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• Assessment of cannabidiol and Δ9-tetrahydrocannabiol in mouse models of medulloblastoma

  These data were used in the following publication: Andradas, C.; Byrne, J.; Kuchibhotla, M.; Ancliffe, M.; Jones, A.C.; Carline, B.; Hii, H.; Truong, A.; Storer, L.C.D.; Ritzmann, T.A.; et al. Assessment of Cannabidiol and delta9-Tetrahydrocannabiol in Mouse Models of Medulloblastoma and Ependymoma. Cancers 2021, 13, 330. https://doi.org/10.3390/cancers13020330 There are 4 paired-end RNA-seq samples from paediatric brain cancer cell lines.

  Dataset EGAD00001006923

• Whole genome sequencing of 40 rainforest hunter-gatherers and neighbouring farmers from Central Africa

  Exome sequencing of 20 rainforest hunter-gatherers (RHG) and 20 neighbouring farmers (AGR) from western central Africa was performed using 101-bp paired-end reads on Illumina HiSeq 2000. All individuals presented very low rates of missing values ranging from 0.5% to 4%, and a mean depth of coverage of 6.5× (ranging from 4× to 13×)(Lopez et al., Curr Biol 2019).

  Dataset EGAD00001005139

• Chromatin 3D interactions mediate genetic effects on gene expression (ChIP-seq)

  ChIP-seq data for Lymphoblastoid Cell Lines (LCL) and Fibroblasts (FIB) from the Gencord Cohort: - 160 LCLs assayed for H3K27ac, H3K4me1 and H3K4me3, - 78 FIB assayed for H3K4me3 and 79 FIB assayed for H3K27ac and H3K4me1 This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.

  Dataset EGAD00001004871

• Megabase scale methylation phasing using Nanopore long reads and NanoMethPhase

  This paper describes the work by Akbari V,. et al. on detection of allele specific methylation using oxford nanopore sequencing data. They have developed set of tools, SNVoter and NanoMethPhase, and workflow which enable the detection of allele specific methylation even in samples with sparse coverage of nanopore sequencing data.

  Dataset EGAD00001007920

• Transcriptome profiling of prostate tissue samples from early onset prostate cancer patients and normal controls by RNA-seq

  The dataset contains RNA-seq data of 96 EOPC patients and 9 controls. For some patients multiple tissue samples were sequenced ("multi-area" samples). The RNA extraction and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001004791

• AT-AML samples dataset

  Serial samples from one AT-AML patient as described in publication Goldgraben et al Pediatric Blood & Cancer 2020. Whole exome sequencing of a AT-'germline' blood sample, one bone marrow sample (at AML diagnosis) and 3 AML blood samples. Library preped using the Illumina Nextera Rapid Capture Exome Enrichment Kit, and sequenced as PE150 on HiSeq4000. Provided: 5 BAM files (GRCh37); 2 VCF analyses (germline and somatic)

  Dataset EGAD00001006090

• Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

  We created three technical replicates of cell-free DNA from AML patient plasma to assess batch effects and utility of spike-in controls for the cfMeDIP-seq method. Each set of samples were given to three different technicians with slightly different protocols. Details can be found in Wilson et al. "Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls".

  Dataset EGAD00001006986

• Genomic Profiling Reveals Spatial Intra-tumour Heterogeneity in Follicular Lymphoma

  Follicular lymphoma (FL) is an incurable indolent non-Hodgkin’s lymphoma (NHL) that behaves heterogeneously and is synonymous with the reciprocal translocation t(14;18)(q32;q21), leading to aberrant constitutive over-expression of BCL2 [ref]. High risk groups with poor overall survival include patients that transform to a high grade lymphoma, most commonly diffuse large B cell lymphoma (DLBCL) or progress early (within 2 years) of receiving treatment. Recently several studies have shed light on the diverse genomic landscape of FL, with frequently mutated genes including those involved in chromatin remodelling, (CREBBP, KMT2D, EZH2, EP300), immune modulation (TNFRSF14), JAK-STAT (STAT6, SOCS1), NF-ĸB (CARD11, MYD88, TNFAIP3) and mTORC1 signalling (RRAGC) [ref]. To date, the majority of these studies have either focussed on inter-patient genetic heterogeneity or established the extent of clonal heterogeneity as a patient’s tumour evolves over time. Furthermore, these temporal studies have alluded to the existence of a tumour-repopulating population (referred to as the common progenitor cell (CPC)) that evades treatment and acts as a reservoir, seeding each subsequent relapse and transformation event. Although these previous studies have illuminated the longitudinal clonal dynamics that occur in FL, our understanding of the degree of spatial or intra-tumour heterogeneity (ITH) that exists within an individual patient thus far remains limited. Earlier studies have predominantly focused on differences in cytological grade and immunophenotype between spatially separated lymph nodes and bone marrow, the most common site of extra-nodal involvement in FL, with genomic profiling restricted to examining somatic hypermutation patterns in IgVH genes [ref]. In contrast next generation sequencing has been increasingly utilised in solid organ malignancies to derive comprehensive genomic profiles from spatially separated sites. The seminal study by Gerlinger et al revealed profound differences in the genetic make-up between individual primary and metastatic sites of renal cell carcinoma [ref]. Significant heterogeneity has since been demonstrated both between and within lesions in the same patient in lung, pancreas and breast cancer with presumed driver mutations distributed within the “branches” of the evolutionary phylogenetic tree, suggesting that a single biopsy is incapable of capturing the full genomic heterogeneity of an individual’s malignancy [ref]. This geographical heterogeneity not only adds to the diverse pool of tumour subclones that may contribute to drug resistance mechanisms but importantly, presents a major obstacle for precision-based approaches focussed on targeting specific lesions within a single biopsy. In FL, the exponential increase in clinical trials using novel agents such as EZH2, PI3K and BTK inhibitors reflects this shift in cancer care and along with the development of molecular prognostic scores such as the m7-FLIPI highlights the clinical need to accurately define genomic alterations with clinical relevance. As the majority of FL patients manifest disseminated tumour involvement, we sought to uncover the extent and clinical importance of spatial heterogeneity in FL by comprehensively genetically profiling 22 synchronously removed spatially separated biopsies from 9 patients. Using a combination of whole exome and targeted deep sequencing, our results inferred the complex subclonal architecture within these tumours and the mutational differences between anatomical sites, demonstrating cases with significant intrinsic genetic diversity.

  Study EGAS00001002492

• Liquid Biopsy Versus Tissue Biopsy to Assess Acquired Resistance and Tumor Heterogeneity in Gastrointestinal Cancers

  Tumor heterogeneity can drive the evolution of multiple tumor subclones harboring unique molecular resistance alterations in different metastatic lesions in an individual patient, under the selective pressure of therapy1-3. Studies have suggested that liquid biopsy may better capture the heterogeneity of acquired resistance, but systematic, direct comparisons of post-progression liquid vs. standard single-lesion tumor biopsies are lacking. In a prospective cohort of 44 patients with molecularly-defined gastrointestinal cancers and acquired resistance to targeted therapy, direct comparison of post-progression liquid vs. tumor biopsy revealed that liquid biopsy more frequently identified clinically-relevant resistance alterations and multiple resistance mechanisms, detecting resistance alterations not detected in matched tumor biopsy in 78% of cases. Whole-exome sequencing of serial cell-free DNA, tumor biopsies and rapid autopsy specimens elucidated geographic and evolutionary characteristics of heterogeneity. Our data suggest that acquired resistance is frequently characterized by profound tumor heterogeneity and highlight the potential clinical utility of liquid biopsy. Burrell, R. A. & Swanton, C. Tumour heterogeneity and the evolution of polyclonal drug resistance. Molecular oncology 8, 1095-1111, doi:10.1016/j.molonc.2014.06.005 (2014). Misale, S. et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 486, 532-536, doi:10.1038/nature11156 (2012). Ahronian, L. G. et al. Clinical Acquired Resistance to RAF Inhibitor Combinations in BRAF-Mutant Colorectal Cancer through MAPK Pathway Alterations. Cancer Disco 5, 358-367, doi:10.1158/2159-8290.Cd-14-1518 (2015).

  Study phs001853

• Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS)

  Advances in antiretroviral therapies (ART) and patient management have improved survival of people living with HIV (PLWH). However, with exposure to ART and associated side effects and toxicities as well as to the virus itself, PLWH are at an increased risk of several chronic diseases. The Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) research network integrates longitudinal clinical data and treatment management of PLWH and provides research infrastructure to support HIV-associated clinical, social, and behavioral outcomes and comparative effectiveness research using data collected from 8 Centers for AIDS Research clinical sites across United States. For detailed study description, see Kitahata et al. (2008, PMID:18263650).

  Study phs001788