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Hereditary Cancer Diagnostics with I2HCP gene panel

ABSTRACT: This dataset contains targetted DNA sequencing data generated in the context of genetic diagnostics of hereditary cancer. Target enrichment was performed with the I2HCP, a custom hereditary cancer gene panel based in Agilent SureSelect and developed by the Germans Trias i Pujol Research Institute (IGTP, Badalona, Catalonia, Spain) and the Catalan Institute of Oncology (ICO, L'Hospitalet de Llobregat, Catalonia, Spain). After the enrichment, 108 samples were sequenced in Illumina HiSeq machines and 130 in MiSeq machines. Some of the samples were sequenced on both platforms. The dataset also includes MLPA validation data for all identified copy-number alterations, annotated with exon resolution and information about negative MLPA results. All this data was generated in the context of routine diagnostics and compiled together with MPLA validation data for a genetic diagnostics oriented benchmark of germline CNV calling tools.

PROVIDER: EGAS00001004316 | EGA |

REPOSITORIES: EGA

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f55c7ef3-bc0e-4a9f-842b-dd4094ce327e - samples

Project description:Germline blood DNA sequencing data generated in routine diagnostics of hereditary cancer using the I2HCP gene panel (~135 genes). There are 130 samples sequenced in a MiSeq machine and 108 sequenced in a HiSeq machine. There is a partial overlap between those two sets, meaning that some samples were sequenced in both machines. There is a strong enrichment in samples with copy-number variants (CNV), both single- and multi-exon, since this dataset was compiled for a benchmarking effort of CNV calling tools for genetic diagnostics.

| EGAD00001006171 | EGA

Identification of Tissue Specific DNA Methylation Signatures for Thyroid Nodule Diagnostics

Project description:PURPOSE: Thyroid cancer is frequently difficult to diagnose due to an overlap of cytological features between malignant and benign nodules. This overlap leads to unnecessary removal of the thyroid in patients without cancer. While providing some improvement over cytopathologic diagnostics, molecular methods frequently fail to provide a correct diagnosis for thyroid nodules. These approaches are based on the difference between malignant nodules and normal adjacent thyroid tissue and assume that normal thyroid tissues are the same as benign nodules. However, in contrast to normal thyroid tissues, benign thyroid nodules can contain genetic alterations that can be found in cancerous nodules. PATIENTS AND METHODS: For the development of a new molecular diagnostic test for thyroid cancer, we evaluated DNA methylation in 109 thyroid tissues by using genome wide single base resolution DNA methylation analysis (Reduced Representation Bisulfite Sequencing). The test was validated in the retrospective cohort containing 64 thyroid nodules. RESULTS: By conducting Reduced Representation Bisulfite Sequencing in 109 thyroid specimens, we found significant differences between normal tissue, benign nodules, and cancer. Based on tissue-specific epigenetic signatures for benign and malignant nodules, we developed a new epigenetic approach for thyroid diagnostics. According to the validation cohort, our test has an estimated specificity of 97% (95% CI, 80 to 100), sensitivity of 100% (95% CI, 86 to 100), PPV of 97% (95% CI, 82-100), NPV of 100% (95%, 85 to 100). CONCLUSION: These data show that epigenetic testing can provide outstanding diagnostic accuracy for thyroid nodules by evaluating tissue specific DNA methylation.

2018-11-30 | GSE107738 | GEO

NGS of virus derived small RNAs as a diagnostics method used to determine viromes of Hungarian vineyards

Project description:As virus diseases cannot be controlled by traditional plant protection methods the risk of their spread have to be minimized on vegetatively propagated plants, such as grapevine. Metagenomics approaches used for virus diagnostics, offer a unique opportunity to reveal the presence of all viral pathogens in the investigated plant, why their usage can reduce the risk of using infected material for a new plantation. Here we used a special field, deep sequencing of virus derived small RNAs, of this high throughput method for virus diagnostics and determined viromes of vineyards in Hungary. With NGS of virus derived small RNAs we could detect not only the viruses tested routinely, but also new ones, which have never been described in Hungary before. Virus presence didn’t correlated with the age of the plantation, moreover phylogenetic analysis of the identified virus isolates suggests that infections mostly caused by the usage of infected propagating material. Our results, validated by other molecular methods, highlighted further questions to be answered before these method can be introduced as a routine, reliable test for grapevine virus diagnostics.

2018-04-05 | GSE106240 | GEO

Molecular Diagnostics in Sepsis: from Bedside to Bench

Project description:Accuracy of sepsis prediction was obtained using cross-validation of gene expression data from 12 human spleen samples and from 16 mouse spleen samples. For blood studies, classifiers were constructed using data from a training data set of 26 microarrays. The error rate of the classifiers was estimated on seven de-identified microarrays, and then on a subsequent cross-validation for all 33 blood microarrays. Estimates of classification accuracy of sepsis in human spleen were 67.1%; in mouse spleen, 96%; and in mouse blood, 94.4% (all estimates were based on nested cross-validation). Lists of genes with substantial changes in expression between study and control groups were used to identify nine mouse common inflammatory response genes, six of which were mapped into a single pathway using contemporary pathway analysis tools. Keywords: genomics, diagnosis, microarray, calprotectin

2006-08-29 | GSE5663 | GEO

Identification of nine genomic regions of amplification in bladder cancer, correlation with stage, and potential prognositic and therapeutic value

Project description:We sought to test the hypothesis that ascertainment of genome-wide copy number alterations in bladder cancer may have value for clinical management. We performed a genome wide analysis of 164 bladder cancer samples and 27 bladder cancer cell lines to identify genetic changes associated with disease characteristics. Multiplex inversion probe (MIP) analysis, a newly developed genomic technique, was used to study 80 bladder cancers to identify mutations and copy number changes. Selected amplification events were then analyzed in a validation cohort of 84 bladder cancers by multiplex ligation-dependent probe assay (MLPA). In the MIP analysis, 44 regions of significant copy number change were identified using GISTIC. Nine gene-containing regions of amplification were selected for validation in the second cohort by MLPA. Amplification events at these 9 genomic regions were found to correlate strongly with stage, being seen in only 2 of 23 (9%) Ta grade 1 or 1-2 cancers, in contrast to 31 of 61 (51%) Ta grade 3 and T2 grade 2 cancers, p < 0.001. These observations suggest that analysis of genomic amplification of these 9 regions might serve as a guide for clinical decision making, in terms of management decisions following transurethral resection of bladder cancers. This approach is facilitated by the capability of each of the MIP and MLPA methods to analyze formalin-fixed paraffin-embedded DNA, as done here. Furthermore several of the amplified genes identified here (ERBB2, MDM2, CCND1) render the bladder cancers potentially sensitive to targeted therapy.

2013-04-29 | GSE44323 | GEO

Rapid Acceleration of Diagnostics - Radical (RADx-rad): Portable GC Detector for COVID Diagnostics

Project description:Rapid Acceleration of Diagnostics - Radical (RADx-rad): Portable GC Detector for COVID Diagnostics

| PRJNA761805 | ENA

Rapid Acceleration of Diagnostics - Radical (RADx-rad): Portable GC Detector for COVID Diagnostics

Project description:Rapid Acceleration of Diagnostics - Radical (RADx-rad): Portable GC Detector for COVID Diagnostics

| PRJNA761804 | ENA

Identification of nine genomic regions of amplification in bladder cancer, correlation with stage, and potential prognositic and therapeutic value

2013-04-29 | E-GEOD-44323 | biostudies-arrayexpress

Methylation profiling and machine learning distinguishes primary lung squamous cell carcinomas from head and neck metastases

Project description:Head and neck squamous cell carcinoma (HNSC) patients are at risk of suffering from both pulmonary metastases or a second squamous cell carcinoma of the lung (LUSC). Differentiating pulmonary metastases from primary lung cancers is of high clinical importance, but not possible in most cases with current diagnostics. To address this, we performed DNA methylation profiling of primary tumors and trained three different machine learning methods to distinguish metastatic HNSC from primary LUSC. We developed an artificial neural network that correctly classi- fied 96.4% of the cases in a validation cohort of 279 patients with HNSC and LUSC as well as normal lung controls, outperforming support vector machines (95.7%) and random forests (87.8%). Prediction accuracies of more than 99% were achieved for 92.1% (neural network), 90% (support vector machine), and 43% (random forest) of these cases by applying thresholds to the resulting probability scores and excluding samples with low confidence. As independent clinical validation of the approach, we analyzed a series of 51 patients with a history of HNSC and a second lung tumor, demonstrating the correct classifications based on clinicopathological properties. In summary, our approach may facilitate the reliable diagnostic differentiation of pulmonary metastases of HNSC from primary LUSC to guide therapeutic decisions.

2019-09-10 | GSE124052 | GEO

Affymetrix SNP6.0 array data for PAX5 amplified acute lymphoblastic leukemia

Project description:Intragenic PAX5 amplification in <1%of B-cell precursor acute lymphoblastic leukaemia. Affymetrix SNP 6.0 array analysis was undertaken in patients who showed amplication of PAX5 by MLPA testing using the P335-IKZF1 MLPA kit (www.mlpa.com, MRC Holland, The Netherlands)

2017-06-09 | GSE99813 | GEO

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