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• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211

• DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy"

  DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy" with Florian Janke (f.janke@dkfz-heidelberg.de) and Holger Sültmann (h.sueltmann@dkfz-heidelberg.de)

  Dac EGAC50000000308

• The dataset for Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  The dataset for “Detection of brain cancer using genome-wide cell-free DNA fragmentomes” includes 310 bam files from whole genome next-generation sequencing on the Illumina Novaseq 6000. The dataset analyzed include plasma cfDNA samples from patients with cancer, patients with neurological conditions, and healthy individuals.

  Dataset EGAD50000001445

• Epigenetic analyses of methylation and nucleosome occupancy in cell-free DNA (cfNOMe)

  Cell-free DNA (cfDNA) has become essential in cancer diagnostics and prenatal testing. We investigate enzymatic cytosine conversion for epigenetic analyses of cfDNA and find that it reliably measures cytosine methylation and nucleosome occupancy. Whereas previously, separate experiments had to be performed to study either epigenetic marking, this approach delivers reliable results for both, enabling more comprehensive and inexpensive epigenetic profiling of cfDNA.

  Study EGAS00001004370

• Longitudinal Study of Vaginal Flora

  This prospective observational study aims to advance our knowledge of the natural history and abnormal alteration in vaginal microbial flora, and to identify risk factors that are associated with these changes. A total of 5500 healthy, non-pregnant women of reproductive age will be enrolled and followed up in Birmingham, Alabama, for one year (baseline visit plus once every three months afterwards, totaling 5 visits). Detailed information on sociodemographic status, medical history, hygiene practice, sexual behavior and psychosocial stress will be collected through in-person interviews. Routine gynecological and dental examinations will be carried out during the study visits. Samples of vaginal secretion and blood will be collected. Laboratory tests to quantify vaginal microbial flora and to identify infection of bacterial vaginosis as well as common sexually transmitted diseases will be conducted. Future submissions may contain metadata or molecular data from additional subjects.

  Study phs002367

• Stress and Treatment Response in Puerto Rican and African American Children with Asthma (STAR)

  The Stress and Treatment Response in Puerto Rican and African American Children with Asthma Study (STAR) was a 6-week study of response to inhaled corticosteroids (ICS) in youth aged 8-20 years recruited at the University of Puerto Rico Medical Center and UPMC Children's Hospital of Pittsburgh from June 5, 2018 to May 16, 2022. At a baseline visit, participants completed questionnaires and underwent collection of nasal specimens. After nasal sampling, participants were treated with daily medium-dose inhaled Mometasone for 6 weeks, with adherence measured using a dose-counter. Spirometry and fractional exhaled nitric oxide (FeNO) measurements were conducted at baseline and after 6 weeks of ICS. STAR was approved by the institutional review boards (IRBs) of the University of Puerto Rico and the University of Pittsburgh. Written parental consent and assent were obtained from participants

  Study phs004052

• A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

  The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect. The full dataset includes FASTQ files, target BED file, and MLPA results.

  Study EGAS00001002428

• T cell receptor repertoire in cell-free DNA as a proxy for tumor infiltrates in patients treated with pembrolizumab

  Bulk TCR sequences from tumor, peripheral blood mononuclear cell (PBMC), and cell-free DNA (cfDNA) samples from 81 patients with solid tumors treated with pembrolizumab.

  Dataset EGAD50000001857

• The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer

  The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer includes 57 BAM files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010891

• Prostate cancer datasets WGS

  Low pass WGS: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (Next Seq )

  Dataset EGAD00001004466