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• SNP data for Breast cancer PRS

  SNP data for 313 loci required for calculation of the Breast cancer PRS

  Dataset EGAD00001008144

• Whole Genome Sequence and RNASeq Samples for Lung Cancer

  Short Read Whole Genome Sequence and RNASeq Samples for Lung Cancer

  Study EGAS00001007832

• Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized controlled trial AGITG-MAX

  Patients and methods: We analyzed tumor samples of 256 patients enrolled in the AGITG-MAX 3-arm randomized controlled trial (RCT) who were randomly assigned to receive either capecitabine, or capecitabine and bevacizumab with- or without mitomycin. Chromosome 18q11.2-q12.1 copy number status was measured and correlated with PFS according to a predefined analysis plan with marker-treatment interaction as the primary end-point.Results: Chromosome 18q11.2-q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the non-randomized study, significant PFS benefit of bevacizumab was observed in chromosome 18q11.2-q12.1 loss patients (P=0.009), and not in 18q no-loss patients (P=0.67). Although significance for marker-treatment interaction was not reached (Pinteraction = 0.28), hazard ratio and 95% confidence interval (HRinteraction 0.72, CI 0.39 - 1.32) show striking overlap with the non-randomized study cohorts (HRinteraction 0.41, CI 0.32 - 0.8) supported by a non-significant Cochrane chi-squared (P=0.11) for heterogeneity. Conclusions: PFS characteristics for marker positive- and negative patients randomized for treatment with- or without bevacizumab were consistent with those of the non-randomized discovery study, though the number of AGITG-MAX samples fell short to reach significance for marker-treatment interaction. Post-hoc analysis of the AGITG-MAX RCT provides supportive evidence for chromosome 18q11.2-q12.1 as a clinically relevant predictive marker for mCRC patients.

  Study EGAS00001005453

• Dataset for COPD human sputum 16S rRNA gene sequencing data

  Dataset for 16S rRNA gene sequencing data for sputum samples 61 COPD patients, generated using PacBio sequencing technology.

  Dataset EGAD00001009103

• WTCCC case-control study for Multiple Sclerosis - Combined controls

  WTCCC genome-wide accosication study for Multiple Sclerosis (MS) - Combined controls

  Study EGAS00000000023

• Container Study for ICGC Malignant Lymphoma Master Study (MMML)

  Master Container Study for Malignant Lymphoma data (ICGC - Germany)

  Study EGAS00001001600

• Data Access Committee for Maurice Lab - UMC Utrecht

  The Data Access Committee of the Maurice lab at the Center for Molecular Medicine, University Medical Center Utrecht, is responsible for reviewing and approving requests for access to controlled human transcriptomics and genomics data generated by the lab. The DAC ensures that data access requests are consistent with informed consent, ethical approvals, and applicable legal and institutional regulations, including GDPR.

  Dac EGAC50000000876

• Comparison between phenotypic-defined stage of blasts and transcriptional profile

  Established a proof-of-concept methodology with potential integration into flow cytometry software for objective AML subtype classification based on blast differentiation, offering valuable prognostic insights for elderly patients.

  Study EGAS50000000336

• An efficient and comprehensive strategy for genetic diagnostics of polycystic kidney disease

  We established and validated sequence capture based NGS testing approach for all genes known for cystic and polycystic kidney disease including PKD1. This setup overcomes the complication of unspecific capture of pseudogenes by applying a mapping algorithm efficiently and specifically aligning reads to the PKD1 locus.

  Study EGAS00001001003

• Whole genome sequencing of matched patient sample sets of normal and tumor DNA

  Sixteen matched, male and female patient sample sets, each comprising normal DNA, tumor DNA, and RNA, were processed for storage comparison studies. Upon receipt, 10 μl quality control aliquots were prepared from each sample. DNA samples were characterized using Qubit dsDNA High Sensitivity assay for quantification, Genomic DNA TapeStation for integrity assessment (DIN scores), and NanoDrop for purity evaluation. RNA samples were analyzed using Qubit RNA High Sensitivity assay, RNA TapeStation (RIN scores), and NanoDrop. Each sample was divided equally by volume for parallel processing.

  Dataset EGAD50000002441