scholarly journals Pan-Cancer chromatin analysis of the human vtRNA genes uncovers their association with cancer biology

2020 ◽  
Author(s):  
Rafael Sebastián Fort ◽  
María Ana Duhagon
Keyword(s):  
Dna Methylation ◽  
Cancer Biology ◽  
Gene Networks ◽  
Expression Patterns ◽  
Rna Polymerase Iii ◽  
Chromatin Accessibility ◽  
The Cancer Genome Atlas ◽  
Gene Sets ◽  
Gene Expression Studies ◽  
Promoter Dna

AbstractThe vault RNAs (vtRNAs) are a class of 84-141 nt eukaryotic non-coding RNAs transcribed by RNA polymerase III, named for their association with the conserved vault particle, a riboprotein complex whose function remains poorly understood. Of the 4 human vtRNA genes, the three clustered at locus 1, i.e. vtRNA1-1, vtRNA1-2 and vtRNA1-3, are integral components of the vault particle, while vtRNA2-1 is a more divergent homologue located in a second locus. Gene expression studies of vtRNAs in large cancer cohorts have been hindered by the failure of vtRNA sequencing using conventional transcriptomic approaches. However, since the vtRNAs transcription is regulated by DNA methylation, the analysis of the chromatin status of their promoters is a suitable surrogate approach to study their expression. Here we infer the landscape of vtRNA expression in cancer from the genome-wide DNA methylation (Illumina Infinium Human Methylation 450 K BeadChip) and chromatin accessibility (ATAC-seq) data of The Cancer Genome Atlas (TCGA). On average, vtRNA1-1 has the most accessible chromatin, followed by vtRNA1-2, vtRNA2-1 and vtRNA1-3. The correlation of the chromatin status of the vtRNA promoters and the binding sites of a common core of transcription factors stands for their transcriptional co-regulation by factors related to viral infection. Yet, vtRNA2-1 is the most independently regulated vtRNA homologue across tissue types. VtRNA1-1 and vtRNA1-3 chromatin status does not significantly change in cancer, though vtRNA1-3 promoter has repressive chromatin marks in a few cancer types. However, vtRNA2-1 and vtRNA1-2 expression are widely deregulated in neoplastic tissues and is compatible with a broad oncogenic role of vtRNA1-2, and both tumor suppressor and oncogenic functions of vtRNA2-1 depending of tissue contexts. Yet, vtRNA1-1, vtRNA1-2 and vtRNA2-1 promoter DNA methylation predicts a shorter patient overall survival cancer-wide. In addition, gene ontology analyses of co-regulated genes identifies a chromosome 5 regulatory domain controlling vtRNA1-1 and neighboring genes, and epithelial differentiation, immune and thyroid cancer gene sets for vtRNA1-2, vtRNA2-1 and vtRNA1-3 respectively. Furthermore, vtRNA expression patterns are associated with cancer immune subtypes. Finally, vtRNA1-2 expression is positively associated with cell proliferation and wound healing, in agreement with its oncogenic expression profile. Overall, our study presents the landscape of vtRNA expression cancer-wide, identifying co-regulated gene networks and ontological pathways associated with the different vtRNA genes that may account for their diverse roles in cancer.

scholarly journals Pan-cancer chromatin analysis of the human vtRNA genes uncovers their association with cancer biology

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 182
Author(s):  
Rafael Sebastián Fort ◽  
María Ana Duhagon
Keyword(s):  
Dna Methylation ◽  
Cancer Biology ◽  
Gene Networks ◽  
Expression Patterns ◽  
Rna Polymerase Iii ◽  
Chromatin Accessibility ◽  
The Cancer Genome Atlas ◽  
Gene Expression Studies ◽  
Promoter Dna ◽  
Pan Cancer

Background: The vault RNAs (vtRNAs) are a class of 84-141-nt eukaryotic non-coding RNAs transcribed by RNA polymerase III, associated to the ribonucleoprotein complex known as vault particle. Of the four human vtRNA genes, vtRNA1-1, vtRNA1-2 and vtRNA1-3, clustered at locus 1, are integral components of the vault particle, while vtRNA2-1 is a more divergent homologue located in a second locus. Gene expression studies of vtRNAs in large cohorts have been hindered by their unsuccessful sequencing using conventional transcriptomic approaches. Methods: VtRNA expression in The Cancer Genome Atlas (TCGA) Pan-Cancer cohort was estimated using the genome-wide DNA methylation and chromatin accessibility data (ATAC-seq) of their genes as surrogate variables. The association between vtRNA expression and patient clinical outcome, immune subtypes and transcriptionally co-regulated gene programs was analyzed in the dataset. Results: VtRNA1-1 has the most accessible chromatin, followed by vtRNA1-2, vtRNA2-1 and vtRNA1-3. Although the vtRNAs are co-regulated by transcription factors related to viral infection, vtRNA2-1 is the most independently regulated homologue. VtRNA1-1 and vtRNA1-3 chromatin status does not significantly change in cancer tissues. Meanwhile, vtRNA2-1 and vtRNA1-2 expression is widely deregulated in neoplastic tissues and its alteration is compatible with a broad oncogenic role for vtRNA1-2, and both tumor suppressor and oncogenic functions for vtRNA2-1. Yet, vtRNA1-1, vtRNA1-2 and vtRNA2-1 promoter DNA methylation predicts a shorter patient overall survival cancer-wide. In addition, gene ontology analyses of vtRNAs co-regulated genes identify a chromosome regulatory domain, epithelial differentiation, immune and thyroid cancer gene sets for specific vtRNAs. Furthermore, vtRNA expression patterns are associated with cancer immune subtypes and vtRNA1-2 expression is positively associated with cell proliferation and wound healing. Conclusions: Our study presents the landscape of vtRNA expression cancer-wide, identifying co-regulated gene networks and ontological pathways associated with the different vtRNA genes that may account for their diverse roles in cancer.

scholarly journals Pan-cancer chromatin analysis of the human vtRNA genes uncovers their association with cancer biology

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 182
Author(s):  
Rafael Sebastián Fort ◽  
María Ana Duhagon
Keyword(s):  
Dna Methylation ◽  
Cancer Biology ◽  
Gene Networks ◽  
Expression Patterns ◽  
Rna Polymerase Iii ◽  
Chromatin Accessibility ◽  
The Cancer Genome Atlas ◽  
Gene Expression Studies ◽  
Promoter Dna ◽  
Pan Cancer

Background: The vault RNAs (vtRNAs) are a class of 84-141-nt eukaryotic non-coding RNAs transcribed by RNA polymerase III, associated to the ribonucleoprotein complex known as vault particle. Of the four human vtRNA genes, vtRNA1-1, vtRNA1-2 and vtRNA1-3, clustered at locus 1, are integral components of the vault particle, while vtRNA2-1 is a more divergent homologue located in a second locus. Gene expression studies of vtRNAs in large cohorts have been hindered by their unsuccessful sequencing using conventional transcriptomic approaches. Methods: VtRNA expression in The Cancer Genome Atlas (TCGA) Pan-Cancer cohort was estimated using the genome-wide DNA methylation and chromatin accessibility data (ATAC-seq) of their genes as surrogate variables. The association between vtRNA expression and patient clinical outcome, immune subtypes and transcriptionally co-regulated gene programs was analyzed in the dataset. Results: VtRNAs promoters are enriched in transcription factors related to viral infection. VtRNA2-1 is likely the most independently regulated homologue. VtRNA1-1 has the most accessible chromatin, followed by vtRNA1-2, vtRNA2-1 and vtRNA1-3. VtRNA1-1 and vtRNA1-3 chromatin status does not significantly change in cancer tissues. Meanwhile, vtRNA2-1 and vtRNA1-2 expression is widely deregulated in neoplastic tissues and its alteration is compatible with a broad oncogenic role for vtRNA1-2, and both tumor suppressor and oncogenic functions for vtRNA2-1. Yet, vtRNA1-1, vtRNA1-2 and vtRNA2-1 promoter DNA methylation predicts a shorter patient overall survival cancer-wide. In addition, gene ontology analyses of vtRNAs co-regulated genes identify a chromosome regulatory domain, epithelial differentiation, immune and thyroid cancer gene sets for specific vtRNAs. Furthermore, vtRNA expression patterns are associated with cancer immune subtypes and vtRNA1-2 expression is positively associated with cell proliferation and wound healing. Conclusions: Our study presents the landscape of vtRNA chromatin status cancer-wide, identifying co-regulated gene networks and ontological pathways associated with the different vtRNA genes that may account for their diverse roles in cancer.

scholarly journals Intratumoral Adipocyte-High Breast Cancer Enrich for Metastatic and Inflammation-Related Pathways but Associated with Less Cancer Cell Proliferation

2020 ◽  
Vol 21 (16) ◽  
pp. 5744 ◽  
Author(s):  
Yoshihisa Tokumaru ◽  
Masanori Oshi ◽  
Eriko Katsuta ◽  
Li Yan ◽  
Jing Li Huang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Proliferation ◽  
Cancer Progression ◽  
Cancer Biology ◽  
The Cancer Genome Atlas ◽  
Related Gene ◽  
Immune Microenvironment ◽  
Gene Sets ◽  
Tumor Immune Microenvironment ◽  
Er Positive

Cancer-associated adipocytes are known to cause inflammation, leading to cancer progression and metastasis. The clinicopathological and transcriptomic data from 2256 patients with breast cancer were obtained based on three cohorts: The Cancer Genome Atlas (TCGA), GSE25066, and a study by Yau et al. For the current study, we defined the adipocyte, which is calculated by utilizing a computational algorithm, xCell, as “intratumoral adipocyte”. These intratumoral adipocytes appropriately reflected mature adipocytes in a bulk tumor. The amount of intratumoral adipocytes demonstrated no relationship with survival. Intratumoral adipocyte-high tumors significantly enriched for metastasis and inflammation-related gene sets and are associated with a favorable tumor immune microenvironment, especially in the ER+/HER2- subtype. On the other hand, intratumoral adipocyte-low tumors significantly enriched for cell cycle and cell proliferation-related gene sets. Correspondingly, intratumoral adipocyte-low tumors are associated with advanced pathological grades and inversely correlated with MKI67 expression. In conclusion, a high amount of intratumoral adipocytes in breast cancer was associated with inflammation, metastatic pathways, cancer stemness, and favorable tumor immune microenvironment. However, a low amount of adipocytes was associated with a highly proliferative tumor in ER-positive breast cancer. This cancer biology may explain the reason why patient survival did not differ by the amount of adipocytes.

scholarly journals GENE EXPRESSION STUDIES USING MICROARRAYS: PRINCIPLES, PROBLEMS, AND PROSPECTS

2002 ◽  
Vol 26 (4) ◽  
pp. 256-270 ◽  
Author(s):  
David Murphy
Keyword(s):  
Gene Networks ◽  
Time Course ◽  
Expression Patterns ◽  
Rna Isolation ◽  
Microarray Experiment ◽  
Bioinformatic Analysis ◽  
Microarray Technology ◽  
Microarray Probe ◽  
Advantages And Disadvantages ◽  
Gene Expression Studies

Anumber of mammalian genomes having been sequenced, an important next step is to catalog the expression patterns of all transcription units in health and disease by use of microarrays. Such discovery programs are crucial to our understanding of the gene networks that control developmental, physiological, and pathological processes. However, despite the excitement, the full promise of microarray technology has yet to be realized, as the superficial simplicity of the concept belies considerable problems. Microarray technology is very new; methodologies are still evolving, common standards have yet to be established, and many problems with experimental design and variability have still to be fully understood and overcome. This review will describe the time course of a microarray experiment—RNA isolation from sample, target preparation, hybridization to the microarray probe, data capture, and bioinformatic analysis. For each stage, the advantages and disadvantages of competing techniques are compared, and inherent sources of error are identified and discussed.

scholarly journals High Expression of miR-34a Associated with Less Aggressive Cancer Biology but Not with Survival in Breast Cancer

2020 ◽  
Vol 21 (9) ◽  
pp. 3045 ◽  
Author(s):  
Yoshihisa Tokumaru ◽  
Eriko Katsuta ◽  
Masanori Oshi ◽  
Judith C. Sporn ◽  
Li Yan ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Proliferation ◽  
Cancer Biology ◽  
Epithelial Mesenchymal Transition ◽  
Molecular Taxonomy ◽  
The Cancer Genome Atlas ◽  
P53 Pathway ◽  
Mesenchymal Transition ◽  
Gene Sets ◽  
Aggressive Cancer

Most breast cancer (BC) patients succumb to metastatic disease. MiR-34a is a well-known tumor suppressive microRNA which exerts its anti-cancer functions by playing a role in p53, apoptosis induction, and epithelial-mesenchymal transition (EMT) suppression. Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas (TCGA) cohorts were used to test our hypothesis that miR-34a high BCs translate to less aggressive cancer biology and better survival in large cohorts. There was no association between miR-34a expression levels and clinicopathological features of BC patients except for HER2 positivity. MiR-34a high expressing tumors were associated with lower Nottingham pathological grades and lower MKI67 expression. In agreement, high miR-34a tumors demonstrated lower GSVA scores of cell cycle and cell proliferation-related gene sets. High miR-34a tumors enriched the p53 pathway and apoptosis gene sets. Unexpectedly, high miR-34a tumors also associated with elevated EMT pathway score and ZEB1 and two expressions. MiR-34a expression did not associate with any distant metastasis. Further, high miR-34a tumors did not associate with better survival compared with miR-34a low tumors. In conclusion, the clinical relevance of miR-34a high expressing tumors was associated with suppressed cell proliferation, enhanced p53 pathway and apoptosis, but enhanced EMT and these findings did not reflect better survival outcomes in large BC patient cohorts.

scholarly journals Distinct Murine Pancreatic Transcriptomic Signatures during Chronic Pancreatitis Recovery

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yinjie Zhang ◽  
Baibing Yang ◽  
Joy M. Davis ◽  
Madeline M. Drake ◽  
Mamoun Younes ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Extracellular Matrix ◽  
Chronic Pancreatitis ◽  
Signaling Pathways ◽  
Cancer Biology ◽  
Molecular Level ◽  
Rna Seq ◽  
Gene Sets ◽  
And Control ◽  
Therapeutic Responses

We have previously demonstrated that the pancreas can recover from chronic pancreatitis (CP) lesions in the cerulein-induced mouse model. To explore how pancreatic recovery is achieved at the molecular level, we used RNA-sequencing (seq) and profiled transcriptomes during CP transition to recovery. CP was induced by intraperitoneally injecting cerulein in C57BL/6 mice. Time-matched controls (CON) were given normal saline. Pancreata were harvested from mice 4 days after the final injections (designated as CP and CON) or 4 weeks after the final injections (designated as CP recovery (CPR) and control recovery (CONR)). Pancreatic RNAs were extracted for RNA-seq and quantitative (q) PCR validation. Using RNA-seq, we identified a total of 3,600 differentially expressed genes (DEGs) in CP versus CON and 166 DEGs in CPR versus CONR. There are 132 DEGs overlapped between CP and CPR and 34 DEGs unique to CPR. A number of selected pancreatic fibrosis-relevant DEGs were validated by qPCR. The top 20 gene sets enriched from DEGs shared between CP and CPR are relevant to extracellular matrix and cancer biology, whereas the top 10 gene sets enriched from DEGs specific to CPR are pertinent to DNA methylation and specific signaling pathways. In conclusion, we identified a distinct set of DEGs in association with extracellular matrix and cancer cell activities to contrast CP and CPR. Once during ongoing CP recovery, DEGs relevant to DNA methylation and specific signaling pathways were induced to express. The DEGs shared between CP and CPR and the DEGs specific to CPR may serve as the unique transcriptomic signatures and biomarkers for determining CP recovery and monitoring potential therapeutic responses at the molecular level to reflect pancreatic histological resolution.

scholarly journals Pan-Cancer Analysis of DNA Methylation Identifies Genes and Biological Functions Associated with Overall Survival

2021 ◽  
Author(s):  
Romola Grace Cavet ◽  
Peng Yue ◽  
Guy Lawrence Cavet
Keyword(s):  
Dna Methylation ◽  
Overall Survival ◽  
Cancer Biology ◽  
Gene Clusters ◽  
The Cancer Genome Atlas ◽  
Biological Functions ◽  
Cancer Types ◽  
Genomic Regions ◽  
The Relationship ◽  
Pan Cancer

DNA methylation influences gene expression and is altered in many cancers, but the relationship between DNA methylation and cancer outcomes is not yet fully understood. If methylation of specific genes is associated with better or worse outcomes, it could implicate genes in driving cancer and suggest therapeutic strategies. To advance our understanding of DNA methylation in cancer biology, we conducted a pan-cancer analysis of the relationship between methylation and overall survival. Using data on 28 tumor types from The Cancer Genome Atlas (TCGA), we identified genes and genomic regions whose methylation was recurrently associated with survival across multiple cancer types. While global DNA methylation levels are associated with outcome in some cancers, we found that the gene-specific associations were largely independent of these global effects. Genes with recurrent associations across cancer types were enriched for certain biological functions, such as immunity and cell-cell adhesion. While these recurrently associated genes were found throughout the genome, they were enriched in certain genomic regions, which may further implicate certain gene families and gene clusters in affecting survival. By finding common features across cancer types, our results link DNA methylation to patient outcomes, identify biological mechanisms that could explain survival differences, and support the potential value of treatments that modulate the methylation of tumor DNA.

scholarly journals Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures

2021 ◽  
Vol 11 ◽  
Author(s):  
Sven de Mey ◽  
Inès Dufait ◽  
Mark De Ridder
Keyword(s):  
Mrna Expression ◽  
Cancer Patients ◽  
Clinical Relevance ◽  
Expression Patterns ◽  
Molecular Data ◽  
The Cancer Genome Atlas ◽  
Gene Set ◽  
Gene Sets ◽  
Cancer Genome Atlas ◽  
Cancer Types

Although radiotherapy is given to more than 50% of cancer patients, little progress has been made in identifying optimal radiotherapy - drug combinations to improve treatment efficacy. Using molecular data from The Cancer Genome Atlas (TCGA), we extracted a total of 1016 cancer patients that received radiotherapy. The patients were diagnosed with head-and-neck (HNSC - 294 patients), cervical (CESC - 166 patients) and breast (BRCA - 549 patients) cancer. We analyzed mRNA expression patterns of 50 hallmark gene sets of the MSigDB collection, which we divided in eight categories based on a shared biological or functional process. Tumor samples were split into upregulated, neutral or downregulated mRNA expression for all gene sets using a gene set analysis (GSEA) pre-ranked analysis and assessed for their clinical relevance. We found a prognostic association between three of the eight gene set categories (Radiobiological, Metabolism and Proliferation) and overall survival in all three cancer types. Furthermore, multiple single associations were revealed in the other categories considered. To the best of our knowledge, our study is the first report suggesting clinical relevance of molecular characterization based on hallmark gene sets to refine radiation strategies.

scholarly journals Pan-Cancer Analysis of Human Kinome Gene Expression and Promoter DNA Methylation Identifies Dark Kinase Biomarkers in Multiple Cancers

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1189
Author(s):  
Siddesh Southekal ◽  
Nitish Kumar Mishra ◽  
Chittibabu Guda
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Intracellular Signaling ◽  
Expression Patterns ◽  
Tissue Type ◽  
Kinase Gene ◽  
Promoter Dna Methylation ◽  
Level 3 ◽  
Promoter Dna ◽  
Intracellular Signaling Molecules

Kinases are a group of intracellular signaling molecules that play critical roles in various biological processes. Even though kinases comprise one of the most well-known therapeutic targets, many have been understudied and therefore warrant further investigation. DNA methylation is one of the key epigenetic regulators that modulate gene expression. In this study, the human kinome’s DNA methylation and gene expression patterns were analyzed using the level-3 TCGA data for 32 cancers. Unsupervised clustering based on kinome data revealed the grouping of cancers based on their organ level and tissue type. We further observed significant differences in overall kinase methylation levels (hyper- and hypomethylation) between the tumor and adjacent normal samples from the same tissue. Methylation expression quantitative trait loci (meQTL) analysis using kinase gene expression with the corresponding methylated probes revealed a highly significant and mostly negative association (~92%) within 1.5 kb from the transcription start site (TSS). Several understudied (dark) kinases (PKMYT1, PNCK, BRSK2, ERN2, STK31, STK32A, and MAPK4) were also identified with a significant role in patient survival. This study leverages results from multi-omics data to identify potential kinase markers of prognostic and diagnostic importance and further our understanding of kinases in cancer.

scholarly journals cg04448376, cg24387542, cg08548498, and cg14621323 as a Novel Signature to Predict Prognosis in Kidney Renal Papillary Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Ying-Lei Wang ◽  
Ying-Ying Zhang
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cell Carcinoma ◽  
Proportional Hazards ◽  
Expression Patterns ◽  
Cox Proportional Hazards ◽  
Low Risk ◽  
The Cancer Genome Atlas ◽  
Risk Scores ◽  
Hub Genes

Introduction. DNA methylation plays a vital role in prognosis prediction of cancers. In this study, we aimed to identify novel DNA methylation site biomarkers and create an efficient methylated site model for predicting survival in kidney renal papillary cell carcinoma (KIRP). Methods. DNA methylation and gene expression profile data were downloaded from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. Differential methylated genes (DMGs) and differential expression genes (DEGs) were identified and then searched for the hub genes. Cox proportional hazards regression was applied to identify DNA methylated site biomarkers from the hub genes. Kaplan–Meier survival and ROC analyses were used to validate the effective prognostic ability of the methylation gene site biomarker. The biomarker sites were validated in the GEO cohorts. The GO and KEGG annotation was done to explore the biological function of DNA methylated site signature. Results. Nine DMGs with opposite expression patterns containing 47 methylated sites were identified. Finally, four methylated sites were identified using the hazard regression model (cg04448376, cg24387542, cg08548498, and cg14621323) located in UTY, LGALS9B, SLPI, and PFN3, respectively. These sites classified patients into high- and low-risk groups in the training cohort. The 5-year survival rates for patients with low-risk and high-risk scores were 97.5% and 75.9% ( P < 0.001 ). The prognostic accuracy and signature methylation sites were validated in the test (TCGA, n = 87 ) and GEO cohorts ( n = 14 ). Multivariate regression analysis showed that the signature was an independent prediction prognostic factor for KIRP. Based on this analysis, we developed methylated site signature nomogram that predicts an individual’s risk of survival. Functional analysis suggested that these signature genes are involved in the biological processes of protein binding. Conclusions. Our study demonstrated that the methylated gene site signature might be a powerful prognostic tool for evaluating survival rate and guiding tailored therapy for KIRP patients.

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