33 research outputs found
Comparison of Whole Genome Amplification Methods for Analysis of DNA Extracted from Microdissected Early Breast Lesions in Formalin-Fixed Paraffin-Embedded Tissue
To understand cancer progression, it is desirable to study the earliest stages of its development, which are often microscopic lesions. Array comparative genomic hybridization (aCGH) is a valuable high-throughput molecular approach for discovering DNA copy number changes; however, it requires a relatively large amount of DNA, which is difficult to obtain from microdissected lesions. Whole genome amplification (WGA) methods were developed to increase DNA quantity; however their reproducibility, fidelity, and suitability for formalin-fixed paraffin-embedded (FFPE) samples are questioned. Using aCGH analysis, we compared two widely used approaches for WGA: single cell comparative genomic hybridization protocol (SCOMP) and degenerate oligonucleotide primed PCR (DOP-PCR). Cancer cell line and microdissected FFPE breast cancer DNA samples were amplified by the two WGA methods and subjected to aCGH. The genomic profiles of amplified DNA were compared with those of non-amplified controls by four analytic methods and validated by quantitative PCR (Q-PCR). We found that SCOMP-amplified samples had close similarity to non-amplified controls with concordance rates close to those of reference tests, while DOP-amplified samples had a statistically significant amount of changes. SCOMP is able to amplify small amounts of DNA extracted from FFPE samples and provides quality of aCGH data similar to non-amplified samples
Performance of ACMG-AMP Variant-Interpretation Guidelines among Nine Laboratories in the Clinical Sequencing Exploratory Research Consortium
Evaluating the pathogenicity of a variant is challenging given the plethora of types of genetic evidence that laboratories consider. Deciding how to weigh each type of evidence is difficult, and standards have been needed. In 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published guidelines for the assessment of variants in genes associated with Mendelian diseases. Nine molecular diagnostic laboratories involved in the Clinical Sequencing Exploratory Research (CSER) consortium piloted these guidelines on 99 variants spanning all categories (pathogenic, likely pathogenic, uncertain significance, likely benign, and benign). Nine variants were distributed to all laboratories, and the remaining 90 were evaluated by three laboratories. The laboratories classified each variant by using both the laboratory's own method and the ACMG-AMP criteria. The agreement between the two methods used within laboratories was high (K-alpha = 0.91) with 79% concordance. However, there was only 34% concordance for either classification system across laboratories. After consensus discussions and detailed review of the ACMG-AMP criteria, concordance increased to 71%. Causes of initial discordance in ACMG-AMP classifications were identified, and recommendations on clarification and increased specification of the ACMG-AMP criteria were made. In summary, although an initial pilot of the ACMG-AMP guidelines did not lead to increased concordance in variant interpretation, comparing variant interpretations to identify differences and having a common framework to facilitate resolution of those differences were beneficial for improving agreement, allowing iterative movement toward increased reporting consistency for variants in genes associated with monogenic disease
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The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine
Background: The diversity of clinical tumor profiling approaches (small panels to whole exomes with matched or unmatched germline analysis) may engender uncertainty about their benefits and liabilities, particularly in light of reported germline false positives in tumor-only profiling and use of global mutational and/or neoantigen data. The goal of this study was to determine the impact of genomic analysis strategies on error rates and data interpretation across contexts and ancestries. Methods: We modeled common tumor profiling modalitiesālarge (n = 300 genes), medium (n = 48 genes), and small (n = 15 genes) panelsāusing clinical whole exomes (WES) from 157 patients with lung or colon adenocarcinoma. We created a tumor-only analysis algorithm to assess germline false positive rates, the impact of patient ancestry on tumor-only results, and neoantigen detection. Results: After optimizing a germline filtering strategy, the germline false positive rate with tumor-only large panel sequencing was 14 % (144/1012 variants). For patients whose tumor-only results underwent molecular pathologist review (n = 91), 50/54 (93 %) false positives were correctly interpreted as uncertain variants. Increased germline false positives were observed in tumor-only sequencing of non-European compared with European ancestry patients (p < 0.001; Fisherās exact) when basic germline filtering approaches were used; however, the ExAC database (60,706 germline exomes) mitigated this disparity (p = 0.53). Matched and unmatched large panel mutational load correlated with WES mutational load (r2 = 0.99 and 0.93, respectively; p < 0.001). Neoantigen load also correlated (r2 = 0.80; p < 0.001), though WES identified a broader spectrum of neoantigens. Small panels did not predict mutational or neoantigen load. Conclusions: Large tumor-only targeted panels are sufficient for most somatic variant identification and mutational load prediction if paired with expanded germline analysis strategies and molecular pathologist review. Paired germline sequencing reduced overall false positive mutation calls and WES provided the most neoantigens. Without patient-matched germline data, large germline databases are needed to minimize false positive mutation calling and mitigate ethnic disparities. Electronic supplementary material The online version of this article (doi:10.1186/s13073-016-0333-9) contains supplementary material, which is available to authorized users
The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine
High throughput Detection of Molecular Targets in Cancer Using Nanoparticles: Application in Diagnostics
In light of cancer as a multi-parameter disease, technological advancements are being developed to obtain automated and high throughput assessment of molecular targets in diagnostics, with the aim to reduce subjective analytical assessment of tumours and/or to integrate molecular data obtained from different tests on given tumour samples. Towards this goal, a multi-disciplinary approach is presented in this dissertation using nanotechnology. First, by combining quantum dot (QD) nanocrystals, tissue microarray, optical spectroscopy, and algorithm design, an automated and high throughput quantitative approach in the assessment of biomarker surrogates in neoplastic tissue is introduced. The validation study was performed using epidermal growth factor (EGFR) in 8 formalin-fixed paraffin-embedded (FFPE) xenografts of lung adenocarcinoma (r2=0.9) (chapter 2). Furthermore, in chapter 3 a novel design of QD-based fluorescent probes, nanobeads, was presented by encapsulation of QDs in polystyrene in an emulsion polymerization reaction. Nanobeads exhibited resistance to fluorescent quenchers such as solutions of extreme pH and colorimetric dyes of hematoxylin & eosin (H&E) and Giemsa, key standard dyes used in cancer diagnostic. Comparative studies with organic dye, phycoerythrin (PE), and QDs demonstrated significant (P<0.001) fluorescent quenching in H&E and Giemsa using Kruskal Wallis test. The design allowed a simultaneous consolidation of fluorescent immunoassaying, using nanobeads, and morphologic and parametric visualization of cellular features, using colorimetric stains, in a given biopsy. Sten-volmer analysis demonstrated a reduction of fluorescence resonance energy transfer among nanobead610nm and nanobead560nm. The application of the QD-based methods bears potential significance in cancer diagnosis and in tumor management, especially human core biopsies of limited quantity. In chapter 4, cellular endocytosis of gold particles was shown to be size dependence, with gold particles of 50 nm demonstrating the highest uptake. The cellular response subsequent to gold uptake was assessed using 10k cDNA microarrays. Significant analysis of microarray (SAM) showed the gene expression of treated and non-treated particles to be 99.65% similar. The remaining 35 genes however, demonstrated down regulation of apoptosis, cell proliferation and cell adhesion responses in treated cells. While promising, future research and development are required to adopt nanoparticles in diagnostics.Ph
Sensitive and Direct Detection of Circulating Tumor Cells by Multimarker Āµ-Nuclear Magnetic Resonance12
Identifying circulating tumor cells (CTCs) with greater sensitivity could facilitate early detection of cancer and rapid assessment of treatment response. Most current technologies use EpCAM expression as a CTC identifier. However, given that a significant fraction of cancer patients have low or even absent EpCAM levels, there is a need for better detection methods. Here, we hypothesize that a multimarker strategy combined with direct sensing of CTC in whole blood would increase the detection of CTC in patients. Accordingly, molecular profiling of biopsies from a patient cohort revealed a four-marker set (EpCAM, HER-2, EGFR, and MUC-1) capable of effectively differentiating cancer cells from normal host cells. Using a point-of-care micro-nuclear magnetic resonance (ĀµNMR) system, we consequently show that this multimarker combination readily detects individual CTC directly in whole blood without the need for primary purification. We also confirm these results in a comparative trial of patients with ovarian cancer. This platform could potentially benefit a broad range of applications in clinical oncology
Cellular Imaging and Surface Marker Labeling of Hematopoietic Cells Using Quantum Dot Bioconjugates
Genomic Alterations in Sporadic Synchronous Primary Breast Cancer Using Array and Metaphase Comparative Genomic Hybridization1
Synchronous primary breast cancer describes the occurrence of multiple tumors affecting one or both breasts at initial diagnosis. This provides a unique opportunity to identify tissue-specific genomic markers that characterize each tumor while controlling for the individual genetic background of a patient. The aim of this study was to examine the genomic alterations and degree of similarity between synchronous cancers. Using metaphase comparative genomic hybridization and array comparative genomic hybridization (aCGH), the genomic alterations of 23 synchronous breast cancers from 10 patients were examined at both chromosomal and gene levels. Synchronous breast cancers, when compared to their matched counterparts, were found to have a common core set of genetic alterations, with additional unique changes present in each. They also frequently exhibited features distinct from the more usual solitary primary breast cancers. The most frequent genomic alterations included chromosomal gains of 1q, 3p, 4q, and 8q, and losses of 11q, 12q, 16q, and 17p. aCGH identified copy number amplification in regions that are present in all 23 tumor samples, including 1p31.3-1p32.3 harboring JAK1. Our findings suggest that synchronous primary breast cancers represent a unique type of breast cancer and, at least in some instances, one tumor may give rise to the other
Comparison of Whole Genome Amplification Methods for Analysis of DNA Extracted from Microdissected Early Breast Lesions in Formalin-Fixed Paraffin-Embedded Tissue
To understand cancer progression, it is desirable to study the earliest stages of its development, which are often microscopic lesions. Array comparative genomic hybridization (aCGH) is a valuable high-throughput molecular approach for discovering DNA copy number changes; however, it requires a relatively large amount of DNA, which is difficult to obtain from microdissected lesions. Whole genome amplification (WGA) methods were developed to increase DNA quantity; however their reproducibility, fidelity, and suitability for formalin-fixed paraffin-embedded (FFPE) samples are questioned. Using aCGH analysis, we compared two widely used approaches for WGA: single cell comparative genomic hybridization protocol (SCOMP) and degenerate oligonucleotide primed PCR (DOP-PCR). Cancer cell line and microdissected FFPE breast cancer DNA samples were amplified by the two WGA methods and subjected to aCGH. The genomic profiles of amplified DNA were compared with those of non-amplified controls by four analytic methods and validated by quantitative PCR (Q-PCR). We found that SCOMP-amplified samples had close similarity to non-amplified controls with concordance rates close to those of reference tests, while DOP-amplified samples had a statistically significant amount of changes. SCOMP is able to amplify small amounts of DNA extracted from FFPE samples and provides quality of aCGH data similar to non-amplified samples.Peer Reviewe