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 Identification of ALDH3A2 as novel prognostic biomarker in gastric adenocarcinoma by integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Xiyi Wei ◽  
Jianping Shi ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Extensive experiments and researches have elucidated that genes plays a pivotal role in tumorigenesis and development. Nonetheless, its latent involvement in gastric carcinoma (GC) remains to be further investigated. In this study, we identified overlapping differentially expressed genes (DEGs) by comparing the tumor tissue and adjacent normal tissue from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database, which included 79 up-regulated and 10 down-regulated genes. Based on these genes, functional enrichment analysis, protein-protein interaction (PPI) and prognosis analysis were conducted, and thus the gene ALDH3A2 was chosen for further analysis. Then, we performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations and checkpoints) to comprehend the in-deep mechanism of ALDH3A2. In a word, ALDH3A2 might have potential reference value for the relief and immunotherapy, and become an independent predictive marker for the prognosis of GC.

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.

scholarly journals Exosomal circRNA in Digestive System Tumors: The Main Player or Coadjuvants?

2021 ◽  
Vol 11 ◽  
Author(s):  
Haoying Wang ◽  
Xi Zeng ◽  
Ya Zheng ◽  
Yuping Wang ◽  
Yongning Zhou
Keyword(s):  
Colorectal Cancer ◽  
Gastric Cancer ◽  
Hepatocellular Carcinoma ◽  
Digestive System ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Circular Rna ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment

Exosomes are a type of extracellular microvesicles with a diameter of 40–160 nm. Circular RNA (circRNA) is a type of closed circular RNA molecule that is highly conserved in evolution. Exosomal circRNA plays a vital role in the proliferation, invasion, migration, and drug resistance of digestive system tumors. In this study, we used The Cancer Genome Atlas (TCGA) database, UALCAN, Python crawler, miRTargetLink Human, Database for Annotation, Visualization, and Integrated Discovery (DAVID), micBioinformatic online tool, and Cytoscape software (3.7.1). The results showed that circ-RanGAP1 in gastric cancer, circUHRF1 in hepatocellular carcinoma, and circFMN2 in colorectal cancer regulate the malignant behavior of tumors and affect the expression of their host gene through sponging miR-877-3p, miR-449c-5p, and miR-1182, respectively. Twenty exosomal circRNAs regulate 6,570 target genes through sponging 23 miRNAs. Firstly, 270 of those target genes are regulated by two or more miRNAs, which are highly correlated with 83 tumor-related pathways and six Kyoto Encyclopedia of Genes and Genomes pathways. Secondly, 1,146 target genes were significantly differentially expressed in corresponding digestive system tumors, and functional enrichment analysis revealed that 78 of those were involved in 20 cancer-related pathways. In short, the bioinformatics analysis showed that these exosomal circRNAs are stably expressed in body fluids, and regulate the occurrence and development of gastric cancer, hepatocellular carcinoma, colorectal cancer, and other digestive system tumors through sponging miRNAs. Exosomal circRNAs may be used as biomarkers for the diagnosis of disease and identification of effective therapeutic targets in the future, as well as improve the prognosis of patients with digestive system tumors.

scholarly journals Proteomic Analysis of the Secretome and Exosomes of Feline Adipose-Derived Mesenchymal Stem Cells

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 295
Author(s):  
Antonio J. Villatoro ◽  
María del Carmen Martín-Astorga ◽  
Cristina Alcoholado ◽  
María del Mar Sánchez-Martín ◽  
José Becerra
Keyword(s):  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Endocrine System ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Junctions ◽  
Bioactive Molecules ◽  
Protein Protein Interaction ◽  
Cell Signaling Pathways

Mesenchymal stem cells (MSCs) have been shown to have therapeutic efficacy in different complex pathologies in feline species. This effect is attributed to the secretion of a wide variety of bioactive molecules and extracellular vesicles, such as exosomes, with significant paracrine activity, encompassed under the concept of the secretome. However, at present, the exosomes from feline MSCs have not yet been studied in detail. The objective of this study is to analyze and compare the protein profiles of the secretome as a whole and its exosomal fraction from feline adipose-derived MSCs (fAd-MSCs). For this, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and Protein–Protein Interaction Networks Functional Enrichment Analysis (STRING) were utilized. A total of 239 proteins were identified in the secretome, and 228 proteins specific to exosomes were identified, with a total of 133 common proteins. The proteins identified in the secretome were located in the extracellular regions and in the cytoplasm, while the exosomal proteins were located mainly in the membrane, cytoplasm and cytosol. Regarding function, in the secretome, proteins involved in different metabolic pathways, in pathways related to the immune system and the endocrine system and in the processing of proteins in the endoplasmic reticulum predominated. In contrast, proteins specific to exosomes were predominantly associated with endocytosis, cell junctions, platelet activation and other cell signaling pathways. The possible future use of the secretome, or some of its components, such as exosomes, would provide a non-cell-based therapeutic strategy for the treatment of different diseases that would avoid the drawbacks of cell therapy.

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

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.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Identifying and characterizing lincRNA genomic clusters reveals its cooperative functions in human cancer

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Hanxiao Zhou ◽  
Yue Gao ◽  
Xin Li ◽  
Shipeng Shang ◽  
Peng Wang ◽  
...  
Keyword(s):  
Human Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Computational Method ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Pathophysiological Mechanism ◽  
Multiple Cancer ◽  
Cancer Types ◽  
Genomic Clusters

Abstract Background Emerging evidence has revealed that some long intergenic non-coding RNAs (lincRNAs) are likely to form clusters on the same chromosome, and lincRNA genomic clusters might play critical roles in the pathophysiological mechanism. However, the comprehensive investigation of lincRNA clustering is rarely studied, particularly the characterization of their functional significance across different cancer types. Methods In this study, we firstly constructed a computational method basing a sliding window approach for systematically identifying lincRNA genomic clusters. We then dissected these lincRNA genomic clusters to identify common characteristics in cooperative expression, conservation among divergent species, targeted miRNAs, and CNV frequency. Next, we performed comprehensive analyses in differentially-expressed patterns and overall survival outcomes for patients from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) across multiple cancer types. Finally, we explored the underlying mechanisms of lincRNA genomic clusters by functional enrichment analysis, pathway analysis, and drug-target interaction. Results We identified lincRNA genomic clusters according to the algorithm. Clustering lincRNAs tended to be co-expressed, highly conserved, targeted by more miRNAs, and with similar deletion and duplication frequency, suggesting that lincRNA genomic clusters may exert their effects by acting in combination. We further systematically explored conserved and cancer-specific lincRNA genomic clusters, indicating they were involved in some important mechanisms of disease occurrence through diverse approaches. Furthermore, lincRNA genomic clusters can serve as biomarkers with potential clinical significance and involve in specific pathological processes in the development of cancer. Moreover, a lincRNA genomic cluster named Cluster127 in DLK1-DIO3 imprinted locus was discovered, which contained MEG3, MEG8, MEG9, MIR381HG, LINC02285, AL132709.5, and AL132709.1. Further analysis indicated that Cluster127 may have the potential for predicting prognosis in cancer and could play their roles by participating in the regulation of PI3K-AKT signaling pathway. Conclusions Clarification of the lincRNA genomic clusters specific roles in human cancers could be beneficial for understanding the molecular pathogenesis of different cancer types.

scholarly journals Co-expression network analysis identifies specific hub genes in association with developmental neuronal remodeling in Drosophila melanogaster

2019 ◽  
Author(s):  
Yunze Liu ◽  
Xiaojie Sun ◽  
Aijun Qu
Keyword(s):  
Drosophila Melanogaster ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Neuronal Remodeling ◽  
Gene Modules

As an evolutionarily conserved mechanism, developmental neuronal remodeling is needed for the proper wiring of the nervous system and is critical for understanding the neurodevelopment mechanisms. Previous studies have shown that during metamorphosis lots of Drosophila melanogaster mushroom body neurons experience stereotypic remodeling. However, the related regulators and downstream executors of pathways are yet unclear, especially studies of transcriptional gene co-expression analysis of nervous systems remain insufficient. In this study, we develop a weighted gene co-expression network (WGCNA) to classify gene modules associated with neuronal remodeling. Moreover, functional and pathway enrichment analysis with protein-protein network construction is applied to detect high informative hub genes in the targeted gene module. Thus, we select a total of five hub genes that play critical roles in neuronal remodeling and identify them with functional enrichment analysis and protein-protein interaction network. Overall, this study provides insight into the underlying molecular mechanism of developmental neuronal remodeling in Drosophila melanogaster.

scholarly journals Long Noncoding RNA RP11-357H14.17 Plays an Oncogene Role in Gastric Cancer by Activating ATF2 Signaling and Enhancing Treg Cells

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Tang Xiaoli ◽  
Wang Wenting ◽  
Zhang Meixiang ◽  
Zuo Chunlei ◽  
Hu Chengxia
Keyword(s):  
Gastric Cancer ◽  
Noncoding Rna ◽  
Prognostic Value ◽  
Malignant Tumors ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Treg Cells ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Biological Behavior

Background. Gastric cancer (GC) is one of the most common malignant tumors in the world. The potential functions and mechanisms of long noncoding RNAs (lncRNAs) in GC development are still unclear. It is of great significance to explore the prognostic value of LncRNA signatures for GC. Methods. LncRNAs differently expressed in GC and their prognostic value were studied based on The Cancer Genome Atlas (TCGA) database. The functional regulatory network and immune infiltration of RP11-357H14.17 were further studied using a variety of bioinformatics tools and databases. Results. We found that the high expression of RP11-357H14.17 was closely associated with shortened overall survival (OS) and poor prognosis in gastric cancer patients. We also found that its expression was related to clinical features including tumor volume, metastasis, and differentiation. Functional enrichment analysis revealed that RP11-357H14.17 is closely related to enhanced DNA replication and metabolism; ssGSEA analysis implied the oncogenic roles of RP11-357H14.17 was related to ATF2 signaling and Treg cell differentiation. Furthermore, we verified such link by using real-time PCR and IHC staining in human GC samples. Conclusion. We demonstrate that RP11-357H14.17 may play a crucial role in the occurrence, development, and malignant biological behavior of gastric cancer as a potential prognostic marker for gastric cancer.

scholarly journals Apolipoprotein B Is Associated With the Microenvironment of Cholangiocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Xiaofeng Xu ◽  
Diyu Chen ◽  
Xiaode Feng ◽  
Jiating Hu ◽  
Jiangzhen Ge ◽  
...  
Keyword(s):  
Immune Cells ◽  
Apolipoprotein B ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Abundance Ratio ◽  
Functional Enrichment ◽  
Score System ◽  
Protein Protein Interaction ◽  
New Ideas ◽  
Differential Expressed Genes

BackgroundCholangiocarcinoma (CCA) is a kind of devastating malignancy, which is correlated with the extremely high mortality. Due to the occult pathogenesis of CCA, most patients are diagnosed in the advanced stage. However, the efficacy of chemotherapy and immunotherapy is limited for these patients. The cause for this phenomenon is unclear, the recent researches indicate that it could be related to predisposing genetic factors and tumor microenvironment (TME) changes. The TME is created by the tumor and dominated by tumor-induced interactions. And the tumor prognosis could be influenced by the extent of infiltrating immune cells and stromal cells in TME.Materials and methodsThe abundance ratio of immune cells for each sample was obtained via the CIBERSORT algorithm, and we used ESTIMATE score system to calculate the immune and stromal scores in CCA. The CCA cases in TCGA database were categorized into high and low score groups according to their immune/stromal scores. And then, we identified the differential expressed genes (DEGs) in two groups. Functional enrichment analysis and protein‐protein interaction networks were carried out for DEGs. Interestingly, we found out that apolipoprotein B (APOB) is the most down-regulated among these genes. Then we performed the immunohistochemistry staining of APOB in a CCA tumor microarray which contained 100 CCA cases, APOB was down-regulated in CCA samples. Thus, we evaluated the APOB function in the TME of CCA through TIMER.Results and ConclusionThe results demonstrate that the infiltration degree of immune cells in CCA could be influenced by the expression of APOB, and the APOB expression could be mediated by DNA methylation. Our study not only indicates APOB is a potential target for CCA immunotherapy but also provides new ideas for researchers to explore the immunotherapy of various tumors.

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