Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing
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PROVIDER: EGAS00001000566 | EGA |
REPOSITORIES: EGA
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Project description:We explored the detection of genome-wide hypomethylation in plasma using shotgun massively parallel bisulfite sequencing as a marker for cancer. Tumor-associated copy number aberrations (CNAs) could also be observed from the bisulfite DNA sequencing data. Hypomethylation and CNAs were detected in the plasma DNA of patients with hepatocellular carcinoma, breast cancer, lung cancer, nasopharyngeal cancer, smooth muscle sarcoma, and neuroendocrine tumor. For the detection of nonmetastatic cancer cases, plasma hypomethylation gave a sensitivity and specificity of 74% and 94%, respectively, when a mean of 93 million reads per case were obtained. Reducing the sequencing depth to 10 million reads per case was found to have no adverse effect on the sensitivity and specificity for cancer detection, giving respective figures of 68% and 94%. This characteristic thus indicates that analysis of plasma hypomethylation by this sequencing-based method may be a relatively cost-effective approach for cancer detection. We also demonstrated that plasma hypomethylation had utility for monitoring hepatocellular carcinoma patients following tumor resection and for detecting residual disease. Plasma hypomethylation can be combined with plasma CNA analysis for further enhancement of the detection sensitivity or specificity using different diagnostic algorithms. Using the detection of at least one type of aberration to define an abnormality, a sensitivity of 87% could be achieved with a specificity of 88%. These developments have thus expanded the applications of plasma DNA analysis for cancer detection and monitoring.
| S-EPMC3839703 | biostudies-literature
Project description:Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing
| EGAD00001001093 | EGA
Project description:MOTIVATION: Because of its low cost, amplicon sequencing, also known as ultra-deep targeted sequencing, is now becoming widely used in oncology for detection of actionable mutations, i.e. mutations influencing cell sensitivity to targeted therapies. Amplicon sequencing is based on the polymerase chain reaction amplification of the regions of interest, a process that considerably distorts the information on copy numbers initially present in the tumor DNA. Therefore, additional experiments such as single nucleotide polymorphism (SNP) or comparative genomic hybridization (CGH) arrays often complement amplicon sequencing in clinics to identify copy number status of genes whose amplification or deletion has direct consequences on the efficacy of a particular cancer treatment. So far, there has been no proven method to extract the information on gene copy number aberrations based solely on amplicon sequencing. RESULTS: Here we present ONCOCNV, a method that includes a multifactor normalization and annotation technique enabling the detection of large copy number changes from amplicon sequencing data. We validated our approach on high and low amplicon density datasets and demonstrated that ONCOCNV can achieve a precision comparable with that of array CGH techniques in detecting copy number aberrations. Thus, ONCOCNV applied on amplicon sequencing data would make the use of additional array CGH or SNP array experiments unnecessary.
| S-EPMC4253825 | biostudies-other
Project description:Detection of copy number variants as an integral part of noninvasive prenatal testing is increasingly used in clinical practice worldwide. We performed validation on plasma samples from 34 pregnant women with known aberrations using cell-free DNA sequencing to evaluate the sensitivity for copy number variants (CNV) detection using an in-house CNV fraction-based detection algorithm. The sensitivity for CNVs smaller than 3 megabases (Mb), larger than 3Mb, and overall was 78.57%, 100%, and 90.6%, respectively. Regarding the fetal fraction, detection sensitivity in the group with a fetal fraction of less than 10% was 57.14%, whereas there was 100% sensitivity in the group with fetal fraction exceeding 10%. The assay is also capable of indicating whether the origin of an aberration is exclusively fetal or fetomaternal/maternal. This validation demonstrated that a CNV fraction-based algorithm was applicable and feasible in clinical settings as a supplement to testing for common trisomies 21, 18, and 13.
| S-EPMC7460070 | biostudies-literature
Project description:MotivationDNA copy number (CN) data are a fast-growing source of information used in basic and translational cancer research. Most CN segmentation data are presented without regard to the relationship between chromosomal regions. We offer both a toolkit to help scientists without programming experience visually explore the CN interactome and a package that constructs CN interactomes from publicly available data sets.ResultsThe CNVScope visualization, based on a publicly available neuroblastoma CN data set, clearly displays a distinct CN interaction in the region of the MYCN, a canonical frequent amplicon target in this cancer. Exploration of the data rapidly identified cis and trans events, including a strong anticorrelation between 11q loss and17q gain with the region of 11q loss bounded by the cell cycle regulator CCND1.AvailabilityThe shiny application is readily available for use at http://cnvscope.nci.nih.gov/, and the package can be downloaded from CRAN (https://cran.r-project.org/package=CNVScope), where help pages and vignettes are located. A newer version is available on the GitHub site (https://github.com/jamesdalg/CNVScope/), which features an animated tutorial. The CNVScope package can be locally installed using instructions on the GitHub site for Windows and Macintosh systems. This CN analysis package also runs on a linux high-performance computing cluster, with options for multinode and multiprocessor analysis of CN variant data. The shiny application can be started using a single command (which will automatically install the public data package).
| S-EPMC6887803 | biostudies-literature
Project description:BACKGROUND:Mucinous carcinoma (MC) is found in 10%-15% of colorectal cancer (CRC) patients. It differs from the common adenocarcinoma (AC) in histopathological appearance and clinical behavior. METHODS:Genome-wide DNA copy number and survival data from MC and AC primary CRC samples from patients from two phase III trials (CAIRO and CAIRO2) was compared. Chromosomal copy number data from The Cancer Genome Atlas (TCGA) was used for validation. Altogether, 470 ACs were compared to 57 MCs. RESULTS:MC showed a reduced amount of copy number aberrations (CNAs) compared with AC for the CAIRO/CAIRO2 cohort, with a median amount of CNAs that was 1.5-fold lower (P = 0.002). Data from TCGA also showed a reduced amount of CNAs for MC. MC samples in both cohorts displayed less gain at chromosome 20q and less loss of chromosome 18p. A high rate of chromosomal instability was a strong negative prognostic marker for survival in MC patients from the CAIRO cohorts (hazard ratio 15.60, 95% CI 3.24-75.05). CONCLUSIONS:Results from this study indicate that the distinct MC phenotype is accompanied by a different genetic basis when compared with AC and show a strong association between the rate of chromosomal instability and survival in MC patients.
| S-EPMC4694861 | biostudies-literature
Project description:Copy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected "driver" genes with limited application to rare drivers and other genomic elements. In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification.
| S-EPMC8155688 | biostudies-literature
Project description:A collection of intracranial astrocytomas of different malignancy grades was analyzed for copy number aberrations (CNA) in order to identify regions that are driving cancer pathogenesis. Astrocytomas were analyzed by Array Comparative Genomic Hybridization (aCGH) and bioinformatics utilizing a Bioconductor package, Genomic Identification of Significant Targets in Cancer (GISTIC) 2.0.23 and DAVID software. Altogether, 1438 CNA were found of which losses prevailed. On our total sample, significant deletions affected 14 chromosomal regions, out of which deletions at 17p13.2, 9p21.3, 13q12.11, 22q12.3 remained significant even at 0.05 q-value. When divided into malignancy groups, the regions identified as significantly deleted in high grades were: 9p21.3; 17p13.2; 10q24.2; 14q21.3; 1p36.11 and 13q12.11, while amplified were: 3q28; 12q13.3 and 21q22.3. Low grades comprised significant deletions at 3p14.3; 11p15.4; 15q15.1; 16q22.1; 20q11.22 and 22q12.3 indicating their involvement in early stages of tumorigenesis. Significantly enriched pathways were: PI3K-Akt, Cytokine-cytokine receptor, the nucleotide-binding oligomerization domain (NOD)⁻like receptor, Jak-STAT, retinoic acid-inducible gene (RIG)-I-like receptor and Toll-like receptor pathways. HPV and herpex simplex infection and inflammation pathways were also represented. The present study brings new data to astrocytoma research amplifying the wide spectrum of changes that could help us identify the regions critical for tumorigenesis.
| S-EPMC6429132 | biostudies-literature
Project description:Affymetrix Human Gene 1.1 ST Array profiling of 285 primary medulloblastoma samples. Total RNA was extracted from primary medulloblastoma samples and hybridized to Affymetrix Human Gene 1.1 ST Arrays (24-Array Plates) according to the manufacturer's instructions.
| S-ECPF-GEOD-37382 | biostudies-other
Project description:BackgroundSomatic copy number alterations (SCNAs) occurring in tumors can provide information about tumor classification, patient's outcome or treatment targets. Liquid biopsies, incl. plasma samples containing circulating cell-free tumor DNA (ccfDNA) can be used to assess SCNAs for clinical purposes, however specify and reliability of methods have to be tested.MethodsSNP microarrays (Affymetrix) were used to generate whole-genome copy number profiles from plasma ccfDNA (OncoScan) and paired tumor biopsies (CytoScan) from ten patients with metastatic cancers. Numerical, segmental and focal SCNAs were assessed using ASCAT/TuScan and SNP-FASST2.ResultsAberrations in ccfDNA in 4 patients resembled numerical (76%) and segmental (80%) aberrations in tDNA. Three patients represented low correlation due to postponed sampling time, ccfDNA quality and possible treatment interference. Breakpoints of high-amplitude amplification were assessed with high accuracy and relative breakpoints difference of only 7% (0.02-37%). Similarly, biallelic losses were reliably detected. Array was 100% successful in detection of SCNAs on clinically relevant genes compared to SCNAs in tumor biopsies. Tracking of SCNAs changes during the treatment course of one patient also indicated that apoptosis/necrosis of non-cancerous cells presumably induced by treatment can influence ccfDNA composition and introduce false-negative findings into the analysis of liquid biopsies.ConclusionsGenomic alterations detected in ccfDNA from liquid biopsies by comprehensive SNP array are reliable source for information for stratification of patients for targeted treatment.General significanceClinically relevant SCNAs can be detected in ccfDNA with high resolution and can therefore serve as an alternative to tumor biopsy in defining treatment targets.
| S-EPMC5390666 | biostudies-literature