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

2020 ◽  
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

ABSTRACTDysregulation 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 10,000 gene expression profiling RNA-seq datasets from TCGA with over 7,000 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 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.

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 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 Novel Epigenetic Eight-Gene Signature Predictive of Poor Prognosis and MSI-Like Phenotype in Human Metastatic Colorectal Carcinomas

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 158
Author(s):  
Valentina Condelli ◽  
Giovanni Calice ◽  
Alessandra Cassano ◽  
Michele Basso ◽  
Maria Grazia Rodriquenz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Poor Prognosis ◽  
Cpg Island ◽  
Colon Adenocarcinoma ◽  
Gene Signature ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Cpg Island Methylator Phenotype ◽  
Prognostic Information ◽  
Global Methylation

Epigenetics is involved in tumor progression and drug resistance in human colorectal carcinoma (CRC). This study addressed the hypothesis that the DNA methylation profiling may predict the clinical behavior of metastatic CRCs (mCRCs). The global methylation profile of two human mCRC subgroups with significantly different outcome was analyzed and compared with gene expression and methylation data from The Cancer Genome Atlas COlon ADenocarcinoma (TCGA COAD) and the NCBI GENE expression Omnibus repository (GEO) GSE48684 mCRCs datasets to identify a prognostic signature of functionally methylated genes. A novel epigenetic signature of eight hypermethylated genes was characterized that was able to identify mCRCs with poor prognosis, which had a CpG-island methylator phenotype (CIMP)-high and microsatellite instability (MSI)-like phenotype. Interestingly, methylation events were enriched in genes located on the q-arm of chromosomes 13 and 20, two chromosomal regions with gain/loss alterations associated with adenoma-to-carcinoma progression. Finally, the expression of the eight-genes signature and MSI-enriching genes was confirmed in oxaliplatin- and irinotecan-resistant CRC cell lines. These data reveal that the hypermethylation of specific genes may provide prognostic information that is able to identify a subgroup of mCRCs with poor prognosis.

scholarly journals Functions and clinical significance of KLRG1 in the development of lung adenocarcinoma and immunotherapy

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xiaodong Yang ◽  
Yuexin Zheng ◽  
Zhihai Han ◽  
Xiliang Zhang
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Killer Cell ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Normal Lung ◽  
Using Data ◽  
Low Expression

Abstract Background As a marker of differentiation, Killer cell lectin like receptor G1 (KLRG1) plays an inhibitory role in human NK cells and T cells. However, its clinical role remains inexplicit. This work intended to investigate the predictive ability of KLRG1 on the efficacy of immune-checkpoint inhibitor in the treatment of lung adenocarcinoma (LUAD), as well as contribute to the possible molecular mechanisms of KLRG1 on LUAD development. Methods Using data from the Gene Expression Omnibus, the Cancer Genome Atlas and the Genotype-Tissue Expression, we compared the expression of KLRG1 and its related genes Bruton tyrosine kinase (BTK), C-C motif chemokine receptor 2 (CCR2), Scm polycomb group protein like 4 (SCML4) in LUAD and normal lung tissues. We also established stable LUAD cell lines with KLRG1 gene knockdown and investigated the effect of KLRG1 knockdown on tumor cell proliferation. We further studied the prognostic value of the four factors in terms of overall survival (OS) in LUAD. Using data from the Gene Expression Omnibus, we further investigated the expression of KLRG1 in the patients with different responses after immunotherapy. Results The expression of KLRG1, BTK, CCR2 and SCML4 was significantly downregulated in LUAD tissues compared to normal controls. Knockdown of KLRG1 promoted the proliferation of A549 and H1299 tumor cells. And low expression of these four factors was associated with unfavorable overall survival in patients with LUAD. Furthermore, low expression of KLRG1 also correlated with poor responses to immunotherapy in LUAD patients. Conclusion Based on these findings, we inferred that KLRG1 had significant correlation with immunotherapy response. Meanwhile, KLRG1, BTK, CCR2 and SCML4 might serve as valuable prognostic biomarkers in LUAD.

scholarly journals Development and validation of a 13-m6a related lncRNA prognostic signature for lung adenocarcinoma

2021 ◽  
Author(s):  
Pingfan Wu ◽  
Xiaowen Zhao ◽  
Ling Xue ◽  
Xiaojing Yang ◽  
Yuxiang Shi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Adenocarcinoma ◽  
Treatment Strategies ◽  
Risk Groups ◽  
Gene Expression Omnibus ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Prognostic Signature ◽  
P53 Signaling ◽  
Selection Operator

Abstract Considerable evidence suggests that N6-methyladenosine (m6A) is involved in the regulation of long non-coding RNA (lncRNA), whichparticipates in the occurrence, development and prognosis of tumorscancerBut the relationship between m6A regulators-related lncRNA (mRlncRNA) and lung adenocarcinoma (LUAD) remains unclear. This study aims to determine a feature based on mRlncRNA for prognostic evaluation of LUAD patients. By integrating the gene expression data of LUAD and normal samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, the m6A gene and mRlncRNA with imbalanced expression were screened out. Then we used the least absolute shrinkage and selection operator (LASSO) to obtain the 13-lncRNA prognostic signature in the TCGA training cohort. Patients were divided into two risk groups based on the risk score of lncRNAs characteristics, and their overall survival (OS) was significantly different. The predictive power of this signature was verified in TCGA testing cohort and entire TCGA cohort. These landmark lncRNAs were involved in several biologiocal processes and pathways related to cell cycle, DNA replication, P53 signaling pathway and mismatch repair. Besides, the high-risk group was low-response to cisplatin, while high-response to mitomycin, docetaxel and immunotherapy. In conclusion, we identified a 13-mRlncRNA model associated with prognosis and treatment sensitivity in LUAD, which may provide clues about the influence of m6A on lncRNA in LUAD and promote the further improvement of LUAD individualized treatment strategies.

scholarly journals Data mining of immune-related prognostic genes in metastatic melanoma microenvironment

2020 ◽  
Vol 40 (11) ◽  
Author(s):  
Wei Han ◽  
Biao Huang ◽  
Xiao-Yu Zhao ◽  
Guo-Liang Shen
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Metastatic Melanoma ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
Protein Protein Interaction ◽  
Subtype Identification ◽  
Cancer Genome Atlas ◽  
Immune Related Genes

Abstract Skin cutaneous melanoma (SKCM) is one of the most deadly malignancies. Although immunotherapies showed the potential to improve the prognosis for metastatic melanoma patients, only a small group of patients can benefit from it. Therefore, it is urgent to investigate the tumor microenvironment in melanoma as well as to identify efficient biomarkers in the diagnosis and treatments of SKCM patients. A comprehensive analysis was performed based on metastatic melanoma samples from the Cancer Genome Atlas (TCGA) database and ESTIMATE algorithm, including gene expression, immune and stromal scores, prognostic immune-related genes, infiltrating immune cells analysis and immune subtype identification. Then, the differentially expressed genes (DEGs) were obtained based on the immune and stromal scores, and a list of prognostic immune-related genes was identified. Functional analysis and the protein–protein interaction network revealed that these genes enriched in multiple immune-related biological processes. Furthermore, prognostic genes were verified in the Gene Expression Omnibus (GEO) databases and used to predict immune infiltrating cells component. Our study revealed seven immune subtypes with different risk values and identified T cells as the most abundant cells in the immune microenvironment and closely associated with prognostic outcomes. In conclusion, the present study thoroughly analyzed the tumor microenvironment and identified prognostic immune-related biomarkers for metastatic melanoma.

scholarly journals TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment

2020 ◽  
Vol 49 (D1) ◽  
pp. D1420-D1430
Author(s):  
Dongqing Sun ◽  
Jin Wang ◽  
Ya Han ◽  
Xin Dong ◽  
Jun Ge ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Large Scale ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Multiple Cancer ◽  
Web Resource ◽  
Cancer Types

Abstract Cancer immunotherapy targeting co-inhibitory pathways by checkpoint blockade shows remarkable efficacy in a variety of cancer types. However, only a minority of patients respond to treatment due to the stochastic heterogeneity of tumor microenvironment (TME). Recent advances in single-cell RNA-seq technologies enabled comprehensive characterization of the immune system heterogeneity in tumors but posed computational challenges on integrating and utilizing the massive published datasets to inform immunotherapy. Here, we present Tumor Immune Single Cell Hub (TISCH, http://tisch.comp-genomics.org), a large-scale curated database that integrates single-cell transcriptomic profiles of nearly 2 million cells from 76 high-quality tumor datasets across 27 cancer types. All the data were uniformly processed with a standardized workflow, including quality control, batch effect removal, clustering, cell-type annotation, malignant cell classification, differential expression analysis and functional enrichment analysis. TISCH provides interactive gene expression visualization across multiple datasets at the single-cell level or cluster level, allowing systematic comparison between different cell-types, patients, tissue origins, treatment and response groups, and even different cancer-types. In summary, TISCH provides a user-friendly interface for systematically visualizing, searching and downloading gene expression atlas in the TME from multiple cancer types, enabling fast, flexible and comprehensive exploration of the TME.

scholarly journals Integrative In Silico and In Vitro Transcriptomics Analysis Revealed Gene Expression Changes and Oncogenic Features of Normal Cholangiocytes after Chronic Alcohol Exposure

2019 ◽  
Vol 20 (23) ◽  
pp. 5987
Author(s):  
Suthipong Chujan ◽  
Tawit Suriyo ◽  
Jutamaad Satayavivad
Keyword(s):  
Gene Expression ◽  
Rna Polymerase Ii ◽  
Molecular Mechanisms ◽  
Function Analysis ◽  
Alcohol Exposure ◽  
Gene Expression Omnibus ◽  
Regulation Of Transcription ◽  
Chronic Alcohol ◽  
Chronic Alcohol Exposure

Cholangiocarcinoma (CCA) is a malignant tumor originating from cholangiocyte. Prolonged alcohol consumption has been suggested as a possible risk factor for CCA, but there is no information about alcohol’s mechanisms in cholangiocyte. This study was designed to investigate global transcriptional alterations through RNA-sequencing by using chronic alcohol exposure (20 mM for 2 months) in normal human cholangiocyte MMNK-1 cells. To observe the association of alcohol induced CCA pathogenesis, we combined differentially expressed genes (DEGs) with computational bioinformatics of CCA by using publicly gene expression omnibus (GEO) datasets. For biological function analysis, Gene ontology (GO) analysis showed biological process and molecular function related to regulation of transcription from RNA polymerase II promoter, while cellular component linked to the nucleoplasm. KEGG pathway presented pathways in cancer that were significantly enriched. From KEGG result, we further examined the oncogenic features resulting in chronic alcohol exposure, enhanced proliferation, and migration through CCND-1 and MMP-2 up-regulation, respectively. Finally, combined DEGs were validated in clinical data including TCGA and immunohistochemistry from HPA database, demonstrating that FOS up-regulation was related to CCA pathogenesis. This study is the first providing more information and molecular mechanisms about global transcriptome alterations and oncogenic enhancement of chronic alcohol exposure in normal cholangiocytes.

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