70 research outputs found
Genetic Analysis of the Early Natural History of Epithelial Ovarian Carcinoma
The high mortality rate associated with epithelial ovarian carcinoma (EOC) reflects diagnosis commonly at an advanced stage, but improved early detection is hindered by uncertainty as to the histologic origin and early natural history of this malignancy.Here we report combined molecular genetic and morphologic analyses of normal human ovarian tissues and early stage cancers, from both BRCA mutation carriers and the general population, indicating that EOCs frequently arise from dysplastic precursor lesions within epithelial inclusion cysts. In pathologically normal ovaries, molecular evidence of oncogenic stress was observed specifically within epithelial inclusion cysts. To further explore potential very early events in ovarian tumorigenesis, ovarian tissues from women not known to be at high risk for ovarian cancer were subjected to laser catapult microdissection and gene expression profiling. These studies revealed a quasi-neoplastic expression signature in benign ovarian cystic inclusion epithelium compared to surface epithelium, specifically with respect to genes affecting signal transduction, cell cycle control, and mitotic spindle formation. Consistent with this gene expression profile, a significantly higher cell proliferation index (increased cell proliferation and decreased apoptosis) was observed in histopathologically normal ovarian cystic compared to surface epithelium. Furthermore, aneuploidy was frequently identified in normal ovarian cystic epithelium but not in surface epithelium.Together, these data indicate that EOC frequently arises in ovarian cystic inclusions, is preceded by an identifiable dysplastic precursor lesion, and that increased cell proliferation, decreased apoptosis, and aneuploidy are likely to represent very early aberrations in ovarian tumorigenesis
A classification model for distinguishing copy number variants from cancer-related alterations
<p>Abstract</p> <p>Background</p> <p>Both somatic copy number alterations (CNAs) and germline copy number variants (CNVs) that are prevalent in healthy individuals can appear as recurrent changes in comparative genomic hybridization (CGH) analyses of tumors. In order to identify important cancer genes CNAs and CNVs must be distinguished. Although the Database of Genomic Variants (DGV) contains a list of all known CNVs, there is no standard methodology to use the database effectively.</p> <p>Results</p> <p>We develop a prediction model that distinguishes CNVs from CNAs based on the information contained in the DGV and several other variables, including segment's length, height, closeness to a telomere or centromere and occurrence in other patients. The models are fitted on data from glioblastoma and their corresponding normal samples that were collected as part of The Cancer Genome Atlas project and hybridized to Agilent 244 K arrays.</p> <p>Conclusions</p> <p>Using the DGV alone CNVs in the test set can be correctly identified with about 85% accuracy if the outliers are removed before segmentation and with 72% accuracy if the outliers are included, and additional variables improve the prediction by about 2-3% and 12%, respectively. Final models applied to data from ovarian tumors have about 90% accuracy with all the variables and 86% accuracy with the DGV alone.</p
Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications.
Analysis of DNA methylation patterns relies increasingly on sequencing-based profiling methods. The four most frequently used sequencing-based technologies are the bisulfite-based methods MethylC-seq and reduced representation bisulfite sequencing (RRBS), and the enrichment-based techniques methylated DNA immunoprecipitation sequencing (MeDIP-seq) and methylated DNA binding domain sequencing (MBD-seq). We applied all four methods to biological replicates of human embryonic stem cells to assess their genome-wide CpG coverage, resolution, cost, concordance and the influence of CpG density and genomic context. The methylation levels assessed by the two bisulfite methods were concordant (their difference did not exceed a given threshold) for 82% for CpGs and 99% of the non-CpG cytosines. Using binary methylation calls, the two enrichment methods were 99% concordant and regions assessed by all four methods were 97% concordant. We combined MeDIP-seq with methylation-sensitive restriction enzyme (MRE-seq) sequencing for comprehensive methylome coverage at lower cost. This, along with RNA-seq and ChIP-seq of the ES cells enabled us to detect regions with allele-specific epigenetic states, identifying most known imprinted regions and new loci with monoallelic epigenetic marks and monoallelic expression
Association between Ancestry-Specific 6q25 Variants and Breast Cancer Subtypes in Peruvian Women
Background: Breast cancer incidence in the United States is lower in Hispanic/Latina (H/L) compared with African American/ Black or Non-Hispanic White women. An Indigenous American breast cancer-protective germline variant (rs140068132) has been reported near the estrogen receptor 1 gene. This study tests the association of rs140068132 and other polymorphisms in the 6q25 region with subtype-specific breast cancer risk in H/Ls of high Indigenous American ancestry. Methods: Genotypes were obtained for 5,094 Peruvian women with (1,755) and without (3,337) breast cancer. Associations between genotype and overall and subtype-specific risk for the protective variant were tested using logistic regression models and conditional analyses, including other risk-associated polymorphisms in the region. Results: We replicated the reported association between rs140068132 and breast cancer risk overall [odds ratio (OR), 0.53; 95% confidence interval (CI), 0.47-0.59], as well as the lower odds of developing hormone receptor negative (HR-) versus HR+ disease (OR, 0.77; 95% CI, 0.61-0.97). Models, including HER2, showed further heterogeneity with reduced odds for HR+HER2+ (OR, 0.68; 95% CI, 0.51-0.92), HR-HER2+ (OR, 0.63; 95% CI, 0.44-0.90) and HR-HER2- (OR, 0.77; 95% CI, 0.56-1.05) compared with HR+HER2-. Inclusion of other risk-associated variants did not change these observations. Conclusions: The rs140068132 polymorphism is associated with decreased risk of breast cancer in Peruvians and is more protective against HR- and HER2+ diseases independently of other breast cancer-associated variants in the 6q25 region. Impact: These results could inform functional analyses to understand the mechanism by which rs140068132-G reduces risk of breast cancer development in a subtype-specific manner. They also illustrate the importance of including diverse individuals in genetic studies.National Institutes of HealthRevisión por pare
Clonal expansion and epigenetic reprogramming following deletion or amplification of mutant
IDH1 mutation is the earliest genetic alteration in low-grade gliomas (LGGs), but its role in tumor recurrence is unclear. Mutant IDH1 drives overproduction of the oncometabolite d-2-hydroxyglutarate (2HG) and a CpG island (CGI) hypermethylation phenotype (G-CIMP). To investigate the role of mutant IDH1 at recurrence, we performed a longitudinal analysis of 50 IDH1 mutant LGGs. We discovered six cases with copy number alterations (CNAs) at the IDH1 locus at recurrence. Deletion or amplification of IDH1 was followed by clonal expansion and recurrence at a higher grade. Successful cultures derived from IDH1 mutant, but not IDH1 wild type, gliomas systematically deleted IDH1 in vitro and in vivo, further suggestive of selection against the heterozygous mutant state as tumors progress. Tumors and cultures with IDH1 CNA had decreased 2HG, maintenance of G-CIMP, and DNA methylation reprogramming outside CGI. Thus, while IDH1 mutation initiates gliomagenesis, in some patients mutant IDH1 and 2HG are not required for later clonal expansions
Analysis of genetic variation in Ashkenazi Jews by high density SNP genotyping.
BACKGROUND: Genetic isolates such as the Ashkenazi Jews (AJ) potentially offer advantages in mapping novel loci in whole genome disease association studies. To analyze patterns of genetic variation in AJ, genotypes of 101 healthy individuals were determined using the Affymetrix EAv3 500 K SNP array and compared to 60 CEPH-derived HapMap (CEU) individuals. 435,632 SNPs overlapped and met annotation criteria in the two groups. RESULTS: A small but significant global difference in allele frequencies between AJ and CEU was demonstrated by a mean FST of 0.009 (P < 0.001); large regions that differed were found on chromosomes 2 and 6. Haplotype blocks inferred from pairwise linkage disequilibrium (LD) statistics (Haploview) as well as by expectation-maximization haplotype phase inference (HAP) showed a greater number of haplotype blocks in AJ compared to CEU by Haploview (50,397 vs. 44,169) or by HAP (59,269 vs. 54,457). Average haplotype blocks were smaller in AJ compared to CEU (e.g., 36.8 kb vs. 40.5 kb HAP). Analysis of global patterns of local LD decay for closely-spaced SNPs in CEU demonstrated more LD, while for SNPs further apart, LD was slightly greater in the AJ. A likelihood ratio approach showed that runs of homozygous SNPs were approximately 20% longer in AJ. A principal components analysis was sufficient to completely resolve the CEU from the AJ. CONCLUSION: LD in the AJ versus was lower than expected by some measures and higher by others. Any putative advantage in whole genome association mapping using the AJ population will be highly dependent on regional LD structure
Efficient oligonucleotide probe selection for pan-genomic tiling arrays
Background: Array comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome.
Results: This paper presents a new probe selection algorithm (PanArray) that can tile multiple whole genomes using a minimal number of probes. Unlike arrays built on clustered gene families, PanArray uses an unbiased, probe-centric approach that does not rely on annotations, gene clustering, or multi-alignments. Instead, probes are evenly tiled across all sequences of the pangenome at a consistent level of coverage. To minimize the required number of probes, probes conserved across multiple strains in the pan-genome are selected first, and additional probes are used only where necessary to span polymorphic regions of the genome. The viability of the algorithm is demonstrated by array designs for seven different bacterial pan-genomes and, in particular, the design of a 385,000 probe array that fully tiles the genomes of 20 different Listeria monocytogenes strains with overlapping probes at greater than twofold coverage.
Conclusion: PanArray is an oligonucleotide probe selection algorithm for tiling multiple genome sequences using a minimal number of probes. It is capable of fully tiling all genomes of a species on a single microarray chip. These unique pan-genome tiling arrays provide maximum flexibility for the analysis of both known and uncharacterized strains.https://doi.org/10.1186/1471-2105-10-29
Molecular and phenotypic diversity of <I>CBL</I>-mutated juvenile myelomonocytic leukemia
Mutations in the CBL gene were first identified in adults with various myeloid malignancies. Some patients with juvenile myelomonocytic leukemia (JMML) were also noted to harbor mutations in CBL, but were found to have generally less aggressive disease courses compared to patients with other forms of Ras pathway-mutant JMML. Importantly, and in contrast to most reports in adults, the majority of CBL mutations in JMML patients are germline with acquired uniparental disomy occurring in affected marrow cells. Here, we systematically studied a large cohort of 33 JMML patients with CBL mutations and found that this disease is highly diverse in presentation and overall outcome. Moreover, we discovered somatically acquired CBL mutations in 15% of pediatric patients who presented with more aggressive disease. Neither clinical features nor methylation profiling were able to distinguish patients with somatic CBL mutations from those with germline CBL mutations, highlighting the need for germline testing. Overall, we demonstrate that disease courses are quite heterogeneous even among patients with germline CBL mutations. Prospective clinical trials are warranted to find ideal treatment strategies for this diverse cohort of patients
The genomic landscape of juvenile myelomonocytic leukemia
Juvenile myelomonocytic leukemia (JMML) is a myeloproliferative neoplasm (MPN) of childhood with a poor prognosis. Mutations in NF1, NRAS, KRAS, PTPN11 and CBL occur in 85% of patients, yet there are currently no risk stratification algorithms capable of predicting which patients will be refractory to conventional treatment and therefore be candidates for experimental therapies. In addition, there have been few other molecular pathways identified aside from the Ras/MAPK pathway to serve as the basis for such novel therapeutic strategies. We therefore sought to genomically characterize serial samples from patients at diagnosis through relapse and transformation to acute myeloid leukemia in order to expand our knowledge of the mutational spectrum in JMML. We identified recurrent mutations in genes involved in signal transduction, gene splicing, the polycomb repressive complex 2 (PRC2) and transcription. Importantly, the number of somatic alterations present at diagnosis appears to be the major determinant of outcome
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