scholarly journals Prognostic Impact and Functional Annotations of KIF11 and KIF14 Expression in Patients with Colorectal Cancer

2021 ◽  
Vol 22 (18) ◽  
pp. 9732
Author(s):  
Izabela Neska-Długosz ◽  
Karolina Buchholz ◽  
Justyna Durślewicz ◽  
Maciej Gagat ◽  
Dariusz Grzanka ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Mrna Level ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Tissue Microarrays ◽  
Functional Enrichment ◽  
Prognostic Impact ◽  
Aberrant Expression ◽  
Functional Value

Genomic instability (GIN) has an important contribution to the pathology of colorectal cancer (CRC). Therefore, we selected mitosis and cytokinesis kinesins, KIF11 and KIF14, as factors of potential clinical and functional value in CRC, as their aberrant expression has been suspected to underlie GIN. We examined the expression and the prognostic and biological significance of KIF11 and KIF14 in CRC via in-house immunohistochemistry on tissue microarrays, public mRNA expression datasets, as well as bioinformatics tools. We found that KIF11 and KIF14 expression, at both the protein and mRNA level, was markedly altered in cancer tissues compared to respective controls, which was reflected in the clinical outcome of CRC patients. Specifically, we provide the first evidence that KIF11 protein and mRNA, KIF14 mRNA, as well as both proteins together, can significantly discriminate between CRC patients with better and worse overall survival independently of other relevant clinical risk factors. The negative prognostic factors for OS were high KIF11 protein, high KIF11 protein + low KIF14 protein, low KIF11 mRNA and low KIF14 mRNA. Functional enrichment analysis revealed that the gene sets related to the cell cycle, DNA replication, DNA repair and recombination, among others, were positively associated with KIF11 or KIF14 expression in CRC tissues. In TCGA cohort, the positive correlations between several measures related to GIN and the expression of KIFs were also demonstrated. In conclusion, our results suggest that CRC patients can be stratified into distinct risk categories by biological and molecular determinants, such as KIF11 and KIF14 expression and, mechanistically, this is likely attributable to their role in maintaining genome integrity.

scholarly journals Downregulation of miRNA-205 Expression and Biological Mechanism in Prostate Cancer Tumorigenesis and Bone Metastasis

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Yu Sun ◽  
Sheng-Hua Li ◽  
Ji-Wen Cheng ◽  
Gang Chen ◽  
Zhi-Guang Huang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Bone Metastasis ◽  
Protein Level ◽  
Target Genes ◽  
Mrna Level ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Forest Plot ◽  
Biological Mechanism

Background. The expression and mechanism of microRNA-205 (miRNA-205) in prostate cancer (PCa) and its bone metastasis remain controversial. Materials and Methods. The expression and discriminating capability of miRNA-205 were assessed by drawing a forest plot and a summarized receiver operating characteristic (SROC) curve, using data available from 27 miRNA-array and miRNA-sequencing datasets. The miRNA-205 target genes were acquired from online prediction tools, differentially upregulated genes in PCa, and differentially expressed genes (DEGs) after miRNA-205 transfection into PCa cell lines. Functional enrichment analysis was conducted to explore the biological mechanism of miRNA-205 targets. Immunohistochemistry (IHC) was applied to verify the protein level of the hub gene. Results. The expression of miRNA-205 in the PCa group (1,461 samples) was significantly lower than that in the noncancer group (510 samples), and the downregulation of miRNA-205 showed excellent sensitivity and specificity in differentiating between the two groups. In bone metastatic PCa, the miRNA-205 level was further reduced than in nonbone metastatic PCa, and it showed a good capability in distinguishing between the two groups. In total, 153 miRNA-205 targets were screened through the three aforementioned methods. Based on the results of functional enrichment analysis, the targets of miRNA-205 were mainly enriched during chromosome segregation and phospholipid-translocating ATPase activity and in the spindle microtubule and the p53 signaling pathway. CDK1 had the highest connectivity in the PPI network analysis and was screened as one of the hub genes. A statistically significant negative correlation between miRNA-205 and CDK1 was observed. The expression of CDK1 in PCa samples was pronouncedly upregulated in terms of both the mRNA level and the protein level when compared with noncancer samples. Conclusion. miRNA-205 may play a vital role in PCa tumorigenesis and bone metastasis by targeting CDK1.

scholarly journals Improved cancer biomarkers identification using network-constrained infinite latent feature selection

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0246668
Author(s):  
Lihua Cai ◽  
Honglong Wu ◽  
Ke Zhou
Keyword(s):  
Feature Selection ◽  
Expression Profiles ◽  
Biological Significance ◽  
Feature Selection Method ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Gene Sets ◽  
Significant Gene

Identifying biomarkers that are associated with different types of cancer is an important goal in the field of bioinformatics. Different researcher groups have analyzed the expression profiles of many genes and found some certain genetic patterns that can promote the improvement of targeted therapies, but the significance of some genes is still ambiguous. More reliable and effective biomarkers identification methods are then needed to detect candidate cancer-related genes. In this paper, we proposed a novel method that combines the infinite latent feature selection (ILFS) method with the functional interaction (FIs) network to rank the biomarkers. We applied the proposed method to the expression data of five cancer types. The experiments indicated that our network-constrained ILFS (NCILFS) provides an improved prediction of the diagnosis of the samples and locates many more known oncogenes than the original ILFS and some other existing methods. We also performed functional enrichment analysis by inspecting the over-represented gene ontology (GO) biological process (BP) terms and applying the gene set enrichment analysis (GSEA) method on selected biomarkers for each feature selection method. The enrichments analysis reports show that our network-constraint ILFS can produce more biologically significant gene sets than other methods. The results suggest that network-constrained ILFS can identify cancer-related genes with a higher discriminative power and biological significance.

scholarly journals The Methylation of SDC2 and TFPI2 Defined Three Methylator Phenotypes of Colorectal Cancer

2021 ◽  
Author(s):  
Ruixue Lei ◽  
Yanteng Zhao ◽  
Kai Huang ◽  
Qian Wang ◽  
Kangkang Wan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cpg Island ◽  
Methylation Status ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Tumor Location ◽  
Functional Enrichment ◽  
Cpg Island Methylator Phenotype ◽  
Methylator Phenotype ◽  
Almost All

Abstract BackgroudMethylated SDC2 and TFPI2 are applied frequently for the early detection of colorectal cancer (CRC). However, they often miss some positive samples, which directly affects their sensitivities, and the underlining mechanism is not well known.Methods:CRC samples from TCGA and GEO datasets were divided into three groups, Highmethylation/ High-methylation (HH), High-methylation/Low-methylation (HL), and Lowmethylation/Low-methylation (LL) according to the methylation status of SDC2 and TFPI2 promoters. Variations in age, tumor location, and microsatellite instable were then assessed between the three groups and verified in our custom cohort.ResultsSamples of HL group preferred to derive from left-sided CRCs (P < 0.05). HH samples showed the highest microsatellite instability and mutation load (mean nonsynonymous mutations for HH/HL/LL: 10.55/3.91/7.02, P = 0.0055). Almost all mutations of BRAF, one of the five typical CpG island methylator phenotype (CIMP) related genes, were observed in HH group (HH/HL/LL: 51/0/1, P = 0.018). Besides, older patients were frequently found in HH group. Expression analysis identified 37, 84, and 22 group-specific differentially expressed genes (DEGs) for HH, HL, and LL, respectively. Functional enrichment analysis revealed that HH-specific DEGs were mainly related to transcription regulation, while LL-specific DEGs were enriched in the biological processes of extracellular matrix interaction and cell migration.Conclusions:The three methylation phenotypes identified based on SDC2 and TFPI2 methylation status showed extensive variations in tumor location, patient age, MSI and ECM biology processes, suggesting that these respective sides should be considered when developing new methylation-based biomarkers for CRC detection.

Bioinformatics analysis of prognostic value genes in colorectal cancer microenvironment

2019 ◽  
Author(s):  
Taohua Yue ◽  
Jing Zhu ◽  
Xin Wang ◽  
Yisheng Pan ◽  
Yucun Liu ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Large Scale ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Previous Literature ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Gastrointestinal Malignancies ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Colorectal cancer (CRC) is one of the most deadly gastrointestinal malignancies. The openness of the Cancer Genome Atlas (TCGA) allows us to perform correlation analysis between large-scale transcriptome data and overall survival (OS) of multiple malignancies. Previous literature reports that the infiltration of immune cells and stromal cells in the tumor microenvironment (TME) significantly associate with the prognosis of cancers. Based on the ESTIMATE algorithm, the immune and stromal components in TME can be quantified by immune and stromal scores. To determine the effects of immune and stromal cell associated genes on CRC prognosis, we divided the CRC cases into high- and low-groups based on the immune/stromal scores and identified 999 differentially expressed genes (DEGs). Heatmaps, functional enrichment analysis and protein‐protein interaction (PPIs) networks further indicated that 999 DEGs mainly participated in stromal composition and immune response. Finally, we obtained 56 genes that were significantly associated with CRC prognosis from 999 DEGs and identified the PPIs networks. The role of 41 genes in CRC has been reported in previous literature, and the other 15 genes have never been reported. Therefore, we found 15 novel TME genes associated with CRC prognosis waiting for more researches.

scholarly journals Construction of ceRNA Coexpression Network and Screening of Molecular Targets in Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Zhao Hui ◽  
Wang Zhanwei ◽  
Yang Xi ◽  
Liu Jin ◽  
Zhuang Jing ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Normal Tissues ◽  
Cerna Network ◽  
Cancer Tissues

Objective. To screen some RNAs that correlated with colorectal cancer (CRC). Methods. Differentially expressed miRNAs, lncRNAs, and mRNAs between cancer tissues and normal tissues in CRC were identified using data from the Gene Expression Omnibus (GEO) database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interactions (PPIs) were performed to do the functional enrichment analysis. And a lncRNA-miRNA-mRNA network was constructed which correlated with CRC. RNAs in this network were subjected to analyze the relationship with the patient prognosis. Results. A total of 688, 241, and 103 differentially expressed genes (diff-mRNA), diff-lncRNA, and diff-miRNA were obtained between cancer tissues and normal tissues. A total of 315 edges were obtained in the ceRNA network. lncRNA RP11-108K3.2 and mRNA ONECUT2 correlated with prognosis. Conclusion. The identified RNAs and constructed ceRNA network could provide great sources for the researches of therapy of the CRC. And the lncRNA RP11-108K3.2 and mRNA ONECUT2 may serve as a novel prognostic predictor of CRC.

scholarly journals Competing Endogenous RNA in Colorectal Cancer: An Analysis for Colon, Rectum, and Rectosigmoid Junction

2021 ◽  
Vol 11 ◽  
Author(s):  
Lucas Maciel Vieira ◽  
Natasha Andressa Nogueira Jorge ◽  
João Batista de Sousa ◽  
João Carlos Setubal ◽  
Peter F. Stadler ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Anatomical Site ◽  
Rna Expression ◽  
Rectosigmoid Junction

BackgroundColorectal cancer (CRC) is a heterogeneous cancer. Its treatment depends on its anatomical site and distinguishes between colon, rectum, and rectosigmoid junction cancer. This study aimed to identify diagnostic and prognostic biomarkers using networks of CRC-associated transcripts that can be built based on competing endogenous RNAs (ceRNA).MethodsRNA expression and clinical information data of patients with colon, rectum, and rectosigmoid junction cancer were obtained from The Cancer Genome Atlas (TCGA). The RNA expression profiles were assessed through bioinformatics analysis, and a ceRNA was constructed for each CRC site. A functional enrichment analysis was performed to assess the functional roles of the ceRNA networks in the prognosis of colon, rectum, and rectosigmoid junction cancer. Finally, to verify the ceRNA impact on prognosis, an overall survival analysis was performed.ResultsThe study identified various CRC site-specific prognosis biomarkers: hsa-miR-1271-5p, NRG1, hsa-miR-130a-3p, SNHG16, and hsa-miR-495-3p in the colon; E2F8 in the rectum and DMD and hsa-miR-130b-3p in the rectosigmoid junction. We also identified different biological pathways that highlight differences in CRC behavior at different anatomical sites, thus reinforcing the importance of correctly identifying the tumor site.ConclusionsSeveral potential prognostic markers for colon, rectum, and rectosigmoid junction cancer were found. CeRNA networks could provide better understanding of the differences between, and common factors in, prognosis of colon, rectum, and rectosigmoid junction cancer.

MIMPFC: Identifying miRNA–mRNA regulatory modules by combining phase-only correlation and improved rough-fuzzy clustering

2018 ◽  
Vol 16 (01) ◽  
pp. 1750028
Author(s):  
Dan Luo ◽  
Shu-Lin Wang ◽  
Jianwen Fang ◽  
Wei Zhang
Keyword(s):  
Fuzzy Clustering ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Computational Method ◽  
Functional Enrichment ◽  
Regulatory Relationship ◽  
Regulatory Modules ◽  
Wide Range ◽  
Highly Correlated

MicroRNAs (miRNAs) play a key role in gene expression and regulation in various organisms. They control a wide range of biological processes and are involved in several types of cancers by causing mRNA degradation or translational inhibition. However, the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With the accumulation of the expression data of miRNAs and mRNAs, many computational methods have been proposed to predict miRNA–mRNA regulatory relationship. However, most existing methods require the number of modules predefined that may be difficult to determine beforehand. Here, we propose a novel computational method to discover miRNA–mRNA regulatory modules by combining Phase-only correlation and improved rough-Fuzzy Clustering (MIMPFC). The proposed method is evaluated on three heterogeneous datasets, and the obtained results are further validated through relevant literatures, biological significance and functional enrichment analysis. The analysis results show that the identified modules are highly correlated with the biological conditions. A large part of the regulatory relationships found by MIMPFC has been confirmed in the experimentally verified databases. It demonstrates that the modules found by MIMPFC are biologically significant.

scholarly journals Identification of Potential Key Genes and Pathways in Early-Onset Colorectal Cancer Through Bioinformatics Analysis

2019 ◽  
Vol 26 (1) ◽  
pp. 107327481983126 ◽  
Author(s):  
Bin Zhao ◽  
Zulqarnain Baloch ◽  
Yunhan Ma ◽  
Zheng Wan ◽  
Yani Huo ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Muscle Contraction ◽  
Protein Interactions ◽  
Early Onset ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Smooth Muscle Contraction ◽  
Functional Enrichment ◽  
Early Onset Colorectal Cancer

This study was designed to identify the potential key protein interaction networks, genes, and correlated pathways in early-onset colorectal cancer (CRC) via bioinformatics methods. We selected microarray data GSE4107 consisting 12 patient’s colonic mucosa and 10 healthy control mucosa; initially, the GSE4107 were downloaded and analyzed using limma package to identify differentially expressed genes (DEGs). A total of 131 DEGs consisting of 108 upregulated genes and 23 downregulated genes of patients in early-onset CRC were selected by the criteria of adjusted P values <.01 and |log2 fold change (FC)| ≥ 2. The gene ontology functional enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were accomplished to view the biological process, cellular components, molecular function, and the KEGG pathways of DEGs. Finally, protein–protein interactions (PPIs) were constructed, and the hub protein module was identified. Genes such as ACTA2, ACTG2, MYH11, CALD1, MYL9, TPM2, and LMOD1 were strongly implicated in CRC. In summary, in this study, we indicated that molecular mechanisms were involved in muscle contraction and vascular smooth muscle contraction signaling pathway, which improve our understanding of CRC and could be used as new therapeutic targets for CRC.

scholarly journals Transcriptomic Analysis of Respiratory Tissue and Cell Line Models to Examine Glycosylation Machinery during SARS-CoV-2 Infection

Viruses ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 82
Author(s):  
Anup Oommen ◽  
Stephen Cunningham ◽  
Lokesh Joshi
Keyword(s):  
Immune Response ◽  
Biological Significance ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Vital Role ◽  
Biomedical Literature ◽  
Transcriptomic Analysis ◽  
Functional Enrichment ◽  
Post Translational Modification ◽  
And Function

Glycosylation, being the most abundant post-translational modification, plays a profound role affecting expression, localization and function of proteins and macromolecules in immune response to infection. Presented are the findings of a transcriptomic analysis performed using high-throughput functional genomics data from public repository to examine the altered transcription of the human glycosylation machinery in response to SARS-CoV-2 stimulus and infection. In addition to the conventional in silico functional enrichment analysis methods we also present results from the manual analysis of biomedical literature databases to bring about the biological significance of glycans and glycan-binding proteins in modulating the host immune response during SARS-CoV-2 infection. Our analysis revealed key immunomodulatory lectins, proteoglycans and glycan epitopes implicated in exerting both negative and positive downstream inflammatory signaling pathways, in addition to its vital role as adhesion receptors for SARS-CoV-2 pathogen. A hypothetical correlation of the differentially expressed human glycogenes with the altered host inflammatory response and the cytokine storm-generated in response to SARS-CoV-2 pathogen is proposed. These markers can provide novel insights into the diverse roles and functioning of glycosylation pathways modulated by SARS-CoV-2, provide avenues of stratification, treatment, and targeted approaches for COVID-19 immunity and other viral infectious agents.

scholarly journals Identification of key gene in colorectal cancer using bioinformatics analysis.

2020 ◽  
Author(s):  
Rongrong Xiao ◽  
Ping Wang ◽  
Tian Xia ◽  
Chun-Yi Li ◽  
Ting Jiang ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Colon Cancer ◽  
Tumor Microenvironment ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Hub Genes

Abstract Background Tumor microenvironment plays important roles in the development of cancer. The aim of our study was to examine the expression of genes in colorectal cancer and also to evaluate the association value between expression level of these genes and clinical features. Methods We combined The Cancer Genome Atlas (TCGA) datasets to identify differentially expressed genes in colon cancer. Using these differentially expressed genes, we constructed protein-protein interaction network and conducted functional enrichment analysis. Genes with degree beyond 10 in the PPI network were regarded as hub genes. Then, we verified of the expression of molecules in Oncomine datasets and conducted Kaplan-Meier curve and log-rank test and functional enrichment analysis on these hub genes. Finally, we analyzed the relationship clinicopathological features analysis with the key gene. Results There were 719 differentially expressed genes identified to be associated with colon cancer microenvironment. We screened out 10 hub genes by construction of PPI network. The functions of these hub genes were enriched in cytokine-cytokine receptor interaction, alcoholism and systemic lupus erythematosus, which provided further insight into the roles of these genes in the tumor microenvironment. GNG4, with the highest degrees in the PPI network, were highly exprepressed in metastasis(P = 9.5-05) ,N1(P = 0.0025) and N2(,0.037).It was a relationship with stage. It was significantly different between with stage I and IV, II and III, II and IV,III and IV (P = 0.0015,0.029,3.9-05,0.00074,0.01,respectively) Conclusions We identified GNG4 can be regarded as a prognostic biomarker in colon cancer.

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