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• Center for Common Disease Genomics (CCDG) - Cardiovascular: eMERGE - Northwestern Cohort

  The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study contains variant calls derived from the whole genome sequence data of an early-onset coronary artery disease case-control cohort selected from the NUgene Project biobank at Northwestern University. Case status was assigned based on the presence of myocardial infarction, coronary artery stenosis greater than 70% in at least one coronary artery, and/or revascularization (coronary angioplasty with or without stent placement or coronary artery bypass grafting) at an early age. In this study "early age" is defined as men 60 years of age or younger and women 70 years of age or younger.

  Study phs001913

• Genomic Tumor Correlates of Clinical Outcomes Following Organ-Sparing Chemoradiation Therapy for Bladder Cancer

  Bladder preservation with trimodality therapy (TMT), consisting of transurethral tumor resection followed by chemoradiation, is an alternative to radical cystectomy for muscle-invasive bladder cancer (MIBC), but molecular determinants of response are poorly understood. Patients with cT2-T4aN0M0 MIBC treated with definitive-intent chemoradiation as part of TMT were retrospectively identified from a single institution between 1986-2015. Pre-treatment Formalin Fixed Paraffin Embedded (FFPE) tumors from 76 MIBC patients were subjected to whole exome sequencing (WES). Our integrated analysis yielded insights into molecular features associated with favorable long-term response to TMT, including alterations in DNA damage response genes. Of these, mutations in ERCC2, a DNA helicase in the nucleotide excision repair pathway, were significantly associated with improved long-term outcomes after TMT, particularly in patients who received concurrent cisplatin-based chemotherapy.

  Study phs003402

• Spatiotemporal Charting of Human Esophageal Development for Epidermolysis Bullosa Cell Therapy

  Human fetal esophageal development is not well understood. We present a spatio-temporal single-cell multi-omics atlas to close such a long-standing knowledge gap. With such an atlas, we describe the cellular heterogeneity and lineage transitions of esophageal epithelium and stroma. We delineate the cellular dynamics of both epithelial and stromal populations during the establishment of esophageal tissue architecture. We identify niche paracrine signals that drive the development of the epithelium. We develop an in silico perturbation deep learning algorithm to further enlighten the in vitro derivation of esophageal basal cells (eBCs) and we use the algorithm to screen for effective and efficient signaling pathway perturbations that could guide in vitro eBC differentiation. We observe that chemically perturbing prioritized pathways yields functional eBCs. Such success sheds light on cell replacement therapy of eBC dysfunction, such as Epidermolysis Bullosa.

  Study phs003281

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• How mitochondrial DNA research can benefit from data reuse through EGA?

  Mitochondria are the only cellular organelles harbouring their own DNA, which encodes for proteins essentials in its respiration process. Despite its discovery in 1960, Mitochondrial DNA is often overlooked compared to nuclear DNA. Indeed, not all sequencing technologies capture a good representation of mtDNA (mitochondrial DNA). Recently, Ed Reznik's team (The Ed Reznik Lab | Memorial Sloan Kettering Cancer Center) carried out a massive analysis and reanalysis of single cells WGS (whole genome sequencing) produced with an amplification-free protocol (Direct library prep, DLP). As they demonstrated in the paper Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes - PMC, DLP is more effective in catching mtDNA compared to classical single-cell sequencing. These data allowed the team to unravel mtDNA dynamics in tumoral and normal samples, highlighting how mtDNA and nuclear DNA are co-regulated and their ratio is critical for phenotype. Data reuse to achieve the greatest results For this project, Reznik's team re-used data from 3 studies stored at the European Genome-phenome Archive (EGAS00001006343, EGAS00001004448 and EGAS00001003190) that comprised a total of 602 datasets. All of them were initially produced by the teams of Sam Aparicio and Sohrab P. Shah at the Memorial Sloan Kettering Cancer Centre, where Ed Reznik is a promising group leader. This demonstrates, once again, that networking, collaboration and data sharing can achieve the greatest results when coupled with innovative and smart ideas. At the EGA we are proud to provide the scientific community with an infrastructure to enable all those very smart ideas out there to find the right data to be tested.

  Blog mitochondrial-dna-research

• Ensilication as a Cold‑Chain–Free Solution for High‑Fidelity DNA Preservation in tumor samples

  Nucleic acid preservation requires continuous refrigeration at -20 °C to -80 °C, creating infrastructure barriers limiting genomic medicine access globally. While ambient-temperature preservation methods exist, their effects on DNA integrity and sequence fidelity remain incompletely characterized. The project aims to evaluate ensilication as a method for preserving DNA at ambient temperatures and to determine whether it can match or exceed the fidelity of conventional ultra‑low‑temperature storage. It seeks to assess the technology’s ability to maintain diagnostic accuracy, including detection of clinically actionable variants in tumor samples. Another goal is to compare sequencing‑related artifact rates between ensilicated and cryogenically stored DNA to quantify improvements in data quality. Ultimately, the project aims to establish ensilication as a cold‑chain‑independent solution that enables more accessible global genomic testing and biobanking.

  Study EGAS50000001698

• BLUEPRINT ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  ChIP-seq data for cells in the haematopoietic lineages, from adult and cord blood samples.

  Study EGAS00001000326

• Pilot study for Illumina TST170 NGS panel on cutaneous T cell lymphoma samples

  A number of genomic studies using next generation sequencing (NGS) techniques have attempted to understand the underlying genetic basis of cutaneous T-cell lymphoma and found alterations in genes that are involved in T-cell activation, NF-kB and JAK-signal transducer and activator of transcription (STAT) pathways. 8 diagnostic skin biopsy samples (2xplaque, 6xtumour) on FFPE blocks were selected from 8 MF patients (stage IB:n=1, IIB:n=6, IVA2:n=1). An H&E was performed in order to assess percentage of tumor cells, viable cells, necrosis and immune infiltration, to determine the number of slides required for NGS. Freshly cut unstained slides were manually macrodissected prior to DNA and RNA extraction. Targeted deep sequencing was performed using panel of 170 genes associated with common solid tumours (Illumina TruSight Tumour 170 NGS panel). VCF files generated via the Illumina’s Basespace platform.

  Study EGAS00001002567

• WGS and WTS data of patients diagnosed with MEITL.

  WGS from 4 patients, WTS from only 3 patients (insufficient tissue from 4th patient for WTS). Whole-genome sequencing (WGS) was performed for 60 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000. Whole-transcriptome sequencing (WTS): Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on Illumina HiSeq 2500 with 2x101 bp read length. Description of prefix used in filenames: T: Tumor samples N: Normal samples (Blood) P: PDX samples

  Dataset EGAD00001005341

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Dataset EGAD00001006293