Classifying leukemia types with chromatin conformation data (ChIP-Seq)
Ontology highlight
ABSTRACT: Background: Although genetic or epigenetic alterations have shown to affect the three-dimensional organization of genomes, the utility of chromatin conformation in the classification of human disease has never been addressed. Results: Here, we explore whether chromatin conformation can be used to classify human leukemia. We map the conformation of the HOXA gene cluster in a panel of cell lines with 5C chromosome conformation capture technology, and use the data to train and test a support vector machine classifier named 3D-SP. We show that 3D-SP is able to accurately distinguish leukemias expressing MLL-fusion proteins from those expressing only wild-type MLL, and that it can also classify leukemia subtypes according to MLL fusion partner, based solely on 5C data. Conclusions: Our study provides the first proof-of-principle demonstration that chromatin conformation contains the information value necessary for classification of leukemia subtypes.
Project description:Background: Although genetic or epigenetic alterations have shown to affect the three-dimensional organization of genomes, the utility of chromatin conformation in the classification of human disease has never been addressed. Results: Here, we explore whether chromatin conformation can be used to classify human leukemia. We map the conformation of the HOXA gene cluster in a panel of cell lines with 5C chromosome conformation capture technology, and use the data to train and test a support vector machine classifier named 3D-SP. We show that 3D-SP is able to accurately distinguish leukemias expressing MLL-fusion proteins from those expressing only wild-type MLL, and that it can also classify leukemia subtypes according to MLL fusion partner, based solely on 5C data. Conclusions: Our study provides the first proof-of-principle demonstration that chromatin conformation contains the information value necessary for classification of leukemia subtypes. Analysis of 38 samples using 5C technology. All data normalized using a 'master' BAC consisting of 5C data from 6 samples.
Project description:Background: Although genetic or epigenetic alterations have shown to affect the three-dimensional organization of genomes, the utility of chromatin conformation in the classification of human disease has never been addressed. Results: Here, we explore whether chromatin conformation can be used to classify human leukemia. We map the conformation of the HOXA gene cluster in a panel of cell lines with 5C chromosome conformation capture technology, and use the data to train and test a support vector machine classifier named 3D-SP. We show that 3D-SP is able to accurately distinguish leukemias expressing MLL-fusion proteins from those expressing only wild-type MLL, and that it can also classify leukemia subtypes according to MLL fusion partner, based solely on 5C data. Conclusions: Our study provides the first proof-of-principle demonstration that chromatin conformation contains the information value necessary for classification of leukemia subtypes. Examination of CTCF and RAD21 binding sites in THP-1 cell.
Project description:Background: Although genetic or epigenetic alterations have shown to affect the three-dimensional organization of genomes, the utility of chromatin conformation in the classification of human disease has never been addressed. Results: Here, we explore whether chromatin conformation can be used to classify human leukemia. We map the conformation of the HOXA gene cluster in a panel of cell lines with 5C chromosome conformation capture technology, and use the data to train and test a support vector machine classifier named 3D-SP. We show that 3D-SP is able to accurately distinguish leukemias expressing MLL-fusion proteins from those expressing only wild-type MLL, and that it can also classify leukemia subtypes according to MLL fusion partner, based solely on 5C data. Conclusions: Our study provides the first proof-of-principle demonstration that chromatin conformation contains the information value necessary for classification of leukemia subtypes.
Project description:This study developed a triple-negative breast cancer (TNBC) surrogate subtype classification that represents TNBC subtypes based on the Vanderbilt subtype classification The web-based subtyping tool TNBCtype was used to classify the TNBC cohort into Vanderbilt subtypes
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized accurate molecular classification of leukemia. The goal of this study is to show the value of a sequential approach to classify the leukemia with various data types.
Project description:Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17)[PML-RARalpha], t(8;21)[AML1-ETO], inv(16) [CBFbeta-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation. All the gene expression arrays are available through http://www.stjuderesearch.org/site/data/AML1/ in the original study (PMID:15226186). To study the RAS gene expression in the human AML patients, a total of 104 AML cases with known KRAS and NRAS status (including 72 gene expression arrays in the original study and 32 additional arrays acquired later on), as well as 4 CD34+ normal bone marrow cases deposited in GEO GSE33315, were including in this depository. Gene expression profiling was performed on 104 single diagnosis tumor samples and 4 CD34+ normal bone marrow samples
Project description:In this study, we aim to identify sputum proteins that can classify individuals with lung cancer, and to build a classification model with potential clinical utility based on the panel of proteins that can identify lung cancer patients and even different lung cancer subtypes.
Project description:Mammalian genomes are folded in a hierarchy of compartments, topologically associating domains (TADs), subTADs and looping interactions. Currently, there is a great need to evaluate the link between chromatin topology and genome function across many biological conditions and genetic perturbations. Hi-C generates high quality, high resolution maps of looping interactions genome-wide, but is intractable for high-throughput screening of loops across conditions due to the requirement of an enormous number of reads (>6 Billion) per library. Here, we describe 5C-ID, an updated version of Chromosome-Conformation-Capture-Carbon-Copy (5C) with restriction digest and ligation performed in the nucleus (in situ ChromosomeConformation-Capture (3C)) and ligation-mediated amplification performed with a new double alternating design. 5C-ID reduces spatial noise and enables higher resolution 3D genome folding maps than canonical 5C, allowing for a marked improvement in sensitivity and specificity of loop detection. 5C-ID enables the creation of high-resolution, high-coverage maps of chromatin loops in up to a 30 Megabase subset of the genome at a fraction of the cost of Hi-C.
Project description:Cancer progression is associated with genetic and epigenetic aberrations that affect chromatin 3D organization in the nucleus. Changes in loop extrusion or phase separation alter the relationships between enhancer and promoter elements, defining novel gene expression programs that are selected to promote growth and survival. Here, we provide an integrative approach based on chromatin conformation, accessibility and transcription, further validated by CRISPR interference screenings in order to identify chromatin topologies relevant to different subtypes of T-cell leukemia, namely T-ALL and ETP-ALL. By focusing on highly interconnected elements, we characterized 3D hubs as headquarters of leukemia progression and identity, demonstrating that oncogenes and disease markers are regulated by multiple cis-regulatory regions.