scholarly journals Integrative analysis of mRNA and miRNA sequencing data for gliomas of various grades

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Dmitry Y. Gvaldin ◽  
Anton A. Pushkin ◽  
Nataliya N. Timoshkina ◽  
Eduard E. Rostorguev ◽  
Arbi M. Nalgiev ◽  
...  
Keyword(s):  
Overall Survival ◽  
Mirna Expression ◽  
Interaction Analysis ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Differential Analysis ◽  
Sequencing Data ◽  
Aberrant Expression

Abstract Background The purpose of this study was to characterize subtype-specific patterns of mRNA and miRNA expression of gliomas using The Cancer Genome Atlas (TCGA) data to search for genetic determinants that predict prognosis in terms of overall survival and to create interaction networks for grade 2 and 3 (G2 and G3) astrocytomas, oligodendrogliomas and grade 4 (G4) glioblastoma multiforme. Based on open-access TCGA data, 5 groups were formed: astrocytoma G2 (n = 58), astrocytoma G3 (n = 128), oligodendroglioma G2 (n = 102), oligodendroglioma G3 (n = 72) and glioblastoma G4 (n = 564); normal samples of brain tissue were also analysed (n = 15). Data of patient age, sex, survival and expression patterns of mRNA and miRNA were extracted for each sample. After stratification of the data into groups, a differential analysis of expression was carried out, genes and miRNAs that affect overall survival were identified and gene set enrichment analysis (GSEA) and interaction analysis were performed. Results A total of 939 samples of glial tumours were analysed, for which subtype-specific expression profiles of genes and miRNAs were identified and networks of mRNA-miRNA interactions were constructed. Genes whose aberrant expression level was associated with survival were determined, and pairwise correlations between differential gene expression (DEG) and differential miRNA expression (DE miRNA) were calculated. Conclusions The developed panel of genes and miRNAs allowed us to differentiate glioma subtypes and evaluate prognosis in terms of the overall survival of patients. The regulatory miRNA-mRNA pairs unique to the five glioma subtypes identified in this study can stimulate the development of new therapeutic approaches based on subtype-specific mechanisms of oncogenesis.

scholarly journals Data analysis of high-throughput sequencing and microarray to identify key signatures of microribonucleic acids in glioblastoma

2021 ◽  
Vol 8 (3) ◽  
pp. 21-33
Author(s):  
A. A. Pushkin ◽  
E. A. Dzenkova ◽  
N. N. Timoshkina ◽  
D. Yu. Gvaldin
Keyword(s):  
Mirna Expression ◽  
High Throughput Sequencing ◽  
Patient Survival ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Differential Expression Analysis ◽  
The Cancer Genome Atlas ◽  
Normal Brain ◽  
Sequencing Data ◽  
Tissue Samples

Purpose of the study. This research was devoted to study of mRNA and miRNA expression patterns in glioglastomas using The Cancer Genome Atlas (TCGA) data, to search for genetic determinants that determine the prognosis of patient survival and to create of interaction networks for glioblastomas.Materials and methods. Based on the data of the open TCGA database groups of glioblastomas and conventionally normal brain tissue samples were formed. Survival gene and miRNA expression data were extracted for each sample. After the data stratification by groups the differential expression analysis and search the genes affecting patient survival was carried out. The enrichment analysis by functional affiliation and an interactome analysis were performed.Results. A total of 156 glioblastoma samples with mRNA sequencing data, 571 samples with microarray microRNA analysis data, and 15 control samples were analyzed. Networks of mRNA-miRNA interactions were built and expression profiles of genes and miRNAs characteristic of glioblastomas were developed. We have determined the genes which aberrant level is associated with survival and shown the pairwise DEG and DE of microRNA correlations.Conclusion. The microRNA-mRNA regulatory pairs identified for glioblastomas can stimulate the development of new therapeutic approaches based on subtype-specific regulatory mechanisms of oncogenesis.

scholarly journals Single-cell analysis of a tumor-derived exosome signature correlates with prognosis and immunotherapy response

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jiani Wu ◽  
Dongqiang Zeng ◽  
Shimeng Zhi ◽  
Zilan Ye ◽  
Wenjun Qiu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Single Cell ◽  
Immune Modulation ◽  
Expression Profiles ◽  
Predictive Biomarkers ◽  
Disease Diagnosis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Cancer Types

Abstract Background Tumor-derived exosomes (TEXs) are involved in tumor progression and the immune modulation process and mediate intercellular communication in the tumor microenvironment. Although exosomes are considered promising liquid biomarkers for disease diagnosis, it is difficult to discriminate TEXs and to develop TEX-based predictive biomarkers. Methods In this study, the gene expression profiles and clinical information were collected from The Cancer Genome Atlas (TCGA) database, IMvigor210 cohorts, and six independent Gene Expression Omnibus datasets. A TEXs-associated signature named TEXscore was established to predict overall survival in multiple cancer types and in patients undergoing immune checkpoint blockade therapies. Results Based on exosome-associated genes, we first constructed a tumor-derived exosome signature named TEXscore using a principal component analysis algorithm. In single-cell RNA-sequencing data analysis, ascending TEXscore was associated with disease progression and poor clinical outcomes. In the TCGA Pan-Cancer cohort, TEXscore was elevated in tumor samples rather than in normal tissues, thereby serving as a reliable biomarker to distinguish cancer from non-cancer sources. Moreover, high TEXscore was associated with shorter overall survival across 12 cancer types. TEXscore showed great potential in predicting immunotherapy response in melanoma, urothelial cancer, and renal cancer. The immunosuppressive microenvironment characterized by macrophages, cancer-associated fibroblasts, and myeloid-derived suppressor cells was associated with high TEXscore in the TCGA and immunotherapy cohorts. Besides, TEXscore-associated miRNAs and gene mutations were also identified. Further experimental research will facilitate the extending of TEXscore in tumor-associated exosomes. Conclusions TEXscore capturing tumor-derived exosome features might be a robust biomarker for prognosis and treatment responses in independent cohorts.

scholarly journals A novel survival model based on a Ferroptosis-related gene signature for predicting overall survival in bladder cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Yingchun Liang ◽  
Fangdie Ye ◽  
Chenyang Xu ◽  
Lujia Zou ◽  
Yun Hu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Prognostic Value ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Risk Groups ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognosis Prediction

Abstract Background The effective treatment and prognosis prediction of bladder cancer (BLCA) remains a medical problem. Ferroptosis is an iron-dependent form of programmed cell death. Ferroptosis is closely related to tumour occurrence and progression, but the prognostic value of ferroptosis-related genes (FRGs) in BLCA remains to be further clarified. In this study, we identified an FRG signature with potential prognostic value for patients with BLCA. Methods The corresponding clinical data and mRNA expression profiles of BLCA patients were downloaded from The Cancer Genome Atlas (TCGA). Univariate Cox regression was used to extract FRGs related to survival time, and a Cox regression model was used to construct a multigene signature. Both principal component analysis (PCA) and single-sample gene set enrichment analysis (ssGSEA) were performed for functional annotation. Results Clinical traits were combined with FRGs, and 15 prognosis-related FRGs were identified by Cox regression. High expression of CISD1, GCLM, CRYAB, SLC7A11, TFRC, ACACA, ZEB1, SQLE, FADS2, ABCC1, G6PD and PGD was related to poor survival in BLCA patients. Multivariate Cox regression was used to construct a prognostic model with 7 FRGs that divided patients into two risk groups. Compared with that in the low-risk group, the overall survival (OS) of patients in the high-risk group was significantly lower (P < 0.001). In multivariate regression analysis, the risk score was shown to be an independent predictor of OS (HR = 1.772, P < 0.01). Receiver operating characteristic (ROC) curve analysis verified the predictive ability of the model. In addition, the two risk groups displayed different immune statuses in ssGSEA and different distributed patterns in PCA. Conclusion Our research suggests that a new gene model related to ferroptosis can be applied for the prognosis prediction of BLCA. Targeting FRGs may be a treatment option for BLCA.

scholarly journals Transcriptome Analysis in Vulvar Squamous Cell Cancer

Cancers ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 6372
Author(s):  
Katharina Prieske ◽  
Malik Alawi ◽  
Anna Jaeger ◽  
Maximilian Christian Wankner ◽  
Kathrin Eylmann ◽  
...  
Keyword(s):  
Squamous Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Cell Cancer ◽  
Rna Expression ◽  
Sequencing Data ◽  
Aberrant Expression ◽  
Distinct Cluster ◽  
Whole Exome Sequencing Data ◽  
Chronic Skin

To date, therapeutic strategies in vulvar squamous cell carcinoma (VSCC) are lacking molecular pathological information and targeted therapy hasn’t been approved in the treatment of VSCC, yet. Two etiological pathways are widely accepted: HPV induced vs. HPV independent, associated with chronic skin disease, often harboring TP53 mutations (mut). The aim of this analysis was to analyze the RNA expression patterns for subtype stratification on VSCC samples that can be integrated into the previously performed whole exome sequencing data for the detection of prognostic markers and potential therapeutic targets. We performed multiplex gene expression analysis (NanoString) with 770 genes in 24 prior next generation sequenced samples. An integrative data analysis was performed. Here, 98 genes were differentially expressed in TP53mut vs. HPV+ VSCC, in the TP53mut cohort, where 56 genes were upregulated and 42 were downregulated in comparison to the HPV+ tumors. Aberrant expression was primarily observed in cell cycle regulation, especially in HPV+ disease. Within the TP53mut group, a distinct cluster was identified that was correlated to a significantly worse overall survival (p = 0.017). The RNA expression profiles showed distinct patterns with regard to the known VSCC subtypes and could potentially enable further subclassification in the TP53mut groups

scholarly journals Integrated analysis of differentially expressed profiles and construction of a competing endogenous long non-coding RNA network in renal cell carcinoma

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5124 ◽  
Author(s):  
Qianwei Xing ◽  
Yeqing Huang ◽  
You Wu ◽  
Limin Ma ◽  
Bo Cai
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Rna Expression ◽  
Cerna Network

Background Long non-coding RNAs (lncRNAs) play crucial roles in the initiation and progression of renal cell carcinoma (RCC) by competing in binding to miRNAs, and related competitive endogenous RNA (ceRNA) networks have been constructed in several cancers. However, the coexpression network has been poorly explored in RCC. Methods We collected RCC RNA expression profile data and relevant clinical features from The Cancer Genome Atlas (TCGA). A cluster analysis was explored to show different lncRNA expression patterns. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and gene set enrichment analysis (GSEA) were performed to analyze the functions of the intersecting mRNAs. Targetscan and miRanda bioinformatics algorithms were used to predict potential relationships among RNAs. Univariate Cox proportional hazards regression was conducted to determine the RNA expression levels and survival times. Results Bioinformatics analysis revealed that the expression profiles of hundreds of aberrantly expressed lncRNAs, miRNAs, and mRNAs were significantly changed between different stages of tumors and non-tumor groups. By combining the data predicted by databases with intersection RNAs, a ceRNA network consisting of 106 lncRNAs, 26 miRNAs and 69 mRNAs was established. Additionally, a protein interaction network revealed the main hub nodes (VEGFA, NTRK2, DLG2, E2F2, MYB and RUNX1). Furthermore, 63 lncRNAs, four miRNAs and 31 mRNAs were significantly associated with overall survival. Conclusion Our results identified cancer-specific lncRNAs and constructed a ceRNA network for RCC. A survival analysis related to the RNAs revealed candidate biomarkers for further study in RCC.

scholarly journals A TP53-associated immune prognostic signature for the prediction of the overall survival and therapeutic responses in pancreatic cancer

2021 ◽  
Vol 19 (1) ◽  
pp. 191-208
Author(s):  
Yi Liu ◽  
◽  
Long Cheng ◽  
Xiangyang Song ◽  
Chao Li ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Tp53 Mutation ◽  
Prolactin Receptor ◽  
High Risk Group ◽  
Cancer Genome ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Large Sample Size ◽  
Sequencing Data

<abstract> <p>Pancreatic cancer (PC) is a highly fatal disease correlated with an inferior prognosis. The tumor protein p53 (TP53) is one of the frequent mutant genes in PC and has been implicated in prognosis. We collected somatic mutation data, RNA sequencing data, and clinical information of PC samples in the Cancer Genome Atlas (TCGA) database. TP53 mutation was an independent prognostic predictor of PC patients. According to TP53 status, Gene set enrichment analysis (GSEA) suggested that TP53 mutations were related to the immunophenotype of pancreatic cancer. We identified 102 differentially expressed immune genes (DEIGs) based on TP53 mutation status and developed a TP53-associated immune prognostic model (TIPM), including Epiregulin (EREG) and Prolactin receptor (PRLR). TIPM identified the high-risk group with poor outcomes and more significant response potential to cisplatin, gemcitabine, and paclitaxel therapies. And we verified the TIPM in the International Cancer Genome Consortium (ICGC) cohort (PACA-AU) and Gene Expression Omnibus (GEO) cohort (GSE78229 and GSE28735). Finally, we developed a nomogram that reliably predicts overall survival in PC patients on the bias of TIPM and other clinicopathological factors. Our study indicates that the TIPM derived from TP53 mutation patterns might be an underlying prognostic therapeutic target. But more comprehensive researches with a large sample size is necessary to confirm the potential.</p> </abstract>

The Predominant microRNAs in β-cell Clusters for Insulin Regulation and Diabetic Control

2020 ◽  
Vol 21 (7) ◽  
pp. 722-734
Author(s):  
Adele Soltani ◽  
Arefeh Jafarian ◽  
Abdolamir Allameh
Keyword(s):  
Mirna Expression ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Diabetic Control ◽  
In Vitro Proliferation ◽  
Cell Functions ◽  
Mirna Expression Profiles ◽  
Multiple Processes ◽  
The Impact

micro (mi)-RNAs are vital regulators of multiple processes including insulin signaling pathways and glucose metabolism. Pancreatic &#946;-cells function is dependent on some miRNAs and their target mRNA, which together form a complex regulative network. Several miRNAs are known to be directly involved in &#946;-cells functions such as insulin expression and secretion. These small RNAs may also play significant roles in the fate of &#946;-cells such as proliferation, differentiation, survival and apoptosis. Among the miRNAs, miR-7, miR-9, miR-375, miR-130 and miR-124 are of particular interest due to being highly expressed in these cells. Under diabetic conditions, although no specific miRNA profile has been noticed, the expression of some miRNAs and their target mRNAs are altered by posttranscriptional mechanisms, exerting diverse signs in the pathobiology of various diabetic complications. The aim of this review article is to discuss miRNAs involved in the process of stem cells differentiation into &#946;-cells, resulting in enhanced &#946;-cell functions with respect to diabetic disorders. This paper will also look into the impact of miRNA expression patterns on in vitro proliferation and differentiation of &#946;-cells. The efficacy of the computational genomics and biochemical analysis to link the changes in miRNA expression profiles of stem cell-derived &#946;-cells to therapeutically relevant outputs will be discussed as well.

scholarly journals HEDGEHOG/GLI Modulates the PRR11-SKA2 Bidirectional Transcription Unit in Lung Squamous Cell Carcinomas

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 120
Author(s):  
Yiyun Sun ◽  
Dandan Xu ◽  
Chundong Zhang ◽  
Yitao Wang ◽  
Lian Zhang ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Squamous Cell ◽  
Gene Pair ◽  
Gene List ◽  
Ectopic Expression ◽  
Lung Squamous Cell Carcinoma ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Sequencing Data ◽  
Gene Set

We previously demonstrated that proline-rich protein 11 (PRR11) and spindle and kinetochore associated 2 (SKA2) constituted a head-to-head gene pair driven by a prototypical bidirectional promoter. This gene pair synergistically promoted the development of non-small cell lung cancer. However, the signaling pathways leading to the ectopic expression of this gene pair remains obscure. In the present study, we first analyzed the lung squamous cell carcinoma (LSCC) relevant RNA sequencing data from The Cancer Genome Atlas (TCGA) database using the correlation analysis of gene expression and gene set enrichment analysis (GSEA), which revealed that the PRR11-SKA2 correlated gene list highly resembled the Hedgehog (Hh) pathway activation-related gene set. Subsequently, GLI1/2 inhibitor GANT-61 or GLI1/2-siRNA inhibited the Hh pathway of LSCC cells, concomitantly decreasing the expression levels of PRR11 and SKA2. Furthermore, the mRNA expression profile of LSCC cells treated with GANT-61 was detected using RNA sequencing, displaying 397 differentially expressed genes (203 upregulated genes and 194 downregulated genes). Out of them, one gene set, including BIRC5, NCAPG, CCNB2, and BUB1, was involved in cell division and interacted with both PRR11 and SKA2. These genes were verified as the downregulated genes via RT-PCR and their high expression significantly correlated with the shorter overall survival of LSCC patients. Taken together, our results indicate that GLI1/2 mediates the expression of the PRR11-SKA2-centric gene set that serves as an unfavorable prognostic indicator for LSCC patients, potentializing new combinatorial diagnostic and therapeutic strategies in LSCC.

scholarly journals Differential expression and correlation analysis of miRNA–mRNA profiles in swine testicular cells infected with porcine epidemic diarrhea virus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xiaoqian Zhang ◽  
Chang Li ◽  
Bingzhou Zhang ◽  
Zhonghua Li ◽  
Wei Zeng ◽  
...  
Keyword(s):  
Differential Expression ◽  
Porcine Epidemic Diarrhea Virus ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Bacterial Invasion ◽  
Sequencing Data ◽  
Diarrhea Virus ◽  
Comparison Groups ◽  
Porcine Epidemic Diarrhea

AbstractThe variant virulent porcine epidemic diarrhea virus (PEDV) strain (YN15) can cause severe porcine epidemic diarrhea (PED); however, the attenuated vaccine-like PEDV strain (YN144) can induce immunity in piglets. To investigate the differences in pathogenesis and epigenetic mechanisms between the two strains, differential expression and correlation analyses of the microRNA (miRNA) and mRNA in swine testicular (ST) cells infected with YN15, YN144, and mock were performed on three comparison groups (YN15 vs Control, YN144 vs Control, and YN15 vs YN144). The mRNA and miRNA expression profiles were obtained using next-generation sequencing (NGS), and the differentially expressed (DE) (p-value < 0.05) mRNA and miRNA were obtained using DESeq R package. mRNAs targeted by DE miRNAs were predicted using the miRanda algortithm. 8039, 8631 and 3310 DE mRNAs, and 36, 36, and 22 DE miRNAs were identified in the three comparison groups, respectively. 14,140, 15,367 and 3771 DE miRNA–mRNA (targeted by DE miRNAs) interaction pairs with negatively correlated expression patterns were identified, and interaction networks were constructed using Cytoscape. Six DE miRNAs and six DE mRNAs were randomly selected to verify the sequencing data by real-time relative quantitative reverse transcription polymerase chain reaction (qRT-PCR). Based on bioinformatics analysis, we discovered the differences were mostly involved in host immune responses and viral pathogenicity, including NF-κB signaling pathway and bacterial invasion of epithelial cells, etc. This is the first comprehensive comparison of DE miRNA–mRNA pairs in YN15 and YN144 infection in vitro, which could provide novel strategies for the prevention and control of PED.

scholarly journals Identification of the angiogenesis related genes for predicting prognosis of patients with gastric cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Sheng Zheng ◽  
Zizhen Zhang ◽  
Ning Ding ◽  
Jiawei Sun ◽  
Yifeng Lin ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
High Efficiency ◽  
Cox Regression ◽  
Risk Group ◽  
The Cancer Genome Atlas ◽  
Differentially Expressed ◽  
Lasso Regression ◽  
Sequencing Data ◽  
Cox Regression Analysis

Abstract Introduction Angiogenesis is a key factor in promoting tumor growth, invasion and metastasis. In this study we aimed to investigate the prognostic value of angiogenesis-related genes (ARGs) in gastric cancer (GC). Methods mRNA sequencing data with clinical information of GC were downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. The differentially expressed ARGs between normal and tumor tissues were analyzed by limma package, and then prognosis‑associated genes were screened using Cox regression analysis. Nine angiogenesis genes were identified as crucially related to the overall survival (OS) of patients through least absolute shrinkage and selection operator (LASSO) regression. The prognostic model and corresponding nomograms were establish based on 9 ARGs and verified in in both TCGA and GEO GC cohorts respectively. Results Eighty-five differentially expressed ARGs and their enriched pathways were confirmed. Significant enrichment analysis revealed that ARGs-related signaling pathway genes were highly related to tumor angiogenesis development. Kaplan–Meier analysis revealed that patients in the high-risk group had worse OS rates compared with the low-risk group in training cohort and validation cohort. In addition, RS had a good prognostic effect on GC patients with different clinical features, especially those with advanced GC. Besides, the calibration curves verified fine concordance between the nomogram prediction model and actual observation. Conclusions We developed a nine gene signature related to the angiogenesis that can predict overall survival for GC. It’s assumed to be a valuable prognosis model with high efficiency, providing new perspectives in targeted therapy.

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