13304 results for ""pdc"+"heritage+language"+census+study"

in 32.71 milliseconds.

• Epigenetic landscape of mixed phenotype leukemias

  Leukemias with ambiguous lineage comprise a number of loosely defined entities, often without a clear mechanistic basis. Here, we investigated a group of such leukemias with a CpG Island Methylator Phenotype (CIMP), previously identified as CEBPA-silenced AML. Transcriptomics and epigenomics analyses revealed a hybrid myeloid/lymphoid epigenetic landscape, whereas genetic alterations were heterogenous. This suggests that CIMP leukemias are defined by their shared epigenetic profile rather than a common genetic lesion. Gene expression enrichment showed strong similarity with ETP-ALL and an early lymphoid progenitor cell of origin. Accordingly, integration of differential methylation and expression revealed widespread silencing of myeloid transcription factors (TFs), among which CEBPA was key for differentiation arrest. Hypermethylation also resulted in loss of CTCF binding, accompanied by a few changes in chromatin interactions involving critical TFs like KLF4. In conclusion, epigenetic dysregulation, and not genetic lesions, explain the mixed phenotype of a group of CIMP leukemias resembling ETP-ALL.

  Study EGAS00001007094

• Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes

  DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N=190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P<1x10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.

  Study EGAS00001007118

• Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse

  From all paediatric brain tumours, medulloblastomas with chromothripsis, a form of genome instability leading to massive genome rearrangements, are particularly aggressive. To dissect the complex biology underlying the aggressiveness of chromothriptic medulloblastomas, we applied spatial transcriptomics to i) chromothriptic and non-chromothriptic medulloblastomas from the same molecular subgroup (n=13) and ii) patient-derived xenografts from chromothriptic medulloblastoma, from the minimal residual disease stage to regrown tumours (n=11). Chromothriptic medulloblastomas showed higher spatial intra-tumour heterogeneity, proliferation and stemness, but lower immune infiltration and differentiation, as compared with non-chromothriptic medulloblastomas. Spatial mapping of genetic clones identified phenotypic features such as degree of differentiation, proliferation and immune infiltration enriched in specific clones. Cells from multiple genetic clones resisted treatment and gave rise to relapse in patient-derived xenografts of chromothriptic medulloblastoma. We identified a potential role of tumour microtubes in treatment resistance in chromothriptic medulloblastoma.

  Study EGAS00001007128

• The genetic history of the southern Andes from present-day Mapuche ancestry

  We generate genome-wide data from 64 participants from three Mapuche populations in Southern Chile: Pehuenche, Lafkenche, and Huilliche. Broadly, we describe three main ancestry blocks with a common origin, which characterize the Southern Cone, the Central Andes, and Amazonia. Within the Southern Cone, ancestors of the Mapuche lineages differentiated from those of the Far South during the Middle Holocene, and did not experience further migration waves from the north. We find that the deep genetic split between the Central and Southern Andes is followed by instances of gene flow, which may have accompanied the southward spread of cultural traits from the Central Andes, including crops and loanwords from Quechua into Mapudungun (the language of the Mapuche). Our findings add new perspectives on the genetic (pre)history of South America, from first settlement through to the present-day indigenous presence. Follow-up fieldwork took these results back to the indigenous communities to contextualize the genetic narrative alongside indigenous knowledge and perspectives.

  Study EGAS00001007200

• RNAseq of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007300

• WES of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007301

• A longitudinal single-cell atlas of treatment response in pediatric AML

  Pediatric acute myeloid leukemia (pAML) is a disease characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains relatively understudied in pediatric patients. We therefore used single-cell RNA sequencing and single-cell ATAC sequencing to profile 684,031 diagnosis, remission and relapse cells from 28 patients representing different pAML subtypes. Analysis revealed that at diagnosis, cellular compositions differed between distinct subgroups. Upon relapse, cellular hierarchies transitioned towards a more primitive state regardless of subtype. These primitive cells were distinct compared to cells at diagnosis, having underrepresentation of transcriptional programs involved in myeloid differentiation while programs commonly found in other lineages were overrepresented. In a subset of patients, this appeared to accompany the appearance of a B-lymphoid-like hierarchy. Together, our data reveal the emergence of apparent subtype-specific plasticity upon treatment and inform on potential novel therapeutic angles to target these cell populations.

  Study EGAS00001007323

• Serial TERT rearrangement breakpoint quantification in circulating tumor DNA enables minimal residual disease monitoring in patients with neuroblastoma

  Approximately 30% of high-risk neuroblastomas harbor genomic TERT rearrangements at diagnosis, resulting in high TERT transcript levels and active telomerase. Combined with mutations in the RAS/MAPK/ALK signaling transduction network, these patients have a dismal prognosis. Our objective was to establish a liquid biopsy-based monitoring strategy for this particularly vulnerable patient subgroup, for whom no in-time molecular diagnostic tools exist to date. Detection and quantification of TERT rearrangement breakpoints in cell-free tumor DNA circulating in peripheral blood and bone marrow plasma from patients with TERT-driven neuroblastoma improved minimal residual disease monitoring and early relapse detection in individual patients. TERT rearrangement breakpoints, as a single marker or combined with mutations in the RAS/MAPK/ALK signaling transduction network, can be reliably analyzed from 1ng DNA using droplet digital PCR assays fit for clinical routine use. TERT rearrangement breakpoints are reflected in cell-free tumor DNA and can serve as robust biomarkers for disease activity.

  Study EGAS00001007365

• High-resolution, patient-level dissection of IL-23 blockade in cutaneous psoriasis

  Psoriasis vulgaris and other chronic inflammatory diseases improve markedly with therapeutic blockade of IL-23 signaling in T cells, but the genetic mechanisms of response remain poorly understood. We single-cell transcriptomically profiled CD45+ immune cells isolated from lesional psoriatic skin before and after IL-23 blockade. In clinically responsive patients, a psoriatic transcriptional signature in skin-resident memory T cells was sharply attenuated. In contrast, poorly responsive patients were distinguished by enduring T17 cell activation, a mechanism distinct from alternative cytokine signaling or downstream resistance. Spatial transcriptomic analysis suggests that successful IL-23 blockade requires dampening of > 90% of IL-17-induced signaling in lymphocyte-adjacent keratinocytes, an unexpectedly high threshold. We also detected a subset of persistent, disease-specific T17 abnormalities in responsive patients, revealing an irreversible cell identity that may necessitate ongoing IL-23 inhibition. Collectively, our data establishes a patient-level paradigm for dissecting response to immunomodulatory treatments.

  Study EGAS00001007373

• Immune landscape of oncohistone-mutant gliomas reveals diverse myeloid populations and tumor-promoting behavior

  Histone H3-mutant gliomas are deadly brain tumors characterized by a dysregulated epigenome and stalled differentiation. In contrast to the extensive datasets available on tumor cells, limited information exists on their tumor microenvironment (TME), including the immune infiltrate. Here, we characterize the TME of H3.3K27M and G34R/V-mutant gliomas, and multiple H3.3K27M mouse models, using transcriptomic and proteomic, including spatial single-cell approaches. Resolution of immune lineages indicates uniform high-infiltration of H3-mutant gliomas with diverse myeloid populations, high-level expression of immune checkpoints, and scarce lymphoid cells, findings uniformly reproduced in all H3.3K27M models tested. We show these myeloid populations communicate with H3-mutant cells mediating immunosuppression and sustaining tumor formation and maintenance. Dual inhibition of myeloid cells and immune checkpoints showed significant therapeutic benefit in pre-clinical syngeneic models. Our findings provide valuable characterization of the TME of oncohistone-mutant gliomas, and insights into means to modulate the myeloid infiltrate for the benefit of patients.

  Study EGAS00001007510

• A clinically applicable connectivity signature for glioblastoma includes the tumor network driver CHI3L1

  Tumor microtubes (TMs) connect glioma cells to a network with considerable relevance for tumor progression and therapy resistance. The determination of TM-interconnectivity in individual tumors has been challenging and the impact on patient survival unresolved. Here, a connectivity signature from single-cell RNA-sequenced (scRNA-Seq) xenografted primary glioblastoma (GB) cells has been established using a dye uptake methodology, confirmed with recording of cellular calcium epochs and validated with clinical correlations. Astrocyte-like and mesenchymal-like GB cells have the highest connectivity signature scores in scRNA-sequenced patient-derived xenografts and patient samples. In large GB cohorts, network connectivity correlated with the mesenchymal subtype and dismal patient survival. CHI3L1 has been identified and validated as a robust molecular marker of connectivity with functional relevance. The connectivity signature allows novel insights into brain tumor biology, provides a proof-of-principle that tumor cell TM-connectivity is relevant for patients’ prognosis, and serves as a robust prognostic biomarker.

  Study EGAS00001007611

• Unraveling mutagenic processes influencing the tumor mutational patterns of individuals with Constitutional Mismatch Repair Deficiency

  Constitutional mismatch repair deficiency (CMMRD), caused by bi-allelic germline variants in one of the mismatch repair (MMR) genes, is a childhood cancer predisposition syndrome that often results in the development of multiple tumors early in life. A better understanding of mutational processes driving subsequent CMMRD tumors could advance optimal treatment. Therefore, we performed a genomic characterization of 41 tumors from 17 individuals with CMMRD. Mutational patterns in these tumors were found to be influenced by multiple factors, including the affected MMR genes, tumor types and somatic polymerase proofreading mutations. Temozolomide treatment left prominent mutational signatures in two second primary hematologic malignancies. Furthermore, a novel indel signature was found in 54% of the tumors, characterized by one base pair cytosine insertions in cytosine homopolymers. In conclusion, the analysis of sequential tumors in individuals with CMMRD reveals diverse mutational patterns influenced by the underlying mutated MMR gene, tumor type and treatment history.

  Study EGAS00001007660

• Cross-species Comparison Reveals Therapeutic Vulnerabilities Halting Glioblastoma Progression

  The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecast how tumor cells organize to sustain growth and identifies rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA- related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt- antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte- like one. Our findings offer a framework for patient stratification with prognostic value, biomarker identification, and therapeutic avenues to halt GBM progression.

  Study EGAS00001008155

• Epigenetic characterization of glioblastoma stem cells

  Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary human GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In-depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival, in line with the higher invasive properties of Invasive state GSCs compared to Reactive and Constructive GSCs as shown by in vitro and in vivo assays. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

  Study EGAS50000001804

• HGSC WGS for the study Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  HGSC cases in the OvCaRe and CRCHUM Tumour Banks were selected according to the following criteria: (i) were administered platinum taxane based therapy; (ii) relapsed within 12 months (365 days) or had at least longer than 4.5 years (1642.5 days) follow-up data; (iii) had at least 50% tumour content by H&E staining and expert pathology review. All cases were re-reviewed by expert pathologists to confirm the diagnosis of HGSC. Germline BRCA1 and BRCA2 was determined for all patients through hereditary cancer screening programs. The design of cases selection as a discovery cohort was engineered to amplify biological differences by selecting cases from the extremes of the outcome distribution. All HGSC tumours are primary tumour samples. Library construction and sequencing Frozen specimens with >50% tumour cellularity (based on initial slide review) were used for cryosectioning and subsequent nucleic acid extraction. Patient tumour and normal blood samples derived from primary, untreated fresh frozen tumour specimens harvested at diagnosis during standard of care debulking surgery. Germline DNA was provided from peripheral blood buffy coat on all specimens except 13 from Tokyo, where non-cancer frozen tissue was used as a germline source. DNA extraction from both matched normal (blood) and tumour samples (frozen tissue) were performed using the QIAamp Blood and Tissue DNA kit (Qiagen) and quantified using a Qbit fluorometer and reagents (high-sensitivity assay). Three lanes of Illumina HiSeq 2500 v4 chemistry for normal samples and five lanes for tumour samples were obtained. The PCR-free protocol was adopted to eliminate the PCR-induced bias and improve coverage across the genome.

  Dataset EGAD00001003268

• Natural history of clonal haematopoiesis (2017-09-04)

  The incidence of acute myeloid leukemia (AML) increases with age and mortality exceeds 90% when diagnosed after age 60. Only 10-15% of cases evolve from a pre-existing myeloproliferative or myelodysplastic disorder; the remaining cases arise de novo without a detectable prodrome and are diagnosed upon development of bone marrow failure. Analysis of diagnostic blood samples has demonstrated that de novo AML is preceded by the accumulation of somatic mutations in pre-leukemic hematopoietic stem and progenitor cells (preL-HSPCs) that subsequently undergo clonal expansion. If individuals in this pre-leukemic phase could be identified, methods for determination of risk and monitoring for progression to overt AML could be developed. However recurrent AML mutations also accumulate during aging in healthy individuals who never develop AML, referred to as age related clonal hematopoiesis (ARCH). To distinguish individuals with preL-HSPCs at high risk of developing AML from those with ARCH, we undertook deep targeted sequencing of genes recurrently mutated in AML in blood samples from 133 individuals in the European Prospective Investigation into Cancer and Nutrition (EPIC) study taken on average 6 years before they developed AML (pre-AML group), together with 683 matched healthy individuals (Control group). Pre-AML cases displayed accelerated age-correlated accumulation of somatic mutations.The identity, number and variant allele frequency (VAF) of mutations differed between the two groups, and were incorporated into a computational model of AML risk prediction that accurately distinguished pre-AML cases from controls on average 7 years prior to AML development. Our findings provide proof of concept that early prediction of AML development is feasible in high-risk populations, paving the way for early disease detection, monitoring, and potentially prevention.

  Dataset EGAD00001003703

• Molecular diagnosis of albinism (2018-03-14)

  Albinism is genetically heterogeneous rare genetic condition affecting 1:17000 in the Western world (but more frequent in Africa) whose main feature is a profound visual impairment, characterised by foveal hypoplasia, abnormal chiasmatic connections, nystagmus and photofobia. All these features result in severly altered visual acuity (<0,1), absent depth perception and poor night vision. People with albinism are primarily visually handicapped. In addition, for some types of albinism, the visual phenotype can be presented with partial or total hypopigmentation, hence resulting in a secondary phenotype which can lead to skin cancer if skin is not adequately protected. Recently a new syndrome has been described, FHONDA, with the same visual abnormalities of albinism but without pigment alteration. The traditional classification differentiates Oculoculatenous albinism (OCA), where hypopigmentation involves hair, skin and eyes versus Ocular Albinism (OA), where hypopigmentation only affects the eyes. These are non-sydrimic types of albinism. Some syndromic forms (Hermansky-Pudlak=HPS, Chediak-Higashi=CHS) affect cells beyond pigment cells, present in the lungs, immune system, platelets and intestines, resulting in more severe phenotypes that can be fatal. Mutations in at least 19 genes are assocaited with the corresponding types of albinism. Most hospitals will only diagnose the most frequent cases using traditional Sanger, MLPA approaches. Some will use CGH arrays. We aim to diagnose all cases of albinism through the Albinochip proposal, which combines a Sequenom first step of known mutations combined with subsequent NGS approaches. In some cases we fail to find a second mutation, these are good candidates for further full exome analyses. 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/ . This dataset contains all the data available for this study on 2018-03-14.

  Dataset EGAD00001004039

• Spiradenocarcinoma (2018-10-29)

  Spiradenocarcinoma is a rare cutaneous sweat gland adnexal cancer with potential for aggressive behaviour. They are classified histologically into low- and high-grade tumours, with morphologically low-grade tumours thought to behave more favourably. However, limited information is available, with only 18 published cases. We have collected morphologically low-grade spiroadenocarcinomas (one with a lung metastasis) and high-grade spiroadenocarcinomas, as well as some spiradenomas (benign lesions), cylindromas (another type of malignant cutaneous sweat gland adnexal tumour) and hybrid spiradenoma-cylindromas. H&E-stained sections were reviewed, follow-up was obtained, and immunohistochemistry for Ki-67, p53 and, MYB has been performed. The tumours were solitary, measuring 0.8-7?cm (median: 2.7?cm), with a predilection for the head and neck of elderly patients (median age: 72 years; range 53-92) without gender bias. Histologically, the tumours were multinodular and located in deep dermis and subcutis. A pre-existing spiradenoma was present in all cases. The malignant component was characterized by expansile growth with loss of the dual cell population, up to moderate cytological atypia and increased mitotic activity (median: 10/10 HPF; range 1-28). Additional findings included squamoid differentiation (n=9), necrosis (n=7), and ulceration (n=5). P53 expression was variable and no significant differences were noted in the benign compared with the malignant parts of the tumours. In contrast, in the malignant components the Ki-67 proliferative index was slightly increased, and MYB expression was lost. Follow-up (median: 67 months; range: 13-132) available for 16 patients (84%) revealed a local recurrence rate of 19% but no metastases or disease-related mortality. Here we wish to exome sequence these cases to define the first genomic landscape for this malignancy. This dataset contains all the data available for this study on 2018-10-29.

  Dataset EGAD00001004426

• Exome sequencing of Congenital Heart Disease families Leuven

  This project aims to study at least 90 exomes from families with congenital heart disease. The samples have been selected in Leuven in collaboration with Koen Devriendt. Ethic approval has been sought for in Leuven, Belgium and a HDMMC agreement for submitting these samples is in place at the WTSI. The phenotype we wil primarily focus our analysis is severe Left Ventricular Outflow Tract Obstructions (LVOTO) and Atrioventricular Septal Defect (AVSD). The indexed Agilent whole exome pulldown libraries will be sequenced on 75bp PE HiSeq (Illumina).

  Dataset EGAD00001000796

• Exome sequencing of Congenital Heart Disease families Royal Brompton

  This project aims to study at least 90 exomes from families with congenital heart disease. The samples have been selected at the Royal, Brompton Hospital in collaboration with Stuart Cook and Piers Daubeney. Ethic approval has been sought for in the UK and a HDMMC agreement for submitting these samples is in place at the WTSI. The phenotype we wil primarily focus our analysis is severe Left Ventricular Outflow Tract Obstructions (LVOTO) and Atrioventricular Septal Defect (AVSD). The indexed Agilent whole exome pulldown libraries will be sequenced on 75bp PE HiSeq (Illumina).

  Dataset EGAD00001000797

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: pancreas (2019-04-03)

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (Illumina HiSeqX, 40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004893

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005141

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005142

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005143

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX021_SA854_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005144

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005145

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX023_SA604X9XB02413_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005146

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005147

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX024_SA604X9XB02417_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005148

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX020_SA604X8XB02164_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005149

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005150

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 36 samples; filetype=fastq

  Dataset EGAD00001005151

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005152

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX019_SA604X7XB02089_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005153

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX_014_SA604X6XB01979_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005154

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX_015_SA604X6XB01979_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005155

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX018_VOA11019SA_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005156

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX018_VOA11019SA_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 24 samples; filetype=fastq

  Dataset EGAD00001005157

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX026_VOA11083SD_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005158

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX003_SA605X3XB01966_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005159

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX003_SA605X3XB01966_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005160

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_003

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005161

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX004_SA605X3XB01966_004

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005162

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005163

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX006_PBC04106_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005164

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX038_VOA11267_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 3 samples; filetype=fastq

  Dataset EGAD00001005165

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX050_PBC04573_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005166

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX050_PBC04573_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005167

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX051_PBC04633_001

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005168

• Sequencing data for study Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses for library TENX051_PBC04633_002

  Single-cell RNA-sequencing data generated using the 10X genomics chromium platform, comprising patient derived xenograft, cell line, and primary tumour data. This includes different digestion conditions (37C collagenase vs 6C cold protease) and FACS sorting for live, dying, and dead cells. 12 samples; filetype=fastq

  Dataset EGAD00001005169