The Clinical Value of miRNA-21 in Cervical Cancer: A Comprehensive Investigation Based on Microarray Datasets

Abstract Previous work has demonstrated that the expression of microRNA-21 (miR-21) is implicated in cervical cancer (CC). However, little is known regarding its associations with clinical parameters. We first conducted a meta-analysis using data from Gene Expression Omnibus (GEO) microarrays and The Cancer Genome Atlas (TCGA). Then, enrichment analysis and hub gene screening were performed by bioinformatics methods. Finally, the roles of the screened target genes in CC were explored. From the meta-analysis, more miR-21 was expressed in cancer tissues than in adjacent nontumor tissues (P < 0.05). In addition, 46 genes were predicted as potential targets of miR-21. After enrichment analyses, it was detected that these genes were enriched in various cancer pathways, including the phosphatidylinositol signaling system and mammalian target of rapamycin (mTOR) signaling pathway. In this study, bioinformatics tools and meta-analysis validated that miR-21 may function as a highly sensitive and specific marker for the diagnosis of CC, which may provide a novel approach to the diagnosis and treatment of CC.

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Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma

BioMed Research International ◽

10.1155/2021/5524486 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Guangyu Gao ◽

Zhen Yao ◽

Jiaofeng Shen ◽

Yulong Liu

Keyword(s):

Drug Resistance ◽

Molecular Mechanism ◽

Target Genes ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Protein Protein Interaction ◽

Obvious Association

Dabrafenib resistance is a significant problem in melanoma, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism of drug resistance of dabrafenib and to explore the key genes and pathways that mediate drug resistance in melanoma. GSE117666 was downloaded from the Gene Expression Omnibus (GEO) database and 492 melanoma statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Besides, differentially expressed miRNAs (DEMs) were identified by taking advantage of the R software and GEO2R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) and FunRich was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential pathways and functional annotations linked with melanoma chemoresistance. 9 DEMs and 872 mRNAs were selected after filtering. Then, target genes were uploaded to Metascape to construct protein-protein interaction (PPI) network. Also, 6 hub mRNAs were screened after performing the PPI network. Furthermore, a total of 4 out of 9 miRNAs had an obvious association with the survival rate ( P < 0.05 ) and showed a good power of risk prediction model of over survival. The present research may provide a deeper understanding of regulatory genes of dabrafenib resistance in melanoma.

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Dysregulated microRNAs in laryngeal cancer: a comprehensive meta-analysis using a robust rank aggregation approach

Future Oncology ◽

10.2217/fon-2020-0394 ◽

2020 ◽

Vol 16 (33) ◽

pp. 2723-2734

Author(s):

Zaizai Cao ◽

Yu Guo ◽

Yinjie Ao ◽

Shuihong Zhou

Keyword(s):

Target Genes ◽

Laryngeal Squamous Cell Carcinoma ◽

Meta Analysis ◽

Enrichment Analysis ◽

Rank Aggregation ◽

The Cancer Genome Atlas ◽

Aggregation Method ◽

Multiple Cancer ◽

Cancer Genome Atlas ◽

Genome Atlas

We need a reasonable method of compiling data from different studies regarding the expression of microRNA (miRNA) in laryngeal squamous cell carcinoma (LSCC). The robust rank aggregation method was used to integrate the rank lists of miRNAs from 11 studies. The enrichment analysis was performed on target genes of meta-signature miRNAs. The Cancer Genome Atlas database was used to confirm the results of meta-analysis. Three meta-signature miRNAs (miR-21-5p, miR-196a-5p and miR-145-5p) were obtained. All three miRNAs could be prognostic for LSCC. The enrichment analysis showed that these miRNAs were associated significantly with multiple cancer-related signaling pathways. The robust rank aggregation approach is an effective way to identify important miRNAs from different studies. All identified miRNAs could be candidates for LSCC diagnostic and prognostic biomarkers.

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Longitudinal Analysis of Gene Expression Changes During Cervical Carcinogenesis Reveals Potential Therapeutic Targets

Evolutionary Bioinformatics ◽

10.1177/1176934320920574 ◽

2020 ◽

Vol 16 ◽

pp. 117693432092057

Author(s):

Lijun Yu ◽

Meiyan Wei ◽

Fengyan Li

Keyword(s):

Gene Expression ◽

Western Blotting ◽

Protein Interactions ◽

Target Genes ◽

Quantitative Polymerase Chain Reaction ◽

Enrichment Analysis ◽

Gene Interaction ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Gene Expressions

Despite advances in the treatment of cervical cancer (CC), the prognosis of patients with CC remains to be improved. This study aimed to explore candidate gene targets for CC. CC datasets were downloaded from the Gene Expression Omnibus database. Genes with similar expression trends in varying steps of CC development were clustered using Short Time-series Expression Miner (STEM) software. Gene functions were then analyzed using the Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Protein interactions among genes of interest were predicted, followed by drug-target genes and prognosis-associated genes. The expressions of the predicted genes were determined using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blotting. Red and green profiles with upward and downward gene expressions, respectively, were screened using STEM software. Genes with increased expression were significantly enriched in DNA replication, cell-cycle-related biological processes, and the p53 signaling pathway. Based on the predicted results of the Drug-Gene Interaction database, 17 drug-gene interaction pairs, including 3 red profile genes (TOP2A, RRM2, and POLA1) and 16 drugs, were obtained. The Cancer Genome Atlas data analysis showed that high POLA1 expression was significantly correlated with prolonged survival, indicating that POLA1 is protective against CC. RT-qPCR and Western blotting showed that the expressions of TOP2A, RRM2, and POLA1 gradually increased in the multistep process of CC. TOP2A, RRM2, and POLA1 may be targets for the treatment of CC. However, many studies are needed to validate our findings.

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Upregulated NLGN1 predicts poor survival in colorectal cancer

10.21203/rs.3.rs-275861/v1 ◽

2021 ◽

Author(s):

Qian Yu ◽

Xiaojie Wang ◽

Yinghong Yang ◽

Pan Chi ◽

Jianping Huang ◽

...

Keyword(s):

Colorectal Cancer ◽

Hedgehog Signaling ◽

Enrichment Analysis ◽

Multivariate Regression Analysis ◽

Repair Process ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Poor Prognostic Factor

Abstract Background: Neuroligin1 (NLGN1) is a main component of excitatory glutamatergic synapses complex and is important for synapse assembly and function. The clinical value of NLGN1 in colorectal cancer (CRC) is not clear. Methods: We obtained the expression data of 1143 CRC patients from 3 independent Gene Expression Omnibus (GEO) datasets (GSE32323, GSE24551, GSE39582) and The Cancer Genome Atlas (TCGA) to make the comparison of the NLGN1 expression level between CRC tissues and matched noncancerous tissues, and to evaluate its value in predicting survival of CRC patients. At the protein level, these results were further confirmed by immunohistochemical staining of 52 CRC samples in our own centre. Finally, the function of NLGN1 was explored by gene set enrichment analysis (GSEA). Results: Increased mRNA and protein levels of NLGN1 expression were associated with worse overall survival or recurrence-free survival in CRC patients from 2 GEO datasets, the TCGA database, and our cohort. In addition, multivariate regression analysis showed that NLGN1 was an independent poor prognostic factor of survival in patients with CRC in TCGA database (OR = 2.524, P = 0.010). Functional analysis revealed that NLGN1 was correlated with function involving the Hedgehog signaling pathway, mismatch repair process, and some material metabolism processes. Conclusions: This study is the first to implicate and verify NLGN1 as a new poor prognostic marker for CRC.

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miR-224, miR-147b and miR-31 associated with lymph node metastasis and prognosis for lung adenocarcinoma by regulating PRPF4B, WDR82 or NR3C2

PeerJ ◽

10.7717/peerj.9704 ◽

2020 ◽

Vol 8 ◽

pp. e9704

Author(s):

Yan Wang ◽

Shengtao Shang ◽

Kun Yu ◽

Hongbin Sun ◽

Wenduan Ma ◽

...

Keyword(s):

Lymph Node ◽

Lymph Node Metastasis ◽

Lung Adenocarcinoma ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Microarray Dataset ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Node Metastasis

Background The present study is to screen lymph node metastasis-related microRNAs (miRNAs) in lung adenocarcinoma (LUAD) and uncover their underlying mechanisms. Methods The miRNA microarray dataset was collected from the Gene Expression Omnibus database under accession number GSE64859. The differentially expressed miRNAs (DEMs) were identified using a t-test. Target genes of DEMs were predicted through the miRWalk2.0 database. The function of these target genes was annotated with the clusterProfiler and the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools. Protein-protein interaction network was established using the STRING database to extract hub target genes. The expressions and associations with survival and lymph node metastasis of miRNAs and target genes were validated by analysis of The Cancer Genome Atlas (TCGA) dataset. Results Eight DEMs were identified between lymph node metastasis and non-metastasis samples of GSE64859 dataset. miRNA-target gene pairs were predicted between six DEMs and 251 target genes (i.e. hsa-miR-224-PRPF4B, hsa-miR-147b-WDR82 and hsa-miR-31-NR3C2). The clusterProfiler analysis showed WDR82 was involved in the mRNA surveillance pathway, while the GO enrichment analysis using the DAVID database indicated PRPF4B participated in the protein phosphorylation and NR3C2 was related with the transcription, DNA-templated. WDR82 and PRPF4B may be hub genes because they could interact with others. Two DEMs (miR-31-5p and miR-31-3p) and 45 target genes (including PRPF4B and NR3C2) were significantly associated with overall survival. The expressions of miR-224 and miR-147b were validated to be upregulated, while WDR82, PRPF4B and NR3C2 were downregulated in lymph node metastasis samples of TCGA datasets compared with non-metastasis samples. Also, there were significantly negative expression correlations between miR-147b and WDR82, between miR-224 and PRPF4B, as well as between miR-31 and NR3C2 in LUAD samples. Conclusions The present study identified several crucial miRNA-mRNA interaction pairs, which may provide novel explanations for the lymph node metastasis and poor prognosis for LUAD patients.

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Upregulated NLGN1 predicts poor survival in colorectal cancer

BMC Cancer ◽

10.1186/s12885-021-08621-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Qian Yu ◽

Xiaojie Wang ◽

Yinghong Yang ◽

Pan Chi ◽

Jianping Huang ◽

...

Keyword(s):

Colorectal Cancer ◽

Hedgehog Signaling ◽

Enrichment Analysis ◽

Multivariate Regression Analysis ◽

Repair Process ◽

Gene Expression Omnibus ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Clinical Value ◽

Poor Prognostic Factor

Abstract Background Neuroligin1 (NLGN1) is a main component of excitatory glutamatergic synapses complex and is important for synapse assembly and function. The clinical value of NLGN1 in colorectal cancer (CRC) is not clear. Methods We obtained the expression data of 1143 CRC patients from 3 independent Gene Expression Omnibus (GEO) datasets (GSE32323, GSE24551, GSE39582) and The Cancer Genome Atlas (TCGA) to make the comparison of the NLGN1 expression level between CRC tissues and matched noncancerous tissues, and to evaluate its value in predicting survival of CRC patients. At the protein level, these results were further confirmed by immunohistochemical staining of 52 CRC samples in our own centre. Finally, the function of NLGN1 was explored by gene set enrichment analysis (GSEA). Results Increased mRNA and protein levels of NLGN1 expression were associated with worse overall survival or recurrence-free survival in CRC patients from 2 GEO datasets, the TCGA database, and our cohort. In addition, multivariate regression analysis showed that NLGN1 was an independent poor prognostic factor of survival in patients with CRC in TCGA database (OR = 2.524, P = 0.010). Functional analysis revealed that NLGN1 was correlated with function involving the Hedgehog signaling pathway, mismatch repair process, and some material metabolism processes. Conclusions This study is the first to implicate and verify NLGN1 as a new poor prognostic marker for CRC.

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Identifying Personalized Metabolic Signatures in Breast Cancer

Metabolites ◽

10.3390/metabo11010020 ◽

2020 ◽

Vol 11 (1) ◽

pp. 20

Author(s):

Priyanka Baloni ◽

Wikum Dinalankara ◽

John C. Earls ◽

Theo A. Knijnenburg ◽

Donald Geman ◽

...

Keyword(s):

Drug Targets ◽

Metabolic Networks ◽

Target Genes ◽

Enrichment Analysis ◽

Metabolic Reprogramming ◽

The Cancer Genome Atlas ◽

Estrogen Metabolism ◽

Acid Oxidation ◽

A Genome ◽

Context Specific

Cancer cells are adept at reprogramming energy metabolism, and the precise manifestation of this metabolic reprogramming exhibits heterogeneity across individuals (and from cell to cell). In this study, we analyzed the metabolic differences between interpersonal heterogeneous cancer phenotypes. We used divergence analysis on gene expression data of 1156 breast normal and tumor samples from The Cancer Genome Atlas (TCGA) and integrated this information with a genome-scale reconstruction of human metabolism to generate personalized, context-specific metabolic networks. Using this approach, we classified the samples into four distinct groups based on their metabolic profiles. Enrichment analysis of the subsystems indicated that amino acid metabolism, fatty acid oxidation, citric acid cycle, androgen and estrogen metabolism, and reactive oxygen species (ROS) detoxification distinguished these four groups. Additionally, we developed a workflow to identify potential drugs that can selectively target genes associated with the reactions of interest. MG-132 (a proteasome inhibitor) and OSU-03012 (a celecoxib derivative) were the top-ranking drugs identified from our analysis and known to have anti-tumor activity. Our approach has the potential to provide mechanistic insights into cancer-specific metabolic dependencies, ultimately enabling the identification of potential drug targets for each patient independently, contributing to a rational personalized medicine approach.

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Immunogenomic Identification for Predicting the Prognosis of Cervical Cancer Patients

International Journal of Molecular Sciences ◽

10.3390/ijms22052442 ◽

2021 ◽

Vol 22 (5) ◽

pp. 2442

Author(s):

Qun Wang ◽

Aurelia Vattai ◽

Theresa Vilsmaier ◽

Till Kaltofen ◽

Alexander Steger ◽

...

Keyword(s):

Cervical Cancer ◽

Clinical Data ◽

Regulatory Network ◽

Univariate Analysis ◽

Predictive Biomarkers ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Functional Enrichment ◽

Wilcoxon Test

Cervical cancer is primarily caused by the infection of high-risk human papillomavirus (hrHPV). Moreover, tumor immune microenvironment plays a significant role in the tumorigenesis of cervical cancer. Therefore, it is necessary to comprehensively identify predictive biomarkers from immunogenomics associated with cervical cancer prognosis. The Cancer Genome Atlas (TCGA) public database has stored abundant sequencing or microarray data, and clinical data, offering a feasible and reliable approach for this study. In the present study, gene profile and clinical data were downloaded from TCGA, and the Immunology Database and Analysis Portal (ImmPort) database. Wilcoxon-test was used to compare the difference in gene expression. Univariate analysis was adopted to identify immune-related genes (IRGs) and transcription factors (TFs) correlated with survival. A prognostic prediction model was established by multivariate cox analysis. The regulatory network was constructed and visualized by correlation analysis and Cytoscape, respectively. Gene functional enrichment analysis was performed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). A total of 204 differentially expressed IRGs were identified, and 22 of them were significantly associated with the survival of cervical cancer. These 22 IRGs were actively involved in the JAK-STAT pathway. A prognostic model based on 10 IRGs (APOD, TFRC, GRN, CSK, HDAC1, NFATC4, BMP6, IL17RD, IL3RA, and LEPR) performed moderately and steadily in squamous cell carcinoma (SCC) patients with FIGO stage I, regardless of the age and grade. Taken together, a risk score model consisting of 10 novel genes capable of predicting survival in SCC patients was identified. Moreover, the regulatory network of IRGs associated with survival (SIRGs) and their TFs provided potential molecular targets.

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High RPS27A Expression Predicts Poor Prognosis in Patients With HPV Type 16 Cervical Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.752974 ◽

2021 ◽

Vol 11 ◽

Author(s):

Qiming Wang ◽

Yan Cai ◽

Xuewen Fu ◽

Liang Chen

Keyword(s):

Cervical Cancer ◽

Poor Prognosis ◽

Biological Significance ◽

Enrichment Analysis ◽

Hpv Infection ◽

Gene Set Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Protein Protein Interaction ◽

Cervical Cancer Cells ◽

Cancer Genome Atlas

In recent years, the incidence and the mortality rate of cervical cancer have been gradually increasing, becoming one of the major causes of cancer-related death in women. In particular, patients with advanced and recurrent cervical cancers present a very poor prognosis. In addition, the vast majority of cervical cancer cases are caused by human papillomavirus (HPV) infection, of which HPV16 infection is the main cause and squamous cell carcinoma is the main presenting type. In this study, we performed screening of differentially expressed genes (DEGs) based on The Cancer Genome Atlas (TCGA) database and GSE6791, constructed a protein–protein interaction (PPI) network to screen 34 hub genes, filtered to the remaining 10 genes using the CytoHubba plug-in, and used survival analysis to determine that RPS27A was most associated with the prognosis of cervical cancer patients and has prognostic and predictive value for cervical cancer. The most significant biological functions and pathways of RPS27A enrichment were subsequently investigated with gene set enrichment analysis (GSEA), and integration of TCGA and GTEx database analyses revealed that RPS27A was significantly expressed in most cancer types. In this study, our analysis revealed that RPS27A can be used as a prognostic biomarker for HPV16 cervical cancer and has biological significance for the growth of cervical cancer cells.

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The Prognostic Significance of MAFK and its Methylation in Cervical Cancer

10.21203/rs.3.rs-582069/v1 ◽

2021 ◽

Author(s):

Mengjun Zhang ◽

Hao Li ◽

Yuan Liu ◽

Siyu Hou ◽

Ping Cui ◽

...

Keyword(s):

Cervical Cancer ◽

Prognostic Significance ◽

Enrichment Analysis ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Aberrant Methylation ◽

Cancer Data ◽

Drug Candidates ◽

Cancer Genome Atlas ◽

Cancer Tissues

Abstract Background: The purpose of this study was to determine the value of MAFK as a biomarker of cervical cancer prognosis and to explore its methylation and possible cellular signaling pathways. Methods: We analyzed the cervical cancer data of The Cancer Genome Atlas (TCGA) through bioinformatics, including MAFK expression, methylation, prognosis and genome enrichment analysis. Results: MAFK expression was higher in cervical cancer tissues and was negatively correlated with the methylation levels of five CpG sites. MAFK is an independent prognostic factor of cervical cancer and is involved in the Nod-like receptor signaling pathway. CMap analysis screened four drug candidates for cervical cancer treatment. Conclusions: We confirmed that MAFK is a novel prognostic biomarker for cervical cancer and aberrant methylation may also affect MAFK expression and carcinogenesis. This study provides a new molecular target for the prognostic evaluation and treatment of cervical cancer.

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