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• Genetic Analysis of Desmoplastic Melanoma

  Desmoplastic melanoma is an infrequent variant of melanoma with sarcomatous histology, distinct clinical behavior, and unknown pathogenesis. We performed low-coverage genome and high-coverage exome sequencing of 20 desmoplastic melanomas, followed by targeted sequencing of 293 genes to validate candidate genes. A high mutation burden (median 62 mutations/Mb) ranked desmoplastic melanoma among the most highly mutated cancers. Mutation patterns strongly implicate UV-radiation as the dominant mutagen, indicating a superficially located cell of origin. Novel alterations included recurrent promoter mutations of NF-kappa B inhibitor epsilon, NFKBIE (IkBε) in 14.5% of samples. Commonly mutated oncogenes in melanomas, in particular BRAF(V600E) and NRAS(Q61K/R), were absent. Instead, other genetic alterations known to activate the MAPK and PI3K signaling cascades were identified in 73% of samples, affecting NF1, CBL, ERBB2, MAP2K1, MAP3K1, BRAF, EGFR, PTPN11, MET, RAC1, SOS2, NRAS, and PIK3CA, some of which being candidates for targeted therapies. Reprinted from: Shain, A. H. et al. Exome sequencing of desmoplastic melanoma identifies recurrent NFKBIE promoter mutations and diverse activating mutations in the MAPK pathway. Nat. Genet. With permission from Nature Genetics

  Study phs000977

• Comparative transcriptome of CD34+ hematopoietic progenitors from myeloproliferative patients and control donors

  BCR-ABL-negative MPNs are related to mutations activating the JAK2/STAT pathway and occurring in hematopoietic stem cells (HSC). The most prevalent mutation is JAK2V617F. Calreticulin (CALR) and activating MPLW515 mutations are also observed in ET and PMF. Additional non-MPN mutations may be found, particularly in PMF, and can change disease phenotype or accelerate progression to myelofibrosis or leukemia. In this study, we wanted to compare the transcriptome of CD34+ progenitors from JAK2V617F postive MPN patients to the CD34+ progenitors from control donors. The patients were selected for their high JAK2V617F variant allele frequency (from 60 to 100% VAF). Peripheral blood from patients was collected in EDTA tubes. Hematopoietic progenitors (CD34+) were isolated from mononuclear cells (MNCs) by immunomagnetic enrichment (Miltenyi, Biotech) and were amplified for 5 days in serum-free medium in the presence of a cocktail of human recombinant cytokines containing EPO (1 U/mL) (Amgen Thousand Oaks, CA), TPO (20 ng/mL) (Kirin, Japan), SCF (25 ng/mL) (Biovitrum AB, Sweden), IL-3 (10 ng/mL), FLT3-L (10 ng/mL), G-CSF (20 ng/mL) and IL-6 (100 U/mL) (MiltenyiBiotec).

  Study EGAS00001005106

• RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

  RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dataset EGAD50000000333

• CNS Embryonal tumors

  The dataset represents a total of 58 DNA samples from 16 male and 12 female pediatric patients affected with embryonal central nervous system tumors. The samples were subject to whole genome sequencing, WGS, [48 samples, (representing 12 male and 11 female individuals)] and whole exome sequencing, WES, [10 samples, (representing 4 male and 1 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 26 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from two patients. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 58 files in the CRAM format (lossless compression) with a total file size of ~8,8 TB. All CRAM files but one, are derived from one sequence run and one sample. P4551_227N_P4552_112N is a CRAM file where 2 sequence runs (P4551_227N and P4552_112N) from peripheral blood samples from the same individual, P019, were aligned into one single CRAM file. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000298

• Whole Exome and Target Sequencing Data in 75 Samples from 5 Hepatocellular Carcinoma Patients.

  Whole Exome and Target Sequencing Data in 75 Samples from 5 Hepatocellular Carcinoma Patients. The sequencing was performed by Illumina HiSeq 4000. Background and aims: Intratumoral heterogeneity (ITH) challenges identifying mutations with target therapy potential whereas circulating cell-free DNAs (cfDNAs) could reflect nearly the entire mutation spectrum in given tumors. We investigated how to minimize the limit of ITH for profiling hepatocellular carcinoma (HCC).Methods: Thirty-two multi-regional HCC samples from five patients were subjected to whole exome sequencing (WES) and targeted deep sequencing (TDS). ITH extent was measured by the average percentage of non-ubiquitous mutations (present in parts of tumor regions). Matched cfDNAs were also analyzed by WES and TDS. Profiling efficiencies of single tumor specimen and cfDNA were compared and the one better depicted mutational landscape was selected to screen therapeutic targets.Results: We found variable extents of ITH in HCCs and observed branched and parallel evolution patterns. ITH level decreased at higher sequencing depth of TDS than that measured by WES (28.1% vs 34.9%, P < 0.01) but it remained unchanged upon additional samples analyzed. TDS of single tumor specimen detected an average of 70% the total mutations in HCC. Although more mutations were detected in cfDNA under TDS than WES, an average of 47.2% total HCC mutations uncovered by cfDNA suggested tissue outperform cfDNA and the latter may serve as alternative in profiling HCC genome. Consequently, TDS of single tumor tissue in 66 patients and cfDNAs in four unresectable HCCs identified 38.6% (26/66 and 1/4) patients bearing therapeutic targets.Conclusions: TDS of single tumor specimen could largely circumvent ITH to uncover mutations indicative of target therapy in HCC.

  Dataset EGAD00001003278

• Single nuclei ATAC-Seq data from the human ganglionic eminences

  Data generated through single nuclei ATAC sequencing on whole ganglionic eminences from 3 human fetuses (two of 16 and one of 17 gestational weeks). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource with ethical approval. snATAC-Seq libraries were prepared from ~8,000 nuclei per sample using Chromium Next GEM Single Cell ATAC (v1.1) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 617 million read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Schizophrenia Bulletin 2024, https://doi.org/10.1093/schbul/sbae083. Please note that 10X generated BAM files, rather than FASTQ files, have been uploded. FASTQ files can be regenerated using the 10X Genomics bamtofastq tool. https://support.10xgenomics.com/docs/bamtofastq

  Dataset EGAD50000000601

• Single cell RNA sequencing of mononuclear cells from synovial fluid of patients with rheumatoid arthritis

  Mononuclear cells were collected from synovial fluid of anti-citrullinated positive antibodies (ACPA)-positive rheumatoid arthritis patients (n=8) and ACPA-negative RA patients (n=8). Global cell types (i.e., no enrichment) were obtained from these cryopreserved synovial fluid mononuclear cells (SFMC) samples and immediately fixed and processed using the GEM-X Flex Gene Expression Reagent Kits (10x Genomics) according to protocol. Following Gel Bead-in Emulsion (GEM) generation, samples were processed using the standard manufacturer’s protocol. Once sequencing libraries passed standard quality control metrics, libraries were sequenced on an Illumina NextSeq2000 P4 100 cycle reagent kit with the following read structure: R1: 28, R2: 90, I1: 10, I2: 10. Libraries were sequenced to obtain a read depth greater than 10,000 reads/cell for gene-expression (GEX). FASTQ files are made available. More detailed information can be obtained in Argyriou A. et al, Annals of the Rheumatic Disease, 2025.

  Dataset EGAD50000001801

• Targeted Sequencing of 173 genes

  Targeted sequencing of 173 genes in 2433 primary breast tumours. Data includes 2433 tumour samples, 523 adjacent normal (breast) samples and 127 blood samples. Libraries were prepared with Illumina's Nextera custom enrichment kit targetting all the exons of the most frequently mutated breast cancer genes. Libraries were multiplexed (48 libraries per lane) and sequenced on Illumina HiSeq 2000 (100bp paired-end reads). Somatic mutations were calling with a custom pipeline. We identified 40 mutation-driver (Mut-driver) genes, and determined associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assessed the clonal states of Mut-driver mutations, and estimated levels of intra-tumour heterogeneity using mutant-allele fractions. The results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Referece: Pereira et al. (2016) The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications

  Dataset EGAD00001002115

• Single nuclei RNA-Seq from 5 regions of the human fetal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Dataset EGAD00001009303

• DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues

  DNA methylation sequencing profiles of 1538 breast tumors and 244 normal breast tissues. Libraries were prepared using a custom Reduced Representation Bisulfite Sequencing pipeline. Sequencing was performed on the Illumina HiSeq 2500 (v4 chemistry), with single-end reads of 125 bp length. Multiplexing was conducted at the level of 8 samples per lane. FASTQ files are provided for 1538 breast tumors and 244 normal breast tissues. Reference: Batra et al. (2021). DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

  Dataset EGAD00001007976