Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution.

ABSTRACT: Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

SUBMITTER: Kaufmann TL

PROVIDER: S-EPMC9661799 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

MEDICC2: whole-genome doubling aware copy-number phylogenies for cancer evolution.

Kaufmann Tom L TL Petkovic Marina M Watkins Thomas B K TBK Colliver Emma C EC Laskina Sofya S Thapa Nisha N Minussi Darlan C DC Navin Nicholas N Swanton Charles C Van Loo Peter P Haase Kerstin K Tarabichi Maxime M Schwarz Roland F RF

Genome biology 20221114 1

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does n ...[more]

PMID: 36376909

Similar Datasets

Tolerance of whole-genome doubling propagates chromosomal instability and accelerates cancer genome evolution.

Project description:UnlabelledThe contribution of whole-genome doubling to chromosomal instability (CIN) and tumor evolution is unclear. We use long-term culture of isogenic tetraploid cells from a stable diploid colon cancer progenitor to investigate how a genome-doubling event affects genome stability over time. Rare cells that survive genome doubling demonstrate increased tolerance to chromosome aberrations. Tetraploid cells do not exhibit increased frequencies of structural or numerical CIN per chromosome. However, the tolerant phenotype in tetraploid cells, coupled with a doubling of chromosome aberrations per cell, allows chromosome abnormalities to evolve specifically in tetraploids, recapitulating chromosomal changes in genomically complex colorectal tumors. Finally, a genome-doubling event is independently predictive of poor relapse-free survival in early-stage disease in two independent cohorts in multivariate analyses [discovery data: hazard ratio (HR), 4.70, 95% confidence interval (CI), 1.04-21.37; validation data: HR, 1.59, 95% CI, 1.05-2.42]. These data highlight an important role for the tolerance of genome doubling in driving cancer genome evolution.SignificanceOur work sheds light on the importance of whole-genome–doubling events in colorectal cancer evolution. We show that tetraploid cells undergo rapid genomic changes and recapitulate the genetic alterations seen in chromosomally unstable tumors. Furthermore, we demonstrate that a genome-doubling event is prognostic of poor relapse-free survival in this disease type.

| S-EPMC4293454 | biostudies-literature

SCONCE: a method for profiling copy number alterations in cancer evolution using single-cell whole genome sequencing.

Project description:MotivationCopy number alterations (CNAs) are a significant driver in cancer growth and development, but remain poorly characterized on the single cell level. Although genome evolution in cancer cells is Markovian through evolutionary time, CNAs are not Markovian along the genome. However, existing methods call copy number profiles with Hidden Markov Models or change point detection algorithms based on changes in observed read depth, corrected by genome content and do not account for the stochastic evolutionary process.ResultsWe present a theoretical framework to use tumor evolutionary history to accurately call CNAs in a principled manner. To model the tumor evolutionary process and account for technical noise from low coverage single-cell whole genome sequencing data, we developed SCONCE, a method based on a Hidden Markov Model to analyze read depth data from tumor cells using matched normal cells as negative controls. Using a combination of public data sets and simulations, we show SCONCE accurately decodes copy number profiles, and provides a useful tool for understanding tumor evolution.Availabilityand implementationSCONCE is implemented in C++11 and is freely available from https://github.com/NielsenBerkeleyLab/sconce.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC8963318 | biostudies-literature

CopyDetective: Detection threshold-aware copy number variant calling in whole-exome sequencing data.

Project description:BackgroundCopy number variants (CNVs) are known to play an important role in the development and progression of several diseases. However, detection of CNVs with whole-exome sequencing (WES) experiments is challenging. Usually, additional experiments have to be performed.FindingsWe developed a novel algorithm for somatic CNV calling in matched WES data called "CopyDetective". Different from other approaches, CNV calling with CopyDetective consists of a 2-step procedure: first, quality analysis is performed, determining individual detection thresholds for every sample. Second, actual CNV calling on the basis of the previously determined thresholds is performed. Our algorithm evaluates the change in variant allele frequency of polymorphisms and reports the fraction of affected cells for every CNV. Analyzing 4 WES data sets (n = 100) we observed superior performance of CopyDetective compared with ExomeCNV, VarScan2, ControlFREEC, ExomeDepth, and CNV-seq.ConclusionsIndividual detection thresholds reveal that not every WES data set is equally apt for CNV calling. Initial quality analyses, determining individual detection thresholds-as realized by CopyDetective-can and should be performed prior to actual variant calling.

| S-EPMC7604644 | biostudies-literature

Absolute copy number fitting from shallow whole genome sequencing data

Project description: Not available

| S-BSST685 | biostudies-other

Interplay between whole-genome doubling and the accumulation of deleterious alterations in cancer evolution.

Project description:Whole-genome doubling (WGD) is a prevalent event in cancer, involving a doubling of the entire chromosome complement. However, despite its prevalence and prognostic relevance, the evolutionary selection pressures for WGD in cancer have not been investigated. Here, we combine evolutionary simulations with an analysis of cancer sequencing data to explore WGD during cancer evolution. Simulations suggest that WGD can be selected to mitigate the irreversible, ratchet-like, accumulation of deleterious somatic alterations, provided that they occur at a sufficiently high rate. Consistent with this, we observe an enrichment for WGD in tumor types with extensive loss of heterozygosity, including lung squamous cell carcinoma and triple-negative breast cancers, and we find evidence for negative selection against homozygous loss of essential genes before, but not after, WGD. Finally, we demonstrate that loss of heterozygosity and temporal dissection of mutations can be exploited to identify novel tumor suppressor genes and to obtain a deeper characterization of known cancer genes.

| S-EPMC7116784 | biostudies-literature

Cyclin E2 Promotes Whole Genome Doubling in Breast Cancer.

Project description:Genome doubling is an underlying cause of cancer cell aneuploidy and genomic instability, but few drivers have been identified for this process. Due to their physiological roles in the genome reduplication of normal cells, we hypothesised that the oncogenes cyclins E1 and E2 may be drivers of genome doubling in cancer. We show that both cyclin E1 (CCNE1) and cyclin E2 (CCNE2) mRNA are significantly associated with high genome ploidy in breast cancers. By live cell imaging and flow cytometry, we show that cyclin E2 overexpression promotes aberrant mitosis without causing mitotic slippage, and it increases ploidy with negative feedback on the replication licensing protein, Cdt1. We demonstrate that cyclin E2 localises with core preRC (pre-replication complex) proteins (MCM2, MCM7) on the chromatin of cancer cells. Low CCNE2 is associated with improved overall survival in breast cancers, and we demonstrate that low cyclin E2 protects from excess genome rereplication. This occurs regardless of p53 status, consistent with the association of high cyclin E2 with genome doubling in both p53 null/mutant and p53 wildtype cancers. In contrast, while cyclin E1 can localise to the preRC, its downregulation does not prevent rereplication, and overexpression promotes polyploidy via mitotic slippage. Thus, in breast cancer, cyclin E2 has a strong association with genome doubling, and likely contributes to highly proliferative and genomically unstable breast cancers.

| S-EPMC7463708 | biostudies-literature

Whole genome doubling in adenomyosis.

Project description: Not available

| S-EPMC11317496 | biostudies-literature

Allele-specific copy-number discovery from whole-genome and whole-exome sequencing.

Project description:Copy-number variants (CNVs) are a major form of genetic variation and a risk factor for various human diseases, so it is crucial to accurately detect and characterize them. It is conceivable that allele-specific reads from high-throughput sequencing data could be leveraged to both enhance CNV detection and produce allele-specific copy number (ASCN) calls. Although statistical methods have been developed to detect CNVs using whole-genome sequence (WGS) and/or whole-exome sequence (WES) data, information from allele-specific read counts has not yet been adequately exploited. In this paper, we develop an integrated method, called AS-GENSENG, which incorporates allele-specific read counts in CNV detection and estimates ASCN using either WGS or WES data. To evaluate the performance of AS-GENSENG, we conducted extensive simulations, generated empirical data using existing WGS and WES data sets and validated predicted CNVs using an independent methodology. We conclude that AS-GENSENG not only predicts accurate ASCN calls but also improves the accuracy of total copy number calls, owing to its unique ability to exploit information from both total and allele-specific read counts while accounting for various experimental biases in sequence data. Our novel, user-friendly and computationally efficient method and a complete analytic protocol is freely available at https://sourceforge.net/projects/asgenseng/.

| S-EPMC4538801 | biostudies-literature

Whole-genome copy number variation analysis in anophthalmia and microphthalmia.

Project description:Anophthalmia/microphthalmia (A/M) represent severe developmental ocular malformations. Currently, mutations in known genes explain less than 40% of A/M cases. We performed whole-genome copy number variation analysis in 60 patients affected with isolated or syndromic A/M. Pathogenic deletions of 3q26 (SOX2) were identified in four independent patients with syndromic microphthalmia. Other variants of interest included regions with a known role in human disease (likely pathogenic) as well as novel rearrangements (uncertain significance). A 2.2-Mb duplication of 3q29 in a patient with non-syndromic anophthalmia and an 877-kb duplication of 11p13 (PAX6) and a 1.4-Mb deletion of 17q11.2 (NF1) in two independent probands with syndromic microphthalmia and other ocular defects were identified; while ocular anomalies have been previously associated with 3q29 duplications, PAX6 duplications, and NF1 mutations in some cases, the ocular phenotypes observed here are more severe than previously reported. Three novel regions of possible interest included a 2q14.2 duplication which cosegregated with microphthalmia/microcornea and congenital cataracts in one family, and 2q21 and 15q26 duplications in two additional cases; each of these regions contains genes that are active during vertebrate ocular development. Overall, this study identified causative copy number mutations and regions with a possible role in ocular disease in 17% of A/M cases.

| S-EPMC3985344 | biostudies-literature

AMYCNE: Confident copy number assessment using whole genome sequencing data.

Project description:Copy number variations (CNVs) within the human genome have been linked to a diversity of inherited diseases and phenotypic traits. The currently used methodology to measure copy numbers has limited resolution and/or precision, especially for regions with more than 4 copies. Whole genome sequencing (WGS) offers an alternative data source to allow for the detection and characterization of the copy number across different genomic regions in a single experiment. A plethora of tools have been developed to utilize WGS data for CNV detection. None of these tools are designed specifically to accurately estimate copy numbers of complex regions in a small cohort or clinical setting. Herein, we present AMYCNE (automatic modeling functionality for copy number estimation), a CNV analysis tool using WGS data. AMYCNE is multifunctional and performs copy number estimation of complex regions, annotation of VCF files, and CNV detection on individual samples. The performance of AMYCNE was evaluated using AMY1A ddPCR measurements from 86 unrelated individuals. In addition, we validated the accuracy of AMYCNE copy number predictions on two additional genes (FCGR3A and FCGR3B) using datasets available through the 1000 genomes consortium. Finally, we simulated levels of mosaic loss and gain of chromosome X and used this dataset for benchmarking AMYCNE. The results show a high concordance between AMYCNE and ddPCR, validating the use of AMYCNE to measure tandem AMY1 repeats with high accuracy. This opens up new possibilities for the use of WGS for accurate copy number determination of other complex regions in the genome in small cohorts or single individuals.

| S-EPMC5868770 | 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