scholarly journals CeRNA Network Analysis Representing Characteristics of Different Tumor Environments Based on 1p/19q Codeletion in Oligodendrogliomas

Cancers ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2543
Author(s):  
Ju Won Ahn ◽  
YoungJoon Park ◽  
Su Jung Kang ◽  
So Jung Hwang ◽  
Kyung Gi Cho ◽  
...  
Keyword(s):  
Network Analysis ◽  
Underlying Mechanism ◽  
The Cancer Genome Atlas ◽  
Potassium Ion Channels ◽  
Low Grade ◽  
Tumor Microenvironments ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
The Central Nervous System ◽  
Composition Changes

Oligodendroglioma (OD) is a subtype of glioma occurring in the central nervous system. The 1p/19q codeletion is a prognostic marker of OD with an isocitrate dehydrogenase (IDH) mutation and is associated with a clinically favorable overall survival (OS); however, the exact underlying mechanism remains unclear. Long non-coding RNAs (lncRNAs) have recently been suggested to regulate carcinogenesis and prognosis in cancer patients. Here, we performed in silico analyses using low-grade gliomas from datasets obtained from The Cancer Genome Atlas to investigate the effects of ceRNA with 1p/19q codeletion on ODs. Thus, we selected modules of differentially expressed genes that were closely related to 1p/19q codeletion traits using weighted gene co-expression network analysis and constructed 16 coding RNA–miRNA–lncRNA networks. The ceRNA network participated in ion channel activity, insulin secretion, and collagen network and extracellular matrix (ECM) changes. In conclusion, ceRNAs with a 1p/19q codeletion can create different tumor microenvironments via potassium ion channels and ECM composition changes; furthermore, differences in OS may occur. Moreover, if extrapolated to gliomas, our results can provide insights into the consequences of identical gene expression, indicating the possibility of tracking different biological processes in different subtypes of glioma.

scholarly journals A New Epigenetic Model to Stratify Glioma Patients According to Their Immunosuppressive State

Cells ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 576
Author(s):  
Maurizio Polano ◽  
Emanuele Fabbiani ◽  
Eva Adreuzzi ◽  
Federica Di Cintio ◽  
Luca Bedon ◽  
...  
Keyword(s):  
The Cancer Genome Atlas ◽  
Classification Model ◽  
Low Grade ◽  
Machine Learning Classification ◽  
Immune State ◽  
Out Of Sample ◽  
Cancer Genome Atlas ◽  
The Central Nervous System ◽  
Neural Network Classifiers ◽  
Definition Of

Gliomas are the most common primary neoplasm of the central nervous system. A promising frontier in the definition of glioma prognosis and treatment is represented by epigenetics. Furthermore, in this study, we developed a machine learning classification model based on epigenetic data (CpG probes) to separate patients according to their state of immunosuppression. We considered 573 cases of low-grade glioma (LGG) and glioblastoma (GBM) from The Cancer Genome Atlas (TCGA). First, from gene expression data, we derived a novel binary indicator to flag patients with a favorable immune state. Then, based on previous studies, we selected the genes related to the immune state of tumor microenvironment. After, we improved the selection with a data-driven procedure, based on Boruta. Finally, we tuned, trained, and evaluated both random forest and neural network classifiers on the resulting dataset. We found that a multi-layer perceptron network fed by the 338 probes selected by applying both expert choice and Boruta results in the best performance, achieving an out-of-sample accuracy of 82.8%, a Matthews correlation coefficient of 0.657, and an area under the ROC curve of 0.9. Based on the proposed model, we provided a method to stratify glioma patients according to their epigenomic state.

Comprehensive assessment of PD-L1 and PD-L2 dysregulation in gastrointestinal cancers

Epigenomics ◽  
2020 ◽  
Author(s):  
Qijie Zhao ◽  
Jinan Guo ◽  
Yueshui Zhao ◽  
Jing Shen ◽  
Parham Jabbarzadeh Kaboli ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Signaling Pathways ◽  
Underlying Mechanism ◽  
Comprehensive Analysis ◽  
The Cancer Genome Atlas ◽  
Gastrointestinal Cancers ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: PD-L1 and PD-L2 are ligands of PD-1. Their overexpression has been reported in different cancers. However, the underlying mechanism of PD-L1 and PD-L2 dysregulation and their related signaling pathways are still unclear in gastrointestinal cancers. Materials & methods: The expression of PD-L1 and PD-L2 were studied in The Cancer Genome Atlas and Genotype-Tissue Expression databases. The gene and protein alteration of PD-L1 and PD-L2 were analyzed in cBioportal. The direct transcription factor regulating PD-L1/ PD-L2 was determined with ChIP-seq data. The association of PD-L1/PD-L2 expression with clinicopathological parameters, survival, immune infiltration and tumor mutation burden were investigated with data from The Cancer Genome Atlas. Potential targets and pathways of PD-L1 and PD-L2 were determined by protein enrichment, WebGestalt and gene ontology. Results: Comprehensive analysis revealed that PD-L1 and PD-L2 were significantly upregulated in most types of gastrointestinal cancers and their expressions were positively correlated. SP1 was a key transcription factor regulating the expression of PD-L1. Conclusion: Higher PD-L1 or PD-L2 expression was significantly associated with poor overall survival, higher tumor mutation burden and more immune and stromal cell populations. Finally, HIF-1, ERBB and mTOR signaling pathways were most significantly affected by PD-L1 and PD-L2 dysregulation. Altogether, this study provided comprehensive analysis of the dysregulation of PD-L1 and PD-L2, its underlying mechanism and downstream pathways, which add to the knowledge of manipulating PD-L1/PD-L2 for cancer immunotherapy.

Identification of novel mRNA-miRNA-lncRNA competing endogenous RNA network associated with prognosis of breast cancer

Epigenomics ◽  
2019 ◽  
Vol 11 (13) ◽  
pp. 1501-1518 ◽  
Author(s):  
Guansheng Zhong ◽  
Weiyang Lou ◽  
Minya Yao ◽  
Chengyong Du ◽  
Haiyan Wei ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cancer Prognosis ◽  
Competing Endogenous Rna ◽  
Hub Genes ◽  
Cerna Network ◽  
Competing Endogenous Rna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: To identify novel competing endogenous RNA (ceRNA) network related to patients prognosis in breast cancer. Materials & methods: Dysregulated mRNA based on intersection of three Gene Expression Omnibus and The Cancer Genome Atlas datasets were analyzed by bioinformatics. Results: In total 72 upregulated and 208 downregulated genes were identified. Functional analysis showed that some pathways related to cancer were significantly enriched. By means of stepwise reverse prediction and validation from mRNA to lncRNA, 19 hub genes, nine key miRNA and four key lncRNAs were identified by expression and survival analysis. Ultimately, the coexpression analysis identified RRM2-let-7a-5p- SNHG16/ MAL2 as key ceRNA subnetwork associated with prognosis of breast cancer. Conclusion: We successfully constructed a novel ceRNA network, among which each component was significantly associated with breast cancer prognosis.

TNFα signalling predicts poor prognosis of patients with endometrial cancer

2020 ◽  
Vol 41 (8) ◽  
pp. 1065-1073
Author(s):  
Verena Wieser ◽  
Samira Abdel Azim ◽  
Susanne Sprung ◽  
Katharina Knoll ◽  
Johanna Kögl ◽  
...  
Keyword(s):  
Endometrial Cancer ◽  
Clinical Outcome ◽  
The Cancer Genome Atlas ◽  
Western World ◽  
Low Grade ◽  
Necrosis Factor Alpha ◽  
Cancer Genome Atlas ◽  
Factor Alpha ◽  
The Impact

Abstract Endometrial cancer (EC) is the most common gynaecologic tumour in the Western world. Previous studies have implicated an imbalance of oestrogens and progestogens in the development of most ECs, while the role of low-grade tissue inflammation remains largely unexplored. We investigated the impact of tumour necrosis factor alpha (TNFα), a central mediator of inflammation and spermatogenesis-associated protein 2 (SPATA2), a regulator of TNF receptor signalling, on clinical outcomes in EC. We evaluated TNFA and SPATA2 transcript levels in 239 EC patients and 25 non-malignant control tissues. Findings were validated in a cohort of 332 EC patients from The Cancer Genome Atlas (TCGA). Expression of TNFA and SPATA2 was increased in EC when compared with control tissues (P < 0.001). TNFA expression correlated with SPATA2 expression in non-malignant (P = 0.003, rS = 0.568) and EC tissue (P = 0.005, rS = 0.179). High TNFA and SPATA2 expression were associated with poor recurrence-free survival (RFS; P = 0.049 and P = 0.018) and disease-specific (P = 0.034 and P = 0.002) survival. Increased SPATA2 expression was also associated with decreased overall survival (OS; P = 0.013). In multivariate analysis, both TNFA and SPATA2 were predictors of clinical outcome. The impact of SPATA2 on RFS and OS could be validated in the TCGA cohort. Our study demonstrates that ECs exhibit a TNF signature which predicts clinical outcome. These findings indicate that TNF signalling modulates the course of EC, which could be therapeutically utilized in the future.

scholarly journals Molecular Determinants of Prognosis and Evolution in Diffuse-Lower Grade Astrocytomas

2020 ◽  
Author(s):  
Mehul Kumar ◽  
J Gregory Cairncross ◽  
Michael D Blough ◽  
Pinaki Bose
Keyword(s):  
The Cancer Genome Atlas ◽  
Low Grade ◽  
Lower Grade ◽  
Mutational Status ◽  
Molecular Determinants ◽  
Pdgf Signaling ◽  
Evolutionary Trajectories ◽  
Cancer Genome Atlas ◽  
Natural Histories ◽  
Worse Prognosis

ABSTRACTLow grade astrocytomas (LGAs) are classified based on the mutational status of the isocitrate dehydrogenase (IDH) gene. While IDH wild-type (WT) LGAs evolve rapidly to glioblastoma, mutant tumors generally have a more indolent course. To identify potential drivers of the differential progression of LGAs, we analyzed transcriptomes from The Cancer Genome Atlas. Compared to mutant LGAs, platelet-derived growth factor (PDGF) signaling is enriched in WT cases, and PDGFA is the top overexpressed gene in the pathway. Putative mechanisms for differential PDGFA expression included copy number gains of chromosome 7 in WT cases and methylation of the PDGFA promoter in mutant LGAs. Additionally, we found that high PDGFA expression is associated with aneuploidy, immunosuppressive features, and worse prognosis, and that WT LGAs use multiple means to inactivate the p53 pathway to progress to GBM. Our work highlights the contribution of PDGF gene family towards the unique behaviour of LGAs.STATEMENT OF SIGNIFICANCEThis study of gene expression in LGAs suggests that differential regulation of the PDGF pathway may underlie the different natural histories of IDH WT and IDH mutant LGAs including divergent evolutionary trajectories to GBM. This insight may inspire new therapeutic strategies to suppress the transformation of LGAs to higher-grade cancers.

scholarly journals A Six-lncRNA Signature for Immunophenotype Prediction of Glioblastoma Multiforme

2021 ◽  
Vol 11 ◽  
Author(s):  
Ming Gao ◽  
Xinzhuang Wang ◽  
Dayong Han ◽  
Enzhou Lu ◽  
Jian Zhang ◽  
...  
Keyword(s):  
Glioblastoma Multiforme ◽  
Immune Cell ◽  
Area Under The Curve ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Non Coding Rna ◽  
Cancer Genome Atlas ◽  
The Central Nervous System

Glioblastoma multiforme (GBM) is the most aggressive primary tumor of the central nervous system. As biomedicine advances, the researcher has found the development of GBM is closely related to immunity. In this study, we evaluated the GBM tumor immunoreactivity and defined the Immune-High (IH) and Immune-Low (IL) immunophenotypes using transcriptome data from 144 tumors profiled by The Cancer Genome Atlas (TCGA) project based on the single-sample gene set enrichment analysis (ssGSEA) of five immune expression signatures (IFN-γ response, macrophages, lymphocyte infiltration, TGF-β response, and wound healing). Next, we identified six immunophenotype-related long non-coding RNA biomarkers (im-lncRNAs, USP30-AS1, HCP5, PSMB8-AS1, AL133264.2, LINC01684, and LINC01506) by employing a machine learning computational framework combining minimum redundancy maximum relevance algorithm (mRMR) and random forest model. Moreover, the expression level of identified im-lncRNAs was converted into an im-lncScore using the normalized principal component analysis. The im-lncScore showed a promising performance for distinguishing the GBM immunophenotypes with an area under the curve (AUC) of 0.928. Furthermore, the im-lncRNAs were also closely associated with the levels of tumor immune cell infiltration in GBM. In summary, the im-lncRNA signature had important clinical implications for tumor immunophenotyping and guiding immunotherapy in glioblastoma patients in future.

scholarly journals Identification of Potential Signatures and Their Functions for Acute Lymphoblastic Leukemia: A Study Based on the Cancer Genome Atlas

2021 ◽  
Vol 12 ◽  
Author(s):  
Weimin Wang ◽  
Chunhui Lyu ◽  
Fei Wang ◽  
Congcong Wang ◽  
Feifei Wu ◽  
...  
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Real Time ◽  
Lymphoblastic Leukemia ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Hub Genes ◽  
Cerna Network ◽  
Cancer Genome Atlas ◽  
Genome Atlas ◽  
Real Time Qpcr

ObjectiveAcute lymphoblastic leukemia (ALL) is a malignant disease most commonly diagnosed in adolescents and young adults. This study aimed to explore potential signatures and their functions for ALL.MethodsDifferentially expressed mRNAs (DEmRNAs) and differentially expressed long non-coding RNAs (DElncRNAs) were identified for ALL from The Cancer Genome Atlas (TCGA) and normal control from Genotype-Tissue Expression (GTEx). DElncRNA–microRNA (miRNA) and miRNA–DEmRNA pairs were predicted using online databases. Then, a competing endogenous RNA (ceRNA) network was constructed. Functional enrichment analysis of DEmRNAs in the ceRNA network was performed. Protein–protein interaction (PPI) network was then constructed. Hub genes were identified. DElncRNAs in the ceRNA network were validated using Real-time qPCR.ResultsA total of 2,903 up- and 3,228 downregulated mRNAs and 469 up- and 286 downregulated lncRNAs were identified for ALL. A ceRNA network was constructed for ALL, consisting of 845 lncRNA-miRNA and 395 miRNA–mRNA pairs. These DEmRNAs in the ceRNA network were mainly enriched in ALL-related biological processes and pathways. Ten hub genes were identified, including SMAD3, SMAD7, SMAD5, ZFYVE9, FKBP1A, FZD6, FZD7, LRP6, WNT1, and SFRP1. According to Real-time qPCR, eight lncRNAs including ATP11A-AS1, ITPK1-AS1, ANO1-AS2, CRNDE, MALAT1, CACNA1C-IT3, PWRN1, and WT1-AS were significantly upregulated in ALL bone marrow samples compared to normal samples.ConclusionOur results showed the lncRNA expression profiles and constructed ceRNA network in ALL. Furthermore, eight lncRNAs including ATP11A-AS1, ITPK1-AS1, ANO1-AS2, CRNDE, MALAT1, CACNA1C-IT3, PWRN1, and WT1-AS were identified. These results could provide a novel insight into the study of ALL.

scholarly journals Aging-Related Tumor Microenvironment Changes Could Worsen The Prognosis of GBM Patients

2020 ◽  
Author(s):  
Hongwang Song ◽  
Xiaojun Fu ◽  
Chenxing Wu ◽  
Shouwei Li
Keyword(s):  
Tumor Microenvironment ◽  
Epithelial Mesenchymal Transition ◽  
Close Correlation ◽  
Underlying Mechanism ◽  
The Cancer Genome Atlas ◽  
Future Research ◽  
Mesenchymal Transition ◽  
Cancer Genome Atlas ◽  
Differential Expressed Genes ◽  
Genome Atlas

Abstract Background: Glioblastoma multiforme (GBM) is the most malignant tumor in human brain, with highly heterogeneity among different patients. Age could function as an incidence and prognosis risk factor for many tumors.Method: A series of bioinformatic experiments were conducted to evaluate the differences of incidence, differential expressed genes, enriched pathways with the data from Surveillance, Epidemiology, and End Results (SEER) program, the cancer genome atlas (TCGA) and Chinese glioma genome atlas (CGGA) project.Results: We discovered in our present study that distinct difference of incidence and prognosis of different aged GBM patients. By a series of bioinformatic method, we found that the tumor associated fibroblasts (TAFs) was the most crucial tumor microenvironment (TME) component that led to this phenomenon. Epithelial-mesenchymal transition (EMT) could be the mechanism by which TAFs regulate the progression of GBM. Conclusion: We have proposed a close correlation between age and GBM incidence and prognosis, and propose the underlying mechanism behind this correlation by mining different databases, which laid the foundation for future research.

scholarly journals Characterization of ceRNA network to reveal potential prognostic biomarkers in triple-negative breast cancer

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7522 ◽  
Author(s):  
Xiang Song ◽  
Chao Zhang ◽  
Zhaoyun Liu ◽  
Qi Liu ◽  
Kewen He ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Triple Negative Breast Cancer ◽  
Triple Negative ◽  
Quantitative Polymerase Chain Reaction ◽  
The Cancer Genome Atlas ◽  
Expression Level ◽  
Cerna Network ◽  
Kaplan Meier ◽  
Cancer Genome Atlas ◽  
Non Coding Rnas

Triple-negative breast cancer (TNBC) is a particular subtype of breast malignant tumor with poorer prognosis than other molecular subtypes. Previous studies have demonstrated that some abnormal expression of non-coding RNAs including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) were closely related to tumor cell proliferation, apoptosis, invasion, migration and drug sensitivity. However, the role of non-coding RNAs in the pathogenesis of TNBC is still unclear. In order to characterize the molecular mechanism of non-coding RNAs in TNBC, we downloaded RNA data and miRNA data from the cancer genome atlas database. We successfully identified 686 message RNAs (mRNAs), 26 miRNAs and 50 lncRNAs as key molecules for high risk of TNBC. Then, we hypothesized that the lncRNA–miRNA–mRNA regulatory axis positively correlates with TNBC and constructed a competitive endogenous RNA (ceRNA) network of TNBC. Our series of analyses has shown that five molecules (TERT, TRIML2, PHBP4, mir-1-3p, mir-133a-3p) were significantly associated with the prognosis of TNBC, and there is a prognostic ceRNA sub-network between those molecules. We mapped the Kaplan–Meier curve of RNA on the sub-network and also suggested that the expression level of the selected RNA is related to the survival rate of breast cancer. Reverse transcription-quantitative polymerase chain reaction showed that the expression level of TRIML2 in TNBC cells was higher than normal. In general, our findings have implications for predicting metastasis, predicting prognosis and discovering new therapeutic targets for TNBC.

scholarly journals Immune Cytolytic Activity for Comprehensive Understanding of Immune Landscape in Hepatocellular Carcinoma

Cancers ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1221 ◽  
Author(s):  
Hideo Takahashi ◽  
Tsutomu Kawaguchi ◽  
Li Yan ◽  
Xuan Peng ◽  
Qianya Qi ◽  
...  
Keyword(s):  
Protective Factor ◽  
Cytolytic Activity ◽  
The Cancer Genome Atlas ◽  
M1 Macrophages ◽  
Tumor Microenvironments ◽  
Gene Sets ◽  
Anti Cancer ◽  
Cancer Genome Atlas ◽  
High Exhaustion ◽  
Editing Enzyme

Cytolytic activity score (CYT), defined by granzyme A and perforin expression, is a useful marker for underlying immunity. We hypothesized that CYT-high hepatocellular carcinomas (HCCs) have stronger immunogenicity and favorable tumor microenvironments, which would result in better clinical outcomes, using the cancer genome atlas (TCGA) cohort with 371 patients with HCC. We found CYT-high HCCs were associated with higher expressions of the apolipoprotein B mRNA editing enzyme catalytic polypeptide-like 3 (APOBEC3), well-known mutagenic enzymes. Further, higher numbers of anti-cancer immune cells, such as CD8+ T cells and M1 macrophages, were infiltrated in CYT-high HCCs. Major T cell exhaustion markers were expressed significantly higher in CYT-high HCCs, likely as a negative feedback loop. Additionally, CYT-high HCCs strongly enriched gene sets related with enhanced immune activity. With strong immunity, patients with CYT-high HCCs had significantly longer disease-specific survival (DSS) and overall survival (OS) (p = 0.03 and <0.01). Furthermore, when the OS is stratified by exhaustion marker expressions, the CYT-high/exhaustion-low group had the best and CYT-low/exhaustion-high groups had the worst OS. Lastly, high CYT was an independent protective factor for prognosis. In conclusion, CYT-high HCCs were associated with enhanced immunity and better survival. Our findings suggest that proper identification of tumor-immune microenvironments could stratify the patients for appropriate treatments.

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