Germline DNA copy number variations as potential prognostic markers for non-muscle invasive bladder cancer progression.
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ABSTRACT:
SUBMITTER: Yamamoto Y
PROVIDER: S-EPMC5494660 | biostudies-other | 2017 Jul
REPOSITORIES: biostudies-other
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Project description:BackgroundMelanoma is an aggressive type of skin cancer whose aetiology remains elusive as both environmental and genetic factors can contribute to its development. Recent studies have demonstrated the existence of multiple copies of E2F1 gene in melanoma specimens which could explain the deregulated E2F1 activity in this type of cancer. This finding suggests a key role for this transcription factor in the malignant transformation of melanocytes. Therefore, E2F1 has been considered as a potential therapeutic target for this form of skin cancer. Since germline copy number variations (CNVs) have been associated with increased susceptibility to different types of cancer, the aim of our study was to assess germline E2F1 CNV in melanoma patients. However, CNVs not necessarily lead to gene dosage imbalance, hence, further factors, in association with CNVs, could contribute to clinical manifestations. Considering that heat stress has been hypothesised as a contributing factor to skin cancer, we also investigated the effect of heat stress on E2F1 expression.MethodsE2F1 CNV was measured in genomic DNA isolated from blood of 552 patients diagnosed with melanoma and 520 healthy subjects using TaqMan Copy Number Assays. E2F1 mRNA expression was also evaluated by RT-qPCR in the melanoma cell line, SK MEL 267, before and after exposure to heat stress.ResultsWe found that patients diagnosed with melanoma (1.6%, 9/552) harboured frequently altered germline E2F1 copies compared to healthy subjects (0%, 0/520). Moreover, the difference among the two groups was statistically significant (p = 0.004). Furthermore, we found that heat exposure alone can significantly induce E2F1 expression.ConclusionsThis is the first study that shows a relation between germline E2F1 CNV and melanoma, suggesting that altered copies of this gene might be a predisposing factor to skin cancer. Our results also suggest that environmental insults, such as heat stress, could contribute to an aberrant E2F1 activity by inducing E2F1 mRNA expression. Therefore, subjects with multiple constitutive copies of E2F1 are at greater risk of developing melanoma when exposed to heat. Altogether our results corroborate with the hypothesis that susceptibility to melanoma depends on both the environment and genetic factors.
| S-EPMC6542053 | biostudies-literature
Project description:Breast cancer recurrence (BCR) is a common treatment outcome despite curative-intent primary treatment of non-metastatic breast cancer. Currently used prognostic and predictive factors utilize tumor-based markers, and are not optimal determinants of risk of BCR. Germline-based copy number aberrations (CNAs) have not been evaluated as determinants of predisposition to experience BCR. In this study, we accessed germline DNA from 369 female breast cancer subjects who received curative-intent primary treatment following diagnosis. Of these, 155 experienced BCR and 214 did not, after a median duration of follow up after breast cancer diagnosis of 6.35 years (range?=?0.60-21.78) and 8.60 years (range?=?3.08-13.57), respectively. Whole genome CNA genotyping was performed on the Affymetrix SNP array 6.0 platform. CNAs were identified using the SNP-Fast Adaptive States Segmentation Technique 2 algorithm implemented in Nexus Copy Number 6.0. Six samples were removed due to poor quality scores, leaving 363 samples for further analysis. We identified 18,561 CNAs with ?1 kb as a predefined cut-off for observed aberrations. Univariate survival analyses (log-rank tests) identified seven CNAs (two copy number gains and five copy neutral-loss of heterozygosities, CN-LOHs) showing significant differences (P<2.01×10(-5)) in recurrence-free survival (RFS) probabilities with and without CNAs.We also observed three additional but distinct CN-LOHs showing significant differences in RFS probabilities (P<2.86×10(-5)) when analyses were restricted to stratified cases (luminal A, n?=?208) only. After adjusting for tumor stage and grade in multivariate analyses (Cox proportional hazards models), all the CNAs remained strongly associated with the phenotype of BCR. Of these, we confirmed three CNAs at 17q11.2, 11q13.1 and 6q24.1 in representative samples using independent genotyping platforms. Our results suggest further investigations on the potential use of germline DNA variations as prognostic markers in cancer-associated phenotypes.
| S-EPMC3547038 | biostudies-literature
Project description:Mounting evidence suggests that copy number variations (CNVs) can contribute to cancer susceptibility. The main goal of this study was to evaluate the role of germline CNVs in melanoma predisposition in high-risk melanoma families. We used genome-wide tiling comparative genomic hybridization and single nucleotide polymorphism arrays to characterize CNVs in 335 individuals (240 melanoma cases) from American melanoma-prone families (22 with germline CDKN2A or CDK4 mutations). We found that the global burden of overall CNVs (or deletions or duplications separately) was not significantly associated with case-control or CDKN2A/CDK4 mutation status after accounting for the familial dependence. However, we identified several rare CNVs that either involved known melanoma genes (e.g., PARP1, CDKN2A) or cosegregated with melanoma (duplication on 10q23.23, 3p12.2 and deletions on 8q424.3, 2q22.1) in families without mutations in known melanoma high-risk genes. Some of these CNVs were correlated with expression changes in disrupted genes based on RNASeq data from a subset of melanoma cases included in the CNV study. These results suggest that rare cosegregating CNVs may influence melanoma susceptibility in some melanoma-prone families and genes found in our study warrant further evaluation in future genetic analyses of melanoma.
| S-EPMC5123914 | biostudies-literature
Project description:Breast cancer is one of the most common cancers among women, and susceptibility is explained by genetic, lifestyle and environmental components. Copy Number Variants (CNVs) are structural DNA variations that contribute to diverse phenotypes via gene-dosage effects or cis-regulation. In this study, we aimed to identify germline CNVs associated with breast cancer susceptibility and their relevance to prognosis. We performed whole genome CNV genotyping in 422 cases and 348 controls using Human Affymetrix SNP 6 array. Principal component analysis for population stratification revealed 84 outliers leaving 366 cases and 320 controls of Caucasian ancestry for association analysis; CNVs with frequency > 10% and overlapping with protein coding genes were considered for breast cancer risk and prognostic relevance. Coding genes within the CNVs identified were interrogated for gene- dosage effects by correlating copy number status with gene expression profiles in breast tumor tissue. We identified 200 CNVs associated with breast cancer (q-value < 0.05). Of these, 21 CNV regions (overlapping with 22 genes) also showed association with prognosis. We validated representative CNVs overlapping with APOBEC3B and GSTM1 genes using the TaqMan assay. Germline CNVs conferred dosage effects on gene expression in breast tissue. The candidate CNVs identified in this study warrant independent replication.
| S-EPMC5677082 | biostudies-literature
Project description:Urinary bladder cancer is a heterogeneous disease with diverse genetic and environmental risk factors that can influence disease risk or clinical course for recurrence, progression, and survival. Therefore, identification of these factors is paramount for disease prevention and optimal clinical management of bladder cancer patients. Of particular interest is the need to identify molecular biomarkers that can give accurate assessment of tumor biological potential and to predict treatment response. Recent advances in molecular biology, cytogenetic, and genomic research have spurred discovery efforts for novel genetic, epigenetic, and proteomic biomarkers that are prognostic for cancer. This review focuses on some of the important germ line polymorphisms found to be correlated with clinical outcomes in bladder cancer. So far, most of the identified candidate loci were based on prior knowledge of pathogenesis and had not been validated for clinical applications. The future challenges are to analyze the wealth of information from whole-genome studies, to understand the underlying biological mechanisms of these associations, the network of gene-gene and gene-environment interactions, and to apply these markers for the identification of high-risk population for targeted, personalized therapy.
| S-EPMC3824379 | biostudies-literature
Project description:BackgroundPregnancy complications could lead to maternal and fetal morbidity and mortality. Early diagnosing and managing complications have been associated with good outcomes. The placenta was an important organ for development of pregnancy complications. Thus, non-invasive prenatal testing technologies could detect genetic variations, such as aneuploidies and sub-chromosomal copy number variations, reflecting defective placenta by maternal plasma cffDNAs. Maternal cffDNAs had been proved to derive from trophoblast cells of placenta.ResultsIn order to find out the relationship between genetic variations and pregnancy complications, we reviewed NIPT results for subchromosomal copy number variations in a cohort of 3890 pregnancies without complications and 441 pregnancies with pregnancy complications including gestational diabetes mellitus (GDM), pregnancy-induced hypertension (PIH), preterm prelabor rupture of membranes (PPROM) and placenta implantation abnormalities (PIA). For GDMs, we identified three CNV regions containing some members of alpha- and beta-defensins, such as DEFA1, DEFA3, DEFB1. For PIHs, we found three duplication and one deletion region including Pcdhα, Pcdhβ, and Pcdhγ, known as protocadherins, which were complicated by hypertensive disorders. For PPROMs and PIAs, we identified one and two CNV regions, respectively. SFTPA2, SFTPD and SFTPA1, belonging to surfactant protein, was considered to moderated the inflammatory activation within the fetal extra-embryonic compartment, associated to duration of preterm prelabor rupture of fetal membranes, while MEF2C and TM6SF1 could be involved in trophoblast invasion and differentiation.ConclusionsOur findings gave a clue to correlation between genetic variations of maternal cell-free DNAs and pregnancy complications.
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Project description:BACKGROUND:Due to the advancement in high throughput technology, single nucleotide polymorphism (SNP) is routinely being incorporated along with phenotypic information into genetic evaluation. However, this approach often cannot achieve high accuracy for some complex traits. It is possible that SNP markers are not sufficient to predict these traits due to the missing heritability caused by other genetic variations such as microsatellite and copy number variation (CNV), which have been shown to affect disease and complex traits in humans and other species. RESULTS:In this study, CNVs were included in a SNP based genomic selection framework. A Nellore cattle dataset consisting of 2230 animals genotyped on BovineHD SNP array was used, and 9 weight and carcass traits were analyzed. A total of six models were implemented and compared based on their prediction accuracy. For comparison, three models including only SNPs were implemented: 1) BayesA model, 2) Bayesian mixture model (BayesB), and 3) a GBLUP model without polygenic effects. The other three models incorporating both SNP and CNV included 4) a Bayesian model similar to BayesA (BayesA+CNV), 5) a Bayesian mixture model (BayesB+CNV), and 6) GBLUP with CNVs modeled as a covariable (GBLUP+CNV). Prediction accuracies were assessed based on Pearson's correlation between de-regressed EBVs (dEBVs) and direct genomic values (DGVs) in the validation dataset. For BayesA, BayesB and GBLUP, accuracy ranged from 0.12 to 0.62 across the nine traits. A minimal increase in prediction accuracy for some traits was noticed when including CNVs in the model (BayesA+CNV, BayesB+CNV, GBLUP+CNV). CONCLUSIONS:This study presents the first genomic prediction study integrating CNVs and SNPs in livestock. Combining CNV and SNP marker information proved to be beneficial for genomic prediction of some traits in Nellore cattle.
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Project description:The popularisation and decreased cost of genome resequencing has resulted in an increased use in molecular diagnostics. While there are a number of established and high quality bioinfomatic tools for identifying small genetic variants including single nucleotide variants and indels, currently there is no established standard for the detection of copy number variants (CNVs) from sequence data. The requirement for CNV detection from high throughput sequencing has resulted in the development of a large number of software packages. These tools typically utilise the sequence data characteristics: read depth, split reads, read pairs, and assembly-based techniques. However, the additional source of information from read balance (defined as relative proportion of reads of each allele at each position) has been underutilised in the existing applications. Here we present Read Balance Validator (RBV), a bioinformatic tool that uses read balance for prioritisation and validation of putative CNVs. The software simultaneously interrogates nominated regions for the presence of deletions or multiplications, and can differentiate larger CNVs from diploid regions. Additionally, the utility of RBV to test for inheritance of CNVs is demonstrated in this report. RBV is a CNV validation and prioritisation bioinformatic tool for both genome and exome sequencing available as a python package from https://github.com/whitneywhitford/RBV.
| S-EPMC6858463 | biostudies-literature
Project description:Non-muscle invasive bladder cancer (NMIBC) patients frequently fail to respond to treatment and experience disease progression because of their clinical and biological diversity. In this study, we identify a prognostic molecular signature for predicting the heterogeneity of NMIBC by using an integrative analysis of copy number and gene expression data. We analyzed the copy number and gene expression profiles of 404 patients with bladder cancer obtained from The Cancer Genome Atlas (TCGA) consortium. Of the 14 molecules with significant copy number alterations that were previously reported, 13 were significantly correlated with copy number and expression changes. Prognostic gene sets based on the 13 genes were developed, and their prognostic values were verified in three independent patient cohorts (n=501). Among them, a signature of CCNE1 and its coexpressed genes was significantly associated with disease progression and validated in the independent cohorts. The CCNE1 signature was an independent risk factor based on the result of a multivariate analysis (hazard ratio=6.849, 95% confidence interval=1.613-29.092, P=0.009). Finally, gene network and upstream regulator analyses revealed that NMIBC progression is potentially mediated by CCND1-CCNE1-SP1 pathways. The prognostic molecular signature defined by copy number and expression changes of CCNE1 suggests a novel diagnostic tool for predicting the likelihood of NMIBC progression.
| S-EPMC5291834 | biostudies-literature
Project description:Stroke is the third leading cause of death worldwide after heart disease and all forms of cancers. Monogenic disorders, genetic, and environmental risk factors contribute to damaging cerebral blood vessels and, consequently, cause stroke. Developments in genomic research led to the discovery of numerous copy number variants (CNVs) that have been recently identified as a new tool for understanding the genetic basis of many diseases. This review discusses the current understanding of the types of stroke, the existing knowledge on the involvement of specific CNVs in stroke as well as the limitations of the methods used for detecting CNVs like SNP-microarray. To confirm an unequivocally association between CNVs and stroke and extend the current findings, it would be desirable to use another methodology to detect smaller CNVs or CNVs in genomic regions poorly covered by this technique, for instance, CGH-array.
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