scholarly journals Bayesian Disease Classification Using Copy Number Data

2014 ◽  
Vol 13s2 ◽  
pp. CIN.S13785 ◽  
Author(s):  
Subharup Guha ◽  
Yuan Ji ◽  
Veerabhadran Baladandayuthapani
Keyword(s):  
Copy Number ◽  
Copy Number Variations ◽  
Disease Classification ◽  
Classification Model ◽  
Basic Knowledge ◽  
Comparative Genomic ◽  
Breast Cancer Dataset ◽  
Disease Category ◽  
Cancer Dataset ◽  
Disease States

DNA copy number variations (CNVs) have been shown to be associated with cancer development and progression. The detection of these CNVs has the potential to impact the basic knowledge and treatment of many types of cancers, and can play a role in the discovery and development of molecular-based personalized cancer therapies. One of the most common types of high-resolution chromosomal microarrays is array-based comparative genomic hybridization (aCGH) methods that assay DNA CNVs across the whole genomic landscape in a single experiment. In this article we propose methods to use aCGH profiles to predict disease states. We employ a Bayesian classification model and treat disease states as outcome, and aCGH profiles as covariates in order to identify significant regions of the genome associated with disease subclasses. We propose a principled two-stage method where we first make inferences on the underlying copy number states associated with the aCGH emissions based on hidden Markov model (HMM) formulations to account for serial dependencies in neighboring probes. Subsequently, we infer associations with disease outcomes, conditional on the copy number states, using Bayesian linear variable selection procedures. The selected probes and their effects are parameters that are useful for predicting the disease categories of any additional individuals on the basis of their aCGH profiles. Using simulated datasets, we investigate the method's accuracy in detecting disease category. Our methodology is motivated by and applied to a breast cancer dataset consisting of aCGH profiles assayed on patients from multiple disease subtypes.

scholarly journals Supervised classification of combined copy number and gene expression data

2007 ◽  
Vol 4 (3) ◽  
pp. 168-185 ◽  
Author(s):  
S. Riccadonna ◽  
G. Jurman ◽  
S. Merler ◽  
S. Paoli ◽  
A. Quattrone ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Copy Number ◽  
Learning System ◽  
Differentially Expressed ◽  
Comparative Genomic ◽  
Breast Cancer Dataset ◽  
Cancer Dataset ◽  
Specific Subset ◽  
Different Response

Summary In this paper we apply a predictive profiling method to genome copy number aberrations (CNA) in combination with gene expression and clinical data to identify molecular patterns of cancer pathophysiology. Predictive models and optimal feature lists for the platforms are developed by a complete validation SVM-based machine learning system. Ranked list of genome CNA sites (assessed by comparative genomic hybridization arrays – aCGH) and of differentially expressed genes (assessed by microarray profiling with Affy HG-U133A chips) are computed and combined on a breast cancer dataset for the discrimination of Luminal/ ER+ (Lum/ER+) and Basal-like/ER- classes. Different encodings are developed and applied to the CNA data, and predictive variable selection is discussed. We analyze the combination of profiling information between the platforms, also considering the pathophysiological data. A specific subset of patients is identified that has a different response to classification by chromosomal gains and losses and by differentially expressed genes, corroborating the idea that genomic CNA can represent an independent source for tumor classification.

scholarly journals Multiplex ligation-dependent probe amplification – a short overview

2020 ◽  
Vol 28 (2) ◽  
pp. 123-131
Author(s):  
Valeriu Moldovan ◽  
Elena Moldovan
Keyword(s):  
Copy Number ◽  
Genetic Disorders ◽  
Cost Effective ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Gene Deletions ◽  
Conventional Cytogenetic Analysis ◽  
Main Technique ◽  
Cost Effective Technique ◽  
Dependent Probe

AbstractMultiplex Ligation-dependent Probe Amplification is a technique proposed for the detection of deletions or duplications that may lead to copy number variations in genomic DNA, mainly due to its higher resolution, and shorter overall diagnosis time, when compared with techniques traditionally used, namely karyotyping, fluorescence in situ hybridization, and array comparative genomic hybridization. Multiplex Ligation-dependent Probe Amplification is a fast (about 2 days), useful and cost-effective technique, being suitable for the diagnosis of hereditary conditions caused by complete or partial gene deletions or duplications, as these conditions are either more difficult or impossible to be diagnosed by other techniques, such as PCR, Real-Time PCR, or sequencing (Sanger or Next Generation). Due to its numerous advantages over conventional cytogenetic analysis techniques, Multiplex Ligation-dependent Probe Amplification could be used in the near future as the main technique for the molecular investigation of genetic conditions caused by copy number variations, in both rare and complex genetic disorders.

Overall Genomic Pattern Is a Predictor of Outcome in Neuroblastoma

2009 ◽  
Vol 27 (7) ◽  
pp. 1026-1033 ◽  
Author(s):  
Isabelle Janoueix-Lerosey ◽  
Gudrun Schleiermacher ◽  
Evi Michels ◽  
Véronique Mosseri ◽  
Agnès Ribeiro ◽  
...  
Keyword(s):  
Copy Number ◽  
Prognostic Significance ◽  
Genetic Alterations ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Mycn Amplification ◽  
Clinical Markers ◽  
Prognostic Information ◽  
Stage 4 ◽  
Risk Of Relapse

Purpose For a comprehensive overview of the genetic alterations of neuroblastoma, their association and clinical significance, we conducted a whole-genome DNA copy number analysis. Patients and Methods A series of 493 neuroblastoma (NB) samples was investigated by array-based comparative genomic hybridization in two consecutive steps (224, then 269 patients). Results Genomic analysis identified several types of profiles. Tumors presenting exclusively whole-chromosome copy number variations were associated with excellent survival. No disease-related death was observed in this group. In contrast, tumors with any type of segmental chromosome alterations characterized patients with a high risk of relapse. Patients with both numerical and segmental abnormalities clearly shared the higher risk of relapse of segmental-only patients. In a multivariate analysis, taking into account the genomic profile, but also previously described individual genetic and clinical markers with prognostic significance, the presence of segmental alterations with (HR, 7.3; 95% CI, 3.7 to 14.5; P < .001) or without MYCN amplification (HR, 4.5; 95% CI, 2.4 to 8.4; P < .001) was the strongest predictor of relapse; the other significant variables were age older than 18 months (HR, 1.8; 95% CI, 1.2 to 2.8; P = .004) and stage 4 (HR, 1.8; 95% CI, 1.2 to 2.7; P = .005). Finally, within tumors showing segmental alterations, stage 4, age, MYCN amplification, 1p and 11q deletions, and 1q gain were independent predictors of decreased overall survival. Conclusion The analysis of the overall genomic pattern, which probably unravels particular genomic instability mechanisms rather than the analysis of individual markers, is essential to predict relapse in NB patients. It adds critical prognostic information to conventional markers and should be included in future treatment stratification.

scholarly journals Motor Chip: A Comparative Genomic Hybridization Microarray for Copy-Number Mutations in 245 Neuromuscular Disorders

2011 ◽  
Vol 57 (11) ◽  
pp. 1584-1596 ◽  
Author(s):  
Giulio Piluso ◽  
Manuela Dionisi ◽  
Francesca Del Vecchio Blanco ◽  
Annalaura Torella ◽  
Stefania Aurino ◽  
...  
Keyword(s):  
Comparative Genomic Hybridization ◽  
Copy Number ◽  
Neuromuscular Disorders ◽  
Neuromuscular Diseases ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Specific Gene ◽  
Disease Genes ◽  
Genomic Hybridization ◽  
Gene Coverage

BACKGROUND Array-based comparative genomic hybridization (aCGH) is a reference high-throughput technology for detecting large pathogenic or polymorphic copy-number variations in the human genome; however, a number of quantitative monogenic mutations, such as smaller heterozygous deletions or duplications, are usually missed in most disease genes when proper multiplex ligation-dependent probe assays are not performed. METHODS We developed the Motor Chip, a customized CGH array with exonic coverage of 245 genes involved in neuromuscular disorders (NMDs), as well as 180 candidate disease genes. We analyzed DNA samples from 26 patients with known deletions or duplications in NMDs, 11 patients with partial molecular diagnoses, and 19 patients with a clinical diagnosis alone. RESULTS The Motor Chip efficiently confirmed and refined the copy-number mutations in all of the characterized patients, even when only a single exon was involved. In noncharacterized or partially characterized patients, we found deletions in the SETX (senataxin), SGCG [sarcoglycan, gamma (35kDa dystrophin-associated glycoprotein)], and LAMA2 (laminin, alpha 2) genes, as well as duplications involving LAMA2 and the DYSF [dysferlin, limb girdle muscular dystrophy 2B (autosomal recessive)] locus. CONCLUSIONS The combination of exon-specific gene coverage and optimized platform and probe selection makes the Motor Chip a complementary tool for molecular diagnosis and gene investigation in neuromuscular diseases.

scholarly journals Characteristics of Highly Polymorphic Segmental Copy-Number Variations Observed in Japanese by BAC-Array-CGH

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Norio Takahashi ◽  
Yasunari Satoh ◽  
Keiko Sasaki ◽  
Yuko Shimoichi ◽  
Keiko Sugita ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Copy Number ◽  
Array Cgh ◽  
Artificial Chromosome ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Bac Clones ◽  
Japanese Cohort ◽  
The Individual ◽  
Chromosome Microarray

Segmental copy-number variations (CNVs) may contribute to genetic variation in humans. Reports of the existence and characteristics of CNVs in a large Japanese cohort are quite limited. We report the data from a large Japanese population. We conducted population screening for 213 unrelated Japanese individuals using comparative genomic hybridization based on a bacterial artificial chromosome microarray (BAC-aCGH). We summarize the data by focusing on highly polymorphic CNVs in ≥5.0% of the individual, since they may be informative for demonstrating the relationships between genotypes and their phenotypes. We found a total of 680 CNVs at 16 different BAC-regions in the genome. The majority of the polymorphic CNVs presented on BAC-clones that overlapped with regions of segmental duplication, and the majority of the polymorphic CNVs observed in this population had been previously reported in other publications. Some of the CNVs contained genes which might be related to phenotypic heterogeneity among individuals.

scholarly journals Array-based comparative genomic hybridization identifies a high frequency of copy number variations in patients with syndromic overgrowth

2009 ◽  
Vol 18 (2) ◽  
pp. 227-232 ◽  
Author(s):  
Valérie Malan ◽  
Suzanne Chevallier ◽  
Gwendoline Soler ◽  
Christine Coubes ◽  
Didier Lacombe ◽  
...  
Keyword(s):  
Comparative Genomic Hybridization ◽  
High Frequency ◽  
Copy Number ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Genomic Hybridization

scholarly journals Increased Frequency of Copy Number Variations Revealed by Array Comparative Genomic Hybridization in the Offspring of Male Mice Exposed to Low Dose-Rate Ionizing Radiation

2021 ◽  
Vol 22 (22) ◽  
pp. 12437
Author(s):  
Keiji Ogura ◽  
Yoshiko Ayabe ◽  
Chihiro Harada ◽  
Ignacia Braga Tanaka ◽  
Satoshi Tanaka ◽  
...  
Keyword(s):  
Ionizing Radiation ◽  
Dose Rate ◽  
Copy Number ◽  
Array Comparative Genomic Hybridization ◽  
Low Dose ◽  
De Novo ◽  
Copy Number Variations ◽  
Comparative Genomic ◽  
Male Mice ◽  
Low Dose Rate

There is very little information on the transgenerational or genetic effects of low dose-rate ionizing radiation. We report the detection of the transgenerational effects of chronic low dose-rate irradiation in mice, at the molecular level in the whole genome, using array comparative genomic hybridization technology. We observed that the number of the mice with de novo copy number variations (specifically, deletions) was significantly increased in the offspring of C57BL/6J male mice exposed to 20 mGy/day gamma-rays for 400 days (total dose: 8000 mGy), as compared to non-irradiated controls. We did not detect any difference in the size of the de novo deletions between the irradiated and the non-irradiated groups. An analysis of the life span of the offspring suggested a possibility that de novo copy-number variations may be associated with shorter life spans.

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