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

  Molecular characterization of 41 tumors from 17 individuals with CMMRD to gain a better understandig of mutational processes driving subsequent tumor development. The molecular characterization includes the investigation of tumor mutational load and mutational signatures.

  Dataset EGAD00001015158

• RNA-Seq Dataset of Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  We generated and characterized tumoroids from small cell carcinoma of the ovary, hypercalcemic type. Furthermore, we identified a drug that is selective and effective against SCCOHT tumoroids.

  Dataset EGAD00001015441

• OMKar: optical map based automated karyotyping of genomes to identify constitutional disorders

  This dataset contains optical genome mapping (OGM) data from 56 samples, processed for structural variation and copy number analysis. The data includes .xmap, .cmap, and .smap files representing high-resolution genome maps and structural variant calls. These samples were used to identify complex rearrangements and reconstruct genome karyotypes.

  Dataset EGAD00001015674

• WGS dataset of Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Creation of living organoid biobank for ewing and ewing-like sarcomas

  Dataset EGAD00001015418

• Profiling the Microbiome of Pediatric Gut with Metagenomic Short-Read Sequencing

  This dataset contains short-read metagenomic sequencing of stool, as well as intestinal tissue and tissue washes, from preterm infants. 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 EGAD00001016052

• WGSPD Project 1: Whole Genome Sequencing for Schizophrenia and Bipolar Disorder

  The Center for Genomic Psychiatry at the University of Southern California (USC) and an extensive network of academic medical centers have created the Genomic Psychiatry Cohort (GPC). The GPC consists of a large clinical cohort of patients with schizophrenia, bipolar disorder, and healthy controls. The pilot phase of whole genome sequencing of the GPC has been done in collaboration with the USC and the Broad Institute of MIT and Harvard. Whole genome sequencing (20X) and analysis of 9,033 well-phenotyped individuals from the Genomic Psychiatry Cohort (GPC), divided among schizophrenia cases, bipolar disorder cases, and psychiatrically normal controls, and comprised of European-Ancestry (EA), African-Ancestry (AA), and Latino individuals. The combination of clinically well-characterized GPC participants and whole genome sequencing with rich functional annotation aims to identify functional variants associated with schizophrenia and bipolar disorder risk. Over half of the sequenced samples are patients with a diagnosis of either schizophrenia or bipolar disorder. The majority of the study participants are of African American ancestry, increasing the diversity of sampling for these important diseases in traditionally understudied populations. This data set also contains 545 samples that have undergone 10x Genomics Linked-Read Sequencing (169 participants overlapping with the 9,033 participant WGS 20X dataset). In addition to the benefits due to disease phenotyping and ancestry selection that apply to all of the WGSPD Project 1 samples, the 10x Genomics Linked-Read samples, through the use of barcodes that can identify the long input DNA fragment that each sequencing read was generated from, can be used to 1) identify structural variants that are difficult to call with standard short read data, 2) map short reads to repetitive regions of the genome that cannot be assayed with standard short reads, and provide highly accurate phasing information about genetic variants, including rare variants that are more difficult to phase using statistical phasing techniques.

  Study phs002041

• Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

  Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

  Study EGAS00001002676

• Molecular Tumor Board to Inform on Personalized Medicine for a Man with Advanced Prostate Cancer

  Purpose: Molecular profiling of cancer is increasingly common as part of routine care in oncology, and germline and somatic profiling may provide insights and actionable targets for men with metastatic prostate cancer. However, all reported cases are of deidentified individuals without full medical and genomic data available in the public domain. Patient and Methods: We present a case of whole genome tumor and germline sequencing in a patient with advanced prostate cancer, who has agreed to make his genomic and clinical data publicly available in an accompanying personal testimonial. Results: We describe an 84-year-old Caucasian male with a Gleason 10 oligometastastic hormone-sensitive prostate cancer. Whole-genome sequencing provided insights into his tumor’s underlying mutational processes and the development of an SPOP mutation. It also revealed an androgen-receptor dependency of his cancer which was reflected in his durable response to radiation and hormonal therapy. Potentially actionable genomic lesions in the tumor were identified through a personalized medicine approach for potential future therapy, but at the moment, he remains in remission, illustrating the hormonal sensitivity of his SPOP-driven prostate cancer. We also placed this patient in the context of a large prostate-cancer cohort from the PCAWG (Pan-cancer Analysis of Whole Genomes) group. In this comparison, the patient's cancer appears typical in terms of the number and type of somatic mutations, but it has a somewhat larger contribution from the mutational process associated with aging. Conclusion: We combined the expertise of medical oncology and genomics approaches to develop a molecular tumor board to integrate the care and study of this patient, who continues to have an outstanding response to his combined modality treatment. This identifiable case potentially helps overcome barriers to clinical and genomic data sharing.

  Study EGAS00001004648

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• The tissue origin of highly elevated cell-free DNA in patients with and without cancer

  Forty years ago, the first measurements of cell free DNA (cfDNA) from cancer patients revealed that its total concentration was often elevated compared to healthy controls. The basis for this increase, and in particular the source of the extra cfDNA in such patients, has never been determined. To address this issue, we assessed methylation patterns of cfDNA from 57 individuals, 34 of whom had unequivocally elevated cfDNA concentrations (i.e., >15 ng/mL of plasma). We found that the excess cfDNA in cancer patients did not come from either neoplastic cells or surrounding cells from the tumor's tissue of origin. Instead, 80% of the cfDNA was derived from neutrophils, B cells or T cells, with neutrophils accounting for ~2/3. B cells contributed more than T cells despite the great excess of T cells over B cells in the blood. To see if this result was generalizable to other clinical situations in which elevated cfDNA concentrations have been described, we evaluated nine patients before and one day following surgery. After surgical resection, cfDNA concentration increased by an average of 16.1-fold, as expected. The majority of this increase (55%) was contributed by leukocytes, though damaged hepatocytes contributed a substantial minority (31% of increase). These data suggest that the elevated concentrations of cfDNA in cancer patients, as with patients after surgery, arises largely from dying leukocytes—not from the neoplastic cells or the tissue of origin of the cancer.

  Study EGAS00001005400