early diagnosis. Furthermore, given the function of miRNAs in various cellular pathways, including cell survival and differentiation, targeting miRNAs could be an interesting approach for the treatment of human cancers. Here, we review our current understanding of the most updated role of the important dysregulation of miRNAs and their roles in the progression and metastasis of ovarian cancer. Furthermore, we meticulously discuss the significance of miRNAs as prognostic and diagnostic markers. Lastly, we mention the opportunities and the efforts made for targeting ovarian cancer through inhibition and/or stimulation of the miRNAs.

MiRNA-182-5p aggravates experimental ulcerative colitis via sponging Claudin-2

Tight junction proteins play crucial roles in maintaining the integrity of intestinal mucosal barrier. MiRNA-182-5p is capable of targeting claudin-2 which is one of the vital tight junction proteins and the effect and mechanism of miRNA-182-5p was explored here in the DSS-induced colitis model. The pathological conditions were evaluated via hematoxylin and eosin staining. The gene expression level was assessed via PCR. Quantitative immunohistochemistry analysis was performed for the measurement of claudin-2. microRNA.org online tool was used for target gene prediction. Luciferase reporter assay and RNA pull-down assay were performed to detect the target of miRNA-182-5p. The inflammatory and oxidative stress level were measured using corresponding kits. MiRNA-182-5p was highly expressed in colitis model and miRNA-182-5p inhibitor exerted protective effects on colitis induced by DSS in mice. The protective effects includded improvement of pathological changes, increases in anti-inflammation and anti-oxidative genes, and up-regulation of TGF-β1. Claudin-2 mRNA was predicted as the target of miRNA-182-5p, which was validated via luciferase reporter assay and RNA pull-down assay. Claudin-2 overexpression was found in miRNA-182-5p inhibitor group. Consistent with the role of miRNA-182-5p, claudin-2 overexpression also exerted protective effects on DSS-induced colitis in mice. Inhibition of miRNA-182-5p exerted protective effects on colitis via targeting and upregulating claudin-2. The findings in study provide a new therapeutic strategy for colitis treatment and lay the foundation for future study.

Role of miR-182/PDCD4 axis in aggressive behavior of prostate cancer in the African Americans

Background

Prostate cancer is one of the most commonly diagnosed cancers among men. African Americans (AA) are at an increased risk of developing prostate cancer compared to European Americans (EA). miRNAs play a critical role in these tumors, leading to tumor progression. In this study, we investigated the role of miR-182 in racial disparity in prostate cancer.

Results

We found significantly increased levels of miR-182 in prostate cancer tissues compared to BPH. Also, miR-182 shows increased expression in AA prostate cancer cell line and tissue samples compared to EA. We performed biochemical recurrence (BCR) - free survival time in AA and EA patients and found that high miR-182 expression had significantly shorter BCR-free survival than patients with low miR-182 expression (P = 0.031). To elucidate the role of miR-182, we knocked down miR-182 in EA (DU-145 and LNCaP) and AA (MDA-PCa-2b) cell lines and found an increase in apoptosis, arrest of the cell cycle, and inhibition of colony formation in the AA cell line to a greater extent than EA cell lines.

Conclusions

Our results showed that PDCD4 is a direct miR-182 target and its inhibition is associated with aggressiveness and high Gleason grade in prostate cancer among AA. These findings show that miR-182 is highly expressed in AA patients and miR-182 may be a target for effective therapy in AA patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08723-6.

miR-182-5p Serves as an Oncogene in Lung Adenocarcinoma through Binding to STARD13

Lung cancer as one of the commonest invasive malignancies is featured by high morbidity and mortality, wherein lung adenocarcinoma (LUAD) is the most prevalent subtype. Accumulating evidence exhibited that microRNAs are involved in LUAD occurrence and progression. In this study, miR-182-5p was observed to increase in both LUAD tissue and cell lines. Overexpression of miR-182-5p could prominently facilitate cell proliferation, migration, and invasion in LUAD. Through bioinformatics analysis, STARD13 was theorized as the target gene of miR-182-5p, which was lowly expressed in LUAD. Further molecular experiments manifested that miR-182-5p bound to the 3'-untranslated region of STARD13, and there was an inverse correlation between STARD13 and miR-182-5p in LUAD. Rescue experiments demonstrated that silencing STARD13 conspicuously restored the inhibitory effect of decreased miR-182-5p on cell proliferation, migration, and invasion in LUAD. Together, our findings revealed novel roles of the miR-182-5p/STARD13 axis in LUAD progression.

MicroRNA miR-502-5p inhibits ovarian cancer genesis by downregulation of GINS complex subunit 2

Ovarian cancer (OC) is one of the most common malignancies with high incidence and mortality and the eighth most common cancer-associated mortality in women worldwide. Aberrant expression of the GINS complex subunit 2 (GINS2) gene and miR-502-5p has been associated with cancer progression. This study aims to investigate the specific molecular mechanism of the miR-502-5p-GINS2 axis in OC. GINS2 and miR-502-5p expression in OC tissues and cell lines was measured using RT-qPCR. Next, we investigated the interaction between miR-502-5p and GINS2 using a luciferase assay. The role of the miR-502-5p-GINS2 axis was detected by assessing cell proliferation, migration, and apoptosis levels, such as caspase-3 activity and caspase-3 protein expression, in the OC cell lines CaOV3 and SKOV3, respectively. MiR-502-5p expression was decreased, and GINS2 expression was dramatically elevated in OC tissues and cells. Upregulation of miR-502-5p expression repressed cellular proliferation and migration levels but increased the cellular apoptosis level. GINS2 overexpression enhanced the proliferation and migration levels but hampered OC cell apoptosis. Moreover, miR-502-5p inhibited GINS2 expression and suppressed OC tumorigenesis. miR-502-5p targeting GINS2 suppressed OC progression by inhibiting cell growth and promoting cell apoptosis. Hence, we provide a comprehensive understanding of OC involving both miR-502-5p and GINS2, which might be effective therapeutic targets for OC patients.

A Comprehensive Analysis of the Downregulation of miRNA-1827 and Its Prognostic Significance by Targeting SPTBN2 and BCL2L1 in Ovarian Cancer

Background: Previous studies demonstrated that miRNA-1827 could repress various cancers on proliferation, angiogenesis, and metastasis. However, little attention has been paid to its role in ovarian cancer as a novel biomarker or intervention target, especially its clinical significance and underlying regulatory network.

Methods: A meta-analysis of six microarrays was adopted here to determine the expression trend of miRNA-1827, and was further validated by gene expression profile data and cellular experiments. We explored the functional annotations through enrichment analysis for the differentially expressed genes targeted by miRNA-1827. Subsequently, we identified two hub genes, SPTBN2 and BCL2L1, based on interaction analysis using two online archive tools, miRWALK (it consolidates the resources of 12 miRNA-focused servers) and Gene Expression Profiling Interactive Analysis (GEPIA). Finally, we validated their characteristics and clinical significance in ovarian cancer.

Results: The comprehensive meta-analysis revealed that miRNA-1827 was markedly downregulated in clinical and cellular specimens. Transfection of the miRNA-1827 mimic could significantly inhibit cellular proliferation. Concerning its target genes, they were involved in diverse biological processes related to tumorigenesis, such as cell proliferation, migration, and the apoptosis signaling pathway. Moreover, interaction analysis proved that two hub genes, SPTBN2 and BCL2L1, were highly associated with poor prognosis in ovarian cancer.

Conclusion: These integrated bioinformatic analyses indicated that miRNA-1827 was dramatically downregulated in ovarian cancer as a tumor suppressor. The upregulation of its downstream modulators, SPTBN2 and BCL2L1, was associated with an unfavorable prognosis. Thus, the present study has identified miRNA-1827 as a potential intervention target for ovarian cancer based on our bioinformatic analysis processes.

MicroRNA-182 is a potential biomarker for prognosis of gastric cancer: A protocol for meta-analysis and bioinformatics analysis

BACKGROUND

Being the second leading cause of cancer death in the world, gastric cancer is a common malignant tumor in digestive system. Most patients were diagnosed in advanced stage and had poor prognosis. In recent years, related studies have displayed that MicroRNA-182 (miRNA-182) can promote the proliferation, infiltration, metastasis and drug resistance of tumor cells, so it can be used as a new molecular marker for the early diagnosis, prognosis, and treatment of tumors. However, the expression and prognosis of miRNA-182 in gastric cancer are not clear. Therefore, this study conducted a meta-analysis to further clarify the relationship between the expression of miRNA-182 in gastric cancer and prognosis. In addition, a bioinformatics analysis was adopted to further analyze the possible molecular mechanism of miRNA-182, so as to provide a theoretical basis for the diagnosis, treatment, and prognosis of patients suffering from gastric cancer.

METHODS

The following electronic databases were searched on computer: Wanfang, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, the Chongqing VIP Chinese Science and Technology Periodical Database, PubMed, Embase, and Web of Science databases. The retrieval time is set to build the database until April 2021. Combined hazard ratios (HRs) and 95% confidence intervals (95% CIs) were used to evaluate the effects of miRNA-182 on the prognosis of gastric cancer. Stata 16.0 software was applied for the meta-analysis. The expression of miRNA-182 in gastric cancer was analyzed by Gene Expression Omnibus database and The Cancer Genome Atlas database. The survival curve of miRNA-182 differential expression was analyzed by OncomiR. The target genes of miRNA-182 were predicted by TargetScan, miRBase, miRTarBase, starBase V2.0, and miRWalk. The target genes were obtained by the intersection of Wayne diagram. DAVID database was used for gene ontology (GO) and Kyoto encyclopedia of genes and genomes enrichment analysis. STRING database and Cytoscape were applied to construct Protein-protein interaction network to obtain key genes (hub gene). The expression of hub gene in gastric cancer was analyzed by gene expression profiling interactive analysis. The survival curve between hub gene and prognosis of gastric cancer was drawn by Kaplan-Meier Plotter database. TIMER database was used to analyze the relationship between hub gene expression and immune cell infiltration in gastric cancer.

RESULTS

The results of this meta-analysis will be submitted to a peer-reviewed journal for publication.

CONCLUSION

This study provides high-quality evidence support for the expression of miRNA-182 and the prognosis of gastric cancer. Through bioinformatics analysis, we further discussed the mechanism of miRNA-182 in gastric cancer and the understanding of related pathways.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/EHJ6X.

WDNE: an integrative graphical model for inferring differential networks from multi-platform gene expression data with missing values

The mechanisms controlling biological process, such as the development of disease or cell differentiation, can be investigated by examining changes in the networks of gene dependencies between states in the process. High-throughput experimental methods, like microarray and RNA sequencing, have been widely used to gather gene expression data, which paves the way to infer gene dependencies based on computational methods. However, most differential network analysis methods are designed to deal with fully observed data, but missing values, such as the dropout events in single-cell RNA-sequencing data, are frequent. New methods are needed to take account of these missing values. Moreover, since the changes of gene dependencies may be driven by certain perturbed genes, considering the changes in gene expression levels may promote the identification of gene network rewiring. In this study, a novel weighted differential network estimation (WDNE) model is proposed to handle multi-platform gene expression data with missing values and take account of changes in gene expression levels. Simulation studies demonstrate that WDNE outperforms state-of-the-art differential network estimation methods. When applied WDNE to infer differential gene networks associated with drug resistance in ovarian tumors, cell differentiation and breast tumor heterogeneity, the hub genes in the estimated differential gene networks can provide important insights into the underlying mechanisms. Furthermore, a Matlab toolbox, differential network analysis toolbox, was developed to implement the WDNE model and visualize the estimated differential networks.