共查询到20条相似文献,搜索用时 31 毫秒
1.
Ewa Przybytkowski Elizabeth Lenkiewicz Michael T Barrett Kathleen Klein Sheida Nabavi Celia MT Greenwood Mark Basik 《BMC genomics》2014,15(1)
Background
Chromosomal breakage followed by faulty DNA repair leads to gene amplifications and deletions in cancers. However, the mere assessment of the extent of genomic changes, amplifications and deletions may reduce the complexity of genomic data observed by array comparative genomic hybridization (array CGH). We present here a novel approach to array CGH data analysis, which focuses on putative breakpoints responsible for rearrangements within the genome.Results
We performed array comparative genomic hybridization in 29 primary tumors from high risk patients with breast cancer. The specimens were flow sorted according to ploidy to increase tumor cell purity prior to array CGH. We describe the number of chromosomal breaks as well as the patterns of breaks on individual chromosomes in each tumor. There were differences in chromosomal breakage patterns between the 3 clinical subtypes of breast cancers, although the highest density of breaks occurred at chromosome 17 in all subtypes, suggesting a particular proclivity of this chromosome for breaks. We also observed chromothripsis affecting various chromosomes in 41% of high risk breast cancers.Conclusions
Our results provide a new insight into the genomic complexity of breast cancer. Genomic instability dependent on chromosomal breakage events is not stochastic, targeting some chromosomes clearly more than others. We report a much higher percentage of chromothripsis than described previously in other cancers and this suggests that massive genomic rearrangements occurring in a single catastrophic event may shape many breast cancer genomes.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-579) contains supplementary material, which is available to authorized users. 相似文献2.
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Thomas Fleischer Arnoldo Frigessi Kevin C Johnson Hege Edvardsen Nizar Touleimat Jovana Klajic Margit LH Riis Vilde D Haakensen Fredrik W?rnberg Bj?rn Naume ?slaug Helland Anne-Lise B?rresen-Dale J?rg Tost Brock C Christensen Vessela N Kristensen 《Genome biology》2014,15(8)
Background
Ductal carcinoma in situ (DCIS) of the breast is a precursor of invasive breast carcinoma. DNA methylation alterations are thought to be an early event in progression of cancer, and may prove valuable as a tool in clinical decision making and for understanding neoplastic development.Results
We generate genome-wide DNA methylation profiles of 285 breast tissue samples representing progression of cancer, and validate methylation changes between normal and DCIS in an independent dataset of 15 normal and 40 DCIS samples. We also validate a prognostic signature on 583 breast cancer samples from The Cancer Genome Atlas. Our analysis reveals that DNA methylation profiles of DCIS are radically altered compared to normal breast tissue, involving more than 5,000 genes. Changes between DCIS and invasive breast carcinoma involve around 1,000 genes. In tumors, DNA methylation is associated with gene expression of almost 3,000 genes, including both negative and positive correlations. A prognostic signature based on methylation level of 18 CpGs is associated with survival of breast cancer patients with invasive tumors, as well as with survival of patients with DCIS and mixed lesions of DCIS and invasive breast carcinoma.Conclusions
This work demonstrates that changes in the epigenome occur early in the neoplastic progression, provides evidence for the possible utilization of DNA methylation-based markers of progression in the clinic, and highlights the importance of epigenetic changes in carcinogenesis.Electronic supplementary material
The online version of this article (doi:10.1186/s13059-014-0435-x) contains supplementary material, which is available to authorized users. 相似文献6.
Enerly E Steinfeld I Kleivi K Leivonen SK Aure MR Russnes HG Rønneberg JA Johnsen H Navon R Rødland E Mäkelä R Naume B Perälä M Kallioniemi O Kristensen VN Yakhini Z Børresen-Dale AL 《PloS one》2011,6(2):e16915
Introduction
Few studies have performed expression profiling of both miRNA and mRNA from the same primary breast carcinomas. In this study we present and analyze data derived from expression profiling of 799 miRNAs in 101 primary human breast tumors, along with genome-wide mRNA profiles and extensive clinical information.Methods
We investigate the relationship between these molecular components, in terms of their correlation with each other and with clinical characteristics. We use a systems biology approach to examine the correlative relationship between miRNA and mRNAs using statistical enrichment methods.Results
We identify statistical significant differential expression of miRNAs between molecular intrinsic subtypes, and between samples with different levels of proliferation. Specifically, we point to miRNAs significantly associated with TP53 and ER status. We also show that several cellular processes, such as proliferation, cell adhesion and immune response, are strongly associated with certain miRNAs. We validate the role of miRNAs in regulating proliferation using high-throughput lysate-microarrays on cell lines and point to potential drivers of this process.Conclusion
This study provides a comprehensive dataset as well as methods and system-level results that jointly form a basis for further work on understanding the role of miRNA in primary breast cancer. 相似文献7.
Julie Earl Daniel Rico Enrique Carrillo-de-Santa-Pau Benjamín Rodríguez-Santiago Marinela Méndez-Pertuz Herbert Auer Gonzalo Gómez Herbert Barton Grossman David G Pisano Wolfgang A Schulz Luis A Pérez-Jurado Alfredo Carrato Dan Theodorescu Stephen Chanock Alfonso Valencia Francisco X Real 《BMC genomics》2015,16(1)
Background
Urothelial bladder cancer is a highly heterogeneous disease. Cancer cell lines are useful tools for its study. This is a comprehensive genomic characterization of 40 urothelial bladder carcinoma (UBC) cell lines including information on origin, mutation status of genes implicated in bladder cancer (FGFR3, PIK3CA, TP53, and RAS), copy number alterations assessed using high density SNP arrays, uniparental disomy (UPD) events, and gene expression.Results
Based on gene mutation patterns and genomic changes we identify lines representative of the FGFR3-driven tumor pathway and of the TP53/RB tumor suppressor-driven pathway. High-density array copy number analysis identified significant focal gains (1q32, 5p13.1-12, 7q11, and 7q33) and losses (i.e. 6p22.1) in regions altered in tumors but not previously described as affected in bladder cell lines. We also identify new evidence for frequent regions of UPD, often coinciding with regions reported to be lost in tumors. Previously undescribed chromosome X losses found in UBC lines also point to potential tumor suppressor genes. Cell lines representative of the FGFR3-driven pathway showed a lower number of UPD events.Conclusions
Overall, there is a predominance of more aggressive tumor subtypes among the cell lines. We provide a cell line classification that establishes their relatedness to the major molecularly-defined bladder tumor subtypes. The compiled information should serve as a useful reference to the bladder cancer research community and should help to select cell lines appropriate for the functional analysis of bladder cancer genes, for example those being identified through massive parallel sequencing.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1450-3) contains supplementary material, which is available to authorized users. 相似文献8.
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Background
Identification of tumor heterogeneity and genomic similarities across different cancer types is essential to the design of effective stratified treatments and for the discovery of treatments that can be extended to different types of tumors. However, systematic investigations on comprehensive molecular profiles have not been fully explored to achieve this goal.Results
Here, we performed a network-based integrative pan-cancer genomic analysis on >3000 samples from 12 cancer types to uncover novel stratifications among tumors. Our study not only revealed recurrently reported cross-cancer similarities, but also identified novel ones. The macro-scale stratification demonstrates strong clinical relevance and reveals consistent risk tendency among cancer types. The micro-scale stratification shows essential pan-cancer heterogeneity with subgroup-specific gene network characteristics and biological functions.Conclusions
In summary, our comprehensive network-based pan-cancer stratification provides valuable information about inter- and intra- cancer stratification for patient clinical assessments and therapeutic strategies.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1687-x) contains supplementary material, which is available to authorized users. 相似文献10.
Introduction
Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis.Aim
The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets.Methods
Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA).Results
Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed.Conclusion
To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering ''hidden'' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. 相似文献11.
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Background
Metagenomics has a great potential to discover previously unattainable information about microbial communities. An important prerequisite for such discoveries is to accurately estimate the composition of microbial communities. Most of prevalent homology-based approaches utilize solely the results of an alignment tool such as BLAST, limiting their estimation accuracy to high ranks of the taxonomy tree.Results
We developed a new homology-based approach called Taxonomic Analysis by Elimination and Correction (TAEC), which utilizes the similarity in the genomic sequence in addition to the result of an alignment tool. The proposed method is comprehensively tested on various simulated benchmark datasets of diverse complexity of microbial structure. Compared with other available methods designed for estimating taxonomic composition at a relatively low taxonomic rank, TAEC demonstrates greater accuracy in quantification of genomes in a given microbial sample. We also applied TAEC on two real metagenomic datasets, oral cavity dataset and Crohn’s disease dataset. Our results, while agreeing with previous findings at higher ranks of the taxonomy tree, provide accurate estimation of taxonomic compositions at the species/strain level, narrowing down which species/strains need more attention in the study of oral cavity and the Crohn’s disease.Conclusions
By taking account of the similarity in the genomic sequence TAEC outperforms other available tools in estimating taxonomic composition at a very low rank, especially when closely related species/strains exist in a metagenomic sample.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-242) contains supplementary material, which is available to authorized users. 相似文献13.
Danny Challis Lilian Antunes Erik Garrison Eric Banks Uday S Evani Donna Muzny Ryan Poplin Richard A Gibbs Gabor Marth Fuli Yu 《BMC genomics》2015,16(1)
Background
Identifying insertion/deletion polymorphisms (INDELs) with high confidence has been intrinsically challenging in short-read sequencing data. Here we report our approach for improving INDEL calling accuracy by using a machine learning algorithm to combine call sets generated with three independent methods, and by leveraging the strengths of each individual pipeline. Utilizing this approach, we generated a consensus exome INDEL call set from a large dataset generated by the 1000 Genomes Project (1000G), maximizing both the sensitivity and the specificity of the calls.Results
This consensus exome INDEL call set features 7,210 INDELs, from 1,128 individuals across 13 populations included in the 1000 Genomes Phase 1 dataset, with a false discovery rate (FDR) of about 7.0%.Conclusions
In our study we further characterize the patterns and distributions of these exonic INDELs with respect to density, allele length, and site frequency spectrum, as well as the potential mutagenic mechanisms of coding INDELs in humans.Electronic supplementary material
The online version of this article (doi:10.1186/s12864-015-1333-7) contains supplementary material, which is available to authorized users. 相似文献14.
Background
Sequencing datasets consist of a finite number of reads which map to specific regions of a reference genome. Most effort in modeling these datasets focuses on the detection of univariate differentially expressed genes. However, for classification, we must consider multiple genes and their interactions.Results
Thus, we introduce a hierarchical multivariate Poisson model (MP) and the associated optimal Bayesian classifier (OBC) for classifying samples using sequencing data. Lacking closed-form solutions, we employ a Monte Carlo Markov Chain (MCMC) approach to perform classification. We demonstrate superior or equivalent classification performance compared to typical classifiers for two synthetic datasets and over a range of classification problem difficulties. We also introduce the Bayesian minimum mean squared error (MMSE) conditional error estimator and demonstrate its computation over the feature space. In addition, we demonstrate superior or leading class performance over an RNA-Seq dataset containing two lung cancer tumor types from The Cancer Genome Atlas (TCGA).Conclusions
Through model-based, optimal Bayesian classification, we demonstrate superior classification performance for both synthetic and real RNA-Seq datasets. A tutorial video and Python source code is available under an open source license at http://bit.ly/1gimnss.Electronic supplementary material
The online version of this article (doi:10.1186/s12859-014-0401-3) contains supplementary material, which is available to authorized users. 相似文献15.
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Filipe C Martins Ines de Santiago Anne Trinh Jian Xian Anne Guo Karen Sayal Mercedes Jimenez-Linan Suha Deen Kristy Driver Marie Mack Jennifer Aslop Paul D Pharoah Florian Markowetz James D Brenton 《Genome biology》2014,15(12)
Background
TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events.Results
Automatic estimates of stromal content combined with genomic analysis of TCGA HGSOC tumours show that stroma strongly biases estimates of PTEN expression. Tumour-specific PTEN expression was tested in two independent cohorts using tissue microarrays containing 521 cases of HGSOC. PTEN loss or downregulation occurred in 77% of the first cohort by immunofluorescence and 52% of the validation group by immunohistochemistry, and is associated with worse survival in a multivariate Cox-regression model adjusted for study site, age, stage and grade. Reanalysis of TCGA data shows that hemizygous loss of PTEN is common (36%) and expression of PTEN and expression of androgen receptor are positively associated. Low androgen receptor expression was associated with reduced survival in data from TCGA and immunohistochemical analysis of the first cohort.Conclusion
PTEN loss is a common event in HGSOC and defines a subgroup with significantly worse prognosis, suggesting the rational use of drugs to target PI3K and androgen receptor pathways for HGSOC. This work shows that integrative approaches combining tissue phenotypes from images with genomic analysis can resolve confounding effects of tissue heterogeneity and should be used to identify new drivers in other cancers.Electronic supplementary material
The online version of this article (doi:10.1186/s13059-014-0526-8) contains supplementary material, which is available to authorized users. 相似文献17.
Background
Breast cancer is classified into three subtypes by the expression of biomarker receptors such as hormone receptors and human epidermal growth factor receptor 2. Triple-negative breast cancer (TNBC) expresses none of these receptors and has an aggressive phenotype with a poor prognosis, which is insensitive to the drugs that target the hormone receptors and human epidermal growth factor receptor 2. It is, thus, required to develop an effective therapeutic reagent to treat TNBC.Results
The study using a panel of 19 breast cancer cell lines revealed that midostaurin, a multi-target protein kinase inhibitor, suppresses preferentially the growth of TNBC cells comparing with non-TNBC cells. Clustering analysis of the drug activity data for the panel of cancer cell lines predicted that midostaurin shares the target with Aurora kinase inhibitors. Following studies indicated that midostaurin attenuates the phosphorylation reaction mediated by Aurora kinase in the cells and directly inhibits this protein kinase in vitro, and that this reagent induces apoptosis accompanying accumulation of 4N and 8N DNA cells in TNBC cells.Conclusion
Midostaurin suppresses the proliferation of TNBC cells among the breast cancer cell lines presumably through the inhibition of the Aurora kinase family. The precise study of midostaurin on cell growth will contribute to the development of the drug for the treatment of TNBC.Electronic supplementary material
The online version of this article (doi:10.1186/s12929-015-0150-2) contains supplementary material, which is available to authorized users. 相似文献18.
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Background
Meta-analysis has become a popular approach for high-throughput genomic data analysis because it often can significantly increase power to detect biological signals or patterns in datasets. However, when using public-available databases for meta-analysis, duplication of samples is an often encountered problem, especially for gene expression data. Not removing duplicates could lead false positive finding, misleading clustering pattern or model over-fitting issue, etc in the subsequent data analysis.Results
We developed a Bioconductor package Dupchecker that efficiently identifies duplicated samples by generating MD5 fingerprints for raw data. A real data example was demonstrated to show the usage and output of the package.Conclusions
Researchers may not pay enough attention to checking and removing duplicated samples, and then data contamination could make the results or conclusions from meta-analysis questionable. We suggest applying DupChecker to examine all gene expression data sets before any data analysis step.Electronic supplementary material
The online version of this article (doi:10.1186/1471-2105-15-323) contains supplementary material, which is available to authorized users. 相似文献20.
Jesús Espinal-Enríquez Said Mu?oz-Montero Ivan Imaz-Rosshandler Aldo Huerta-Verde Carmen Mejía Enrique Hernández-Lemus 《BMC genomics》2015,16(1)