scholarly journals Transposable elements mediate genetic effects altering the expression of nearby genes in colorectal cancer

2021 ◽  
Author(s):  
Nikolaos Lykoskoufis ◽  
Evarist Planet ◽  
Halit Ongen ◽  
Didier Trono ◽  
Emmanouil T Dermitzakis
Keyword(s):  
Colorectal Cancer ◽  
Transposable Elements ◽  
Genetic Effect ◽  
Regulatory Sequences ◽  
Driver Genes ◽  
Cancer Driver ◽  
Tumor Tissues ◽  
Interspersed Repeats ◽  
Methylation Patterns ◽  
The Impact

Abstract Transposable elements (TEs) are interspersed repeats that contribute to more than half of the human genome, and TE-embedded regulatory sequences are increasingly recognized as major components of the human regulome. Perturbations of this system can contribute to tumorigenesis, but the impact of TEs on gene expression in cancer cells remains to be fully assessed. Here, we analyzed 275 normal colon and 276 colorectal cancer (CRC) samples from the SYSCOL colorectal cancer cohort and discovered 10,111 and 5,152 TE expression quantitative trait loci (eQTLs) in normal and tumor tissues, respectively. Amongst the latter, 376 were exclusive to CRC, likely driven by changes in methylation patterns. We identified that transcription factors are more enriched in tumor-specific TE-eQTLs than shared TE-eQTLs, indicating that TEs are more specifically regulated in tumor than normal. Using Bayesian Networks to assess the causal relationship between eQTL variants, TEs and genes, we identified that 1,758 TEs are mediators of genetic effect, altering the expression of 1,626 nearby genes significantly more in tumor compared to normal, of which 51 are cancer driver genes. We show that tumor-specific TE-eQTLs trigger the driver capability of TEs subsequently impacting expression of nearby genes. Collectively, our results highlight a global profile of a new class of cancer drivers, thereby enhancing our understanding of tumorigenesis and providing potential new candidate mechanisms for therapeutic target development.

scholarly journals Transposable elements mediate genetic effects altering the expression of nearby genes in colorectal cancer

2021 ◽  
Author(s):  
Nikolaos M. R. Lykoskoufis ◽  
Evarist Planet ◽  
Halit Ongen ◽  
Didier Trono ◽  
Emmanouil T. Dermitzakis
Keyword(s):  
Colorectal Cancer ◽  
Transposable Elements ◽  
Genetic Effect ◽  
Regulatory Sequences ◽  
Driver Genes ◽  
Cancer Driver ◽  
Tumor Tissues ◽  
Interspersed Repeats ◽  
Methylation Patterns ◽  
The Impact

ABSTRACTTransposable elements (TEs) are interspersed repeats that contribute to more than half of the human genome, and TE-embedded regulatory sequences are increasingly recognized as major components of the human regulome. Perturbations of this system can contribute to tumorigenesis, but the impact of TEs on gene expression in cancer cells remains to be fully assessed. Here, we analyzed 275 normal colon and 276 colorectal cancer (CRC) samples from the SYSCOL colorectal cancer cohort and discovered 10,111 and 5,152 TE expression quantitative trait loci (eQTLs) in normal and tumor tissues, respectively. Amongst the latter, 376 were exclusive to CRC, likely driven by changes in methylation patterns. We identified that transcription factors are more enriched in tumor-specific TE-eQTLs than shared TE-eQTLs, indicating that TEs are more specifically regulated in tumor than normal. Using Bayesian Networks to assess the causal relationship between eQTL variants, TEs and genes, we identified that 1,758 TEs are mediators of genetic effect, altering the expression of 1,626 nearby genes significantly more in tumor compared to normal, of which 51 are cancer driver genes. We show that tumor-specific TE-eQTLs trigger the driver capability of TEs subsequently impacting expression of nearby genes. Collectively, our results highlight a global profile of a new class of cancer drivers, thereby enhancing our understanding of tumorigenesis and providing potential new candidate mechanisms for therapeutic target development.

scholarly journals Role of Transposable Elements in Gene Regulation in the Human Genome

Life ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 118
Author(s):  
Arsala Ali ◽  
Kyudong Han ◽  
Ping Liang
Keyword(s):  
Gene Regulation ◽  
Transposable Elements ◽  
Regulatory Sequences ◽  
Rna Sequences ◽  
Expression Of Genes ◽  
Wide Range ◽  
Lineage Specificity ◽  
Regulatory Rnas ◽  
Potential Factors ◽  
Interspersed Repeats

Transposable elements (TEs), also known as mobile elements (MEs), are interspersed repeats that constitute a major fraction of the genomes of higher organisms. As one of their important functional impacts on gene function and genome evolution, TEs participate in regulating the expression of genes nearby and even far away at transcriptional and post-transcriptional levels. There are two known principal ways by which TEs regulate the expression of genes. First, TEs provide cis-regulatory sequences in the genome with their intrinsic regulatory properties for their own expression, making them potential factors for regulating the expression of the host genes. TE-derived cis-regulatory sites are found in promoter and enhancer elements, providing binding sites for a wide range of trans-acting factors. Second, TEs encode for regulatory RNAs with their sequences showed to be present in a substantial fraction of miRNAs and long non-coding RNAs (lncRNAs), indicating the TE origin of these RNAs. Furthermore, TEs sequences were found to be critical for regulatory functions of these RNAs, including binding to the target mRNA. TEs thus provide crucial regulatory roles by being part of cis-regulatory and regulatory RNA sequences. Moreover, both TE-derived cis-regulatory sequences and TE-derived regulatory RNAs have been implicated in providing evolutionary novelty to gene regulation. These TE-derived regulatory mechanisms also tend to function in a tissue-specific fashion. In this review, we aim to comprehensively cover the studies regarding these two aspects of TE-mediated gene regulation, mainly focusing on the mechanisms, contribution of different types of TEs, differential roles among tissue types, and lineage-specificity, based on data mostly in humans.

Stage-differentiated modelling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression

2021 ◽  
Author(s):  
Sangeetha Muthamilselvan ◽  
Abirami Raghavendran ◽  
Ashok Palaniappan
Keyword(s):  
Colorectal Cancer ◽  
Dna Methylation ◽  
Cpg Island ◽  
Early Stage ◽  
P Value ◽  
Consensus Analysis ◽  
One Stage ◽  
Differentially Methylated Genes ◽  
Methylation Patterns ◽  
The Impact

Abstract Background: Aberrant DNA methylation acts epigenetically to skew the gene transcription rate up or down, with causative roles in the etiology of cancers. However research on the role of DNA methylation in driving the progression of cancers is limited. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer (CRC), and unravelled significant stagewise signposts of CRC progression. Methods: The methylation β - matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with AJCC stages, and analysed for stage-salient genes using multiple approaches involving stage-differentiated linear modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against controls (adjusted p-value <0.001 and |log fold-change of M-value| >2). These results were filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by Kaplan–Meier survival analysis to evaluate the impact of methylation patterns of consensus stage-salient biomarkers on disease prognosis.Results: We found significant genome-wide changes in methylation patterns in cancer cases relative to controls agnostic of stage. Our stage-differentiated analysis yielded the following stage-salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were hypermethylated, indicating down-regulation and signifying a CpG island Methylator Phenotype (CIMP) manifestation. A significant prognostic signature consisting of FBN1 and FOXG1 survived all the steps of our analysis pipeline, and represents a novel early-stage biomarker. Conclusions: We have designed a workflow for stage-differentiated consensus analysis, and identified stage-salient diagnostic biomarkers and an early-stage prognostic biomarker panel. Our studies further yield a novel CIMP-like signature of potential clinical import underlying CRC progression.

scholarly journals Role of Transposable Elements in Gene Regulation in the Human Genome

2021 ◽  
Author(s):  
Arsala Ali ◽  
Kyudong Han ◽  
Ping Liang
Keyword(s):  
Gene Regulation ◽  
Transposable Elements ◽  
Regulatory Sequences ◽  
Rna Sequences ◽  
Expression Of Genes ◽  
Wide Range ◽  
Lineage Specificity ◽  
Regulatory Rnas ◽  
Potential Factors ◽  
Interspersed Repeats

Transposable elements (TEs), also known as mobile elements (MEs), are interspersed repeats that constitute a major fraction of the genomes of higher organisms. As one of their important functional impacts on gene function and genome evolution, TEs participate in regulating the expression of genes nearby and even far away at transcriptional and post-transcriptional levels. There are two known principal ways by which TEs regulate expression of genes. First, TEs provide cis-regulatory sequences in the genome with their intrinsic regulatory properties for their own expression making them potential factors for regulating the expression of the host genes. TE-derived cis-regulatory sites are found in promoter and enhancer elements, providing binding sites for a wide range of trans-acting factors. Second, TEs encode for regulatory RNAs with their sequences showed to be present in a substantial fraction of miRNAs and long non-coding RNAs (lncRNAs), indicating the TE origin of these RNAs. Furthermore, TEs sequences were found to be critical for regulatory functions of these RNAs including binding to the target mRNA. TEs thus provide crucial regulatory roles by being part of cis-regulatory and regulatory RNA sequences. Moreover, both TE-derived cis-regulatory sequences and TE-derived regulatory RNAs, have been implicated to provide evolutionary novelty to gene regulation. These TE-derived regulatory mechanisms also tend to function in tissue-specific fashion. In this review, we aim to comprehensively cover the studies regarding these two aspects of TE-mediated gene regulation, mainly focusing on the mechanisms, contribution of different types of TEs, differential roles among tissue types, and lineage specificity, based on data mostly in humans.

scholarly journals MECoRank: cancer driver genes discovery simultaneously evaluating the impact of SNVs and differential expression on transcriptional networks

2019 ◽  
Vol 12 (S7) ◽  
Author(s):  
Ying Hui ◽  
Pi-Jing Wei ◽  
Junfeng Xia ◽  
Yu-Tian Wang ◽  
Chun-Hou Zheng
Keyword(s):  
Gene Expression ◽  
Gene List ◽  
Interaction Network ◽  
Transcriptional Network ◽  
Transcriptional Networks ◽  
Driver Genes ◽  
Cancer Driver ◽  
Novel Approach ◽  
Novel Method ◽  
The Impact

Abstract Background Although there are huge volumes of genomic data, how to decipher them and identify driver events is still a challenge. The current methods based on network typically use the relationship between genomic events and consequent changes in gene expression to nominate putative driver genes. But there may exist some relationships within the transcriptional network. Methods We developed MECoRank, a novel method that improves the recognition accuracy of driver genes. MECoRank is based on bipartite graph to propagates the scores via an iterative process. After iteration, we will obtain a ranked gene list for each patient sample. Then, we applied the Condorcet voting method to determine the most impactful drivers in a population. Results We applied MECoRank to three cancer datasets to reveal candidate driver genes which have a greater impact on gene expression. Experimental results show that our method not only can identify more driver genes that have been validated than other methods, but also can recognize some impactful novel genes which have been proved to be more important in literature. Conclusions We propose a novel approach named MECoRank to prioritize driver genes based on their impact on the expression in the molecular interaction network. This method not only assesses mutation’s effect on the transcriptional network, but also assesses the differential expression’s effect within the transcriptional network. And the results demonstrated that MECoRank has better performance than the other competing approaches in identifying driver genes.

Development of DNA methylation markers for predicting the prognosis of pancreatic cancer.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16216-e16216
Author(s):  
Jian Zhou ◽  
Yuchen Tang ◽  
Ye Li ◽  
Bin Yi ◽  
Jian Yang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Risk Score ◽  
Clinical Parameters ◽  
Cox Regression Analysis ◽  
Normal Tissues ◽  
Model Based ◽  
Tumor Tissues ◽  
Methylation Patterns ◽  
Migration Pathways ◽  
The Impact

e16216 Background: Pancreatic cancer is an extremely malignant tumor that is associated with low survival rates. Currently, TNM staging, serum CA19–9, CA125 and CEA are used to assess the risk level and estimate prognosis. However, it is still a challenge to predict survival of pancreatic cancer patients (pts) with due to the impact of wide variability of outcomes and genetic heterogeneity. In our study, we aimed to develop a model based on multiple prognostic-related methylation markers and clinical parameters to predict the overall survival (OS) of pancreatic cancer pts. Methods: A total of 50 pts with early-stage resectable pancreatic cancer were included in this study. Preoperative blood, tumor and tumor-distant normal tissue samples were obtained from the pts. Methylation levels from all samples were profiled using targeted bisulfite sequencing using bespoke pancreatic cancer methylation panel covering 80,672 CpG sites, spanning 1.05 mega bases of the human genome. To improve the linkage of methylation sites, we further analyzed the methylation profile as methylation blocks. Results: A total of 1162 tumor-specific methylation blocks, including 737 hypermethylated and 425 hypomethylated blocks were found to be differentially methylated in tumor tissues as compared to tumor-distant normal tissues (P < 0.05). Genes in hypermethylated blocks were significantly enriched in neuroactive ligand−receptor interaction and ca+ signaling pathways, whereas those in hypomethylated blocks were focused in E. coli infection and leukocyte transendothelial migration pathways. All these involved pathways are pancreatic cancer related. Moreover, 7 differentially methylated blocks were identified to significantly associate with OS, including 5 hyper- and 2 hypomethylated blocks. Therefore, we constructed a model based on prognostic-related blocks to predict OS of pancreatic cancer pts. A risk score was derived for each patient based on the model. Pts in the high-risk (HR) group (median risk score as cutoff) showed significantly poorer OS than those in the low-risk (LR) group in survival analysis (p = 0.0016, HR = 0.30). When clinical parameters were also considered, the risk score was found to be the only independent prognostic parameter (p < 0.001) by Cox regression analysis. The prognostic effect of the risk score remained significant in patient groups separated by CA125 levels (p < 0.01). In pre-operative blood samples, risk score was also significantly associated with OS (p = 0.031). Pts in the LR group showed significantly longer OS than those in the HR group. Conclusions: Our data revealed distinct methylation patterns between tumor tissues and tumor-distant normal tissues, suggesting tumor-specific methylation patterns could potentially be developed as diagnostic biomarkers. Importantly, our study also identified 7 blocks-based risk score that could potentially be used as prognostic markers for pancreatic cancer.

scholarly journals Genomics of Viral Hepatitis-Associated Liver Tumors

2021 ◽  
Vol 10 (9) ◽  
pp. 1827
Author(s):  
Camille Péneau ◽  
Jessica Zucman-Rossi ◽  
Jean-Charles Nault
Keyword(s):  
Hepatitis B ◽  
Insertional Mutagenesis ◽  
Liver Tumors ◽  
Tumor Development ◽  
Driver Genes ◽  
Adeno Associated Virus ◽  
Cancer Driver ◽  
B Virus ◽  
The Impact

Virus-related liver carcinogenesis is one of the main contributors of cancer-related death worldwide mainly due to the impact of chronic hepatitis B and C infections. Three mechanisms have been proposed to explain the oncogenic properties of hepatitis B virus (HBV) infection: induction of chronic inflammation and cirrhosis, expression of HBV oncogenic proteins, and insertional mutagenesis into the genome of infected hepatocytes. Hepatitis B insertional mutagenesis modifies the function of cancer driver genes and could promote chromosomal instability. In contrast, hepatitis C virus promotes hepatocellular carcinoma (HCC) occurrence mainly through cirrhosis development whereas the direct oncogenic role of the virus in human remains debated. Finally, adeno associated virus type 2 (AAV2), a defective DNA virus, has been associated with occurrence of HCC harboring insertional mutagenesis of the virus. Since these tumors developed in a non-cirrhotic context and in the absence of a known etiological factor, AAV2 appears to be the direct cause of tumor development in these patients via a mechanism of insertional mutagenesis altering similar oncogenes and tumor suppressor genes targeted by HBV. A better understanding of virus-related oncogenesis will be helpful to develop new preventive strategies and therapies directed against specific alterations observed in virus-related HCC.

scholarly journals Colorectal cancer driver genes identified by patient specific comparison of cytogenetic microarray

Genomics Data ◽  
2014 ◽  
Vol 2 ◽  
pp. 29-31 ◽  
Author(s):  
Mohammad Azhar Aziz ◽  
Sathish Periyasamy ◽  
Zeyad Yousef ◽  
Ahmad Deeb ◽  
Majed AlOtaibi
Keyword(s):  
Colorectal Cancer ◽  
Patient Specific ◽  
Driver Genes ◽  
Cancer Driver ◽  
Cancer Driver Genes ◽  
Specific Comparison

scholarly journals A Platform for Validating Colorectal Cancer Driver Genes Using Mouse Organoids

2021 ◽  
Vol 12 ◽  
Author(s):  
Haruna Takeda
Keyword(s):  
Colorectal Cancer ◽  
Culture System ◽  
Intestinal Tumor ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Organoid Culture ◽  
Cancer Genome Sequencing ◽  
Cancer Tissues ◽  
Tumor Organoids

Systematic approaches for functionally validating cancer genes are needed since numerous genes mutated in cancer tissues have been identified from cancer genome sequencing. The mouse organoid culture system has been extensively used in the field of cancer research since mouse organoids can faithfully recapitulate the physiological behavior of the cells. Taking advantage of this, we recently described a platform for functionally validating colorectal cancer (CRC) driver genes that utilized CRISPR-Cas9 in mouse intestinal tumor organoids. In this review, we will describe how mouse organoids have been applied to CRC research and focus on how CRC genes can be validated using mouse organoids.

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