scholarly journals Novel Insights into Epigenetic Regulation of IL6 Pathway: In Silico Perspective on Inflammation and Cancer Relationship

2021 ◽  
Vol 22 (18) ◽  
pp. 10172
Author(s):  
Saverio Candido ◽  
Barbara Maria Rita Tomasello ◽  
Alessandro Lavoro ◽  
Luca Falzone ◽  
Giuseppe Gattuso ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Epigenetic Regulation ◽  
Computational Analysis ◽  
The Cancer Genome Atlas ◽  
Post Translational Modifications ◽  
Pathway Gene ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Types

IL-6 pathway is abnormally hyperactivated in several cancers triggering tumor cell growth and immune system inhibition. Along with genomic mutation, the IL6 pathway gene expression can be affected by DNA methylation, microRNAs, and post-translational modifications. Computational analysis was performed on the Cancer Genome Atlas (TCGA) datasets to explore the role of IL6, IL6R, IL6ST, and IL6R transmembrane isoform expression and their epigenetic regulation in different cancer types. IL6 was significantly modulated in 70% of tumor types, revealing either up- or down-regulation in an approximately equal number of tumors. Furthermore, IL6R and IL6ST were downregulated in more than 10 tumors. Interestingly, the correlation analysis demonstrated that only the IL6R expression was negatively affected by the DNA methylation within the promoter region in most tumors. Meanwhile, only the IL6ST expression was extensively modulated by miRNAs including miR-182-5p, which also directly targeted all three genes. In addition, IL6 upregulated miR-181a-3p, mirR-214-3p, miR-18a-5p, and miR-938, which in turn inhibited the expression of IL6 receptors. Finally, the patients’ survival rate was significantly affected by analyzed targets in some tumors. Our results suggest the relevance of epigenetic regulation of IL6 signaling and pave the way for further studies to validate these findings and to assess the prognostic and therapeutic predictive value of these epigenetic markers on the clinical outcome and survival of cancer patients.

scholarly journals Epstein-Barr Virus-Positive Cancers Show Altered B-Cell Clonality

mSystems ◽  
2018 ◽  
Vol 3 (5) ◽  
Author(s):  
Sara R. Selitsky ◽  
David Marron ◽  
Lisle E. Mose ◽  
Joel S. Parker ◽  
Dirk P. Dittmer
Keyword(s):  
B Cells ◽  
B Cell ◽  
Epstein Barr Virus ◽  
The Cancer Genome Atlas ◽  
Barr Virus ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Epstein Barr ◽  
Tumor Types ◽  
Genome Atlas

ABSTRACTEpstein-Barr virus (EBV) is convincingly associated with gastric cancer, nasopharyngeal carcinoma, and certain lymphomas, but its role in other cancer types remains controversial. To test the hypothesis that there are additional cancer types with high prevalence of EBV, we determined EBV viral expression in all the Cancer Genome Atlas Project (TCGA) mRNA sequencing (mRNA-seq) samples (n= 10,396) from 32 different tumor types. We found that EBV was present in gastric adenocarcinoma and lymphoma, as expected, and was also present in >5% of samples in 10 additional tumor types. For most samples, EBV transcript levels were low, which suggests that EBV was likely present due to infected infiltrating B cells. In order to determine if there was a difference in the B-cell populations, we assembled B-cell receptors for each sample and found B-cell receptor abundance (P≤ 1.4 × 10−20) and diversity (P≤ 8.3 × 10−27) were significantly higher in EBV-positive samples. Moreover, diversity was independent of B-cell abundance, suggesting that the presence of EBV was associated with an increased and altered B-cell population.IMPORTANCEAround 20% of human cancers are associated with viruses. Epstein-Barr virus (EBV) contributes to gastric cancer, nasopharyngeal carcinoma, and certain lymphomas, but its role in other cancer types remains controversial. We assessed the prevalence of EBV in RNA-seq from 32 tumor types in the Cancer Genome Atlas Project (TCGA) and found EBV to be present in >5% of samples in 12 tumor types. EBV infects epithelial cells and B cells and in B cells causes proliferation. We hypothesized that the low expression of EBV in most of the tumor types was due to infiltration of B cells into the tumor. The increase in B-cell abundance and diversity in subjects where EBV was detected in the tumors strengthens this hypothesis. Overall, we found that EBV was associated with an increased and altered immune response. This result is not evidence of causality, but a potential novel biomarker for tumor immune status.

scholarly journals Identifying Interaction Clusters for MiRNA and MRNA Pairs in TCGA Network

Genes ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 702 ◽  
Author(s):  
Dai ◽  
Ding ◽  
Liu ◽  
Xu ◽  
Jiang ◽  
...  
Keyword(s):  
Messenger Rna ◽  
The Cancer Genome Atlas ◽  
Biological Functions ◽  
Significant Cluster ◽  
Scoring Method ◽  
Nonalcoholic Fatty Liver ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Liver Hepatocellular Carcinoma ◽  
Tumor Types

Existing methods often fail to recognize the conversions for the biological roles of the pairs of genes and microRNAs (miRNAs) between the tumor and normal samples. We have developed a novel cluster scoring method to identify messenger RNA (mRNA) and miRNA interaction pairs and clusters while considering tumor and normal samples jointly. Our method has identified 54 significant clusters for 15 cancer types selected from The Cancer Genome Atlas project. We also determined the shared clusters across tumor types and/or subtypes. In addition, we compared gene and miRNA overlap between lists identified in our liver hepatocellular carcinoma (LIHC) study and regulatory relationships reported from human and rat nonalcoholic fatty liver disease studies (NAFLD). Finally, we analyzed biological functions for the single significant cluster in LIHC and uncovered a significantly enriched pathway (phospholipase D signaling pathway) with six genes represented in the cluster, symbols: DGKQ, LPAR2, PDGFRB, PIK3R3, PTGFR and RAPGEF3.

scholarly journals Enabling transparent and collaborative computational analysis of 12 tumor types within The Cancer Genome Atlas

2013 ◽  
Vol 45 (10) ◽  
pp. 1121-1126 ◽  
Author(s):  
Larsson Omberg ◽  
Kyle Ellrott ◽  
Yuan Yuan ◽  
Cyriac Kandoth ◽  
Chris Wong ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Cancer Genome Atlas ◽  
Tumor Types ◽  
Genome Atlas

scholarly journals Correlation Patterns Between DNA Methylation and Gene Expression in The Cancer Genome Atlas

2019 ◽  
Vol 18 ◽  
pp. 117693511982877 ◽  
Author(s):  
John CG Spainhour ◽  
Hong Seo Lim ◽  
Soojin V Yi ◽  
Peng Qiu
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Promoter Region ◽  
The Cancer Genome Atlas ◽  
Gene Body ◽  
Cpg Sites ◽  
Cpg Site ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Background: DNA methylation is a form of epigenetic modification that has been shown to play a significant role in gene regulation. In cancer, DNA methylation plays an important role by regulating the expression of oncogenes. The role of DNA methylation in the onset and progression of various cancer types is now being elucidated as more large-scale data become available. The Cancer Genome Atlas (TCGA) provides a wealth of information for the analysis of various molecular aspects of cancer genetics. Gene expression data and DNA methylation data from TCGA have been used for a variety of studies. A traditional understanding of the effects of DNA methylation on gene expression has linked methylation of CpG sites in the gene promoter region with the decrease in gene expression. Recent studies have begun to expand this traditional role of DNA methylation. Results: Here we present a pan-cancer analysis of correlation patterns between CpG methylation and gene expression. Using matching patient data from TCGA, 33 cancer-specific correlations were calculated for each CpG site and the expression level of its corresponding gene. These correlations were used to identify patterns on a per-site basis as well as patterns of methylation across the gene body. Using these identified patterns, we found genes that contain conflicting methylation signals beyond the commonly accepted association between the promoter region methylation and silencing of gene expression. Beyond gene body methylation in whole, we examined individual CpG sites and show that, even in the same gene body, some sites can have a contradictory effect on gene expression in cancers. Conclusions: We observed that within promoter regions there was a substantial amount of positive correlation between methylation and gene expression, which contradicts the commonly accepted association. We observed that the correlation between CpG methylation and gene expression does not exhibit in a tissue-specific manner, suggesting that the effects of methylation on gene expression are largely tissue independent. The analysis of correlation associated with the location of the CpG site in the gene body has led to the identification of several different methylation patterns that affect gene expression, and several examples of methylation activating gene expression were observed. Distinctly opposing or conflicting effects were seen in close proximity on the gene body, where negative and positive correlations were seen at the neighboring CpG sites.

scholarly journals TumorFusions: an integrative resource for reporting cancer-associated transcript fusions in 33 tumor types

2017 ◽  
Author(s):  
Xin Hu ◽  
Qianghu Wang ◽  
Floris Barthel ◽  
Ming Tang ◽  
Samirkumar Amin ◽  
...  
Keyword(s):  
The Cancer Genome Atlas ◽  
Whole Genome Sequencing Data ◽  
Fusion Genes ◽  
Sequencing Data ◽  
Structural Variations ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Tumor Types ◽  
Fusion Detection ◽  
Genome Atlas

Fusion genes, particularly those involving kinases, have been demonstrated as drivers and are frequent therapeutic targets in cancer1. Here, we describe our results on detecting transcript fusions across 33 cancer types from The Cancer Genome Atlas (TCGA), totaling 9,966 cancer samples and 648 normal samples2. Preprocessing, including read alignment to both genome and transcriptome, and fusion detection were carried out using a uniform pipeline3. To validate the resultant fusions, we also called somatic structural variations for 561 cancers from whole genome sequencing data. A summary of the data used in this study is provided in Table S1. Our results can be accessed per our portal at http://www.tumorfusions.org.

scholarly journals JAMMIT Analysis Defines 2 Semi-Independent Immune Processes Common to 29 Solid Tumors

2021 ◽  
Author(s):  
Emory Zitello ◽  
Michael Vo ◽  
Shaoqiu Chen ◽  
Scott Bowler ◽  
Vedbar Khadka ◽  
...  
Keyword(s):  
Solid Tumors ◽  
Gene Signature ◽  
The Cancer Genome Atlas ◽  
Published Data ◽  
Molecular Features ◽  
Solid Malignancies ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Bioinformatic Approaches ◽  
Tumor Types

AbstractImmunophenotype of solid tumors has relevance to cancer immunotherapy, as not all patients respond optimally to treatment utilizing monoclonal antibodies. Bioinformatic studies have failed to clearly identify tumor immunophenotype in a way that encompasses a wide variety of tumor types and highlights fundamental differences among them, complicating prediction of patient clinical response. The novel JAMMIT algorithm was used to analyze mRNA data for 33 cancer types in The Cancer Genome Atlas (TCGA). We found that B cells and T cells constitute the principal source of variation in most patient cohorts, and that virtually all solid malignancies formed three hierarchical clustering patterns with similar molecular features. The second main source of variability in transcriptomic studies we attribute to monocytes. We identified the three tumor types as TC1-mediated, TC17-mediated and non-immunogenic immunophenotypes and used a 3-gene signature to approximate infiltration by agranulocytes. Methods of in silico validation such as pathway analysis, Cibersort and published data from treated cohorts were used to substantiate these findings. Monocytic infiltrate is found to be related to patient survival according to immunophenotype, important differences in some solid tumors are identified and deficiencies of common bioinformatic approaches relevant to diagnosis are detailed by this work.

scholarly journals Prognostic and Immunological Role of Gasdermin E in Pan-Cancer Analysis

2021 ◽  
Vol 11 ◽  
Author(s):  
Zheng Zhang ◽  
Shuangshuang Zhao ◽  
Haizhen Yang ◽  
Yanwei Chen ◽  
Huahui Feng ◽  
...  
Keyword(s):  
The Cancer Genome Atlas ◽  
Survival Prognosis ◽  
Cancer Management ◽  
Cancer Associated Fibroblast ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Functional Mechanisms ◽  
Pan Cancer

Despite accumulating cell- or animal-based experiments providing the relationship between Gasdermin E (GSDME) and human diseases, especially in malignant cancers, no pan-cancer analysis about the function of GSMDE in cancer management can be available up to date. Our research, for the first time, explored the potential carcinogenic role of GSDME across 33 tumors from the public platform of TCGA (The cancer genome atlas) database. GSDME is highly expressed in most malignant cancers, and obvious relationship exists between GSDME level and survival prognosis of cancer patients. The expression of GSDME was statically associated with the cancer-associated fibroblast infiltration in diverse cancer types, such as BLCA, CHOL, GBM, KIRC, LIHC, MESO, STAD, and UCEC. Furthermore, pyroptosis, sensory perception of sound, and defense response to bacterium were involved in the functional mechanisms of GSDME expression from GO analysis. Last but not the least, in vitro experiments were also performed to identify GSDME-induced pyroptosis. Our first pan-cancer analysis of GSDME not only broadens the understanding of the carcinogenic roles of GSDME but also provides a promising therapeutic strategy for benefiting an increasing number of cancerous patients based on GSDME-induced pyroptosis.

scholarly journals Identification of Methylation Biomarkers for Early Detection of Prostate Cancer

2021 ◽  
Author(s):  
Yiyi Pu ◽  
Chao Li ◽  
Haining Yuan ◽  
Xiaoju Wang
Keyword(s):  
Prostate Cancer ◽  
Dna Methylation ◽  
Early Detection ◽  
Early Diagnosis ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Prostate Tumors ◽  
Normal Tissues ◽  
Cancer Genome Atlas ◽  
Cancer Types

Abstract Background: DNA methylation has been widely used for development of cancer diagnosis biomarker. However, the clinical translational rate is low. Databases, such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), offer great opportunities for DNA methylation biomarker identification. By taking advantage of the public databases, we aimed to identify cancer specific biomarkers based on DNA methylation level for early detection purpose. Results: We performed a pan-cancer methylation analysis using datasets from TCGA and validated the results using GEO datasets. To identify early-diagnosis biomarkers, we focused on the localized tumors, and identified the biomarkers that can effectively distinguish the localized tumors from normal tissues. After comparing biomarkers for all cancer types, we identified a large group of cancer specific biomarkers. Within all 26 prostate cancer specific biomarkers selected, we confirmed three biomarker sets by multiplex analysis. First, 7 biomarkers (cg26140475, cg24891312, cg24522654, cg21359747, cg03254336, cg12697139, cg19034132) could detect localized prostate tumors from normal tissues (AUC > 0.9). Second, 9 biomarkers (cg17220055, cg26140475, cg24891312, cg09853702, cg22400059, cg16736279, cg27639613, cg06011086, cg00664697) could distinguish between low and high Gleason score prostate tumors (AUC = 0.79). Last, a single biomarker (cg26140475) completely separated prostate tumor from other urinary tumors (AUC = 1). Conclusions: Our study identified and validated a panel of methylation-based biomarkers which could be used for prostate cancer early diagnosis.

scholarly journals Integrative Histologic and Bioinformatics Analysis of BIRC5/Survivin Expression in Oral Squamous Cell Carcinoma

2018 ◽  
Vol 19 (9) ◽  
pp. 2664 ◽  
Author(s):  
Giuseppe Troiano ◽  
Agostino Guida ◽  
Gabriella Aquino ◽  
Gerardo Botti ◽  
Nunzia Losito ◽  
...  
Keyword(s):  
Gene Expression ◽  
Survivin Expression ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Poor Overall Survival ◽  
Squamous Cells ◽  
Nuclear Expression ◽  
Cancer Genome Atlas ◽  
Cancer Types

Survivin is a well-known protein involved in the inhibition of apoptosis in many different cancer types. The aim of this study was to perform an integrated bioinformatic and histologic analysis in order to study the expression and prognostic role of Survivin and its related gene BIRC5 in oral cancer. Publicly available databases were accessed via Gene Expression Omnibus and Oncomine, in addition raw data from The Cancer Genome Atlas (TCGA) were also obtained in order to analyze the rate of gene mutation, expression and methylation in patients with oral squamous cells carcinoma (OSCC). Immunohistochemistry (IHC) was also performed in order to evaluate the nuclear and cytoplasmic expression of Survivin and their correlation with cell proliferation in samples from OSCC patients. Results of this study revealed that Survivin is rarely mutated in OSCC samples and upregulated when compared to non-cancerous tissue. A negative correlation between the methylation of the island cg25986496 and BIRC5 mRNA expression was detected from TCGA data. IHC staining revealed that cytoplasmic (and not nuclear) expression of Survivin is associated with poor overall survival in OSCC patients, while the nuclear expression correlates with higher proliferation rate. In addition, data from TCGA database revealed that BIRC5 gene expression is an independent prognostic factor for OSCC patients.

scholarly journals An Integrative Pan-Cancer Analysis of the Oncogenic Role of COPB2 in Human Tumors

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Biao Wu ◽  
Yumeng Wu ◽  
Xianlin Guo ◽  
Yanping Yue ◽  
Yuanyuan Li ◽  
...  
Keyword(s):  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Comprehensive Understanding ◽  
Chemotherapy Sensitivity ◽  
Tumor Study ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Patient Prognosis ◽  
Pan Cancer

Several studies have suggested that coatomer protein complex subunit beta 2 (COPB2) may act as an oncogene in various cancer types. However, no systematic pan-cancer analysis has been performed to date. Therefore, the present study analyzed the potential oncogenic role of COPB2 using TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) datasets. The majority of the cancer types overexpressed the COPB2 protein, and its expression significantly correlated with tumor prognosis. In certain tumors, such as those found in breast and ovarian tissues, phosphorylated S859 exhibited high expression. It was found that mutations of the COPB2 protein in kidney and endometrial cancers exhibited a significant impact on patient prognosis. It is interesting to note that COPB2 expression correlated with the number of cancer-associated fibroblasts in certain tumors, such as cervical and endocervical cancers and colon adenocarcinomas. In addition, COPB2 was involved in the transport of substances and correlated with chemotherapy sensitivity. This is considered the first pan-tumor study, which provided a relatively comprehensive understanding of the mechanism by which COPB2 promotes cancer growth.

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