scholarly journals Colon Cancer-Related Genes Identification and Function Study Based on Single-Cell Multi-Omics Integration

2021 ◽  
Vol 9 ◽  
Author(s):  
Xuepu Sun ◽  
Yu Guo ◽  
Yu Zhang ◽  
Peng Zhao ◽  
Zhaoqing Wang ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Single Cell ◽  
Tumor Development ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Marker Genes ◽  
Colon Cells ◽  
Cancer Subtypes ◽  
Different Types

Transcriptomes and DNA methylation of colon cancer at the single-cell level are used to identify marker genes and improve diagnoses and therapies. Seven colon cancer subtypes are recognized based on the single-cell RNA sequence, and the differentially expressed genes regulated by dysregulated methylation are identified as marker genes for different types of colon cancer. Compared with normal colon cells, marker genes of different types show very obvious specificity, especially upregulated genes in tumors. Functional enrichment analysis for marker genes indicates a possible relation between colon cancer and nervous system disease, moreover, the weak immune system is verified in colon cancer. The heightened expression of markers and the reduction of methylation in colon cancer promote tumor development in an extensive mechanism so that there is no biological process that can be enriched in different types.

scholarly journals miRNA Mediated Noise Making of 3′UTR Mutations in Cancer

Genes ◽  
2018 ◽  
Vol 9 (11) ◽  
pp. 545 ◽  
Author(s):  
Wei Wu ◽  
Lingxiang Wu ◽  
Mengyan Zhu ◽  
Ziyu Wang ◽  
Min Wu ◽  
...  
Keyword(s):  
Somatic Mutations ◽  
Target Genes ◽  
Expression Profiles ◽  
Tumor Development ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Messenger Rnas ◽  
Cellular Functions ◽  
Mrna Binding

Somatic mutations in 3′-untranslated regions (3′UTR) do not alter amino acids and are considered to be silent in cancers. We found that such mutations can promote tumor progression by altering microRNA (miRNA) targeting efficiency and consequently affecting miRNA–mRNA interactions. We identified 67,159 somatic mutations located in the 3′UTRs of messenger RNAs (mRNAs) which can alter miRNA–mRNA interactions (functional somatic mutations, funcMutations), and 69.3% of these funcMutations (the degree of energy change > 12 kcal/mol) were identified to significantly promote loss of miRNA-mRNA binding. By integrating mRNA expression profiles of 21 cancer types, we found that the expression of target genes was positively correlated with the loss of absolute affinity level and negatively correlated with the gain of absolute affinity level. Functional enrichment analysis revealed that genes carrying funcMutations were significantly enriched in the MAPK and WNT signaling pathways, and analysis of regulatory modules identified eighteen miRNA modules involved with similar cellular functions. Our findings elucidate a complex relationship between miRNA, mRNA, and mutations, and suggest that 3′UTR mutations may play an important role in tumor development.

scholarly journals Comparative transcriptomic analysis of porcine peripheral blood reveals differentially expressed genes from the cytokine–cytokine receptor interaction pathway related to health status

Genome ◽  
2017 ◽  
Vol 60 (12) ◽  
pp. 1021-1028 ◽  
Author(s):  
M.H. Ye ◽  
H. Bao ◽  
Y. Meng ◽  
L.L. Guan ◽  
P. Stothard ◽  
...  
Keyword(s):  
Health Status ◽  
Differentially Expressed Genes ◽  
Peripheral Blood ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Cytokine Receptor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Marker Genes

While some research has looked into the host genetic response in pigs challenged with specific viruses or bacteria, few studies have explored the expression changes of transcripts in the peripheral blood of sick pigs that may be infected with multiple pathogens on farms. In this study, the architecture of the peripheral blood transcriptome of 64 Duroc sired commercial pigs, including 18 healthy animals at entry to a growing facility (set as a control) and 23 pairs of samples from healthy and sick pen mates, was generated using RNA-Seq technology. In total, 246 differentially expressed genes were identified to be specific to the sick animals. Functional enrichment analysis for those genes revealed that the over-represented gene ontology terms for the biological processes category were exclusively immune activity related. The cytokine–cytokine receptor interaction pathway was significantly enriched. Nine functional genes from this pathway encoding members (as well as their receptors) of the interleukins, chemokines, tumor necrosis factors, colony stimulating factors, activins, and interferons exhibited significant transcriptional alteration in sick animals. Our results suggest a subset of novel marker genes that may be useful candidate genes in the evaluation and prediction of health status in pigs under commercial production conditions.

scholarly journals Circular RNA screening identifies circMYLK4 as a regulator of fast/slow myofibers in porcine skeletal muscles

2020 ◽  
Author(s):  
Haigang Cao ◽  
Jieming Liu ◽  
Tianning Du ◽  
Yihao Liu ◽  
Xiaoyu Zhang ◽  
...  
Keyword(s):  
Muscle Development ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Circular Rna ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Marker Genes ◽  
Type Conversion ◽  
Myofiber Type

Abstract Background: The myofiber type is related to the quality of meat; specifically, slow-oxidized myofiber helps to increase the tenderness and juiciness of meat. An increasing number of studies have shown that circRNAs play a key role in skeletal muscle development. However, the key circRNAs that regulate myofiber types and their roles are still poorly understood.Results: A total of 40757 circRNAs were identified from the longissimus dorsi (LD) and the soleus (Sol) muscles, of which 10388 were co-expressed in the two muscles. Further analysis found 181 differentially expressed circRNAs in the LD compared with Sol. Functional enrichment analysis showed that target genes of differentially expressed circRNA-sponge miRNAs were enriched in the AMPK, FoxO and PI3K-Akt signaling pathways. In addition, we focused on a novel circRNA—circMYLK4. CircMYLK4 significantly increased the mRNA and protein levels of slow muscle marker genes and caused the flesh to turn red.Conclusion: Our study laid an essential foundation for further research on circRNAs in myofiber type conversion and the achievement of higher meat quality.

scholarly journals Development and Validation of a Prognostic Classifier Based on Metabolism-Related Genes for Breast Cancer

2021 ◽  
Author(s):  
Nan Wang ◽  
Lin Li ◽  
Jiangrui Chi ◽  
Xinwei Liu ◽  
Youyi Xiong ◽  
...  
Keyword(s):  
Lipid Metabolism ◽  
Cox Regression ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Marker Genes ◽  
Tissue Samples ◽  
Prognostic Gene

Abstract Background: Alterations in lipid metabolism have been implicated in the development of many tumors. However, the contribution of different lipid metabolism pathways to Breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA. Methods: We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set to harvest lipid metabolism-related genes. IPA was applied to identify the potential pathways and functions of DEGs related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature and independent prognostic analyses. Thereafter, the differential expression of the selected marker genes SDC1 and SORBS1 in clinical tissue samples was verified by qRT-PCR, western blotting, and immunohistochemical experiments. Functional enrichment analysis of prognostic genes was achieved by the GO and KEGG databases. Moreover, Kaplan-Meier analysis, ROC curves, clinical immunohistochemistry conditions and follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were then screened by CMap database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database.Results: IPA demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in a variety of lipid metabolism and BRCA pathological signatures. Subsequent functional enrichment analysis of candidate prognostic lipid metabolism DEGs also revealed a similar outcome. The prognostic classifier we constructed comprising SDC1 and SORBS1 has a strong prognostic potency that was verified by the clinical conditions and follow-up results, it also can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes. CTD indicated that the two prognostic genes had 16 drugs in common. Conclusion: Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This classifier had accurately predicted the prognosis of our follow-up BRCA patients and this result highlighted a new perspective on the metabolic exploration of BRCA. In addition, SDC1 and SORBS1 could serve as a possible new target for the synthesis of BRCA drugs.

scholarly journals Detecting Interactive Gene Groups for Single-Cell RNA-Seq Data Based on Co-Expression Network Analysis and Subgraph Learning

Cells ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1938 ◽  
Author(s):  
Xiucai Ye ◽  
Weihang Zhang ◽  
Yasunori Futamura ◽  
Tetsuya Sakurai
Keyword(s):  
Network Analysis ◽  
Single Cell ◽  
Tumor Heterogeneity ◽  
High Throughput Sequencing ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Cell Subpopulation ◽  
Rna Seq ◽  
Cancer Subtypes ◽  
Learning Framework

High-throughput sequencing technologies have enabled the generation of single-cell RNA-seq (scRNA-seq) data, which explore both genetic heterogeneity and phenotypic variation between cells. Some methods have been proposed to detect the related genes causing cell-to-cell variability for understanding tumor heterogeneity. However, most existing methods detect the related genes separately, without considering gene interactions. In this paper, we proposed a novel learning framework to detect the interactive gene groups for scRNA-seq data based on co-expression network analysis and subgraph learning. We first utilized spectral clustering to identify the subpopulations of cells. For each cell subpopulation, the differentially expressed genes were then selected to construct a gene co-expression network. Finally, the interactive gene groups were detected by learning the dense subgraphs embedded in the gene co-expression networks. We applied the proposed learning framework on a real cancer scRNA-seq dataset to detect interactive gene groups of different cancer subtypes. Systematic gene ontology enrichment analysis was performed to examine the detected genes groups by summarizing the key biological processes and pathways. Our analysis shows that different subtypes exhibit distinct gene co-expression networks and interactive gene groups with different functional enrichment. The interactive genes are expected to yield important references for understanding tumor heterogeneity.

scholarly journals Effect of rosemary polyphenols on human colon cancer cells: transcriptomic profiling and functional enrichment analysis

2012 ◽  
Vol 8 (1) ◽  
pp. 43-60 ◽  
Author(s):  
Alberto Valdés ◽  
Virginia García-Cañas ◽  
Lourdes Rocamora-Reverte ◽  
Ángeles Gómez-Martínez ◽  
José Antonio Ferragut ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Cancer Cells ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Human Colon ◽  
Functional Enrichment ◽  
Colon Cancer Cells ◽  
Human Colon Cancer ◽  
Transcriptomic Profiling ◽  
Human Colon Cancer Cells

scholarly journals Construction of a long noncoding RNA-based competing endogenous RNA network and prognostic signatures of left- and right-side colon cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ke-zhi Li ◽  
Yi-xin Yin ◽  
Yan-ping Tang ◽  
Long Long ◽  
Ming-zhi Xie ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Prognostic Value ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Molecular Characteristics ◽  
Prognostic Signature ◽  
Cerna Network ◽  
Colon Cancers ◽  
Cancer Tissues

Abstract Background Cancers located on the right and left sides of the colon have distinct clinical and molecular characteristics. This study aimed to explore the regulatory mechanisms of location-specific long noncoding RNAs (lncRNAs) as competing endogenous RNAs (ceRNAs) in colon cancer and identify potential prognostic biomarkers. Method Differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between right- and left-side colon cancers were identified by comparing RNA sequencing profiles. Functional enrichment analysis was performed for the DEGs, and a ceRNA network was constructed. Associations between DELs and patient survival were examined, and a DEL-based signature was constructed to examine the prognostic value of these differences. Clinical colon cancer tissues and Gene Expression Omnibus (GEO) datasets were used to validate the results. Results We identified 376 DELs, 35 DEMs, and 805 DEGs between right- and left-side colon cancers. The functional enrichment analysis revealed the functions and pathway involvement of DEGs. A ceRNA network was constructed based on 95 DEL–DEM–DEG interactions. Three DELs (LINC01555, AC015712, and FZD10-AS1) were associated with the overall survival of patients with colon cancer, and a prognostic signature was established based on these three DELs. High risk scores for this signature indicated poor survival, suggesting that the signature has prognostic value for colon cancer. Examination of clinical colon cancer tissues and GEO dataset analysis confirmed the results. Conclusion The ceRNA regulatory network suggests roles for location-specific lncRNAs in colon cancer and allowed the development of an lncRNA-based prognostic signature, which could be used to assess prognosis and determine treatment strategies in patients with colon cancer.

scholarly journals Circular RNA screening identifies circMYLK4 as a regulator of fast/slow myofibers in porcine skeletal muscles

2020 ◽  
Author(s):  
Haigang Cao ◽  
Jieming Liu ◽  
Tianning Du ◽  
Yihao Liu ◽  
Xiaoyu Zhang ◽  
...  
Keyword(s):  
Muscle Development ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Circular Rna ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Marker Genes ◽  
Type Conversion ◽  
Myofiber Type

Abstract Background: The myofiber type is related to the quality of meat; specifically, slow-oxidized myofiber helps to increase the tenderness and juiciness of meat. An increasing number of studies have shown that circRNAs play a key role in skeletal muscle development. However, the key circRNAs that regulate myofiber types and their roles are still poorly understood.Results: A total of 40757 circRNAs were identified from the longissimus dorsi (LD) and the soleus (Sol) muscles, of which 10388 were co-expressed in the two muscles. Further analysis found 181 differentially expressed circRNAs in the LD compared with Sol. Functional enrichment analysis showed that target genes of differentially expressed circRNA-sponge miRNAs were enriched in the AMPK, FoxO and PI3K-Akt signaling pathways. In addition, we focused on a novel circRNA—circMYLK4. CircMYLK4 significantly increased the mRNA and protein levels of slow muscle marker genes and caused the flesh to turn red.Conclusion: Our study laid an essential foundation for further research on circRNAs in myofiber type conversion and the achievement of higher meat quality.

scholarly journals Transcriptome Profiling of different types of human respiratory tract cells infected by SARS-CoV-2 Highlight an unique Role for Inflammatory and Interferon Response

2020 ◽  
Author(s):  
Minghui Yang ◽  
Luping Lei ◽  
Qiumei Cao ◽  
Yang Yang ◽  
Jun Wang ◽  
...  
Keyword(s):  
Respiratory Tract ◽  
Interaction Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Interferon Response ◽  
Receptor Interaction ◽  
Public Health Issue ◽  
Human Respiratory Tract ◽  
Different Types

AbstractThe emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19) at the end of 2019 has caused a large global outbreak and now become a major public health issue. Lack of data underlying how the human host interacts with SARS-CoV-2 virus. In the current study, We performed Venn-analysis, Gene ontology (GO), KEGG pathway analysis and Protein-protein interaction analysis of whole transcriptome studies with the aim of clarifying the genes and pathways potentially altered during human respiratory tract cells infected with SARS-CoV-2. We selected four studies through a systematic search of the Gene Expression Omnibus (GEO) database or published article about SARS-CoV-2 infection in different types of respiratory tract cells. We found 36 overlapping upregulated genes among different types of cells after viral infection. Further functional enrichment analysis revealed these DEGs are most likely involved in biological processes related to inflammatory response and response to cytokine, cell component related to extracellular space and I-kappaB/NF-kappaB complex, molecular function related to protein binding and cytokine activity. KEGG pathways analysis highlighted altered conical and casual pathways related to TNF, NF-kappa B, Cytokine-cytokine receptor interaction and IL17 signaling pathways during SARS-CoV-2 infection with CXCL1, CXCL2, CXCL3, CXCL8, CXCL10, IL32, CX3CL1, CCL20, IRF1, NFKB2 and NFKB1A up-regulated which may explain the inflammatory cytokine storms associated with severe cases of COVID-19.

scholarly journals Integrated Single-cell Bioinformatics Analysis Reveals Intrinsic and Extrinsic Biological Characteristics of Hematopoietic Stem Cell Aging

2021 ◽  
Author(s):  
Xiangjun Zeng ◽  
Xia Li ◽  
Mi Shao ◽  
Yulin Xu ◽  
Wei Shan ◽  
...  
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Signaling Pathway ◽  
Hematopoietic Stem Cell ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Biological Characteristics ◽  
Functional Enrichment ◽  
Cell Aging ◽  
Hematopoietic Stem

Abstract Hematopoietic stem cell (HSC) aging, which is accompanied by loss of self-renewal capacity, myeloid-biased differentiation and increased risks of hematopoietic malignancies, is an important focus in stem cell research. However, the mechanisms underlying HSC aging have not been fully elucidated. In the present study, we integrated 3 independent single-cell transcriptome datasets of HSCs together and identified Il10ra and Tnfsf14 as two markers of inflammatory and apoptosis-biased aged HSCs. Besides, common differentially expressed genes (DEGs) between young and aged HSCs were identified and further validated by quantitative RT-PCR. Functional enrichment analysis revealed that these DEGs were predominantly involved in the cell cycle and the tumor necrosis factor (TNF) signaling pathway. We further found that the Skp2-induced signaling pathway (Skp2→Cip1→CycA/CDK2→DP-1) contributed to a rapid transition through G1 phase in aged HSCs. In addition, analysis of the extrinsic alterations on HSC aging revealed the increased expression levels of inflammation genes in bone marrow microenvironment. Colony formation unit assays showed that inflammatory cytokines promoted cellular senescence and that blockade of inflammatory pathway markedly rejuvenated aged HSC functions and increased B cell output. Collectively, our study elucidated the biological characteristics of HSC aging, and the genes and pathways we identified could be potential biomarkers and targets for the identification and rejuvenation of aged HSCs.

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