14977 results for "cancer studies using rna-seq"

in 27.14 milliseconds.

• The Landscape of Antisense Gene Expression in Human Cancers

  High throughput RNA Sequencing has revealed that the human genome is widely transcribed. However, the extent of natural antisense transcription, the molecular mechanisms by which natural antisense transcripts (NATs) might affect their cognate sense genes, and the role of NATs in cancer are less well understood. Here, we use strand-specific paired-end RNA sequencing (ssRNASeq) on a cohort of 376 cancer patients covering 9 tissue types to comprehensively characterize the landscape of antisense expression. Our results reveal that greater than 60% of annotated transcripts have measureable antisense expression and the expression of sense and antisense transcript pairs is in general positively correlated. Furthermore, by studying the expression of sense/antisense pairs across tissues we identify lineage-specific, ubiquitous and cancer-specific antisense loci. Our results raise the possibility that NATs participate in the regulation of well-known tumor suppressors and oncogenes. Finally, this study provides a catalogue of cancer related genes with significant antisense transcription (oncoNAT). This resource will allow researchers to investigate the molecular mechanisms of sense/antisense regulation and further advance our understanding of their role in cancer.

  Study phs000937

• Whole-genome enzymatic DNA methylation sequencing and single-cell RNA sequencing data from nasal cells of COVID-19 patients

  Nasal swabs were collected from COVID-19 patients during the acute phase of infection as well as 3 and 12-months post-infection. Cells isolated from nasal swabs were subjected to whole-genome enzymatic DNA methylation sequencing (n=33) and scRNA-seq (n=24). For n=12 former COVID-19 pateints, follow-up samples were collected at 3 and 12 months post-infection and subjected to scRNA-seq.

  Dataset EGAD50000000398

• Bell_activation_timecourse

  We purified human naive and memory B cells from PBMCs. We stimulated them with IgM cross-linker providing BCR stimulation, multimeric CD40L that engages costimulatory receptor CD40 on the B cell, and cytokines IL-2 and IL-21. To comprehensively characterise activation dynamics of naive and memory B cells, we performed single-cell RNA sequencing (scRNA-seq) and B cell receptor sequencing (BCR-seq) in resting cells (day 0), before the first division (day 1), at the time of the first division (day 3) and following the full B cell differentiation (day 6)

  Dataset EGAD50000002115

• GBM Up and Down Responder EZH2 ChIPseq

  ChIPseq using anti-EZH2 with a sheared input DNA control to assess EZH2 genomic biding in one longitudinal pair of samples (pre- and post-treatment) from one UP and one DOWN responder GBM patient

  Dataset EGAD50000000134

• RNA sequencing data of 66 matched primary and recurrent high grade serous ovarian cancer

  Dac EGAC00001000741

• Targeted RNA sequencing of breast cancer GWAS loci

  Dataset EGAD00001004498

• Multimodal cell-free DNA whole-genome TAPS is sensitive and reveals specific cancer signals

  This study presents a methodology for detecting circulating tumor DNA (ctDNA) using deep whole-genome TET-Assisted Pyridine Borane Sequencing (TAPS), a less destructive alternative to bisulphite sequencing. The method enables simultaneous analysis of genomic and methylomic data for multi-cancer detection and monitoring minimal residual disease. In a diagnostic accuracy study across various cancer types, it achieved 85.3% sensitivity and 88.8% specificity, with validation done using matched tumour biopsies. Additionally, in silico validation showed strong discrimination at low ctDNA levels. The approach also successfully tracks tumour burden and ctDNA shedding from precancerous lesions post-treatment, making it ready for further clinical testing.

  Study EGAS50000000715

• APCIM_Nanostring_FAP

  Expression of immune related genes in 12 familial adenomatous polyposis patients. Expression assessed by analyzing whole blood-derived RNA samples using a Nanostring nCounter Immunology V2 panel (579 genes)

  Dataset EGAD00010002553

• Single Nuclei RNA sequencing batch 2

  This dataset includes the 2 extra normal samples adjacent to PTC tumors that were multiplexed and profiled using kits from different batches.

  Dataset EGAD00001011364

• Uncovering Inversion Formation in the Human Genome and its Impact to Disease

  The relevance of inversions for disease causation, speciation and adaptation is broadly recognized, although the prevalence of inversions is unknown. In humans, de novo inversions are associated with congenital anomalies in approximately 9.6% of patients. Yet, despite the biological relevance of inversions, their molecular features, formation mechanism, impact to the genomic structure of carriers, as well as their contribution to clinical phenotypes, have not been further explored. Inversions are typically classified as balanced reciprocal events generated by ectopic recombination, although recent studies reveal a distinct picture whereby inversions originate from mechanisms that concomitantly generate copy number variants (CNVs). Surprisingly, those complex inversions underlie as much as 30% of neurodevelopmental-associated CNVs. The hypothesis of this project are: inversions are often generated de novo by mechanisms other than ectopic recombination a relevant fraction of inversions are associated with complex genomic rearrangements (CGRs), often overlooked in sporadic diseases, and inversions are a "hidden" type of structural variation for which contribution to a clinical phenotypes has been under assessed due to the lack of appropriate detection tools. A combined strategy using multiple genomic tools will be applied to characterize inversions and associated genomic alterations in individuals with neurodevelopmental disorders and controls: whole genome sequencing (WGS) with short-and long-reads; genome mapping; classical cytogenetics; and array CGH. This project will establish common ground to bridge studies of rare and common diseases, human evolution, and population genetics.

  Study phs002999

• Single Cell RNA-Sequencing in Adenoid Cystic Carcinoma

  This study of salivary adenoid cystic carcinoma aimed to profile individual malignant and stromal cells in treatment-naive head and neck adenoid cystic carcinoma, with or without metastatic cervical lymph nodes. Clinical and pathologic information was collected on all patients, in addition to a fresh biopsy sample from the primary tumor and/or metastatic lymph node at the time of initial surgery. A fresh biopsy sample from a matched local recurrence was also collected for a single unique patient. Biopsy specimens were processed for single cell RNA-seq. A total of ~1,700 single cells from seven participants were included in the final dataset.

  Study phs003070

• Integration of T Cell Repertoire, CyTOF, genotyping and symptomatology data reveals subphenotypic variability in COVID-19 Patients

  A total of 61 patients (33 mild and 28 severe) with a median age of 51 years who recovered from COVID-19 were included in this study (Table 1). All collected samples were confirmed in diagnosis of COVID-19 by RT-PCR and positive IgG serolog. For the 61 patients, TCR-seq, CyTOF, and genotyping data were generated and analyzed in separate studies, as part of larger cohorts. In total, there are 143 variables, with 129 being quantitative (TCRseq and CyTOF metrics) and 13 being qualitative (symptomatology and genotyping). For more information about cohort characteristics, data adquisition an pre-processing, please visit PMID: 39227859, 36969980 and 37287057.

  Dataset EGAD50000000840

• Title: Divergent levels of CD112 and INKA1 define a distinct subset of human long-term hematopoietic stem cells

  The data provided here was critical in establishing that human long-term hematopoietic stem cells (LT-HSC), previously described as the most primitive HSC population, is actually composed of distinct subsets that can be prospectively isolated. Via mechanistic studies centering around the Rho-GTPase effector kinase PAK4 and its inhibitor INKA1, we identified the immune checkpoint ligand CD112 as a marker for hematopoietic stem and progenitor cells, that is highest expressed on LT-HSC. More importantly, CD112 can be used to stratify functionally distinct subsets within LT-HSC: In response to regeneration-mediated stress, the CD112low subset exhibits a transient restraint (termed latency) before contributing to hematopoietic reconstitution, while the CD112high subset is primed to respond rapidly. High resolution RNA-seq of the CD112 surface expression spectrum within rare LT-HSC subsets (human umbilical cord blood) demonstrated that more genes are differentially upregulated in the deeper quiescent and less metabolic active subset. Genes enriched in this subset centre around cell adhesion and Rho-GTPase signaling. This is in agreement with the scRNAseq data from human G-CSF mobilized peripheral blood (mPB) generated here that was used as an model of in vivo activation/priming revealing via RNA-velocity and pseudo-time analysis that INKA1high versus PAK4high, CDK6high and CD112high enrichment are either detected early or late in diffusion pseudotime indicative of quiescent versus primed cell status, respectively. RNAseq following INKA1 overexpression in LT-HSC and ST-HSC revealed by GSEA an overall stemness preserving phenotype and particularly in LT-HSC, but not in short-term HSC (ST-HSC), suppression of transcriptional programs linked to activation. Collectively, our data decipher the molecular intricacies underlying HSC heterogeneity and self-renewal regulation and point to latency as an orchestrated physiological response that integrates quiescence control with HSC fate choices to preserve a stem cell reservoir.

  Dataset EGAD00001006541

• RNASeq profiles from Indian HFrEF Cohort

  The dataset contains whole transcriptomics profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Total transcriptome libraries were prepared using TruSeq Stranded Total RNA Library Prep with Ribo-Zero Gold kit and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001196

• GEI Studies - Psoriasis

  The GEI Studies Project was started as an NIH consortium involving 5 disease groups with funding provided through the Genes, Environment, and Health Initiative (GEI). The objective of the project was to optimize strategies for identifying rare variants as a follow up to genome-wide association studies (GWAS) using next-generation sequencing technology. One of the five targeted diseases, Psoriasis, is a multifactorial skin disease characterized by epidermal hyperproliferation and chronic inflammation that affects approximately 2% of Americans. Because only about one-third of all patients with psoriasis have a relative who is also affected with the disorder, psoriasis is not widely recognized as a genetic disease. However, previous research on families and identical twins has shown psoriasis has a strong genetic component, although environmental factors (such as infections, stress, and injuries) are also important. Although no definite psoriasis gene has yet been identified, research during the last ten years has revealed over forty potential gene locations that may contribute to the disease. Large amounts of data generated using next-generation sequencing technology would provide a more detailed characterization of sequence variation which would in turn increase the likelihood of detecting causative loci. With the presumption that rare variants are frequently the cause of a large portion of phenotypic variation, it was necessary to use large sample sets. In the main body of this study, we sequenced 4,966 samples (812 dermatologist-diagnosed cases of purely cutaneous psoriasis (PsC), 1,497 cases of rheumatologist-diagnosed psoriatic arthritis, 665 cases of cutaneous psoriasis with uncertain psoriatic arthritis status (PsV) and 1,992 controls) across 5.7 Mb of sequence containing 100 psoriasis candidate loci and 769 genes. For each candidate locus, we considered sequences within 250 kb of the strongest association signal. Within this window, three strategies were employed. For ten of the strongest psoriasis signals, we used a whole-region approach which included non-coding intergenic and intronic sequence. For four established loci of lesser significance, we targeted all full transcription units within the +/- 250 kb interval. For the remaining signals, we targeted the exons of all transcription units within the +/- 250 kb interval. Due to complexities of high-efficiency targeting of HLA genes we selected 5 specific candidate genes for sequencing near the HLA-C gene.

  Study phs000766

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  ChIP-seq and matched input data of AR, FOXA1 and H3K27ac for mCRPC patient samples taken prior to and after treatment with AR targeted therapy

  Dataset EGAD00001008688

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064

• Onco-exaptation of an Endogenous Retroviral LTR Drives IRF5 Expression in Hodgkin Lymphoma

  The transcription factor interferon regulatory factor 5 (IRF5) is upregulated in Hodgkin lymphoma (HL) and a key regulator of the aberrant transcriptome characteristic of this disease. Here we show that IRF5 upregulation in HL is driven by transcriptional activation of a normally dormant endogenous retroviral LOR1a long terminal repeat (LTR) upstream of IRF5. Specifically, through screening of RNA-seq libraries, we detected LTR-IRF5 chimeric transcripts in multiple HL cell lines but not in normal B-cell controls. In HL, the LTR was in an open and hypomethylated epigenetic state and we further show the LTR is the site of transcriptional initiation. Among HL cell lines, usage of the LTR promoter strongly correlates with overall levels of IRF5 mRNA and protein, indicating that LTR transcriptional awakening is a major contributor to IRF5 upregulation in HL. Taken together, oncogenic IRF5 overexpression in HL is the result of a specific LTR transcriptional activation. We propose that such LTR derepression is a distinct mechanism of oncogene activation (“onco-exaptation”) and that such a mechanism warrants further investigation in molecular and cancer research.

  Study EGAS00001001205

• Profiling of 27 type 2 diabetes GWAS loci using next-generation (NG) capture C in a human beta-cell model

  Most type 2 diabetes association signals are due to variants that impact gene regulation but identifying the genes they impact is challenging. We generated interaction profiles at 27 T2D GWAS loci using next-generation (NG) capture C (6 replicates) in the human beta-cell model, EndoC-betaH1, along with chromatin accessibility profiling using ATAC-Seq (9 replicates).

  Dataset EGAD00001008655

• Single cell analysis reveals new evolutionary complexity in uveal melanoma

  Uveal melanoma (UM) is a rare eye cancer that is highly aggressive and leads to metastatic death in up to half of patients. Here, we conduct droplet-based single-cell RNA sequencing of 59,915 neoplastic and non-neoplastic cells from 8 primary and 3 metastatic UMs. Single-cell VDJ sequencing of RNA is conducted to determine clonally expanded B/T- cell populations. Single-cell DNA sequencing of 1 primary and 1 metastasis is utilized.

  Study phs001861

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 34 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&sE staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001010135

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 81 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&E staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001009049

• 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

• Sequencing data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Repli-seq data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Dataset EGAD00001015363

• RNA_TPO3_2023

  Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in either glucose or lactate, in the presence and absence of DCA or BRD4 inhibition (JQ1). Samples were collected and processed for bulk RNA-seq.

  Dataset EGAD50000000089

• The function of LAMP5 in multiple myeloma

  This dataset includes Fastq files from bulk RNA seq from myeloma cell lines (MM.1S and NCI-H929) expressing a DOX-inducible LAMP5 shRNA, S1 (CACTTCAAAGACGCAGTCAGT) or S5 (GCACACAGAATACAACCTCAT), or a scramble control treated with DOX during 48h.

  Dataset EGAD50000001178

• Long-read RNA-seq of doxycycline-inducible DUX4 human myoblast cell lines

  The dataset includes the PacBio full-length isoform sequencing data of DUX4i myoblasts (Clone-5) with and without 16-hour DOX-treatment (referred to as DUX4- and DUX4+; n=1 in each condition).

  Dataset EGAD50000000718

• RNA-Seq of primary pediatric kidney tumor controls for the soft tissue sarcoma tumoroid biobank

  Dataset EGAD00001008709

• Gene expression in human monocyte differentiation

  This dataset consists of RNA-seq data data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting TET2, IRF4 and EGR2. In total, it includes 43 samples.

  Dataset EGAD00001006604

• Immune single-cell profiling of human chronic inflammatory skin disease

  This dataset includes 10X Genomics 3' single cell-RNA-seq profiles from 24 human rashes and 7 healthy controls. BAM files are provided for each sample.

  Dataset EGAD00001008624

• Log2 normalized TPM matrix for POPLAR (GO28753)

  This dataset contains log2(TPM + 1) for 192 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from POPLAR (GO28753).

  Dataset EGAD00001008390

• Log2 normalized TPM matrix for OAK (GO28915)

  This dataset contains log2(TPM + 1) for 699 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from OAK (GO28915).

  Dataset EGAD00001008391

• Gene expression in LPS-stimulated human monocyte-derived macrophages

  This dataset consists of RNA-seq data from human monocyte-derived macrophages that were subjected to siRNA treatment targeting RAD21 and either left untreated, or stimulated with LPS. In total, it includes 24 samples.

  Dataset EGAD00001007952

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities - RNA-Seq

  We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles

  Dataset EGAD00001009794

• 17 scRNAseq samples

  17 samples were processed for single cell RNA sequencing (SORT-seq)

  Dataset EGAD00001007523

• Data files for PCGP SJACT RNASEQ

  This dataset contains RNA-Seq files for the SJACT cohort associated with the paper "Genetic landscape of pediatric Adrenocortical Tumor". In this paper, we analyse 37 adrenocortical tumours (ACTs) by whole-genome, whole-exome and/or transcriptome sequencing.

  Dataset EGAD00001002680

• Expression Quantitative Trait Locus Mapping Studies in Mid-Secretory Phase Endometrial Cells Identifies HLA-F and TAP2 as Fecundability-Associated Genes

  We performed an unbiased genome-wide expression quantitative trait locus (eQTL) mapping study to identify common regulatory (expression) single nucleotide polymorphisms (eSNPs) in mid-secretory endometrium, corresponding to the luteal phase of the ovarian cycle. Biopsies were collected from 58 women with two or more early pregnancy losses and 53 of these samples passed all quality control. RNA was extracted from endometrial biopsies and DNA was extracted for sequencing from blood. Gene expression data can be found at NCBI GEO Series GSE77688.

  Study phs001146

• Angiopredict: predicting response for bevacizumab treatment

  In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers worked with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to bevacizumab containing therapy. In this retrospective study, copy number profiles were determined using whole genome shallow sequencing, and progression free survival and treatment data was collected.

  Study EGAS00001002724

• Collagen Proteostasis in Health and Disease

  This study uses human iPSC-derived cartilage to investigate the effects of the p.Arg719Cys mutation in the COL2A1 gene, which is linked to precocious osteoarthritis. Using a CRISPR-edited isogenic cell line pair, we compared wild-type and mutant cartilage for matrix defects and cellular stress responses. We performed RNA-sequencing and quantitative proteomics to characterize changes in gene expression, protein interactions, and collagen folding.

  Study phs004112

• Bulk RNAseq FASTQ files of three PDAC organoid lines treated with LGK974 or DMSO for 24h

  This dataset contains raw FASTQ files from bulk RNA sequencing of three patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid lines (P28, P40, P47). Each organoid line was treated with either the WNT secretion inhibitor LGK974 or DMSO for 24 hours, with three biological replicates per treatment condition. RNA was extracted using the Qiagen QiaSymphony SP system, and libraries were prepared with the Illumina Truseq stranded polyA kit. Sequencing was performed on an Illumina NextSeq2000 platform using single-end 50bp reads. Quality control was conducted with FastQC, and reads were trimmed with TrimGalore as appropriate. Data are controlled-access and intended for transcriptomic analysis of WNT pathway perturbation in PDAC organoid models.

  Dataset EGAD50000002219

• Single-cell multi-omics reveals clonal evolution and T-cell dynamics underlying differential responses to ibrutinib in Waldenström macroglobulinemia.

  To elucidate the molecular basis underlying differential response and resistance to ibrutinib in Waldenström’s macroglobulinemia (WM), we conducted a prospective phase II trial (NCT02604511) of ibrutinib monotherapy in treatment-naïve patients. Seventy-four sequential bone marrow (BM) aspirates from 17 patients, collected from baseline through 48 treatment cycles, were profiled using single-cell RNA and V(D)J sequencing.

  Study EGAS50000001596

• Capture Hi-C on Hodgkin lymphoma cell line L-428

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Study EGAS00001003032

• Dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA

  The dataset for Direct Detection of Early-Stage Cancers using Circulating Tumor DNA includes 602 bam files from next-generation sequencing on the Illumina HiSeq2500 or MiSeq. The samples analyzed include cancer cell lines as well as plasma and tissue specimens from healthy individuals and patients with cancer.

  Dataset EGAD00001003601

• TRACERx100 metastatic samples

  Whole exome sequencing of 10 metastatic biopsies from four TRACERx100 patients (see EGA dataset EGAS00001002247), collected either after relapse or death. The data from these samples are initially published with Abbosh, C. et al. Phylogenetic ctDNA analysis depicts early stage lung cancer evolution. Nature, http://dx.doi.org/10.1038/nature22364 (2017). Abstract: Earlier detection of relapse following primary surgery for non-small cell lung cancer and the characterization of emerging subclones seeding metastatic sites might offer new therapeutic approaches to limit tumor recurrence. The potential to non-invasively track tumor evolutionary dynamics in ctDNA of early-stage lung cancer is not established. Here we conduct a patient-specific approach to ctDNA profiling in the first 100 lung TRACERx (TRAcking Cancer Evolution through therapy (Rx)) study participants, including one patient co-recruited to the PEACE (Posthumous Evaluation of Advanced Cancer Environment) post-mortem study. We identify independent predictors of ctDNA release in early-stage non-small cell lung cancer and perform tumor volume limit of detection analyses. Through blinded profiling of post-operative plasma, we observe evidence of adjuvant chemotherapy resistance and identify patients destined to experience recurrence of their lung cancer. Finally, we show that phylogenetic ctDNA profiling tracks the subclonal nature of lung cancer relapse and metastases, providing a new approach for ctDNA driven therapeutic studies.

  Dataset EGAD00001003301

• Dataset for colorectal_cancer-RNA

  Rare cancer sequencing data of 97 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008855

• Somatic L1 retrotransposition mapping in high-grade serous ovarian carcinoma using LDI-PCR/Nanopore-sequencing

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from the same patient were utilised to understand L1-mediated intrapatient heterogeneity. Long-read data generated by LDI-Nanopore sequencing was aligned to the reference genome (GRCh38).

  Dataset EGAD50000001707

• DNA-seq BAM files from 16 patients affected by acute intermittent porphyria

  Paired-end BAM files from 16 patients affected by acute intermittent porphyria. Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). FASTQ files were processed at the CNAG (Barcelona) using the GEM short-read aligner on the human genome version hs37d5, producing a total of 16 BAM files.

  Dataset EGAD00001006951

• Single cell RNA sequencing of 33 primary colorectal cancer

  Study EGAS00001003779

• Childhood B-cell acute lymphoblastic leukemia genomic and transcriptomic data

  The aim of the two studies was: 1) to genetically characterise childhood leukemia patients that lacked established cytogenetic abnormalities (termed B-other leukemia) and assess the clinical features of recurrent genetic abnormalities. 2) Assess the accuracy of whole genome sequencing as a diagnostic genetic test in childhood leukemia, relative to other traditional methods (karyotyping, FISH, MLPA) and whole transcriptome sequencing. As a result, this study includes targeted DNA-sequencing, whole genome sequencing and whole transcriptome sequencing data on childhood leukemia patients enrolled on UK clinical trials (UKALL2003 and UKALL2011).

  Study EGAS00001006863

• Breast Cancer Family Registry

  The Breast Cancer Family Registry (BCFR) is a multi-center prospective cohort, comprised of over 30,000 women and men from nearly 12,000 families from the United States, Canada, and Australia. Our BCFR resource has been used, and continues to be used, by breast cancer researchers around the world in order to find new ways to prevent, diagnose, and treat cancer. The BCFR provides an extensive and diverse range of resources, expertise, and specialized skills, and has several unique strengths: 1) the collection of a large number of individuals and families across a wide spectrum of breast cancer risk, including both affected and unaffected individuals; 2) the large collection of families with early-onset breast cancer; 3) the large collection of racial/ethnic minority families not replicated elsewhere; 4) the extensive molecular characterization performed to date; and 5) active follow-up of both probands and family members. Thus, the BCFR comprises a unique cohort of probands and family members at familial/genetic risk of breast cancer that will continue to facilitate a wide range of research studies, such as gene discovery, examination of cancer-related outcomes and risk factors in high-risk subjects, investigation of novel behavioral interventions, and cancer prevention trials among at-risk family members. Consequently, the BCFR Cohort, as one of the few cohorts available worldwide with biospecimens and extensive molecular and genetic characterization, combined with epidemiologic data and long-term follow up, will be an invaluable resource for translational research in the genetic epidemiology of breast cancer.

  Study phs002835