scholarly journals Identification of KIF4A and its effect on the progression of lung adenocarcinoma based on the bioinformatics analysis

2021 ◽  
Author(s):  
Yexun Song ◽  
Wenfang Tang ◽  
Hui Li
Keyword(s):  
Lung Adenocarcinoma ◽  
Cell Lines ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Disease Free Survival ◽  
Rank Aggregation ◽  
Clinical Samples ◽  
Hub Genes ◽  
Hub Gene ◽  
Qrt Pcr

Background: Lung adenocarcinoma (LUAD) is the most frequent histological type of lung cancer, and its incidence has displayed an upward trend in recent years. Nevertheless, little is known regarding effective biomarkers for LUAD. Methods: The robust rank aggregation method was used to mine differentially expressed genes (DEGs) from the gene expression omnibus (GEO) datasets. The Search Tool for the Retrieval of Interacting Genes (STRING) database was used to extract hub genes from the protein-protein interaction (PPI) network. The expression of the hub genes was validated using expression profiles from TCGA and Oncomine databases and was verified by real-time quantitative PCR (qRT-PCR). The module and survival analyses of the hub genes were determined using Cytoscape and Kaplan-Meier curves. The function of KIF4A as a hub gene was investigated in LUAD cell lines. Results: The PPI analysis identified seven DEGs including BIRC5, DLGAP5, CENPF, KIF4A, TOP2A, AURKA, and CCNA2, which were significantly upregulated in Oncomine and TCGA LUAD datasets, and were verified by qRT-PCR in our clinical samples. We determined the overall and disease-free survival analysis of the seven hub genes using GEPIA. We further found that CENPF, DLGAP5, and KIF4A expressions were positively correlated with clinical stage. In LUAD cell lines, proliferation and migration were inhibited and apoptosis was promoted by knocking down KIF4A expression.Conclusion: We have identified new DEGs and functional pathways involved in LUAD. KIF4A, as a hub gene, promoted the progression of LUAD and might represent a potential therapeutic target for molecular cancer therapy.

Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

2021 ◽  
pp. 153537022110487
Author(s):  
Zirui Zhu ◽  
Rui Huang ◽  
Baojun Huang
Keyword(s):  
Messenger Rna ◽  
Expression Profiles ◽  
Clinical Stage ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rank Aggregation ◽  
Circular Rnas ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

scholarly journals Identification of RRM2 as a Potential Biomarker for the Diagnosis and Prognosis of Rheumatoid Arthritis

2021 ◽  
Author(s):  
Wu Biao ◽  
Yufeng Chen ◽  
Junlong Zhong ◽  
Shuping Zhong ◽  
Bin Wang ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Mononuclear Cells ◽  
Expression Profiles ◽  
Clinical Samples ◽  
Healthy Controls ◽  
Rna Seq ◽  
Hub Genes ◽  
Healthy Human ◽  
Bioinformatics Analyses ◽  
Potential Biomarker

Abstract Background: Rheumatoid arthritis (RA) is a common autoimmune disease that can occur at any age. If treatment is delayed, RA can seriously affect the patients’ quality of life. However, there is no diagnostic criteria for RA and the positive predictive value of the current biomarkers is moderate. Objective: to identify RA-associated susceptibility genes and explore their potential as a novel biomarker for diagnosis and evaluation of the prognosis of RA.Methods: Peripheral blood mononuclear cells (PBMCs) were collected from healthy human donors and RA patients. RNA-seq analyses were performed to identify the differentially expressed genes (DEGs) between RA and control samples. The PBMCs-mRNA in DEGs were further subjected to enrichment analysis. Furthermore, the hub genes and key modules associated with RA were screened by bioinformatics analyses. Then, the expression of hub genes in RA were assessed in mRNA expression profiles. Next, real time-quantitative PCR (RT-qPCR) analyses were performed to further confirm the expression of the hub genes from the PBMCs that collected from 47 patients with RA and 40 healthy controls. Finally, we evaluated the clinical characters for the candidate mRNAs.Results: RNA-seq analyses revealed the expression of 178 mRNAs from PBMCs were disregulated between the healthy controls and the RA patients. Bioinformatics analyses revealed 10 hub mRNAs. The top 3 significant functional modules screened from PPI network functionally were involved in DNA replication origin binding, chemokine activity, etc. After validating the 10 hub mRNAs in GSE93272 dataset and clinical samples, we identified 3 candidate mRNAs, including ASPM, DTL and RRM2. Among which, RRM2 showed great capacity in discriminating between remissive RA and active RA. Significant correlations were observed between DTL and IL-8, TNF-α, between RRM2 and CDAI, DAS-28, tender joints and swollen joints, respectively. The AUC values of ASPM, DTL and RRM2 were 0.654, 0.995 and 0.990, respectively.Conclusion: We successfully identified multiple candidate mRNAs associated with RA. RRM2 showed high diagnosis efficiency with the AUC of 0.990 (sensitivity=100%, specificity=97.5%). And RRM2 severed as an additional biomarker for evaluating disease activity. The findings provided a novel candidate biomarker for diagnosis and evaluation of the prognosis of RA.

scholarly journals Integrated Transcriptomic Analysis Revealed Hub Genes and Pathways Involved in Sorafenib Resistance in Hepatocellular Carcinoma

2021 ◽  
Vol 27 ◽  
Author(s):  
Xili Jiang ◽  
Wei Zhang ◽  
Lifeng Li ◽  
Shucai Xie
Keyword(s):  
Gene Expression ◽  
Hepatocellular Carcinoma ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Pearson Correlation ◽  
Acquired Resistance ◽  
Rank Aggregation ◽  
Health Concern ◽  
Hub Genes ◽  
Multikinase Inhibitor

Hepatocellular carcinoma (HCC), a high mortality malignancy, has become a worldwide public health concern. Acquired resistance to the multikinase inhibitor sorafenib challenges its clinical efficacy and the survival benefits it provides to patients with advanced HCC. This study aimed to identify critical genes and pathways associated with sorafenib resistance in HCC using integrated bioinformatics analysis. Differentially expressed genes (DEGs) were identified using four HCC gene expression profiles (including 34 sorafenib-resistant and 29 sorafenib-sensitive samples) based on the robust rank aggregation method and R software. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) online tool. A protein–protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING), and small molecules reversing sorafenib resistance were searched for using the connectivity map (CMAP) database. Pearson correlation and survival analyses of hub genes were performed using cBioPortal and Gene Expression Profiling and Interactive Analysis (GEPIA). Finally, the expression levels of hub genes in sorafenib-resistant HCC cells were verified using quantitative polymerase chain reaction (q-PCR). A total of 165 integrated DEGs (66 upregulated and 99 downregulated in sorafenib resistant samples compared sorafenib sensitive ones) primarily enriched in negative regulation of endopeptidase activity, extracellular exosome, and protease binding were identified. Some pathways were commonly shared between the integrated DEGs. Seven promising therapeutic agents and 13 hub genes were identified. These findings provide a strategy and theoretical basis for overcoming sorafenib resistance in HCC patients.

scholarly journals Identification of hub genes and their clinical value for predicting the development of prostate cancer from benign prostate hyperplasia by bioinformatic analysis

2021 ◽  
Author(s):  
Xi Chen ◽  
Junjie Ma ◽  
Chengdang Xu ◽  
Licheng Wang ◽  
Yicong Yao ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Survival Data ◽  
Benign Prostate Hyperplasia ◽  
Disease Free Survival ◽  
Ppi Network ◽  
Hub Genes ◽  
Prostate Hyperplasia ◽  
Hub Gene ◽  
Benign Prostate ◽  
Geo Database

Abstract BackgroundProstate cancer (PCa) and benign prostate hyperplasia (BPH) are commonly encountered diseases in elderly males. The two diseases have some commonalities: both are growth depend on hormone and respond to antiandrogen therapy. Some studies have shown that genetic factors are responsible for the occurrences of both diseases. There may be a correlation between BPH and PCa. MethodsThe GEO database can help determine the differentially expressed genes (DEGs) between BPH and PCa. Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were utilized to find pathways in which the DEGs were enriched. The STRING database can provide a protein–protein interaction (PPI) network, and Cytoscape software can find hub genes in PPI network. GEPIA can be used to analyze expression and survival data for hub genes. R software was used to progress regression analysis, decision curve analysis and built nomograph. UALCAN and The Human Protein Atlas was utilized to test the results. Finally, we made clinical and cell experiments to verify the results.ResultsSixty DEGs, consisting of 15 up-regulated and 45 down-regulated genes, were found based on the GEO database. Using Cytoscape, we found 7 hub gene in the PPI network. The hub gene expression was tested on TCGA database. Except CXCR4, all hub genes expressed differently between tumor and normal samples. Meanwhile, all hub genes exclude CXCR4 has diagnostic value in predicting PCa and their mutations are risk factors leading to PCa. The expression of CSRP1, MYL9 and SNAI2 changed in different tumor stage. CSRP1 and MYH11 could affect the disease-free survival (DFS). The same results reflected in different database. In addition, we also chose three hub gene, MYC, MYL9, and SNAI2, to validate their functions in clinical specimens and cells.ConclusionThese identified hub genes can help us to understand the process and mechanism by which BPH develops into PCa and provide achievable targets for predicting which BPH patients may later develop PCa.

scholarly journals LncRNA SNHG17 Contributes to Proliferation, Migration, and Poor Prognosis of Hepatocellular Carcinoma

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yue Luo ◽  
Junhao Lin ◽  
Jiakang Zhang ◽  
Zhenghui Song ◽  
Dayong Zheng ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Proliferation ◽  
Rna Sequencing ◽  
Expression Pattern ◽  
Cell Lines ◽  
Disease Free Survival ◽  
Loss Of Function ◽  
Poor Overall Survival ◽  
Apoptotic Pathway ◽  
Qrt Pcr

Long noncoding RNAs (lncRNAs) have been substantially reported to have critical roles in regulating tumorigenesis in recent years. However, the expression pattern and biological function of SNHG17 in hepatocellular carcinoma (HCC) remain unclear. Bioinformatics analysis and qRT-PCR were performed to detect the expression pattern of SNHG17 in HCC tissues, adjacent nontumorous tissues, and cell lines. The effect of SNHG17 on proliferation, migration, and apoptosis of HCC was investigated by knockdown and overexpressing SNHG17 in HCC cell lines. RNA sequencing was utilized to explore the underlying mechanism. Utilizing publicly available TCGA-LIHC, GSE102079 HCC datasets, and qRT-PCR, we found SNHG17 was significantly upregulated in HCC tissues and cell lines and was notably associated with larger tumor size, poorly differentiation, presence of vascular invasion, and advanced TNM stage. Furthermore, gain- and loss-of-function studies demonstrated that SNHG17 promoted cell proliferation and migration and inhibited apoptosis of HCC. By employing RNA sequencing, we found knockdown of SNHG17 caused 1037 differentially expressed genes, highly enriched in several pathways, including metabolic, PI3K-Akt, cell adhesion, regulation of cell proliferation, and apoptotic pathway; among them, 92 were overlapped with SNHG17-related genes in the TCGA-LIHC dataset. Furthermore, ERH, TBCA, TDO2, and PDK4 were successfully validated and found significantly dysregulated in HCC tissues. Moreover, HCC patients with higher SNHG17 expression had a relatively poor overall survival and disease-free survival, and ERH and PDK4 also played a marked role in the prognosis of HCC. Broadly, our findings illustrate that SNHG17 acts as a noncoding oncogene in HCC progression, suggesting its potential value as a novel target for HCC therapy.

scholarly journals Baicalein, a Natural Anti-Cancer Compound, Alters MicroRNA Expression Profiles in Bel-7402 Human Hepatocellular Carcinoma Cells

2017 ◽  
Vol 41 (4) ◽  
pp. 1519-1531 ◽  
Author(s):  
Beibei Bie ◽  
Jin Sun ◽  
Jun Li ◽  
Ying Guo ◽  
Wei Jiang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cell Cycle ◽  
Cell Proliferation ◽  
Cell Lines ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Akt Pathway ◽  
Qrt Pcr ◽  
Cycle Arrest ◽  
Mirna Expression Profiles

Background/Aims: Baicalein has been shown to possess significant anti-hepatoma activity by inhibiting cell proliferation. Whether the anti-proliferative effect of baicalein is related to its modulation of miRNA expression in hepatocellular carcinoma (HCC) is still unknown. Methods: The anti-proliferative effects of baicalein on HCC cell line Bel-7402 was assessed by detecting the proliferation activity, cell cycle distribution, expression changes of p21/CDKN1A, P27/CDKN1B, total Akt and phosphoryted AKT. Microarray analysis was conducted to determine the miRNA expression profiles in baicalein-treated or untreated Bel-7402 cells and then validated by qRT-PCR in two HCC cell lines (Bel-7402 and Hep3B). The gain-of-function of miR-3127-5p was performed by detecting anti-proliferative effects after transfecting miRNA mimics in cells. Finally, the expression level of miR-3127-5p in different HCC cell lines was determined by qRT-PCR. Results: Baicalein was able to inhibit the proliferation of Bel-7402 cells by inducing cell cycle arrest at the S and G2/M phase via up-regulating the expression of p21/CDKN1A and P27/CDKN1B and suppressing the PI3K/Akt pathway. Baicalein could alter the miRNA expression profiles in Bel-7402 cells. Putative target genes for differentially expressed miRNAs could be enriched in terms of cell proliferation regulation, cell cycle arrest and were mainly involved in MAPK, PI3K-Akt, Wnt, Hippo and mTOR signaling pathways. MiR- 3127-5p, one of up-regulated miRNAs, exhibits low expression level in several HCC cell lines and its overexpression could inhibit cell growth of Bel-7402 and Hep3B cell lines by inducing S phase arrest by up-regulating the expression of p21and P27 and repressing the PI3K/Akt pathway. Conclusions: Modulation of miRNA expression may be an important mechanism underlying the anti-hepatoma effects of baicalein.

scholarly journals Differentially Expressed miRNAs in Tumor, Adjacent, and Normal Tissues of Lung Adenocarcinoma

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Fei Tian ◽  
Rui Li ◽  
Zhenzhu Chen ◽  
Yanting Shen ◽  
Jiafeng Lu ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Target Genes ◽  
Expression Profiles ◽  
Major Type ◽  
Regulatory Pathways ◽  
Normal Tissues ◽  
Qrt Pcr ◽  
Diagnosis And Prognosis ◽  
Tumor Tissues

Lung cancer is the leading cause of cancer deaths. Non-small-cell lung cancer (NSCLC) is the major type of lung cancer. The aim of this study was to characterize the expression profiles of miRNAs in adenocarcinoma (AC), one major subtype of NSCLC. In this study, the miRNAs were detected in normal, adjacent, and tumor tissues by next-generation sequencing. Then the expression levels of differential miRNAs were quantified by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). In the results, 259, 401, and 389 miRNAs were detected in tumor, adjacent, and normal tissues of pooled AC samples, respectively. In addition, for the first time we have found that miR-21-5p and miR-196a-5p were gradually upregulated from normal to adjacent to tumor tissues; miR-218-5p was gradually downregulated with 2-fold or greater change in AC tissues. These 3 miRNAs were validated by qRT-PCR. Lastly, we predicted target genes of these 3 miRNAs and enriched the potential functions and regulatory pathways. The aberrant miR-21-5p, miR-196a-5p, and miR-218-5p may become biomarkers for diagnosis and prognosis of lung adenocarcinoma. This research may be useful for lung adenocarcinoma diagnosis and the study of pathology in lung cancer.

scholarly journals Genetic variants in histone modification regions are associated with the prognosis of lung adenocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hyo-Gyoung Kang ◽  
Yong Hoon Lee ◽  
Shin Yup Lee ◽  
Jin Eun Choi ◽  
Sook Kyung Do ◽  
...  
Keyword(s):  
Lung Adenocarcinoma ◽  
Histone Modification ◽  
Genetic Variants ◽  
Promoter Activity ◽  
Disease Free Survival ◽  
Clinical Samples ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Curative Surgery ◽  
Validation Set

AbstractWe investigated the association between genetic variants in the histone modification regions and the prognosis of lung adenocarcinoma after curative surgery. Potentially functional SNPs were selected using integrated analysis of ChIP-seq and RNA-seq. The SNPs were analyzed in a discovery set (n = 166) and a validation set (n = 238). The associations of the SNPs with overall survival (OS) and disease-free survival (DFS) were analyzed. A total of 279 SNPs were selected for genotyping. Among these, CAPN1 rs17583C>T was significantly associated with better OS and DFS (P = 0.001 and P = 0.007, respectively), and LINC00959 rs4751162A>G was significantly associated with worse DFS (P = 0.008). Luciferase assays showed a significantly lower promoter activity of CAPN1 in the rs17583 T allele than C allele (P = 0.008), and consistently the CT + TT genotypes had significantly lower CAPN1 expression than CC genotype (P = 0.01) in clinical samples. The rs4751162 G allele had higher promoter activity of GLRX3 than A allele (P = 0.05). The motif analyses and ChIP-qPCR confirmed that the variants are located in the active promoter/enhancer regions where transcription factor binding occurs. This study showed that genetic variants in the histone modification regions could predict the prognosis of lung adenocarcinoma after surgery.

scholarly journals ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bai-Quan Qiu ◽  
Xia-Hui Lin ◽  
Song-Qing Lai ◽  
Feng Lu ◽  
Kun Lin ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Cox Regression ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Immune Infiltration ◽  
Prognostic Effect ◽  
Cancer Genome Atlas

Abstract Background Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study. Methods Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells. Results We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes. Conclusion Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

scholarly journals Identification of Hub Genes Related to Liver Metastasis of Colorectal Cancer by Integrative Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Sicheng Liu ◽  
Yaguang Zhang ◽  
Su Zhang ◽  
Lei Qiu ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Liver Metastasis ◽  
Expression Profiles ◽  
Interaction Network ◽  
Rank Aggregation ◽  
Marker Genes ◽  
Peroxisome Proliferator ◽  
Hub Genes ◽  
Peroxisome Proliferator Activated Receptor ◽  
New Biomarkers

Liver metastasis of colorectal cancer (LMCRC) severely damages patient health, causing poor prognosis and tumor relapse. Marker genes associated with LMCRC identified by previous study did not meet therapeutic demand. Therefore, it is necessary to identify new biomarkers regulating the metastasis network and screen potential drugs for future treatment. Here, we identified that cell adhesion molecules and peroxisome proliferator-activated receptor (PPAR) signaling pathway were significantly enriched by analyzing the integrated-multiple expression profiles. Moreover, analysis with robust rank aggregation approach revealed a total of 138 differentially expressed genes (DEGs), including 108 upexpressed and 30 downexpressed genes. With establishing protein–protein interaction network, we also identified the subnetwork significantly enriching the metastasis-associated hub genes including ALB, APOE, CDH2, and ORM1. ESR2, FOXO3, and SRY were determined as key transcription factors regulating hub genes. In addition, ADH-1, epigallocatechin, CHEMBL1945287, and cochinchinenin C were predicted as potential therapeutic drugs. Moreover, the antimigration capacity of ADH-1 and epigallocatechin were confirmed in CRC cell lines. In conclusion, our findings not only offer opportunities to understand metastasis mechanism but also identify potential therapeutic targets for CRC.

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