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• WGS data for ctDNA monitoring for NSCLC in TRACERx

  Ultrasensitive circulating tumour DNA (ctDNA) detection can stratify clinical risk in early-stage non-small cell lung cancer (NSCLC). Here, we applied a whole-genome, tumour-informed approach to study ctDNA in more than 400 NSCLC of the TRACERx project

  Study EGAS50000001187

• Oxel Pilot Study

  This pilot study will provide preliminary data regarding the role of a peripheral immunoscore (PIS) in predicting the benefit of immune checkpoint inhibition with or without chemotherapy for high risk patients with triple-negative breast cancer (TNBC) and residual disease after effective neoadjuvant chemotherapy.

  Study EGAS50000000222

• Whole genome sequencing of mature B-cell lymphomas to identify MYC, BCL2, and BCL6 rearrangements

  Whole genome sequencing (WGS) data of 12 tumours was generated on an Illumina NovaSeq or HiSeqX instrument. For frozen samples, libraries were constructed using a PCR-free library construction method. For tumours preserved by formalin fixation and paraffin embedding (FFPE), libraries were constructed with a method that included S1 nuclease treatment. Reads were aligned to the grch37 reference with bwa-mem 0.7.17.

  Dataset EGAD50000000474

• WHOLE GENOME SEQUENCING FOR THE CHARACTERIZATION OF CLEAR CELL RENAL CELL CARCINOMA IN VHL PATIENT

  To characterize clear cell Renal Cell Carcinoma (ccRCC), we set up a comprehensive multi-omics pilot study on a VHL-ccRCC-patient. Whole Genome Sequencing (WGS) was applied on six ccRCCs, four cysts and one blood DNA sample as germinal control. Raw-data were analyzed with GENomics-DRAGEN platform. We will upload WGS-Data for 11 samples (6 ccRCCs, 4 Cysts, 1 blood).

  Dataset EGAD50000000425

• WTCCC2 Reading and Mathematics (RM) samples

  A WTCCC2 project genome-wide association study for reading and mathematics ability in 3665 12-year-old individuals from the UK, genotyped on the Affymetrix 6.0 array. Details of the WTCCC2 analysis can be found in Davis et al. [Nat. Commun. 2014 July;5:4204]

  Study EGAS00001000886

• Advanced molecular neuropathology to increase diagnostic accuracy in pediatric neurooncology

  To assess their utility in routine neuropathology, we prospectively integrated DNA methylation-based CNS tumor classification and targeted gene panel sequencing of tumor and constitutional DNA with blinded neuropathological reference diagnostics for a population-based cohort of > 1,200 newly-diagnosed pediatric patients.

  Study EGAS00001006680

• Fine-mapping clustered GWAS hits enhances the identification of disease risk and protective genetic variants

  This dataset contains: 1) Raw FASTQ and BAM files for short reads. Here, DNA libraries were prepared using Nextera Rapid Capture Custom Enrichment kit (Illumina) and paired-end sequenced on a HiSeq2500 (Illumina). 2) Raw FASTQ and BAM files for long reads. Here, DNA libraries were prepared using 1D DNA ligation Sequencing Kit (SQK-LSK109, Oxford Nanopore) and single-end sequenced on a MinION device (Oxford Nanopore).

  Dataset EGAD00001006916

• Enhanced Detection of Landmark Minimal Residual Disease in Lung Cancer using Cell-Free DNA Fragmentomics

  The circulating tumor DNA (ctDNA) mutation-based approach shows limited performance in minimal residual disease (MRD) detection, especially for landmark MRD detection at an early-stage cancer after surgery. Here, A total of 87 NSCLC patients, who received curative surgical resections (23 patients relapsed during follow-up), enrolled in this study. A total of 163 plasma samples, collected at 7 days and 6 months postsurgical, were used for high-throughput sequencing.

  Dataset EGAD00001010300

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Dataset EGAD50000000226

• Uncovering the potential of circulating tumor DNA for pediatric precision oncology

  Pediatric solid high-risk malignancies mostly lack molecular biomarkers for early tumor detection, assessment of minimal residual disease or therapy monitoring. Small patient numbers, limited sample volumes, low tumor mutational burden, and few recurrent alterations in pediatric tumors pose further challenges to liquid biopsy analyses for this patient population. Within the prospective, multinational molecular profiling program INFORM, we collected liquid biopsies from 130 children patients followed by optimized isolation of cell-free DNA (cfDNA). CfDNA was subjected to whole-genome, whole-exome, and targeted panel sequencing applying liquid biopsy-adapted protocols. Integration with tissue-derived molecular information and orthogonal comparison revealed low-coverage whole genome sequencing (lcWGS) as a reliable method for tumor detection. In silico integration of fragment length with differentially weighted genome segment alterations into a ctDNA estimation score (CES) significantly increased sensitivity and specificity to 95% and allowed for plasma-based tumor detection in 93% of patients. Performance of whole exome sequencing (WES) and panel sequencing for detection of molecular targets being predictive for matched treatment responses varied between groups of high-risk entities and cumulative evidence for presence of cancer by all three methods was found in 92% of patients. In-depth analyses for selected patients also demonstrated great the potential of liquid biopsies to decipher temporal and spatial tumor evolution. This study establishes improved methods for liquid biopsy analyses in pediatric oncology and provides the rationale for well-informed implementation of these approaches in future clinical trials to improve the clinical management of high-risk pediatric cancer patients.

  Study EGAS50000000393