scholarly journals Long non-coding RNAs as pan-cancer master gene regulators of associated protein-coding genes: a systems biology approach

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6388 ◽  
Author(s):  
Asanigari Saleembhasha ◽  
Seema Mishra
Keyword(s):  
Gene Expression ◽  
Gene Expression Pattern ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Biological Processes ◽  
Lncrna Gene ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Rna Interaction ◽  
Pan Cancer

Despite years of research, we are still unraveling crucial stages of gene expression regulation in cancer. On the basis of major biological hallmarks, we hypothesized that there must be a uniform gene expression pattern and regulation across cancer types. Among non-coding genes, long non-coding RNAs (lncRNAs) are emerging as key gene regulators playing powerful roles in cancer. Using TCGA RNAseq data, we analyzed coding (mRNA) and non-coding (lncRNA) gene expression across 15 and 9 common cancer types, respectively. 70 significantly differentially expressed genes common to all 15 cancer types were enlisted. Correlating with protein expression levels from Human Protein Atlas, we observed 34 positively correlated gene sets which are enriched in gene expression, transcription from RNA Pol-II, regulation of transcription and mitotic cell cycle biological processes. Further, 24 lncRNAs were among common significantly differentially expressed non-coding genes. Using guilt-by-association method, we predicted lncRNAs to be involved in same biological processes. Combining RNA-RNA interaction prediction and transcription regulatory networks, we identified E2F1, FOXM1 and PVT1 regulatory path as recurring pan-cancer regulatory entity. PVT1 is predicted to interact with SYNE1 at 3′-UTR; DNAJC9, RNPS1 at 5′-UTR and ATXN2L, ALAD, FOXM1 and IRAK1 at CDS sites. The key findings are that through E2F1, FOXM1 and PVT1 regulatory axis and possible interactions with different coding genes, PVT1 may be playing a prominent role in pan-cancer development and progression.

Identification of aberrantly methylated differentially expressed genes in melanoma

2020 ◽  
Author(s):  
Wei Han ◽  
Guo-liang Shen
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Regulation Of Transcription ◽  
Biological Processes ◽  
Hub Genes ◽  
Positive Regulation ◽  
Upregulated Genes

Abstract Background: Skin Cutaneous Melanoma (SKCM) is known as an aggressive malignant cancer, which could be directly derived from melanocytic nevi. However, the molecular mechanisms underlying malignant transformation of melanocytes and melanoma tumor progression still remain unclear. Increasing researches showed significant roles of epigenetic modifications, especially DNA methylation, in melanoma. This study focused on identification and analysis of methylation-regulated differentially expressed genes (MeDEGs) between melanocytic nevus and malignant melanoma in genome-wide profiles. Methods: The gene expression profiling datasets (GSE3189 and GSE114445) and gene methylation profiling datasets (GSE86355 and GSE120878) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) were identified via GEO2R. MeDEGs were obtained by integrating the DEGs and DMGs. Then, functional enrichment analysis of MeDEGs were performed. STRING and Cytoscape were used to describe protein-protein interaction(PPI) network. Furthermore, survival analysis was implemented to select the prognostic hub genes. Finally, we conducted gene set enrichment analysis (GSEA) of hub genes. Results: We identified 237 hypomethylated, upregulated genes and 182 hypermethylated, downregulated genes. Hypomethylation-upregulated genes were enriched in biological processes of the oxidation-reduction process, cell proliferation, cell division, phosphorylation, extracellular matrix disassembly and protein sumoylation. Pathway enrichment showed selenocompound metabolism, small cell lung cancer and lysosome. Hypermethylation-downregulated genes were enriched in biological processes of positive regulation of transcription from RNA polymerase II promoter, cell adhesion, cell proliferation, positive regulation of transcription, DNA-templated and angiogenesis. The most significantly enriched pathways involved the transcriptional misregulation in cancer, circadian rhythm, tight junction, protein digestion and absorption and Hippo signaling pathway. After PPI establishment and survival analysis, seven prognostic hub genes were CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2 and FBL. Moreover, the most involved hallmarks obtained by GSEA were E2F targets, G2M checkpoint and mitotic spindle. Conclusions: Our study identified potential aberrantly methylated-differentially expressed genes participating in the process of malignant transformation from nevus to melanoma tissues based on comprehensive genomic profiles. Transcription profiles of CKS2, DTL, KIF2C, KPNA2, MYBL2, TPX2 and FBL provided clues of aberrantly methylation-based biomarkers, which might improve the development of precise medicine.

scholarly journals Transcriptome Analysis Reveals the Profile of Long Non-coding RNAs During Chicken Muscle Development

2021 ◽  
Vol 12 ◽  
Author(s):  
Jie Liu ◽  
Yan Zhou ◽  
Xin Hu ◽  
Jingchao Yang ◽  
Qiuxia Lei ◽  
...  
Keyword(s):  
Gene Expression ◽  
Muscle Development ◽  
Differentially Expressed ◽  
Chicken Breast ◽  
Regulation Of Transcription ◽  
Rna Seq ◽  
Regulatory Interactions ◽  
Chicken Muscle ◽  
Non Coding Rnas

The developmental complexity of muscle arises from elaborate gene regulation. Long non-coding RNAs (lncRNAs) play critical roles in muscle development through the regulation of transcription and post-transcriptional gene expression. In chickens, previous studies have focused on the lncRNA profile during the embryonic periods, but there are no studies that explore the profile from the embryonic to post-hatching period. Here, we reconstructed 14,793 lncRNA transcripts and identified 2,858 differentially expressed lncRNA transcripts and 4,282 mRNAs from 12-day embryos (E12), 17-day embryos (E17), 1-day post-hatch chicks (D1), 14-day post-hatch chicks (D14), 56-day post-hatch chicks (D56), and 98-day post-hatch chicks (D98), based on our published RNA-seq datasets. We performed co-expression analysis for the differentially expressed lncRNAs and mRNAs, using STEM, and identified two profiles with opposite expression trends: profile 4 with a downregulated pattern and profile 21 with an upregulated pattern. The cis- and trans-regulatory interactions between the lncRNAs and mRNAs were predicted within each profile. Functional analysis of the lncRNA targets showed that lncRNAs in profile 4 contributed to the cell proliferation process, while lncRNAs in profile 21 were mainly involved in metabolism. Our work highlights the lncRNA profiles involved in the development of chicken breast muscle and provides a foundation for further experiments on the role of lncRNAs in the regulation of muscle development.

scholarly journals Transcriptome analysis reveals potential function of long non-coding RNAs in 20-hydroxyecdysone regulated autophagy in Bombyx mori

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Huili Qiao ◽  
Jingya Wang ◽  
Yuanzhuo Wang ◽  
Juanjuan Yang ◽  
Bofan Wei ◽  
...  
Keyword(s):  
Bombyx Mori ◽  
Target Gene ◽  
Fat Body ◽  
Expression Profiles ◽  
Functional Characterization ◽  
Differentially Expressed ◽  
Post Injection ◽  
Biological Processes ◽  
Potential Target ◽  
Non Coding Rnas

Abstract Background 20-hydroxyecdysone (20E) plays important roles in insect molting and metamorphosis. 20E-induced autophagy has been detected during the larval–pupal transition in different insects. In Bombyx mori, autophagy is induced by 20E in the larval fat body. Long non-coding RNAs (lncRNAs) function in various biological processes in many organisms, including insects. Many lncRNAs have been reported to be potential for autophagy occurrence in mammals, but it has not been investigated in insects. Results RNA libraries from the fat body of B. mori dissected at 2 and 6 h post-injection with 20E were constructed and sequenced, and comprehensive analysis of lncRNAs and mRNAs was performed. A total of 1035 lncRNAs were identified, including 905 lincRNAs and 130 antisense lncRNAs. Compared with mRNAs, lncRNAs had longer transcript length and fewer exons. 132 lncRNAs were found differentially expressed at 2 h post injection, compared with 64 lncRNAs at 6 h post injection. Thirty differentially expressed lncRNAs were common at 2 and 6 h post-injection, and were hypothesized to be associated with the 20E response. Target gene analysis predicted 6493 lncRNA-mRNA cis pairs and 42,797 lncRNA-mRNA trans pairs. The expression profiles of LNC_000560 were highly consistent with its potential target genes, Atg4B, and RNAi of LNC_000560 significantly decreased the expression of LNC_000560 and Atg4B. These results indicated that LNC_000560 was potentially involved in the 20E-induced autophagy of the fat body by regulating Atg4B. Conclusions This study provides the genome-wide identification and functional characterization of lncRNAs associated with 20E-induced autophagy in the fat body of B. mori. LNC_000560 and its potential target gene were identified to be related to 20-regulated autophagy in B. mori. These results will be helpful for further studying the regulatory mechanisms of lncRNAs in autophagy and other biological processes in this insect model.

scholarly journals Pan-Cancer Transcriptional Models Predicting Chemosensitivity in Human Tumors

2021 ◽  
Vol 20 ◽  
pp. 117693512110024
Author(s):  
Jason D Wells ◽  
Jacqueline R Griffin ◽  
Todd W Miller
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Human Tumors ◽  
Molecular Characteristics ◽  
Survival Times ◽  
Chemotherapy Drugs ◽  
Testing Dataset ◽  
Cancer Models ◽  
Cancer Types ◽  
Pan Cancer

Motivation: Despite increasing understanding of the molecular characteristics of cancer, chemotherapy success rates remain low for many cancer types. Studies have attempted to identify patient and tumor characteristics that predict sensitivity or resistance to different types of conventional chemotherapies, yet a concise model that predicts chemosensitivity based on gene expression profiles across cancer types remains to be formulated. We attempted to generate pan-cancer models predictive of chemosensitivity and chemoresistance. Such models may increase the likelihood of identifying the type of chemotherapy most likely to be effective for a given patient based on the overall gene expression of their tumor. Results: Gene expression and drug sensitivity data from solid tumor cell lines were used to build predictive models for 11 individual chemotherapy drugs. Models were validated using datasets from solid tumors from patients. For all drug models, accuracy ranged from 0.81 to 0.93 when applied to all relevant cancer types in the testing dataset. When considering how well the models predicted chemosensitivity or chemoresistance within individual cancer types in the testing dataset, accuracy was as high as 0.98. Cell line–derived pan-cancer models were able to statistically significantly predict sensitivity in human tumors in some instances; for example, a pan-cancer model predicting sensitivity in patients with bladder cancer treated with cisplatin was able to significantly segregate sensitive and resistant patients based on recurrence-free survival times ( P = .048) and in patients with pancreatic cancer treated with gemcitabine ( P = .038). These models can predict chemosensitivity and chemoresistance across cancer types with clinically useful levels of accuracy.

scholarly journals BART Cancer: a web resource for transcriptional regulators in cancer genomes

NAR Cancer ◽  
2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Zachary V Thomas ◽  
Zhenjia Wang ◽  
Chongzhi Zang
Keyword(s):  
Gene Expression ◽  
Cancer Research ◽  
Computational Prediction ◽  
Transcriptional Regulators ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Regulation Of Transcription ◽  
Data Resource ◽  
Web Resource ◽  
Cancer Types

Abstract Dysregulation of gene expression plays an important role in cancer development. Identifying transcriptional regulators, including transcription factors and chromatin regulators, that drive the oncogenic gene expression program is a critical task in cancer research. Genomic profiles of active transcriptional regulators from primary cancer samples are limited in the public domain. Here we present BART Cancer (bartcancer.org), an interactive web resource database to display the putative transcriptional regulators that are responsible for differentially regulated genes in 15 different cancer types in The Cancer Genome Atlas (TCGA). BART Cancer integrates over 10000 gene expression profiling RNA-seq datasets from TCGA with over 7000 ChIP-seq datasets from the Cistrome Data Browser database and the Gene Expression Omnibus (GEO). BART Cancer uses Binding Analysis for Regulation of Transcription (BART) for predicting the transcriptional regulators from the differentially expressed genes in cancer samples compared to normal samples. BART Cancer also displays the activities of over 900 transcriptional regulators across cancer types, by integrating computational prediction results from BART and the Cistrome Cancer database. Focusing on transcriptional regulator activities in human cancers, BART Cancer can provide unique insights into epigenetics and transcriptional regulation in cancer, and is a useful data resource for genomics and cancer research communities.

Abstract 286: Long Noncoding RNAs Are Differentially Expressed in Heart Failure

2012 ◽  
Vol 111 (suppl_1) ◽  
Author(s):  
Emma L Robinson ◽  
Syed Haider ◽  
Hillary Hei ◽  
Richard T Lee ◽  
Roger S Foo
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Significant Proportion ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Control Of Gene Expression ◽  
Failing Heart ◽  
Novel Transcripts ◽  
Non Coding Rnas

Heart failure comprises of clinically distinct inciting causes but a consistent pattern of change in myocardial gene expression supports the hypothesis that unifying biochemical mechanisms underlie disease progression. The recent RNA-seq revolution has enabled whole transcriptome profiling, using deep-sequencing technologies. Up to 70% of the genome is now known to be transcribed into RNA, a significant proportion of which is long non-coding RNAs (lncRNAs), defined as polyribonucleotides of ≥200 nucleotides. This project aims to discover whether the myocardium expression of lncRNAs changes in the failing heart. Paired end RNA-seq from a 300-400bp library of ‘stretched’ mouse myocyte total RNA was carried out to generate 76-mer sequence reads. Mechanically stretching myocytes with equibiaxial stretch apparatus mimics pathological hypertrophy in the heart. Transcripts were assembled and aligned to reference genome mm9 (UCSC), abundance determined and differential expression of novel transcripts and alternative splice variants were compared with that of control (non-stretched) mouse myocytes. Five novel transcripts have been identified in our RNA-seq that are differentially expressed in stretched myocytes compared with non-stretched. These are regions of the genome that are currently unannotated and potentially are transcribed into non-coding RNAs. Roles of known lncRNAs include control of gene expression, either by direct interaction with complementary regions of the genome or association with chromatin remodelling complexes which act on the epigenome.Changes in expression of genes which contribute to the deterioration of the failing heart could be due to the actions of these novel lncRNAs, immediately suggesting a target for new pharmaceuticals. Changes in the expression of these novel transcripts will be validated in a larger sample size of stretched myocytes vs non-stretched myocytes as well as in the hearts of transverse aortic constriction (TAC) mice vs Sham (surgical procedure without the aortic banding). In vivo investigations will then be carried out, using siLNA antisense technology to silence novel lncRNAs in mice.

Protein-RNA interactome analysis reveals wide association of KSHV ORF57 with host non-coding RNAs and polysomes

2021 ◽  
Author(s):  
Beatriz Alvarado-Hernandez ◽  
Yanping Ma ◽  
Nishi R. Sharma ◽  
Vladimir Majerciak ◽  
Alexei Lobanov ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Splicing ◽  
Rna Binding ◽  
Viral Gene Expression ◽  
Viral Gene ◽  
28S Rrna ◽  
Protein Coding ◽  
Infected Cells ◽  
Non Coding Rnas ◽  
Rna Interaction

Kaposi’s sarcoma-associated herpesvirus (KSHV) ORF57 is an RNA-binding post-transcriptional regulator. We recently applied an affinity-purified anti-ORF57 antibody to conduct ORF57-CLIP (Cross-linking Immunoprecipitation) in combination with RNA-sequencing (CLIP-seq) and analyzed the genome-wide host RNA transcripts in association with ORF57 in BCBL-1 cells with lytic KSHV infection. Mapping of the CLIPed RNA reads to the human genome (GRCh37) revealed that most of the ORF57-associated RNA reads were from rRNAs. The remaining RNA reads mapped to several classes of host non-coding and protein-coding mRNAs. We found ORF57 binds and regulates expression of a subset of host lncRNAs, including LINC00324, LINC00355, and LINC00839 which are involved in cell growth. ORF57 binds snoRNAs responsible for 18S and 28S rRNA modifications, but does not interact with fibrillarin and NOP58. We validated ORF57 interactions with 67 snoRNAs by ORF57-RNA immunoprecipitation (RIP)-snoRNA-array assays. Most of the identified ORF57 rRNA binding sites (BS) overlap with the sites binding snoRNAs. We confirmed ORF57-snoRA71B RNA interaction in BCBL-1 cells by ORF57-RIP and Northern blot analyses using a 32 P-labeled oligo probe from the 18S rRNA region complementary to snoRA71B. Using RNA oligos from the rRNA regions that ORF57 binds for oligo pulldown-Western blot assays, we selectively verified ORF57 interactions with 5.8S and 18S rRNAs. Polysome profiling revealed that ORF57 associates with both monosomes and polysomes and its association with polysomes increases PABPC1 binding to, but prevent Ago2 from polysomes. Our data indicate a functional correlation with ORF57 binding and suppression of Ago2 activities for ORF57 promotion of gene expression. Significance As an RNA-binding protein, KSHV ORF57 regulates RNA splicing, stability, and translation and inhibits host innate immunity by blocking the formation of RNA granules in virus infected cells. In this report, ORF57 was found to interact many host non-coding RNAs, including lncRNAs, snoRNAs and ribosomal RNAs to carry out additional unknown functions. ORF57 binds a group of lncRNAs via the identified RNA motifs by ORF57 CLIP-seq to regulate their expression. ORF57 associates with snoRNAs independently of fibrillarin and NOP58 proteins, and with ribosomal RNA in the regions that commonly bind snoRNAs. Knockdown of fibrillarin expression decreases the expression of snoRNAs and CDK4, but not affect viral gene expression. More importantly, we found that ORF57 binds translationally active polysomes and enhances PABPC-1 but prevents Ago2 association with polysomes. Data provide a compelling evidence on how ORF57 in KSHV infected cells might regulate protein synthesis by blocking Ago2’s hostile activities on translation.

scholarly journals Involvement of Long Non-Coding RNAs (lncRNAs) in Tumor Angiogenesis

2020 ◽  
Vol 6 (4) ◽  
pp. 42 ◽  
Author(s):  
Julia Teppan ◽  
Dominik A. Barth ◽  
Felix Prinz ◽  
Katharina Jonas ◽  
Martin Pichler ◽  
...  
Keyword(s):  
Tumor Angiogenesis ◽  
Biological Processes ◽  
Protein Coding ◽  
Diagnostic Biomarkers ◽  
Oncogenic Pathways ◽  
Therapeutic Molecules ◽  
Cancer Types ◽  
Non Coding Rnas ◽  
Effective Use ◽  
To Receive

Long non-coding RNAs (lncRNAs) are defined as non-protein coding transcripts with a minimal length of 200 nucleotides. They are involved in various biological processes such as cell differentiation, apoptosis, as well as in pathophysiological processes. Numerous studies considered that frequently deregulated lncRNAs contribute to all hallmarks of cancer including metastasis, drug resistance, and angiogenesis. Angiogenesis, the formation of new blood vessels, is crucial for a tumor to receive sufficient amounts of nutrients and oxygen and therefore, to grow and exceed in its size over the diameter of 2 mm. In this review, the regulatory mechanisms of lncRNAs are described, which influence tumor angiogenesis by directly or indirectly regulating oncogenic pathways, interacting with other transcripts such as microRNAs (miRNAs) or modulating the tumor microenvironment. Further, angiogenic lncRNAs occurring in several cancer types such as liver, gastrointestinal cancer, or brain tumors are summarized. Growing evidence on the influence of lncRNAs on tumor angiogenesis verified these transcripts as potential predictive or diagnostic biomarkers or therapeutic targets of anti-angiogenesis treatment. However, there are many unsolved questions left which are pointed out in this review, hence driving comprehensive research in this area is necessary to enable an effective use of lncRNAs as either therapeutic molecules or diagnostic targets in cancer.

scholarly journals Integrative Analysis of the Genes Induced by the Intestine Microbiota of Infant Born to Term and Breastfed

2020 ◽  
Vol 14 ◽  
pp. 117793222090616
Author(s):  
Badreddine Nouadi ◽  
Yousra Sbaoui ◽  
Mariame El Messal ◽  
Faiza Bennis ◽  
Fatima Chegdani
Keyword(s):  
Gene Expression ◽  
Breast Milk ◽  
Differentially Expressed Genes ◽  
Bacterial Colonization ◽  
Biological Data ◽  
Integrative Analysis ◽  
Differentially Expressed ◽  
Epithelial Tissue ◽  
Biological Processes

Nowadays, the integration of biological data is a major challenge for bioinformatics. Many studies have examined gene expression in the epithelial tissue in the intestines of infants born to term and breastfed, generating a large amount of data. The integration of these data is important to understand the biological processes involved during bacterial colonization of the newborns intestine, particularly through breast milk. This work aims to exploit the bioinformatics approaches, to provide a new representation and interpretation of the interactions between differentially expressed genes in the host intestine induced by the microbiota.

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.

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