Search Results - EGA European Genome-Phenome Archive

Gut Microbiome and Types of Colorectal Polyps

Colorectal cancer is a heterogeneous disease arising from at least two precursors-the conventional adenoma and the serrated polyp. This dataset was used to test the relationship of the gut microbiota to specific colorectal polyp types. We included samples from two independent study populations based at colonoscopy clinics: the Centers for Disease Control and Prevention (CDC) Study of In-home Tests for Colorectal Cancer (SIT), and the New York University (NYU) Human Microbiome and Colorectal Tumor study. Gut microbiota were assessed in 667 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples, of which 540 were included in our analysis. Participants were categorized as conventional adenoma cases, serrated polyp cases, or polyp-free controls. CA cases were further classified as proximal or distal and as non-advanced or advanced. Serrated polyp cases were further classified as hyperplastic polyp or sessile serrated adenoma. Our results show associations between gut microbiome composition and presence of conventional adenomas, including reduced diversity and alterations in taxon abundance.

Study phs001381

The Genomic Landscape of Interval Colorectal Cancers

Interval colorectal cancers (CRC), cancers diagnosed after a screening/surveillance exam in which no cancer is detected, and before the date of the next recommended exam, reflect an unprecedented challenge in CRC detection and prevention. To better understand this poorly characterized CRC variant, we examined the clinical and mutational characteristics of interval CRCs in comparison to screen-detected CRCs. We used data from the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer randomized controlled trial (RCT) of flexible sigmoidoscopy (FS) screening, which enrolled 154,900 men and women aged 55 to 74 years between 1993 and 2001. Whole Exome Sequencing (WES) was performed on 323 samples from 168 participants (data available through dbGaP). We found colorectal cancers diagnosed between screening exams (interval cancers) had significantly increased risk of death than screen detected cancers although no significant molecular differences were observed between screen-detected and interval CRC at the whole exome sequencing level.

Study phs003093

Somatic Mutations in 3,929 HPV-Positive Exfoliated Cervical Cell Samples

We investigated the detection, timing, and HPV type specificity of cervical somatic hotspot mutations (i.e., previously reported cancer driver mutations) in 3,929 HPV-positive exfoliated cervical cell samples from individuals undergoing routine cervical screening in the U.S. using deep-targeted sequencing of 20 candidate genes. Our study included samples from 3,351 women with the following infection outcomes: 1,478 HPV16-, HPV18- and/or HPV45-positive controls (i.e., HPV infections that did not progress to precancer and/or subsequently cleared), 1,712 cervical precancers, and 161 invasive cervical cancers. We utilized residual exfoliated cervical cell samples from women routinely screened for cervical cancer precursors at Kaiser Permanente Northern California (KPNC) as part of the prospective KPNC-NCI HPV Persistence and Progression (PaP) cohort. We included 3,929 samples collected from these 3,351 women, including 974 serial sample from 396 women collected prior to their most recent screening visit to evaluate somatic hotspot mutation detection prior to diagnosis.

Study phs003691

EuCANCan: EUropean-CANadian Cancer network

The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

Blog eucancan

T cell receptor repertoire in cell-free DNA as a proxy for tumor infiltrates in patients treated with pembrolizumab

Profiling tumour and systemic T-cell receptor (TCR) repertoires can identify features associated with clinical benefit of cancer patients on immune checkpoint blockade therapy. This study reports on diversity and specificity analysis of TCR sequences from 59 tumor, 306 peripheral blood (PBMC), and 73 cell-free DNA (cfDNA) samples from 81 patients with solid tumors treated with pembrolizumab. This analysis reveals that head and neck carcinomas have significantly lower PBMC diversity and shorter persistence of pembrolizumab-induced diversification compared to other cancers. Using GLIPHII (Grouping Lymphocyte Interactions with Paratope Hotspots), we find that tumor-derived clonotypes form non-microbial specificity signatures that are shared across patients and cancer types. Tumor-derived clonotypes are enriched in cfDNA compared to PBMCs, despite the diversity of cfDNA TCR repertories being two orders of magnitude lower than PBMCs. TCRs shared between tumors and cfDNAs persist in PBMCs beyond 50 weeks of treatment, suggesting cfDNA captures clonotypes contributing to anti-tumor immune surveillance.

Study EGAS50000001306

Tumor inflammation and mutational burden are differentially associated with response to nivolumab or nivolumab plus ipilimumab in metastatic colorectal cancer

Nivolumab alone and in combination with ipilimumab demonstrated durable clinical benefit in patients with previously treated microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer in the phase 2 CheckMate 142 study. Exploratory biomarker analyses of tumor and microbiome samples from CheckMate 142 were performed to evaluate associations between various biomarkers and the efficacy of nivolumab monotherapy and nivolumab plus ipilimumab combination in these patients. Higher expression of inflammation-related gene expression signatures was associated with improved response per investigator assessment and survival benefit with nivolumab monotherapy. In contrast, higher tumor mutational burden, tumor indel burden and degrees of microsatellite instability were associated with improved response per investigator assessment and survival benefit with nivolumab plus ipilimumab. While interpretation is limited by the exploratory nature of these analyses, they suggest that tumor antigenicity rather than baseline tumor inflammation might be important for the combinatorial efficacy. Validation of these findings in larger, randomized studies is necessary.

Study EGAS50000000416

Origins and functional consequence of somatic mitochondrial DNA mutations

Recent sequencing studies have extensively explored the somatic alterations present in the nuclear genomes of cancers. Although mitochondria control energy metabolism and apoptosis, the origins and impact of cancer-associated mutations in mitochondrial DNA (mtDNA) are unclear. Here, we analysed somatic alterations in mtDNA from 1,675 tumors across 31 histologies. We identified 1,907 somatic substitutions, which exhibited dramatic replicative strand bias, predominantly C>T and A>G on the mitochondrial heavy strand. This strand-asymmetric signature differs from those found in nuclear cancer genomes but matches the inferred germline process shaping primate mtDNA sequence content. Numbers of mtDNA mutations showed considerable heterogeneity across tumor types. Missense mutations were selectively neutral and often gradually drifted towards homoplasmy over time. In contrast, mutations resulting in protein truncation undergo negative selection and were almost exclusively heteroplasmic. Our findings indicate that the endogenous mutational mechanism has far greater impact than any other external mutagens in mitochondria, and is fundamentally linked to mtDNA replication.

Study EGAS00001000968

Impact of mutational profiles on response of primary oestrogen receptor-positive breast cancers to oestrogen deprivation

Presurgical studies allow study of the relationship between mutations and response of estrogen receptor positive (ER+) breast cancer to aromatase inhibitors (AIs) but have been limited to small biopsies. Here in Phase I of this study, we perform exome sequencing on baseline, surgical core-cuts and blood from 60 patients (40 AI treated, 20 Controls). In poor responders (based on Ki67 change) we find significantly more somatic mutations than good responders. Subclones exclusive to baseline or surgical cores occur in approximately 30% of tumours. In Phase II we combine targeted sequencing on another 28 treated patients with Phase I. We find six genes frequently mutated: PIK3CA, TP53, CDH1, MLL3, ABCA13 and FLG with 71% concordance between paired cores. TP53 mutations are associated with poor response. We conclude that multiple biopsies are essential for confident mutational profiling of ER+ breast cancer and TP53 mutations are associated with resistance to oestrogen deprivation therapy.

Study EGAS00001001940

Comparing nodal versus bony metastatic spread using tumour phylogenies

The role of lymph node metastases in distant prostate cancer dissemination and lethality is ill defined. Patients with metastases restricted to lymph nodes have a better prognosis than those with distant metastatic spread, suggesting the possibility of distinct aetiologies. To explore this, we traced patterns of cancer dissemination using tumour phylogenies inferred from genome-wide copy-number profiling of 48 samples across 3 patients with lymph node metastatic disease and 3 patients with osseous metastatic disease. Our results show that metastatic cells in regional lymph nodes originate from evolutionary advanced extra-prostatic tumour cells rather than less advanced central tumour cell populations. In contrast, osseous metastases do not exhibit such a constrained developmental lineage, arising from either intra or extra-prostatic tumour cell populations, at early and late stages in the evolution of the primary. Collectively, this comparison suggests that lymph node metastases may not be an intermediate developmental step for distant osseous metastases, but rather represent a distinct metastatic lineage.

Study EGAS00001001801

A biobank of patient-derived pediatric brain tumor models

Brain tumors are the leading cause of cancer-related death in children. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of pediatric brain tumors that may lead to novel therapeutic strategies. To evaluate new treatments, better preclinical models adequately reflecting the biological heterogeneity are needed. Through the Children’s Oncology Group ACNS02B3 study, we have generated and comprehensively characterized 30 patient-derived orthotopic xenograft models and 7 cell lines representing 14 molecular subgroups of pediatric brain tumors. Patient-derived orthotopic xenograft models were found to be representative of the human tumors they were derived from in terms of histology, immunohistochemistry, gene expression, DNA methylation, copy number, and mutational profiles. In vivo drug sensitivity of targeted therapeutics was associated with distinct molecular tumor subgroups and specific genetic alterations. These models and their molecular characterization provide an unprecedented resource for the cancer community to study key oncogenic drivers and to evaluate novel treatment strategies.

Study EGAS00001002536

Whole-exome sequencing reveals the origin and evolution of Hepato-Cholangiocarcinoma

Hepatocellular-cholangiocarcinoma (H-ChC) is a rare subtype of liver cancer with clinicopathological features of both hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA). To date, molecular mechanisms underlying the co-existence of HCC and iCCA components in a single tumor remain elusive. Here we show that H-ChC samples contain substantial private mutations from WES analyses, ranging from 33.1% to 86.4%, indicative of substantive intratumor heterogeneity (ITH). However, on the other hand, numerous ubiquitous mutations shared by HCC and iCCA suggest the monoclonal origin of H-ChC. Mutated genes identify herein e.g. VCAN, ACVR2A and FCGBP are speculated to contribute to distinct differentiation of HCC and iCCA within H-ChC. Moreover, immunohistochemistry demonstrate that EpCAM is highly expressed in 80% of H-ChC implying the stemness of such liver cancer. In summary, our data highlight the monoclonal origin and stemness of H-ChC, as well as substantial intratumoral heterogeneity.

Study EGAS00001002783

A novel TP53-KPNA3 translocation defines a de novo treatment-resistant clone in osteosarcoma

Osteosarcoma is the most common primary bone cancer. It can be cured by aggressive surgery and chemotherapy, but outcomes for metastatic or chemoresistant disease remain dismal. Cancer sequencing studies have shown that the p53 pathway is dysregulated in nearly every case, often by translocation; however, no studies of osteosarcoma evolution or intratumor heterogeneity have been done to date. We studied a patient with chemoresistant, metastatic disease over the course of three years. We performed exome sequencing on germline DNA and DNA collected from tumor at three separate timepoints. We compared variant calls and variant allele frequencies between different samples. We identified subclonal driver mutations in several different genes in the primary tumor sample and found that one particular subclone dominated subsequent tumor samples at relapse. This clone was marked by a novel TP53-KPNA3 translocation and loss of the opposite-strand wild-type TP53 allele. Future research must focus on functional significance of such clones and strategies to eliminate them.

Study EGAS00001001805

MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (Exome)(Novaseq)

Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

Dataset EGAD00001010117

Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Buccal

Targeted NanoSeq in buccal epithelium obtained longitudinally from a number of donors. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 55 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

Dataset EGAD00001015618

Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedNanoSeq_Blood

Utilising Targeted NanoSeq, we hope to explore the driver landscape in unprecedented detail in donors from TwinsUK. These donors have paired buccal swabs and data from this will help contextualise that work. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

Dataset EGAD00001015619

Somatic mutation and selection at epidemiological scale - TwinsUK_ExomeNanoSeq_Buccal

Exome NanoSeq in buccal swab samples obtained from patients with a wide range of clinical phenotypes. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

Dataset EGAD00001015620

Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Buccal

Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

Dataset EGAD00001015622

Somatic mutation and selection at epidemiological scale - TwinsUK_TargetedEMSeq_Blood

Development of a targeted methylation assay to determine the cell-type composition of a sample. As we age, many tissues become colonised by microscopic clones carrying somatic driver mutations. Some of these clones represent a first step towards cancer whereas others may contribute to ageing and other diseases. However, our understanding of the clonal landscapes of human tissues, and their impact on cancer risk, ageing and disease, remains limited due to the challenge of detecting somatic mutations present in small numbers of cells. Here, we introduce a new version of nanorate sequencing (NanoSeq), a duplex sequencing method with error rates of less than 5 per billion base pairs, which is compatible with whole-exome and targeted gene sequencing. Deep sequencing of polyclonal samples with single-molecule sensitivity enables the simultaneous detection of mutations in large numbers of clones, yielding accurate somatic mutation rates, mutational signatures and driver mutation frequencies in any tissue. Applying targeted NanoSeq to 1,042 non-invasive samples of oral epithelium and 371 samples of blood from a twin cohort, we found an unprecedentedly rich landscape of selection, with 46 genes under positive selection driving clonal expansions in the oral epithelium, over 62,000 driver mutations, and evidence of negative selection in some genes. The high number of positively selected mutations in multiple genes provides high-resolution maps of selection across coding and non-coding sites, a form of in vivo saturation mutagenesis. Multivariate regression models enable mutational epidemiology studies on how carcinogenic exposures and cancer risk factors, such as age, tobacco or alcohol, alter the acquisition and selection of somatic mutations. Accurate single-molecule sequencing has the potential to unveil the polyclonal landscape of any tissue, providing a powerful tool to study early carcinogenesis, cancer prevention and the role of somatic mutations in ageing and disease.

Dataset EGAD00001015623

Drug screening reveals new insight for chemoresistant hepatoblastoma

Hepatoblastoma (HB) is the most prevalent form of pediatric liver cancer. Although the standard treatment, primarily based on cisplatin, is effective in 80% of patients, it falls short in high-risk cases due to the development of chemoresistance. To identify new therapies overcoming this resistance, we screened 101 individual therapeutic compounds and 58 combinations, across 8 pediatric liver cancer cell lines. We identified ATR as a critical target to reverse cisplatin resistance. The ATR inhibitor elimusertib demonstrated the greatest synergy with cisplatin in 2D and 3D cultures and in subcutaneous xenograft models of cisplatin-resistant HB. This combination was found to enhance DNA damage and induces apoptosis through strong p53 activation. In conclusion, our study underscores the crucial role of ATR in cisplatin resistance and highlights the promising anti-proliferative effects of the Elimusertib/Cisplatin combination in cisplatin-resistant HB models, offering a potential new therapeutic option for treating high-risk and refractory HB.

Study EGAS00001007916

Sequencing data from MethylScan assay on plasma

Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Here, we present DeBias, a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias eliminates bias-associated subspaces within the entire feature space using control samples and enables global bias correction across all features, effectively preserving disease-specific signals while minimizing demographic distortions. To demonstrate its effectiveness, we applied DeBias to cfDNA methylation data for cancer detection. It achieved a >6-fold reduction in the number of features containing biases and outperformed existing methods in improving the cancer detection performance for minority populations. Our method represented a promising step toward developing machine learning models that are more accurate, reliable, and equitable for minority populations.

Study EGAS00001008127

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

Targeted long-read snIso-Seq of the human brain in neurodegenerative diseases

Nuclei were extracted from postmortem human brain, and cDNA libraries were generated using the 10X Genomics 3' v3.1 kit. Prior to fragmentation, 75% of the library was reserved for long-read sequencing. This unfragmented library was used for target enrichment with a custom 50 gene probe panel from Twist Biosciences. The resulting amplified cDNA libraries were sequenced on a Sequel II. The files provided have undergone CCS generation, and we recommend following the guidelines in https://isoseq.how/ for further analysis starting with removal of primers using lima. The primer sequences that should be supplied are the Read 1 and TSO primers from the 10X Genomics kit.

Dataset EGAD50000000179

scATAC-seq of CD4+ T cells from blood, lymph nodes and tumors of NSCLC patients

This study explore the CD4+ T cells diversity in paired blood, lymph nodes and tumors of 2 different NSCLC patients. After FACS-sorted of Tregs (DAPI- CD45+ CD4+ CD25hi CD127lo) and Tconvs (DAPI- CD45+ CD4+CD25lo CD127lo/hi), cells were mixed in equal proportion (fifty/fifty ratio) and procesed with 10X Chromium (10X Genomics) scATAC kit and sequenced using Illumina platforms.

Study EGAS50000000294

DPY30 ChIP-seq

H9 human embryonic stem cells (hESCs) were cultured in feeder-free chemically-defined conditions in medium containing 10ng/ml Activin A and 12ng/ml FGF2 (Vallier L. 2011, Methods in Molecular Biology, 690: 57-66). Chromatin immunoprecipitation was performed as described in Brown S. et al. 2011. Stem Cells 29: 1176-85 by using 5ug of anti-DPY30 antibody (Sigma, cat. number HPA043761). This protocol was performed in control hESCs (expressing a scrambled shRNA) and in hESCs stably expressing an shRNA against DPY30 (Sigma, clone n. TRCN0000131112).This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Dataset EGAD00001001268

LLD PhIPSeq

LLD PhIP-Seq reads. Oligopeptides were designed at Eran's Segal group at Weizmann Institute of Science. Dataset include 1,783 plasma samples. In 340 participants, a second time point was taken after a 4-year follow-up.

Dataset EGAD00001010104

12312 results for "cancer rna-seq"

in 23.20 milliseconds.