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• Sensitive and robust liquid biopsy-based detection of PIK3CA mutations

  Over the last years, the treatment of hormone receptor-positive metastatic breast cancer patients has dramatically changed. Combination strategies attempting to overcome resistance to endocrine therapy such as targeting the PI3 kinase pathway are gaining importance. The phase III SOLAR-1 trial demonstrated the benefit of the addition of alpelisib to fulvestrant, thereby providing further clinical evidence of the increasing importance of PIK3CA testing. Here, we performed a comparison of liquid biopsy and tissue-based detection of PIK3CA mutations in HR-positive metastatic breast cancer patients. Plasma samples and the latest available tumor tissue from 69 patients with metastatic hormone-receptor positive breast cancer were analyzed for PIK3CA hotspot mutations. A high-resolution NGS assay (SiMSen-Seq) was used for plasma samples covering 11 recurrent PIK3CA mutations, used for stratification in SOLAR-1. Additionally, mFAST-SeqS was used to estimate the tumor fractions in the plasma samples. For tumor tissue samples, targeted Ion Torrent NGS was employed. Matched tissue and plasma samples were available from 63 patients. PIK3CA mutations were detected in 46.1% of the tissue samples and in 50.7% of the plasma samples. The variant allele frequency (VAF) ranged from 4.36% to 72.93% with a median of 28.60% in tissue samples, and from 0.28% to 49.85% with a median of 1.17% in plasma samples. The most frequent variants in tissue and plasma were H1047R, E545K, and E542K. We detected at least one of 11 PIK3CA mutations from the SOLAR-1 trial in 51/63 patients, both in tissue and plasma. In 7 patients, such mutations were found only in plasma. In 5 patients, PIK3CA mutations found in tissue were not detectable in ctDNA, 2 of which had a low tumor fraction.Together, in 33/67 plasma samples without detectable PIK3CA mutations, 18 samples had elevated tumor fraction, implicating true negative results. In the remaining 15 patients with low tumor fraction, additional tissue analysis was needed. SiMSen-Seq-based detection of PIK3CA mutations in plasma shows advantageous concordance with the tissue analyses. A combination with an untargeted, mutation-independent approach for detecting ctDNA fractions may confirm a negative PIK3CA result and thereby enhance the performance of the SiMSen-Seq test. This combinatory approach for selecting suitable patients for alpelisib treatment should be validated in larger patient cohorts.

  Study EGAS00001004940

• Analysis of cell type contributions to cell free DNA in health and disease.

  This study looks at cell type contributions to cell free DNA in health and disease.

  Study EGAS50000000178

• Processing of tissue and cfDNA samples of CRC patients using Active-seq

  In this study, we have developed a novel technology called Active-Seq (Azide Click Tagging for In Vitro Epigenomic sequencing), a base conversion-free technology used to profile the DNA methylation status of a sample, based on the isolation of DNA containing unmodified CpG sites using a mutated bacterial methyltransferase enzyme and a synthetically prepared cofactor analogue. We procured samples from colorectal cancer (CRC) patients including tumour tissue as well as normal adjacent tissues. The data enabled us to identify CRC-specific markers that could then be used to track and monitor the presence of tumour DNA in cell-free DNA plasma (cfDNA) samples procured in the same patients. The FASTQ files of all the colorectal cancer tissues, normal adjacent tissues as wells as the cfDNA samples are available in this submission. The data made available in this study have been used to outline an approach for tumour-informed disease profiling in colorectal cancer cfDNA samples using Active-Seq.

  Study EGAS50000001226

• cfDNA in health

  This study investigates baseline methylome and fragmentomic profiles in circulating cell-free DNA (cfDNA) from healthy individuals. Two cohorts were assembled: a diurnal cohort to evaluate temporal variation in cfDNA features, and a cross-sectional cohort to assess inter-individual variability. The project’s goal was to generate a reference dataset for plasma cfDNA to support future studies in biomarker discovery and disease detection.

  Study EGAS50000001209

• Multimodal epigenetic sequencing analysis of cell-free DNA identifies biomarkers for ALS diagnosis and progression

  The role of the epigenome in age-related neurodegenerative disorders remains understudied. Here, we analyzed circulating cell-free DNA (cfDNA) from blood to detect methylation changes as a liquid-biopsy for Amyotrophic Lateral Sclerosis (ALS). Our study included 20 patients with sporadic ALS, 10 patients with C9orf72-associated ALS, 10 asymptomatic carriers of the C9orf72 repeat expansion mutation, and 21 non-disease controls.

  Dac EGAC50000000739

• Single cell RNAseq of stenotic, inflamed and non-inflamed transmural lesions from patients with Crohn's disease

  This dataset contains a gene-cell matrix derived from single-cell RNA sequencing (scRNA-seq) data of ileal tissue from Crohn's disease (CD) patients and colorectal cancer (CRC) patients. It includes: Crohn's Disease Patients: A trio of transmural lesions (stenotic, inflamed, and non-inflamed) from each patient. Colorectal Cancer Patients: Unaffected ileal tissue used as external non-inflamed control. Cell Level Metadata: The dataset includes relevant cell-level metadata such as cell type annotations used in the study. Experimental Details: Platform: 10x Genomics Chromium Single Cell 3' GEX Sequencing: Illumina NovaSeq Processing: Data processed with Cell Ranger software. Resulting count matrices were merged for downstream analysis, including integration and dimensionality reduction. Dataset Composition: Crohn's Disease Patients: 10 patients with 3 samples each (non-inflamed, inflamed, stenotic), totaling 30 samples. Colorectal Cancer Patients: 5 patients with 1 sample each of unaffected tissue, totaling 5 samples. Data Provided: Merged Raw Count Matrix: The final merged raw count matrix used for downstream analysis. Cell Metadata File: Contains details of sample, tissue, and patient for each cell in the count matrix. Barcodes File: Indicate each cell barcode which also encodes the sample, tissue, and patient details for each cell. CD.S_Inf: Stenotic Corhn's disease inflamed samples CD.S_Sten: Stenotic CD patient stenosis sample CD.S_Prox: Stenotic CD Patient - proximal non-inflamed sample CC.C_Prox: CRC Patient proximal unaffected sample eg: A barcode 'CC.C_1_Prox_AAGTCGTAGACCCTTA' indicates CRC Patient unaffected proximal sampe from CRC Patient no.1 and the nucleic acid sequence indicate a unique cell from this sample. Total Samples: Crohn's Disease (CD) Patients: 30 samples Colorectal Cancer (CRC) Patients: 5 samples Patient_no Sample Sample_type 1 CC.C_1 CC.C_1_Prox CC.C_Prox 2 CD.S_1 CD.S_1_Prox CD.S_Prox 3 CD.S_1 CD.S_1_Infl CD.S_Infl 4 CD.S_1 CD.S_1_Sten CD.S_Sten 5 CC.C_2 CC.C_2_Prox CC.C_Prox 6 CD.S_2 CD.S_2_Prox CD.S_Prox 7 CD.S_2 CD.S_2_Infl CD.S_Infl 8 CD.S_2 CD.S_2_Sten CD.S_Sten 9 CC.C_3 CC.C_3_Prox CC.C_Prox 10 CC.C_4 CC.C_4_Prox CC.C_Prox 11 CD.S_3 CD.S_3_Prox CD.S_Prox 12 CD.S_3 CD.S_3_Infl CD.S_Infl 13 CD.S_3 CD.S_3_Sten CD.S_Sten 14 CD.S_4 CD.S_4_Prox CD.S_Prox 15 CD.S_4 CD.S_4_Infl CD.S_Infl 16 CD.S_4 CD.S_4_Sten CD.S_Sten 17 CC.C_5 CC.C_5_Prox CC.C_Prox 18 CD.S_5 CD.S_5_Prox CD.S_Prox 19 CD.S_5 CD.S_5_Infl CD.S_Infl 20 CD.S_5 CD.S_5_Sten CD.S_Sten 21 CD.S_6 CD.S_6_Prox CD.S_Prox 22 CD.S_6 CD.S_6_Infl CD.S_Infl 23 CD.S_6 CD.S_6_Sten CD.S_Sten 24 CD.S_7 CD.S_7_Prox CD.S_Prox 25 CD.S_7 CD.S_7_Infl CD.S_Infl 26 CD.S_7 CD.S_7_Sten CD.S_Sten 27 CD.S_8 CD.S_8_Prox CD.S_Prox 28 CD.S_8 CD.S_8_Infl CD.S_Infl 29 CD.S_8 CD.S_8_Sten CD.S_Sten 30 CD.S_9 CD.S_9_Prox CD.S_Prox 31 CD.S_9 CD.S_9_Infl CD.S_Infl 32 CD.S_9 CD.S_9_Sten CD.S_Sten 33 CD.S_10 CD.S_10_Prox CD.S_Prox 34 CD.S_10 CD.S_10_Infl CD.S_Infl 35 CD.S_10 CD.S_10_Sten CD.S_Sten

  Dataset EGAD50000000559

• cell-free Methylated DNA by Immunoprecipitation and Sequencing (cfMeDIP) of human meningioma samples.

  Raw data for cell-free Methylated DNA by Immunoprecipitation and Sequencing (cfMeDIP) of human meningioma samples.

  Study EGAS50000001539

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the "Substudies" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735.

  Study phs001194

• Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome

  Background The methylation pattern of cfDNA, isolated from liquid biopsies, is gaining substantial interest for diagnosis and monitoring of diseases. We have evaluated the impact of type of blood collection tube and time delay between blood draw and plasma preparation on bisulfite-based cfDNA methylation profiling. Methods 15 tubes of blood were drawn from three healthy volunteer subjects (BD Vacutainer K2E EDTA spray tubes, Streck Cell-Free DNA BCT tubes, PAXgene Blood ccfDNA tubes, Roche Cell-Free DNA Collection tubes and Biomatrica LBgard blood tubes in triplicate). Samples were either immediately processed or stored at room temperature for 24 or 72 hours before plasma preparation. DNA fragment size was evaluated by capillary electrophoresis. Reduced representation bisulfite sequencing was performed on the cell-free DNA isolated from these plasma samples. We evaluated the impact of blood tube and time delay on several quality control metrics. Results All preservation tubes performed similar on the quality metrics that were evaluated. Furthermore, a considerable increase in cfDNA concentration and the fraction of it derived from NK cells was observed after a 72-hour time delay in EDTA tubes. Conclusion The methylation pattern of cfDNA is robust and reproducible in between the different preservation tubes. EDTA tubes processed as soon as possible, preferably within 24 hours, are the most cost effective. If immediate processing is not possible, preservation tubes are valid alternatives.

  Study EGAS00001004271

• Characterization of Cell Free Plasma Methyl-DNA From Xenografted Tumors to Guide the Selection of Diagnostic Markers for Early-Stage Cancers

  Circulating cell-free methyl-DNA (mcfDNA) contains promising cancer markers but its low abundance and possibly diverse origin pose challenges toward the accurate diagnosis of early stage cancers. By whole-genome bisulfite sequencing (WGBS) of cell-free DNA (cfDNA) from about 0.5 mL plasma of mice xenografted with human tumors, we obtained and aligned the reads to the human genome, filtered out the mouse and carrier bacterial sequences, and confirmed the tumor origin of methyl-cfDNA (mctDNA) by methylation-sensitive restriction enzyme digestion prior to species-specific PCR. We estimated that human tumor-specific reads (ctDNA) or mctDNA comprised about 0.29 or 0.01%, respectively of the xenograft mouse cfDNA, and about 0.029 or 0.001% of the cfDNA of human early stage cancer patients. Similar WGBS of early stage (0-II, node- and metastasis-free) breast, lung or colorectal cancer samples identified hundreds of specific DMRs (differentially methylated regions) compared to healthy controls. Their association with tumourigenesis was supported by stage-dependent methylation, tumor suppressor or oncogene clusters, and genes also identified in the xenograft samples. Using 20 three-cancer-common and 17 colorectal cancer-specific DMRs in combination (top 0.0018% of the WGBS methylation clusters) was sufficient to distinguish the stage I colorectal cancers from breast and lung cancers and healthy controls. Our data thus confirmed the tumor origin of mctDNA by sequence specificity, and provide a selection threshold for authentic tumor mctDNA markers toward precise diagnosis of early stage cancers solely by top DMRs in combination. Biological Materials were provided by the Ontario Tumour Bank, which is funded by the Ontario Institute for Cancer Research Reference for citation: Ling Liu, Jinghua Feng, Julian Polimeni, Manli Zhang, Hai Nguyen, Urmi Das, Xu Zhang, Harminder Singh, Xiao-Jian Yao, Etienne Leygue, Sam K.P. Kung, and Xie J. Characterization of cell free plasma methyl-DNA from xenografted tumours to guide the selection of diagnostic markers for early-stage cancers. Frontiers in Oncology, 2021 Feb. 5. DOI: 10.3389/fonc.2021.615821.

  Study EGAS00001006175