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• Dataset for whole exome sequencing of PTCLs

  The dataset consists of whole exome sequencing FASTQ files and analyzed data, including single nucleotide variants (SNVs) and short insertions and deletions (Indels) of candidate driver genes.

  Dataset EGAD50000001798

• Whole Genome Sequencing of Two Family Trios with 22q.11.2 Deletion Syndrome

  Two subjects with 22q11.2 deletion syndromes (22q11DS) and their parents were recruited for a whole genome sequencing study to identify candidate genetic modifiers of the various phenotypes seen in 22q11DS. Both probands had a typical 3 megabase deletion on chromosome 22q11.2 but discordant phenotypes.

  Study phs000837

• Clones derived from early passage tumoroids of colorectal cancer

  We obtained different clones from early passage CRC tumoroids to study mutational signatures specific for truncal or private somatic alterations. These whole genome sequences are part of a larger study on the heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer.

  Study EGAS50000000107

• Exomes of High-risk Prostate cancer

  DNA extracted from tumoral tissue of 39 patients was used for exome sequencing. As a comparison, DNA extracted from blood was used as a non-tumoral control. DNA was captured using the EZ SeqCap v3 exome kit from Roche and sequenced using an Illumina HiSeq instrument.

  Study EGAS00001001015

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• RNA-sequencing from ALL patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study.

  Dataset contains RNA-sequencing data (fastq files) from 45 patients treated on the the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study, an MRD-stratified Paediatric Protocol. Patient samples (bone marrow or peripheral blood) were taken at diagnosis. mRNA was extracted from blast cells and underwent paired-end sequencing (75bp) using the illumina NextSeq platform. Genomic data was used for identification of genomic drivers of acute lymphoblastic leukaemia (ALL).

  Dataset EGAD50000001111

• Dataset of PGD PGS study in CITIC Xiangya and BGI

  A total of 395 couples were subjected to IVF-PGD treatment, including 129 couples with NGS-based test and 266 couples with SNP array based test for the detection of embryonic chromosomal abnormalities. The NGS test was performed using low coverage whole genome sequencing with HiSeq 2000 platform. And the SNP array test was using Affymetrix Gene Chip Mapping Nsp I 262K. The average age of patients was 32.1 years (age range 20-44 years).

  Dataset EGAD00001001037

• RNA-seq and Hi-C data of a chromothripsis patient's iPS cells

  This dataset contains RNA-seq and Hi-C data files of induced pluripotent stem (iPS) cells and iPS cell-derived neural progenitors (NPCs) derived from a germline chromothripsis patient and both parents. iPS cells of the patient (cell lines 14 and 15), the father (lines 23 (with two replicates) and 32) and mother (line 30) were differentiated to NPCs and RNA was collected on day 0, day 7 and day 10 of differentiation. In addition, Hi-C data for two iPS cell-derived NPC lines from the patient (14 and 15) and two lines from the father (23 and 32) was generated.

  Dataset EGAD00001002242

• Single Cell Transcriptional Analysis of Human Adenoids Identifies Molecular Features of Airway Microfold Cells

  We aimed to characterize the cellular composition and molecular features of the human adenoid, a mucosa-associated lymphoid tissue located in the upper airway, with a focus on epithelial populations involved in immune surveillance. To this end, we performed single-nucleus RNA sequencing (snRNA-seq) on adenoid tissue obtained from 6 human donors (age 2 – 14; 3 males and 3 females) undergoing routine adenoidectomy. The donor cohort includes clinically annotated samples with no known immunodeficiency or chronic airway disease.Our analysis uncovered distinct epithelial populations, including transcriptionally defined immature and mature microfold (M) cells, and a previously unrecognized interferon-stimulated epithelial population enriched for antiviral response genes, which we term WISP cells (Waldeyer's ring Interferon-Stimulated Population). We validated key transcriptomic findings through multiplex immunofluorescence microscopy in independent donor tissues, confirming the spatial localization of WISP and M cells and their predicted interactions with specific immune subsets.

  Study phs004103

• Genomic analyses of gynecologic carcinosarcomas reveal frequent mutations in chromatin remodeling genes

  Malignant Mixed Müllerian Tumors, also known as carcinosarcomas, are rare tumors of gynecological origin. Here we perform whole exome analyses of 22 tumors using massively parallel sequencing to determine the mutational landscape of this tumor type. On average, we identify 43 mutations per tumor, excluding four cases with a mutator phenotype that harbored inactivating mutations in mismatch repair genes. In addition to mutations in TP53 and KRAS, we identify genetic alterations in chromatin remodeling genes, ARID1A and ARID1B, in histone methyltransferase MLL3, in histone deacetylase modifier SPOP, and in chromatin assembly factor BAZ1A, in nearly two thirds of cases. Alterations in genes with potential clinical utility are observed in more than three quarters of the cases and included members of the PI 3-kinase and homologous DNA repair pathways. These findings highlight the importance of the dysregulation of chromatin remodeling in carcinosarcoma tumorigenesis and suggest new avenues for personalized therapy.

  Study EGAS00001000941