7201 results for "canc*"

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• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• CRC Patient-derived-organoids Whole Genome Sequencing

  Whole Genome Sequencing raw paired-ends reads for 20 matched colorectal patient-derived-organoids (normal and tumor). Tumor samples were obtained from patients treated at Niguarda Cancer Center, (Milano, Italy) and Candiolo Cancer Institute (Candiolo, Turin, Italy).

  Dataset EGAD50000000617

• Efficacy and safety of entrectinib in patients with ROS1-positive advanced/metastatic non-small cell lung cancer (NSCLC) from the Blood First Assay Screening Trial (BFAST)

  BFAST is a global, open-label, multicohort trial that evaluates the efficacy and safety of multiple therapies in patients with advanced/metastatic NSCLC and targetable alterations, identified by blood-based molecular testing. We present data from Cohort D (ROS1-positive). Patients ≥18 years old with stage IIIB/IV, ROS1-positive NSCLC detected by blood-based testing, received entrectinib 600 mg daily. At data cut-off (November 2021), 55 patients were enrolled and 54 had measurable disease. Cohort D met its primary endpoint; the confirmed objective response rate (ORR) by investigator was 81.5% which was consistent with the ORR from the integrated analysis of entrectinib (investigator-assessed ORR: 73.4%, data cut-off May 2019, ≥12 months follow-up). The safety profile of entrectinib was consistent with prior reports. These results demonstrate consistency with those from the integrated analysis of entrectinib in patients with ROS1-positive NSCLC identified by tissue-based testing and support the clinical value of blood-based testing to inform clinical decision-making.

  Study EGAS50000000105

• WES of precancerous lesions from 10 lynch patients and 3 sporadics

  Raw sequencing data of WES that were obtained from precancerous samples as adenoma and MMR-deficient crypts and paired healthy tissue from MSI CRC patients of which 10 are diagnosed with lynch syndrome and 3 had sporadic cancer. These data were analyzed in order to evaluate microsatellite instability though tumorigenesis and associated to splicing deregulation in MSI tumors RNA.

  Dataset EGAD50000000644

• Healthy control cfMeDIP-seq

  This dataset comprises 46 raw fastq files derived from 23 plasma cfDNA samples from 23 healthy (CTL) cancer-free donors. For each sample, 10ng of cfDNA was used for library preparation utilizing the cfMeDIP-seq technology based on the 5mC antibody-immunoprecipitation strategy. Libraries were validated via Bioanalyzer trace analysis and sequenced on the Illumina NovaSeq 6000 platform with paired-end 150-bp model for ~100 million reads per sample.

  Dataset EGAD50000000652

• Clonal Evolution and Blastic Plasmacytoid Dendritic Cell Neoplasm - Two Cases

  Here we present two case studies of sequential whole exome sequencing (WES) in patients, who both developed BPDCN throughout their medical history but primarily presented with lymphoid cancers (clonally related ALK-negative anaplastic large-cell lymphoma (ALCL) and T-lymphoblastic lymphoma (T-LBL)) and whose bone marrow at remission exhibited a CMML phenotype, from which in both cases BPDCN clones arose that subsequently became treatment refractory.

  Study EGAS50000000214

• Dataset for WGS head and neck cancer samples

  This dataset contain WGS sequencing data of head and neck cancer samples as well as blood plasma controls. Sequencing was performed on Illumina Novaseq 6000 using KAPA HyperPrep Kit. The sequencing was always paired.

  Dataset EGAD50000000233

• DAC for "Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy"

  This is the DAC for "Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy" with Florian Janke f.janke@dkfz-heidelberg.de German Cancer Research Center, Division of Cancer Genome Research Holger Sültmann h.sueltmann@dkfz-heidelberg.de German Cancer Research Center, Division of Cancer Genome Research Magdalena Görtz magdalena.goertz@dkfz-heidelberg.de German Cancer Research Center, Multiparametric Methods for Early Detection of Prostate Cancer

  Dac EGAC50000000114

• Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype"

  Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype" with Name: Menghong Yin Email address: menghong.yin@dkfz-heidelberg.de Associated affiliation: Translational Skin Cancer Research Lab (DKFZ)

  Dac EGAC50000000168

• Clinical panel sequencing of cancer of unknown primary using Comprehensive cancer panel (CCP)

  This database includes comprehensive cancer panel (CCP) on paired tumour and germline DNA from cancer of unknown primary samples, all of which are matched to WGS data under this study. This data was used to compare biomarker yield against what was achieved with WGS. This dataset contains n=34 tumour-germline paired samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000655