scholarly journals Pan-Cancer Genome-Wide DNA Methylation Analyses Revealed That Hypermethylation Influences 3D Architecture and Gene Expression Dysregulation in HOXA Locus During Carcinogenesis of Cancers

2021 ◽  
Vol 9 ◽  
Author(s):  
Gang Liu ◽  
Zhenhao Liu ◽  
Xiaomeng Sun ◽  
Xiaoqiong Xia ◽  
Yunhe Liu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cell Lines ◽  
Dna Interaction ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Topological Domains ◽  
Cancer Types ◽  
Pan Cancer

DNA methylation dysregulation during carcinogenesis has been widely discussed in recent years. However, the pan-cancer DNA methylation biomarkers and corresponding biological mechanisms were seldom investigated. We identified differentially methylated sites and regions from 5,056 The Cancer Genome Atlas (TCGA) samples across 10 cancer types and then validated the findings using 48 manually annotated datasets consisting of 3,394 samples across nine cancer types from Gene Expression Omnibus (GEO). All samples’ DNA methylation profile was evaluated with Illumina 450K microarray to narrow down the batch effect. Nine regions were identified as commonly differentially methylated regions across cancers in TCGA and GEO cohorts. Among these regions, a DNA fragment consisting of ∼1,400 bp detected inside the HOXA locus instead of the boundary may relate to the co-expression attenuation of genes inside the locus during carcinogenesis. We further analyzed the 3D DNA interaction profile by the publicly accessible Hi-C database. Consistently, the HOXA locus in normal cell lines compromised isolated topological domains while merging to the domain nearby in cancer cell lines. In conclusion, the dysregulation of the HOXA locus provides a novel insight into pan-cancer carcinogenesis.

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 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.

scholarly journals Epigenetic Variation Analysis Leads to Biomarker Discovery in Gastric Adenocarcinoma

2020 ◽  
Vol 11 ◽  
Author(s):  
Yan Zhang ◽  
Dianjing Guo
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Dna Methylation ◽  
Gastric Adenocarcinoma ◽  
Histone Modifications ◽  
Biomarker Discovery ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Integrated Analysis ◽  
Epigenetic Variation

As one of the most common malignant tumors worldwide, gastric adenocarcinoma (GC) and its prognosis are still poorly understood. Various genetic and epigenetic factors have been indicated in GC carcinogenesis. However, a comprehensive and in-depth investigation of epigenetic alteration in gastric cancer is still missing. In this study, we systematically investigated some key epigenetic features in GC, including DNA methylation and five core histone modifications. Data from The Cancer Genome Atlas Program and other studies (Gene Expression Omnibus) were collected, analyzed, and validated with multivariate statistical analysis methods. The landscape of epi-modifications in gastric cancer was described. Chromatin state transition analysis showed a histone marker shift in gastric cancer genome by employing a Hidden-Markov-Model based approach, indicated that histone marks tend to label different sets of genes in GC compared to control. An additive effect of these epigenetic marks was observed by integrated analysis with gene expression data, suggesting epigenetic modifications may cooperatively regulate gene expression. However, the effect of DNA methylation was found more significant without the presence of the five histone modifications in our study. By constructing a PPI network, key genes to distinguish GC from normal samples were identified, and distinct patterns of oncogenic pathways in GC were revealed. Some of these genes can also serve as potential biomarkers to classify various GC molecular subtypes. Our results provide important insights into the epigenetic regulation in gastric cancer and other cancers in general. This study describes the aberrant epigenetic variation pattern in GC and provides potential direction for epigenetic biomarker discovery.

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 The role of miR-92b in cholangiocarcinoma patients

2018 ◽  
Vol 33 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Min-hang Zhou ◽  
Hong-wei Zhou ◽  
Mo Liu ◽  
Jun-zhong Sun
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Positive Regulation ◽  
Cancer Genome Atlas ◽  
High Level ◽  
Genome Atlas

Purpose: The role of microRNA (miRNA) in cholangiocarcinoma was not clear. The aim of this study was to find the potential diagnostic and prognostic miRNA in cholangiocarcinoma patients. Methods: The miRNA expression profiles in cholangiocarcinoma patients from The Cancer Genome Atlas and Gene Expression Omnibus (GSE53870) were analyzed. The comparison of overall survival was performed using the Kaplan–Meier method. The targeted genes of prognostic miRNA were identified in miRanda, PicTar, or TargetScan, and their cell signaling pathways were analyzed by the Database for Annotation, Visualization and Integrated Discovery. Results: In The Cancer Genome Atlas and the Gene Expression Omnibus miRNA dataset, miR-92b and miR-99a were found with concordant directionality, up-regulated and down-regulated, respectively. In The Cancer Genome Atlas survival data, patients with the high level of miR-99b had obviously shorter overall survival time ( P=0.038). However, the level of miR-99a was not found to be significant. The 17 shared target genes of miR-92b were identified, such as DAB21IP, BCL21L11, SPHK2, PER2, and TSC1. The related pathways included positive regulation of transcription, positive regulation of cellular biosynthetic process, regulation of programmed cell death, etc. Conclusion: miR-92b was up-regulated in cholangiocarcinoma compared with normal controls. The high level of miR-92b was associated with adverse outcomes in cholangiocarcinoma patients, which might be partly explained by the targeted genes of miR-92b and their signaling pathways.

scholarly journals Pan-cancer driver copy number alterations identified by joint expression/CNA data analysis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Gaojianyong Wang ◽  
Dimitris Anastassiou
Keyword(s):  
Gene Expression ◽  
Copy Number ◽  
The Cancer Genome Atlas ◽  
Copy Number Alterations ◽  
Multiple Cancer ◽  
Cancer Driver ◽  
Large Gene ◽  
Cancer Genome Atlas ◽  
Cancer Types ◽  
Pan Cancer

Abstract Analysis of large gene expression datasets from biopsies of cancer patients can identify co-expression signatures representing particular biomolecular events in cancer. Some of these signatures involve genomically co-localized genes resulting from the presence of copy number alterations (CNAs), for which analysis of the expression of the underlying genes provides valuable information about their combined role as oncogenes or tumor suppressor genes. Here we focus on the discovery and interpretation of such signatures that are present in multiple cancer types due to driver amplifications and deletions in particular regions of the genome after doing a comprehensive analysis combining both gene expression and CNA data from The Cancer Genome Atlas.

Using machine learning method to identify MYLK as a novel marker to predict biochemical recurrence in prostate cancer

2021 ◽  
Vol 15 (1) ◽  
pp. 29-41
Author(s):  
Peng Qiao ◽  
Di Zhang ◽  
Song Zeng ◽  
Yicun Wang ◽  
Biao Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Biochemical Recurrence ◽  
Surgical Margin ◽  
Gene Expression Omnibus ◽  
Cancer Genome ◽  
The Cancer Genome Atlas ◽  
Support Vector ◽  
Cancer Genome Atlas ◽  
Genome Atlas

Aim: This study aims to identify novel marker to predict biochemical recurrence (BCR) in prostate cancer patients after radical prostatectomy with negative surgical margin. Materials & methods: The Cancer Genome Atlas database, Gene Expression Omnibus database and Cancer Cell Line Encyclopedia database were employed. The ensemble support vector machine-recursive feature elimination method was performed to select crucial gene for BCR. Results: We identified MYLK as a novel and independent biomarker for BCR in The Cancer Genome Atlas training cohort and confirmed in four independent Gene Expression Omnibus validation cohorts. Multi-omic analysis suggested that MYLK was a DNA methylation-driven gene. Additionally, MYLK had significant positive correlations with immune infiltrations. Conclusion: MYLK was identified and validated as a novel, robust and independent biomarker for BCR in prostate cancer.

scholarly journals Multi-omics characterization and validation of invasiveness-related molecular features across multiple cancer types

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Guoshu Bi ◽  
Jiaqi Liang ◽  
Yuansheng Zheng ◽  
Runmei Li ◽  
Mengnan Zhao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Predictive Biomarker ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Multiple Cancer ◽  
Tumor Invasiveness ◽  
Molecular Features ◽  
Cancer Types

Abstract Background Tumor invasiveness reflects many biological changes associated with tumorigenesis, progression, metastasis, and drug resistance. Therefore, we performed a systematic assessment of invasiveness-related molecular features across multiple human cancers. Materials and methods Multi-omics data, including gene expression, miRNA, DNA methylation, and somatic mutation, in approximately 10,000 patients across 30 cancer types from The Cancer Genome Atlas, Gene Expression Omnibus, PRECOG, and our institution were enrolled in this study. Results Based on a robust gene signature, we established an invasiveness score and found that the score was significantly associated with worse prognosis in almost all cancers. Then, we identified common invasiveness-associated dysregulated molecular features between high- and low-invasiveness score group across multiple cancers, as well as investigated their mutual interfering relationships thus determining whether the dysregulation of invasiveness-related genes was caused by abnormal promoter methylation or miRNA expression. We also analyzed the correlations between the drug sensitivity data from cancer cell lines and the expression level of 685 invasiveness-related genes differentially expressed in at least ten cancer types. An integrated analysis of the correlations among invasiveness-related genetic features and drug response were conducted in esophageal carcinoma patients to outline the complicated regulatory mechanism of tumor invasiveness status in multiple dimensions. Moreover, functional enrichment suggests the invasiveness score might serve as a predictive biomarker for cancer patients receiving immunotherapy. Conclusion Our pan-cancer study provides a comprehensive atlas of tumor invasiveness and may guide more precise therapeutic strategies for tumor patients.

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