Bayesian detection of recurrent copy number alterations across multiple array samples

Abstract Adult diffuse gliomas are central nervous system (CNS) tumors that arise from the malignant transformation of glial cells. Nearly all gliomas will recur despite standard treatment however, current histopathological grading fails to predict which of them will relapse and/or progress. The Glioma Longitudinal AnalySiS (GLASS) consortium is a large-scale collaboration that aims to investigate the molecular profiling of matched primary and recurrent glioma samples from multiple institutions in order to better understand the dynamic evolution of these tumors. At this time, the cohort comprises 946 samples across 11 institutions and among those, 864 have DNA methylation data available. The current molecular classification based on 7 subtypes published by TCGA in 2016 was applied to the dataset. Among the IDH wildtype tumors, 33% (16/49) of the patients showed a change of subtype upon recurrence, whereas most of them (9/16) were Classic-like at the primary stage but changed to either Mesenchymal-like or PA-like at the recurrent level. Among the IDH mutant tumors, 15% (22/142) showed a change of subtype at recurrent stage, in which 16 out of 22 progressed from G-CIMP-high to G-CIMP-low. Although some tumors progressed to a different subtype upon recurrence, an unsupervised analysis showed that the samples tend to cluster by patient instead of by subtype. By estimating the copy number alterations of these tumors using DNA methylation, the overall copy number profile of the recurrent samples remains similar to their primary counterpart. From this initial analysis using epigenomic data, we were able to characterize some aspects of glioma evolution and how the DNA methylation is associated with the progression of these tumors to different subtypes. These findings corroborate the importance of epigenetics in gliomas and can potentially lead to the identification of new biomarkers that can reflect tumor burden and predict its development.

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From Benign Inflammatory Dermatosis to Cutaneous Lymphoma. DNA Copy Number Imbalances in Mycosis Fungoides versus Large Plaque Parapsoriasis

Medicina ◽

10.3390/medicina57050502 ◽

2021 ◽

Vol 57 (5) ◽

pp. 502

Author(s):

Georgiana Gug ◽

Caius Solovan

Keyword(s):

Mycosis Fungoides ◽

Copy Number ◽

Snp Array ◽

Chromosome 1 ◽

Copy Number Alterations ◽

Dna Copy Number ◽

Large Plaque ◽

Inflammatory Dermatosis ◽

Fresh Frozen ◽

Dna Copy Number Alterations

Background and Objectives: Mycosis fungoides (MF) and large plaque parapsoriasis (LPP) evolution provide intriguing data and are the cause of numerous debates. The diagnosis of MF and LPP is associated with confusion and imprecise definition. Copy number alterations (CNAs) may play an essential role in the genesis of cancer out of genes expression dysregulation. Objectives: Due to the heterogeneity of MF and LPP and the scarcity of the cases, there are an exceedingly small number of studies that have identified molecular changes in these pathologies. We aim to identify and compare DNA copy number alterations and gene expression changes between MF and LPP to highlight the similarities and the differences between these pathologies. Materials and Methods: The patients were prospectively selected from University Clinic of Dermatology and Venereology Timișoara, Romania. From fresh frozen skin biopsies, we extracted DNA using single nucleotide polymorphism (SNP) data. The use of SNP array for copy number profiling is a promising approach for genome-wide analysis. Results: After reviewing each group, we observed that the histograms generated for chromosome 1–22 were remarkably similar and had a lot of CNAs in common, but also significant differences were seen. Conclusions: This study took a step forward in finding out the differences and similarities between MF and LPP, for a more specific and implicitly correct approach of the case. The similarity between these two pathologies in terms of CNAs is striking, emphasizing once again the difficulty of approaching and differentiating them.

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Accucopy: accurate and fast inference of allele-specific copy number alterations from low-coverage low-purity tumor sequencing data

BMC Bioinformatics ◽

10.1186/s12859-020-03924-5 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Xinping Fan ◽

Guanghao Luo ◽

Yu S. Huang

Keyword(s):

Copy Number ◽

Bayesian Learning ◽

Kernel Smoothing ◽

Gaussian Mixture ◽

Copy Number Alterations ◽

Sequencing Data ◽

Copy Numbers ◽

Allele Specific ◽

Tumor Sequencing ◽

Low Coverage

Abstract Background Copy number alterations (CNAs), due to their large impact on the genome, have been an important contributing factor to oncogenesis and metastasis. Detecting genomic alterations from the shallow-sequencing data of a low-purity tumor sample remains a challenging task. Results We introduce Accucopy, a method to infer total copy numbers (TCNs) and allele-specific copy numbers (ASCNs) from challenging low-purity and low-coverage tumor samples. Accucopy adopts many robust statistical techniques such as kernel smoothing of coverage differentiation information to discern signals from noise and combines ideas from time-series analysis and the signal-processing field to derive a range of estimates for the period in a histogram of coverage differentiation information. Statistical learning models such as the tiered Gaussian mixture model, the expectation–maximization algorithm, and sparse Bayesian learning were customized and built into the model. Accucopy is implemented in C++ /Rust, packaged in a docker image, and supports non-human samples, more at http://www.yfish.org/software/. Conclusions We describe Accucopy, a method that can predict both TCNs and ASCNs from low-coverage low-purity tumor sequencing data. Through comparative analyses in both simulated and real-sequencing samples, we demonstrate that Accucopy is more accurate than Sclust, ABSOLUTE, and Sequenza.

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Screening and detection of chromosomal copy number alterations in the domestic horse using SNP‐array genotyping data

Animal Genetics ◽

10.1111/age.13077 ◽

2021 ◽

Author(s):

Y. Pirosanto ◽

N. Laseca ◽

M. Valera ◽

A. Molina ◽

M. Moreno‐Millán ◽

...

Keyword(s):

Copy Number ◽

Snp Array ◽

Domestic Horse ◽

Copy Number Alterations ◽

Chromosomal Copy Number ◽

Chromosomal Copy

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Comprehensive Assessment of Copy Number Alterations Uncovers Recurrent AIFM3 and DLK1 Copy Gain in Medullary Thyroid Carcinoma

Cancers ◽

10.3390/cancers13020218 ◽

2021 ◽

Vol 13 (2) ◽

pp. 218

Author(s):

Aline Neves Araujo ◽

Cléber Pinto Camacho ◽

Thais Biude Mendes ◽

Susan Chow Lindsey ◽

Lais Moraes ◽

...

Keyword(s):

Thyroid Carcinoma ◽

Medullary Thyroid Carcinoma ◽

Copy Number ◽

Snp Array ◽

In Silico Analysis ◽

Pcr Analysis ◽

Copy Number Alterations ◽

Medullary Thyroid ◽

Thyroid C Cells ◽

Ajcc Staging

Medullary thyroid carcinoma (MTC) is a malignant tumor originating from thyroid C-cells that can occur either in sporadic (70–80%) or hereditary (20–30%) form. In this study we aimed to identify recurrent copy number alterations (CNA) that might be related to the pathogenesis or progression of MTC. We used Affymetrix SNP array 6.0 on MTC and paired-blood samples to identify CNA using PennCNV and Genotyping Console software. The algorithms identified recurrent copy number gains in chromosomes 15q, 10q, 14q and 22q in MTC, whereas 4q cumulated losses. Coding genes were identified within CNA regions. The quantitative PCR analysis performed in an independent series of MTCs (n = 51) confirmed focal recurrent copy number gains encompassing the DLK1 (14q32.2) and AIFM3 (22q11.21) genes. Immunohistochemistry confirmed AIFM3 and DLK1 expression in MTC cases, while no expression was found in normal thyroid tissues and few MTC samples were found with normal copy numbers. The functional relevance of CNA was also assessed by in silico analysis. CNA status correlated with protein expression (DLK1, p = 0.01), tumor size (DLK1, p = 0.04) and AJCC staging (AIFM3p = 0.01 and DLK1p = 0.05). These data provide a novel insight into MTC biology, and suggest a common CNA landscape, regardless of if it is sporadic or hereditary MTC.

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