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• ChIP-seq in colorectal cancer and paired adjacent normal mucosa

  This dataset includes ChIP-seq data for H3K27ac and H3K4me1 on 20 paired samples of colorectal cancer and adjacent normal mucosa. One tumor sample that failed QC is not available.

  Dataset EGAD00001007707

• Evolution of Core Archetypal Phenotypes in High-Grade Serous Ovarian Cancer (HGSOC)

  The evolution of resistance in high-grade serous ovarian cancer (HGSOC) cells in response to chemotherapy is only partially understood. To uncover phenotypic changes associated with chemotherapy resistance, we performed single-cell RNA-sequencing (scRNA-seq) or whole-genome sequencing of 23 total patients, with longitudinal samples collected from 9, treatment-naïve samples from 8 patients, and post-treatment samples from 6 patients. Our study revealed that the HGSOC transcriptome could be described using three core archetypal phenotypes, defined as oncogenic tasks that describe majority of the transcriptional data. We implemented a multi-task learning approach to identify the biological tasks of each archetype and identified metabolism and proliferation, cellular defense response, and DNA repair signaling. The “metabolism and proliferation” archetype evolved during treatment and was enriched in cancer cells from patients that received multiple-lines of treatment and had elevated tumor burden indicated by CA-125 levels. The emergence of archetypes was not consistently linked to specific whole-genome driver mutations. However, archetypes were closely associated with sub-clonal clusters at the single-cell level, indicating that cancer cell sub-populations specialize in particular biological tasks. Our study reveals a defining principle of ovarian tumor evolution using temporal scRNA-seq profiles, identifies the key phenotypic features across patients and links metabolic shifts with a response to chemotherapy.

  Study phs002294

• PD-L1 blockade immunotherapy rewires cancer-induced emergency myelopoiesis

  Introduction Immune checkpoint blockade (ICB) immunotherapy has revolutionized cancer treatment, demonstrating exceptional clinical responses in a wide range of cancers. Despite the success, a significant proportion of patients still fail to respond, highlighting the existence of unappreciated mechanisms of immunotherapy resistance. Delineating such mechanisms is paramount to minimize immunotherapy failures and optimize the clinical benefit. Methods In this study, we treated tumour-bearing mice with PD-L1 blockage antibody (aPD-L1) immunotherapy, to investigate its effects on cancer-induced emergency myelopoiesis, focusing on bone marrow HSPCs. We examined the impact of aPD-L1 treatment on HSPC quiescence, proliferation, transcriptomic profile, and functionality. Results Herein, we reveal that aPD-L1 in tumour-bearing mice targets the hematopoietic stem and progenitor cells (HSPCs) in the bone marrow (ΒΜ), mediating their exit from quiescence and promoting their proliferation. Notably, disruption of the PDL1/PD1 axis induces transcriptomic reprogramming in HSPCs, observed in both individuals with Hodgkin lymphoma (HL) and tumour-bearing mice, shifting towards an inflammatory state. Furthermore, HSPCs from aPDL1-treated mice demonstrated resistance to cancer-induced emergency myelopoiesis, evidenced by a lower generation of MDSCs compared to control-treated mice. Discussion: Our findings shed light on unrecognized mechanisms of action of ICB immunotherapy in cancer, which involves targeting of BM-driven HSPCs and reprogramming of cancer-induced emergency myelopoiesis.

  Study EGAS00001007873

• Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

  Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1 and IL-1. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

  Study EGAS50000000490

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• Ultrasensitive detection of minor allele fractions in maternal samples based on microhaplotype analysis

  Background: Tools for quantifying and studying genetic variation in heterogeneous cell populations have a limited sensitivity. However, many biological problems require ultrasensitive genetic deconvolution of cell mixtures. The detection of fetal cells in cervical samples from pregnant women presents such a challenge. Methods: Using deep sequencing of microhaplotype loci and analysis of the error profiles in genetically pure and mixed samples, we increase the sensitivity for minor allele detection and demonstrate the potential for paternal allele detection in cervical samples from pregnant women. Results: Using artificial DNA mixtures, we show that unique alleles can be readily identified in mixtures with a ratio of 1 in 10,000 (0.01%). By applying this method on ten non-invasive cervical samples from pregnant women we could identify the presence of paternal alleles in half of the samples. Unexpectedly, we demonstrate those alleles not to be of fetal origin but of sperm. Conclusions: We developed a novel method that can deconvolute genetic mixtures to at least 0.01%, which can be applied to study minor allele fractions in genetic mixtures and, for example, could aid in trophoblast cell detection in maternal blood or cervix. Our results demonstrate the importance of discriminating fetal and paternal alleles when analyzing cervical fetal cells and may pinpoint a potential cause of erroneous results in previous trophoblast isolation studies.

  Study EGAS00001007057

• Whole Exome Sequencing of healthy Spanish individuals

  The need for a detailed catalogue of local variability for the study of rare diseases within the context of the Medical Genome Project motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population.

  Study EGAS00001000938

• Linguistic utterance counts for The admixture histories of Cabo Verde

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_225CaboVerde_FreeSpeech_Utterance_counts_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See See Material and Methods in Romain Laurent et al. 2022 - doi pendingColumn 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file. Note that only 225 unrelated Cabo Verdean-born individuals are considered here, out of the 233 individuals in the genotype file. See Material and Methods in Romain Laurent et al. 2022 - doi pending Each 4831 other column correspond to the respective individual's utterance count in the free speech transcribed in ALUPEC and provided as column header. See Material and Methods in Laurent R et al. eLife 2023

  Dataset EGAD00001008978

• Subclonal diversification of primary breast cancer

  Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

  Dataset EGAD00001000965

• M116 CHIP Amplicon Sequencing

  Genomic DNA was obtained from M116 peripheral blood sample and was used for targeted deep sequencing (TDS) studies. Barcoded libraries were prepared according to the manufacturer’s instructions, using a probe-based panel (KAPA HyperCap, Roche®) targeting frequently mutated regions of 50 myeloid-related genes. Samples were run on a MiSeq (Illumina®) sequencer for paired-end 2x75 bp reads with a mean coverage of 1000X.

  Dataset EGAD50000001287

• Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors

  Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of various cancers but its utility in renal cell cancer (RCC) has not been well established. A combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n=90) with various renal tumour subtypes, were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of ~33% for both cohorts. A highly sensitive personalised approach, applied to plasma and urine from select patients (n=22), improved detection to ~50%, including in patients with early stage and even benign lesions. A machine-learning based model, applied to untargeted data, predicted this detection, potentially offering a means of triaging patient samples for personalised analysis. We observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than a single tissue biopsy. Longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. These data highlight low ctDNA levels in RCC but indicate potential clinical utility provided improvement in isolation and detection approaches.

  Study EGAS00001003530

• Study on rectal mucus sampling for colorectal cancer diagnostics

  DAC for a study on rectal mucus sampling for colorectal cancer diagnostics

  Dac EGAC50000000643

• Cell-type, allelic and genetic signatures in the human pancreatic beta cell transcriptome

  Pancreatic beta cells within the islets of Langerhans are centrally involved in the pathogenesis of both type 1 and type 2 diabetes. Describing the differentiated state of the human beta cell has been hampered so far by technical (low resolution microarrays) and biological limitations (whole islet preparations rather than isolated beta cells). We circumvent these by deep RNA sequencing of purified beta cells from 11 individuals, presenting here the first characterization of the human beta cell transcriptome. Additionally, we perform the first comparison of gene expression profiles between beta cells, whole islets (N=7) and beta cell depleted islet preparations (N=5), revealing thus beta cell specific expression signatures. Finally, we combine this with whole-genome sequencing data for 7 of our donors, describing here the first set of genetic variants controlling inter-individual variability in beta cell gene expression.

  Study EGAS00001000442

• Whole transcriptome RNA sequencing on bone marrow and peripheral blood samples from patients with acute myeloid leukemia at diagnosis or relapse.

  One hundred cryopreserved bone marrow and peripheral blood samples from patients with acute myeloid leukemia (AML) with 10-90% blasts were selected from the biobank of the Department of Hematology of Leiden University Medical Center (LUMC). The AML cases cover all subtypes, and specifically include known subtype-defining balanced chromosomal translocations according to the WHO classification. The samples were obtained from 96 patients and include three pairs of de novo and relapsed AML and one pair of de novo and presumed therapy-related AML (tAML). Total RNA was isolated from mononuclear cells without prior enrichment for leukemic blasts. The quality and integrity of total RNA was checked and RNA libraries were prepared using the TruSeq RNA library preparation kit v2 (Illumina, San Diego, CA) in an ISO/IEC 17025-accredited protocol. This workflow started with enrichment of messenger RNA by oligo dT magnetic beads. After fragmentation, cDNA synthesis was performed, followed by adaptor ligation and PCR amplification. Paired-end sequencing with a read length of 126 bp was performed on an Illumina HiSeq 2500 v4 sequencer to at least 12.5 Gbp per sample. Image analysis, base calling, and quality check was performed with Illumina data analysis pipeline RTA v1.18.64 and Bcl2fastq v1.8.4. RNAseq reads are provided in compressed Sanger FASTQ format.

  Dataset EGAD00001004187

• Persistence of circulating tumor DNA in breast cancer patients during neoadjuvant treatment is a significant predictor of poor tumor response

  Purpose:Accurate assessment of response during neoadjuvant systemic treatment (NST) poses a major clinical challenge. Therefore, a minimally-invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions.Experimental Design: We profiled 93 genes in tissue from 193 early breast cancer patients. Patient-specific assays were designed to track ctDNA during NST from 145 patients with available plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as with clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release. Moreover, we tested the predictive value of driver events identified in the tumor.Results:At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR 0.062, 95% CI 0.01-0.48, P=0.0077). Out of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were non-responders (RCB II, n=8; RCB III, n=22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, while 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result. Conclusion:Overall, our results demonstrate that the detection and persistence of ctDNA at mid-therapy may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

  Study EGAS00001005798

• Genetic analysis in an inherited cardiac arrhythmia

  To identify a causative gene for an inherited cardiac arrhythmia, exome sequence analysis was conducted in 6 patients and 5 controls.

  Study JGAS000041

• Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Dataset EGAD00001011123

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

  Dataset EGAD00001004796

• (ATAC-seq) Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in endometriod carcinomas

  Raw and processed ATAC-seq data from the VOA1066 undifferentiated endometrial carcinoma cell-line (10 samples). Samples were treated with DMSO, dBRD9, or compound 12, without doxycycline; some samples instead received doxycycline-induced ARID1A treatment, or doxycycline alone. Samples were sequenced on Illumina NextSeq 500 using 37 bp paired-end sequencing parameters. Raw fastq fastq files, bigwig files giving normalized genomic coverage per region, and called broad peaks are included for each sample.

  Dataset EGAD50000001472

• Genetic differences between primary colorectal cancer and its paired synchronous and metachronous metastases

  This study contains data obtained from 210 CRC samples (87 pairs and 36 singletons for whom only one of the sample pair was available). Our sample set consisted of 105 primary tumor and 105 metastatic samples. Data are analysis-ready BAM files. Sequencing libraries were prepared with the SureSelect Human All Exon V8 kit by Agilent. Sequencing was done on NovaSeq X Plus instrument (Illumina, San Diego, CA, USA) using 150-bp paired-end reads.

  Dataset EGAD50000001460

• PanelSeq IDC samples

  PDX samples of breast cancer IDC mouse models created from patient tumor material of the NKI. Genomescan prepared the samples according to the procedure for Hybridization Capture using an Agilent SureSelect custom 0.5-2.9Mb kit. The prepared libraries were sequenced with Illumina sequencing technology. The samples are in fastq format and consist of the following PDX samples: IDC025, IDC026, IDC029, IDC031, IDC032, IDC038, IDC057, IDC062, IDC065, IDC069, IDC072, IDC090B, IDC092, IDC097, IDC099, IDC107, IDC113, IDC117, IDC143, IDC152, IDC159A, IDC159B, IDC180, IDC186, IDC192, IDC197, IDC198, IDC207, IDC209, IDC216, IDC218, IDC222, IDC229, IDC232, IDC274, IDC282, IDC290, IDC299, IDC307, IDC338, IDC344, IDC346, ILC006, ILC012, ILC083 and ILC248.

  Dataset EGAD50000001149

• RNA, ATAC, ChIP datasets from iPSC Derived Macrophages with and without TNFRSF1A intronic deletion using CRISPR

  This dataset consists of functional genomic data from iPSC derived Macrophages with or without CRISPR deletions and controls. It contains 21 paired end fastq files consisting of 6 total RNA-seq samples and 9 ATAC samples, for ChIP there are 2 H3K4me3 samples, 2 H3K27ac samples along with 2 paired input samples. The samples were sequenced on the Illumina HiSeq4000 amd Illumina NextSeq500 platforms.

  Dataset EGAD50000000984

• Facioscapulohumeral muscular dystrophy (FSHD): RNA-seq of isogenic TIRM+, TIRM- muscle and PBMCs from patients and matched controls

  FASTQ files describing paired-end RNA-sequencing of isogenic TIRM+ and TIRM- muscle biopsies from 24 FSHD patients (48 samples) and vastus lateralis muscle biopsies from 11 matched control individuals. FASTQ files are also provided describing RNA-sequencing of 15 FSHD peripheral blood mononuclear samples and 14 matched controls. For muscle biopsies sequencing was at 21.7-35.5 million reads/sample. RNA was extracted from PBMCs followed by globin depletion with sequencing at 19.7-46.5 million reads/sample.

  Dataset EGAD00001011077

• Characterization of Autosomal CNV Among the Negrito from Peninsular Malaysia

  Copy number variation (CNV) has been recognized as a major contributor to human genome diversity. It plays an important role in determining phenotypes and has been associated with a number of common and complex diseases. However the CNV data from diverse populations is rather limited. Here we report the first investigation of copy number variation (CNV) in the indigenous populations from Peninsular Malaysia. We genotyped 34 Negrito genomes from Peninsular Malaysia using the Affymetrix SNP 6.0 microarray and identified 62 putative novel CNVs, consisting of 25 gains and 37 losses. These CNVs appear unique to the Negrito population and were absent in the DGV, HapMap3 and Singapore Genome Variation Project (SGVP) datasets. Analysis of gene ontology revealed that genes within these CNVs were enriched in the immune system (GO:0002376), response to stimulus mechanisms (GO:0050896), as well as the metabolic pathways (GO:0001852). Copy number gains in CNVRs enriched with genes were significantly higher than the losses (P value <0.001). Therefore, in view of the small population size, relative isolation and semi-normadic lifestyles of this community, we speculate that these CNVs may be attributed to recent local adaptation of Negritos from Peninsular Malaysia.

  Study phs000664

• Linking the epigenetic landscape in chronic lymphocytic leukemia to deregulated chromatin networks

  Aberrant chromatin features and epigenetic signaling emerge as an important part of the tumor disease state in chronic lymphocytic leukemia (CLL). However, an integrative analysis of the malignant chromatin landscape is currently missing. Here, we mapped DNA-methylation, nucleosome position, 7 histone modifications, ATAC-seq and the transcriptome in primary CD19+ sorted B-cells from the peripheral blood of CLL patients in comparison to non-malignant lymphocytes of healthy donor reference samples. On the > 50 kb scale we identified global differences with respect to DNA methylation, nucleosome positioning and histone modifications in CLL. Furthermore, a chromatin state annotation was developed to identify deregulated chromatin features of promoters and enhancers in CLL. By integrating these findings with an ATAC-seq based transcription factor binding analysis we identified a set of promoters and enhancers specific to CLL that were enriched in certain transcription factors binding motifs and genes of the BCR signaling pathway. Thus, our study provides an in-depth map of the CLL chromatin landscape and links chromatin state changes at promoters and enhancers to deregulated pathways.

  Study EGAS00001002518