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• Single cell RNA-seq of two rare cases of human glioblastoma at multiple sampling points

  Glioblastoma is characterized by large cellular diversity whose complexity and organizing principles are only starting to be uncovered. Both neurodevelopment-like and mesenchymal-like cell states have been described in glioblastoma but the nature of the mesenchymal-like cell states remains unresolved. Here, we performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex with the aim of understanding these tumor cell states.

  Study EGAS50000001030

• Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

  Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genome- wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories.

  Study EGAS00001006598

• scRNAseq dataset of circulating T cells in FL patient before and after Lenalidomide treatment

  scRNAseq dataset of circulating T cells from 3 FL patients (P011, P014 and P020) included in the GALEN clinical trial. There is two time points for each patient : One before treatment (D0) and one at day 7 of Lenalidomide treatment (D7).

  Dataset EGAD50000001529

• Cord blood progenitor CITE-seq dataset

  Sequencing results of single-cell transcriptome and antibody libraries from two biological experiments of cord blood progenitor cells. Four samples from different time points were processed using 10X Genomics Chromium Next GEM Single Cell 3’ Reagent Kits v3.1. Gene expression and antibody-derived libraries were sequenced separately.

  Dataset EGAD50000000405

• Novel Strategies to Eliminate Resistance to B-cell Receptor Inhibitor Therapy in Lymphoid Malignancies

  Ibrutinib and acalabrutinib are BTK inhibitors (BTKi) used as frontline therapies for chronic lymphocytic leukemia (CLL). Clonal evolution during ibrutinib treatment has previously been studied, but limited study of clonal evolution in patients receiving acalabrutinib has been done. Our group analyzed 216 blood samples from 38 CLL patients at multiple time points during their BTKi treatment. Samples were prepared by standard protocols and sequenced using 200x Illumina sequencing. Using the longitudinal data, we reconstructed the clonal evolution of each patient using somatic mutations found within the B-cell populations. Three patterns of clonal evolution were identified: 1) new clone emergence, 2) clonal selection, and 3) clonal replacement. As previously seen in ibrutinib treatment, the evolution of subclones containing CLL-driver mutations was associated with worse clinical outcomes for patients treated with acalabrutinib (Log-rank p=0.04). Understanding clonal evolution during treatment with acalabrutinib can help determine and modify the clinical course of patients with CLL.

  Study phs003042

• Transcriptomic classes of BCR-ABL1 lymphoblastic leukemia

  In BCR-ABL1 lymphoblastic leukemia, treatment heterogeneity to tyrosine kinase inhibitors (TKIs), especially in the absence of kinase domain mutations in BCR-ABL1, is poorly understood. Through deep molecular profiling, we uncovered three transcriptomic subtypes of BCR-ABL1 lymphoblastic leukemia, each representing a maturation arrest at a stage of B-cell progenitor differentiation. An earlier arrest was associated with lineage promiscuity, treatment refractoriness, and poor patient outcomes. A later arrest was associated with lineage fidelity, deep and durable leukemia remissions, and improved patient outcomes. Each maturation arrest was marked by specific genomic events that control different transition points in B-cell development. Interestingly, these events were absent in BCR-ABL1+ pre-leukemic stem cells isolated from patients regardless of subtype, which supports that transcriptomic phenotypes are determined downstream of the leukemia-initialing event. Overall, our data indicate that treatment response and TKI-efficacy is an unexpected outcome of the differentiation stage at which this leukemia transforms.

  Study EGAS00001007167

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the 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 measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• A Perioperative Study of Safusidenib in Patients with IDH1-Mutated Glioma

  10 participants with a radiological or pathological diagnosis of WHO Grade 2 lower-grade glioma (LGG) were recruited at a single center starting in December, 2022. Eligibility criteria permitted participants who had undergone prior surgery for WHO Grade 2 LGG, but excluded those with a history of prior radiation or chemotherapy.In Part A of the study, participants underwent an initial craniotomy with tumor biopsy and a lumbar puncture for cerebrospinal fluid (CSF) collection at study entry. Following sample collection, participants received safusidenib at the recommended phase 2 doses of 250 mg twice daily (b.i.d.) for a period of 22–36 days. This was followed by a second craniotomy for maximal safe tumor resection and a repeat lumbar puncture within 5 hours of the final pre-resection dose of safusidenib. Tumor, blood, and CSF samples were collected at both surgical time points for comprehensive translational research.Molecular analyses were performed on samples collected at both time points. These included pharmacokinetics (PK), targeted metabolomics, whole-genome sequencing (WGS) of tumor tissue, single-nucleus RNA sequencing (snRNA-seq), and DNA methylation profiling on all patients. Targeted metabolomics was conducted on samples from 9 participants, while spatial transcriptomics and spatial metabolomics were performed on tumor tissue from 3 participants each. Histone methylation profiling was conducted on samples from 8 participants.

  Study phs003976

• 16S-based fecal microbiota composition

  The dataset reports the 16S rRNA gene sequencing of the fecal microbiota of donors from the Milieu Intérieur Cohort. The Milieu Intérieur cohort includes a total of 1,000 healthy individuals of western European ancestry, recruited in France as part of the Milieu Intérieur project. To assess their fecal microbiota composition, 16S rRNA profiles were generated from stool samples of 863 of the 1,000 donors. Human stool samples were produced at home no more than 24 hours before the scheduled medical visit and collected in a double-lined sealable bag maintaining strict anaerobic conditions. Upon reception at the clinical site, the fresh stool samples were aliquoted and stored immediately at -80°C. DNA was extracted from stool and barcoding PCR was carried out using indexed primers targeting the V3-V5 region of the 16S rRNA gene. Equal volumes of normalized PCR reaction were pooled and thoroughly mixed. The amplicon libraries were sequenced on Illumina MiSeq.

  Dataset EGAD00001004979

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746