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 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 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 Integrated Dissection of lncRNA-Perturbated Triplets Reveals Novel Prognostic Signatures Across Cancer Types

2020 ◽  
Vol 21 (17) ◽  
pp. 6087
Author(s):  
Yunzhen Wei ◽  
Limeng Zhou ◽  
Yingzhang Huang ◽  
Dianjing Guo
Keyword(s):  
Cancer Biology ◽  
Noncoding Rna ◽  
The Cancer Genome Atlas ◽  
Dynamic Changes ◽  
Computational Framework ◽  
Potential Biomarker ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tcga Dataset ◽  
Pan Cancer

Long noncoding RNA (lncRNA)/microRNA(miRNA)/mRNA triplets contribute to cancer biology. However, identifying significative triplets remains a major challenge for cancer research. The dynamic changes among factors of the triplets have been less understood. Here, by integrating target information and expression datasets, we proposed a novel computational framework to identify the triplets termed as “lncRNA-perturbated triplets”. We applied the framework to five cancer datasets in The Cancer Genome Atlas (TCGA) project and identified 109 triplets. We showed that the paired miRNAs and mRNAs were widely perturbated by lncRNAs in different cancer types. LncRNA perturbators and lncRNA-perturbated mRNAs showed significantly higher evolutionary conservation than other lncRNAs and mRNAs. Importantly, the lncRNA-perturbated triplets exhibited high cancer specificity. The pan-cancer perturbator OIP5-AS1 had higher expression level than that of the cancer-specific perturbators. These lncRNA perturbators were significantly enriched in known cancer-related pathways. Furthermore, among the 25 lncRNA in the 109 triplets, lncRNA SNHG7 was identified as a stable potential biomarker in lung adenocarcinoma (LUAD) by combining the TCGA dataset and two independent GEO datasets. Results from cell transfection also indicated that overexpression of lncRNA SNHG7 and TUG1 enhanced the expression of the corresponding mRNA PNMA2 and CDC7 in LUAD. Our study provides a systematic dissection of lncRNA-perturbated triplets and facilitates our understanding of the molecular roles of lncRNAs in cancers.

scholarly journals Integrative Analysis Reveals Comprehensive Altered Metabolic Genes Linking with Tumor Epigenetics Modification in Pan-Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-17 ◽  
Author(s):  
Yahui Shi ◽  
Jinfen Wei ◽  
Zixi Chen ◽  
Yuchen Yuan ◽  
Xingsong Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Histone Acetylation ◽  
Epigenetic Modification ◽  
Metabolic Reprogramming ◽  
The Cancer Genome Atlas ◽  
Altered Expression ◽  
Metabolic Genes ◽  
Cancer Types ◽  
Pan Cancer

Background. Cancer cells undergo various rewiring of metabolism and dysfunction of epigenetic modification to support their biosynthetic needs. Although the major features of metabolic reprogramming have been elucidated, the global metabolic genes linking epigenetics were overlooked in pan-cancer. Objectives. Identifying the critical metabolic signatures with differential expressions which contributes to the epigenetic alternations across cancer types is an urgent issue for providing the potential targets for cancer therapy. Method. The differential gene expression and DNA methylation were analyzed by using the 5726 samples data from the Cancer Genome Atlas (TCGA). Results. Firstly, we analyzed the differential expression of metabolic genes and found that cancer underwent overall metabolism reprogramming, which exhibited a similar expression trend with the data from the Gene Expression Omnibus (GEO) database. Secondly, the regulatory network of histone acetylation and DNA methylation according to altered expression of metabolism genes was summarized in our results. Then, the survival analysis showed that high expression of DNMT3B had a poorer overall survival in 5 cancer types. Integrative altered methylation and expression revealed specific genes influenced by DNMT3B through DNA methylation across cancers. These genes do not overlap across various cancer types and are involved in different function annotations depending on the tissues, which indicated DNMT3B might influence DNA methylation in tissue specificity. Conclusions. Our research clarifies some key metabolic genes, ACLY, SLC2A1, KAT2A, and DNMT3B, which are most disordered and indirectly contribute to the dysfunction of histone acetylation and DNA methylation in cancer. We also found some potential genes in different cancer types influenced by DNMT3B. Our study highlights possible epigenetic disorders resulting from the deregulation of metabolic genes in pan-cancer and provides potential therapy in the clinical treatment of human cancer.

scholarly journals Integrative pharmacogenomic profiling identifies novel cancer drugs and gene networks modulating ferroptosis sensitivity in pan-cancer

2020 ◽  
Author(s):  
Haitang Yang ◽  
Liang Zhao ◽  
Feng Yao ◽  
Yanyun Gao ◽  
Thomas M. Marti ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Cells ◽  
Cancer Cell ◽  
Gene Networks ◽  
Gene Expression Signature ◽  
The Cancer Genome Atlas ◽  
P Value ◽  
Solid Cancer ◽  
Cancer Drugs ◽  
Pan Cancer

Abstract Background: Ferroptosis is an apoptosis-independent cell death program implicated in various diseases including cancer. Emerging evidence has demonstrated the promise of pharmacological induction of ferroptosis as a novel anti-cancer approach, but the molecular underpinnings of ferroptosis regulation and biomarkers associated with sensitivity to ferroptosis indcuers has been poorly defined. Methods: By implementing integrated pharmacogenomic analysis, we correlated the sensitivity of small-molecule compounds (n=481) against the transcriptomes of solid cancer cell lines (n=659). The potential of a drug compound to modulate ferroptosis was determined by significant (empirical p-value < 0.01) association of drug effectiveness with SLC7A11 expression. To establish generalized gene signatures for ferroptosis sensitivity and resistance, we interrogated drug effects of multiple ferroptosis inducers (n=7) with transcriptomic data of pan-solid cancer cells. Finally, the ferroptosis gene signature was applied to The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE) project to identify cancer patients and cells that likely benefit from ferroptosis-based therapeutics. Results: We report, for the first time, the comprehensive identification of cancer drugs with the potential to induce ferroptosis and a generalized gene expression signature predicting ferroptosis response in pan-cancer. Informed by the findings, we reveal an unanticipated role for class I histone deacetylase (HDAC) in regulating ferroptosis and show that targeting HDAC significantly enhances the ferroptosis-promoting effect of Erastin in lung cancer cells. Moreover, our data indicate that small cell lung cancer (SCLC) and isocitrate dehydrogenase ( IDH )-mutant brain tumors are highly primed for ferroptosis, suggesting that relaunching ferroptosis might be an innovative strategy to target these malignancies. Conclusions: Expanding arsenal targeting aberrant ferroptosis and deciphering gene networks dictating ferroptosis sensitivity shed light on ferroptosis regulatory networks and may facilitate biomarker-guided stratification for ferroptosis-based therapy.

scholarly journals Systematic Pan-Cancer Analysis Identifies TREM2 as an Immunological and Prognostic Biomarker

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Cheng ◽  
Xiaowei Wang ◽  
Kechao Nie ◽  
Lin Cheng ◽  
Zheyu Zhang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Immune Cell ◽  
Lung Squamous Cell Carcinoma ◽  
The Cancer Genome Atlas ◽  
Immunoglobulin Superfamily ◽  
Cancer Types ◽  
Pan Cancer

Triggering receptor expressed on myeloid cells-2 (TREM2) is a transmembrane receptor of the immunoglobulin superfamily and a crucial signaling hub for multiple pathological pathways that mediate immunity. Although increasing evidence supports a vital role for TREM2 in tumorigenesis of some cancers, no systematic pan-cancer analysis of TREM2 is available. Thus, we aimed to explore the prognostic value, and investigate the potential immunological functions, of TREM2 across 33 cancer types. Based on datasets from The Cancer Genome Atlas, and the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and Human Protein Atlas, we employed an array of bioinformatics methods to explore the potential oncogenic roles of TREM2, including analyzing the relationship between TREM2 and prognosis, tumor mutational burden (TMB), microsatellite instability (MSI), DNA methylation, and immune cell infiltration of different tumors. The results show that TREM2 is highly expressed in most cancers, but present at low levels in lung cancer. Further, TREM2 is positively or negatively associated with prognosis in different cancers. Additionally, TREM2 expression was associated with TMB and MSI in 12 cancer types, while in 20 types of cancer, there was a correlation between TREM2 expression and DNA methylation. Six tumors, including breast invasive carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, lung squamous cell carcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, were screened out for further study, which demonstrated that TREM2 gene expression was negatively correlated with infiltration levels of most immune cells, but positively correlated with infiltration levels of M1 and M2 macrophages. Moreover, correlation with TREM2 expression differed according to T cell subtype. Our study reveals that TREM2 can function as a prognostic marker in various malignant tumors because of its role in tumorigenesis and tumor immunity.

scholarly journals Precise, pan-cancer discovery of gene fusions reveals a signature of selection in primary tumors

2017 ◽  
Author(s):  
Donald Eric Freeman ◽  
Gillian Lee Hsieh ◽  
Jonathan Michael Howard ◽  
Erik Lehnert ◽  
Julia Salzman
Keyword(s):  
Cancer Biology ◽  
The Cancer Genome Atlas ◽  
Future Research ◽  
Gene Fusions ◽  
Primary Tumors ◽  
Detection Algorithms ◽  
Signature Of Selection ◽  
Minimal Treatment ◽  
Open Question ◽  
Pan Cancer

Short AbstractThe extent to which gene fusions function as drivers of cancer remains a critical open question in cancer biology. In principle, transcriptome sequencing provided by The Cancer Genome Atlas (TCGA) enables unbiased discovery of gene fusions and post-analysis that informs the answer to this question. To date, such an analysis has been impossible because of performance limitations in fusion detection algorithms. By engineering a new, more precise, algorithm and statistical approaches to post-analysis of fusions called in TCGA data, we report new recurrent gene fusions, including those that could be druggable; new candidate pan-cancer oncogenes based on their profiles in fusions; and prevalent, previously overlooked, candidate oncogenic gene fusions in ovarian cancer, a disease with minimal treatment advances in recent decades. The novel and reproducible statistical algorithms and, more importantly, the biological conclusions open the door for increased attention to gene fusions as drivers of cancer and for future research into using fusions for targeted therapy.

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 Prognostic and immunological role of Fam20C in pan-cancer

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Xinpeng Liu ◽  
Yuanbo Zhan ◽  
Wenxia Xu ◽  
Xiaoyao Liu ◽  
Yawei Geng ◽  
...  
Keyword(s):  
Prognostic Value ◽  
Sequence Similarity ◽  
Expression Patterns ◽  
The Cancer Genome Atlas ◽  
Lower Grade ◽  
Tumor Cell Migration ◽  
Immune Infiltration ◽  
Normal Tissues ◽  
Kaplan Meier ◽  
Pan Cancer

Abstract Background: The family with sequence similarity 20-member C (Fam20C) kinase plays important roles in physiopathological process and is responsible for majority of the secreted phosphoproteome, including substrates associated with tumor cell migration. However, it remains unclear whether Fam20C plays a role in cancers. Here, we aimed to analyze the expression and prognostic value of Fam20C in pan-cancer and to gain insights into the association between Fam20C and immune infiltration. Methods: We analyzed Fam20C expression patterns and the associations between Fam20C expression levels and prognosis in pan-cancer via the ONCOMINE, TIMER (Tumor Immune Estimation Resource), PrognoScan, GEPIA (Gene Expression Profiling Interactive Analysis), and Kaplan–Meier Plotter databases. After that, GEPIA and TIMER databases were applied to investigate the relations between Fam20C expression and immune infiltration across different cancer types, especially BLCA (bladder urothelial carcinoma), LGG (brain lower grade glioma), and STAD (stomach adenocarcinoma). Results: Compared with adjacent normal tissues, Fam20C was widely expressed across many cancers. In general, Fam20C showed a detrimental role in pan-cancer, it was positively associated with poor survival of BLCA, LGG, and STAD patients. Specifically, based on TCGA (The Cancer Genome Atlas) database, a high expression level of Fam20C was associated with worse prognostic value in stages T2–T4 and stages N0–N2 in the cohort of STAD patients. Moreover, Fam20C expression had positive associations with immune infiltration, including CD4+ T cells, macrophages, neutrophils, and dendritic cells, and other diverse immune cells in BLCA, LGG, and STAD. Conclusion: Fam20C may serve as a promising prognostic biomarker in pan-cancer and has positive associations with immune infiltrates.

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