Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Predicting master transcription factors from pan-cancer expression data.

ABSTRACT: [Figure: see text].

SUBMITTER: Reddy J

PROVIDER: S-EPMC8612691 | biostudies-literature | 2021 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Predicting master transcription factors from pan-cancer expression data.

Reddy Jessica J Fonseca Marcos A S MAS Corona Rosario I RI Nameki Robbin R Segato Dezem Felipe F Klein Isaac A IA Chang Heidi H Chaves-Moreira Daniele D Afeyan Lena K LK Malta Tathiane M TM Lin Xianzhi X Abbasi Forough F Font-Tello Alba A Sabedot Thais T Cejas Paloma P Rodríguez-Malavé Norma N Seo Ji-Heui JH Lin De-Chen DC Matulonis Ursula U Karlan Beth Y BY Gayther Simon A SA Pasaniuc Bogdan B Gusev Alexander A Noushmehr Houtan H Long Henry H Freedman Matthew L ML Drapkin Ronny R Young Richard A RA Abraham Brian J BJ Lawrenson Kate K

Science advances 20211124 48

Critical developmental “master transcription factors” (MTFs) can be subverted during tumorigenesis to control oncogenic transcriptional programs. Current approaches to identifying MTFs rely on ChIP-seq data, which is unavailable for many cancers. We developed the CaCTS (Cancer Core Transcription factor Specificity) algorithm to prioritize candidate MTFs using pan-cancer RNA sequencing data. CaCTS identified candidate MTFs across 34 tumor types and 140 subtypes including predictions for cancer ty ...[more]

PMID: 34818047

Similar Datasets

Predicting Master Transcription Factors from Pan-Cancer Expression Data

Project description:Critical developmental “master transcription factors” (MTFs) can be subverted during tumorigenesis to control expression of oncogenic transcriptional programs. Current approaches to identify MTFs rely on chromatin immunoprecipitation-sequencing data, which is currently unavailable for many cancer types. We developed the CaCTS (Cancer Core Transcription factor Specificity) algorithm to prioritize candidate MTFs using pan-cancer RNA-sequencing data. CaCTS identified candidate MTFs across 34 tumor types and 140 subtypes, including known MTFs. We also made novel predictions, including for cancer types/subtypes for which MTFs are unknown. This included PAX8, SOX17, and MECOM as candidate MTFs in ovarian cancer (OV). In OV cells, these factors are required for viability, lie proximal to super-enhancers, co-occupy regulatory elements globally and co-bind at critical gene loci encoding OV biomarkers. Identification of tumor MTFs, especially for tumor types with limited understanding of transcriptional drivers, paves the way to therapeutic targeting of MTFs in a broad spectrum of cancers.

2021-04-19 | GSE150443 | GEO

Predicting master transcription factors from pan-cancer expression data

2021-09-15 | GSE152885 | GEO

Predicting Master Transcription Factors from Pan-Cancer Expression Data

Project description:Predicting Master Transcription Factors from Pan-Cancer Expression Data

| PRJNA632047 | ENA

Predicting master transcription factors from pan-cancer expression data

Project description:Predicting master transcription factors from pan-cancer expression data

| PRJNA640799 | ENA

MTFAP: a comprehensive platform for predicting and analyzing master transcription factors

Project description: Not available

| S-EPMC11685651 | biostudies-literature

Pan-cancer predictions of transcription factors mediating aberrant DNA methylation.

Project description:BackgroundAberrant DNA methylation is a hallmark of cancer cells. However, the mechanisms underlying changes in DNA methylation remain elusive. Transcription factors initially thought to be repressed from binding by DNA methylation, have recently emerged as being able to shape DNA methylation patterns.ResultsHere, we integrated the massive amount of data available from The Cancer Genome Atlas to predict transcription factors driving aberrant DNA methylation in 13 cancer types. We identified differentially methylated regions between cancer and matching healthy samples, searched for transcription factor motifs enriched in those regions and selected transcription factors with corresponding changes in gene expression. We predict transcription factors known to be involved in cancer as well as novel candidates to drive hypo-methylated regions such as FOXA1 and GATA3 in breast cancer, FOXA1 and TWIST1 in prostate cancer and NFE2L2 in lung cancer. We also predict transcription factors that lead to hyper-methylated regions upon transcription factor loss such as EGR1 in several cancer types. Finally, we validate that FOXA1 and GATA3 mediate hypo-methylated regions in breast cancer cells.ConclusionOur work highlights the importance of some transcription factors as upstream regulators shaping DNA methylation patterns in cancer.

| S-EPMC8944071 | biostudies-literature

Functional Hierarchy and Cooperation of EMT Master Transcription Factors in Breast Cancer Metastasis.

Project description:Several master transcription factors (TF) can activate the epithelial-to-mesenchymal transition (EMT). However, their individual and combinatorial contributions to EMT in breast cancer are not defined. We show that overexpression of EMT-TFs individually in epithelial cells upregulated endogenous SNAI2, ZEB1/2, TCF4, and TWIST1/2 as a result of positive feedback mediated in part by suppression of their negative regulator miRNAs miR200s/203/205. We identified TCF4 as a potential new target of miR200s. Expression of ZEB1/2 strongly correlated with the mesenchymal phenotype in breast cancer cells, with the CD24-/CD44+ stemness profile, and with lower expression of core epithelial genes in human breast tumors. Knockdown of EMT-TFs identified the key role of ZEB1 and its functional cooperation with other EMT-TFs in the maintenance of the mesenchymal state. Inducible ZEB1+2 knockdown in xenograft models inhibited pulmonary metastasis, emphasizing their critical role in dissemination from primary site and in extravasation. However, ZEB1+2 depletion one-week after intravenous injection did not inhibit lung colonization, suggesting that ZEB1/2 and EMT are not essential for macrometastatic outgrowth. These results provide strong evidence that EMT is orchestrated by coordinated expression of several EMT-TFs and establish ZEB1 as a key master regulator of EMT and metastasis in breast cancer. IMPLICATIONS: The EMT program is orchestrated by coordinated expression of multiple EMT transcription factors, whereas ZEB1 integrates the EMT master regulatory network and plays the major role in promoting EMT and metastasis.

| S-EPMC8137545 | biostudies-literature

Pan-cancer predictions of transcription factors mediating aberrant DNA methylation

Project description:Aberrant DNA methylation is a hallmark of cancer cells. However, the mechanisms underlying changes in DNA methylation remain elusive. Transcription factors initially thought to be repressed from binding by DNA methylation, have recently emerged as being able to shape DNA methylation patterns. Here, we integrated the massive amount of data available from The Cancer Genome Atlas to predict transcription factors drivingAQ1 aberrant DNA methylation in 13 cancer types. We identified differentially methylated regions between cancer and matching healthy samples, searched for transcription factor motifs enriched in those regions and selected transcription factors with corresponding changes in gene expression. We predict transcription factors known to be involved in cancer as well as novel candidates to drive hypo-methylated regions such as FOXA1 and GATA3 in breast cancer, FOXA1 and TWIST1 in prostate cancer and NFE2L2 in lung cancer. We also predict transcription factors that lead to hyper-methylated regions upon transcription factor loss such as EGR1 in several cancer types. Finally, we validate that FOXA1 and GATA3 mediate hypo-methylated regions in breast cancer cells. Our work highlights the importance of some transcription factors as upstream regulators shaping DNA methylation patterns in cancer.

2022-03-16 | GSE167870 | GEO

Master Transcription Regulators and Transcription Factors Regulate Immune-Associated Differences Between Patients of African and European Ancestry With Colorectal Cancer.

Project description:Background and aimsIndividuals of African (AFR) ancestry have a higher incidence of colorectal cancer (CRC) than those of European (EUR) ancestry and exhibit significant health disparities. Previous studies have noted differences in the tumor microenvironment between AFR and EUR patients with CRC. However, the molecular regulatory processes that underpin these immune differences remain largely unknown.MethodsMultiomics analysis was carried out for 55 AFR and 456 EUR patients with microsatellite-stable CRC using The Cancer Genome Atlas. We evaluated the tumor microenvironment by using gene expression and methylation data, transcription factor, and master transcriptional regulator analysis to identify the cell signaling pathways mediating the observed phenotypic differences.ResultsWe demonstrate that downregulated genes in AFR patients with CRC showed enrichment for canonical pathways, including chemokine signaling. Moreover, evaluation of the tumor microenvironment showed that cytotoxic lymphocytes and neutrophil cell populations are significantly decreased in AFR compared with EUR patients, suggesting AFR patients have an attenuated immune response. We further demonstrate that molecules called "master transcriptional regulators" (MTRs) play a critical role in regulating the expression of genes impacting key immune processes through an intricate signal transduction network mediated by disease-associated transcription factors (TFs). Furthermore, a core set of these MTRs and TFs showed a positive correlation with levels of cytotoxic lymphocytes and neutrophils across both AFR and EUR patients with CRC, thus suggesting their role in driving the immune infiltrate differences between the two ancestral groups.ConclusionOur study provides an insight into the intricate regulatory landscape of MTRs and TFs that orchestrate the differences in the tumor microenvironment between patients with CRC of AFR and EUR ancestry.

| S-EPMC9151447 | biostudies-literature

Master transcription factors determine cell-type-specific responses to TGF-? signaling.

Project description:Transforming growth factor beta (TGF-?) signaling, mediated through the transcription factors Smad2 and Smad3 (Smad2/3), directs different responses in different cell types. Here we report that Smad3 co-occupies the genome with cell-type-specific master transcription factors. Thus, Smad3 occupies the genome with Oct4 in embryonic stem cells (ESCs), Myod1 in myotubes, and PU.1 in pro-B cells. We find that these master transcription factors are required for Smad3 occupancy and that TGF-? signaling largely affects the genes bound by the master transcription factors. Furthermore, we show that induction of Myod1 in nonmuscle cells is sufficient to redirect Smad3 to Myod1 sites. We conclude that cell-type-specific master transcription factors determine the genes bound by Smad2/3 and are thus responsible for orchestrating the cell-type-specific effects of TGF-? signaling.

| S-EPMC3212730 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data