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• Whole exome sequencing data of germline and two independent primary leukemias of five patients

  The contribution of genetic predisposing factors to the development of pediatric acute lymphoblastic leukemia (ALL), the most frequently diagnosed cancer in childhood, has not been fully elucidated. Children presenting with multiple de novo leukemias are more likely to suffer from genetic predisposition. Here, we selected five of these patients and analyzed the mutational spectrum of normal and malignant tissues. In two patients, we identified germline mutations in TYK2, a member of the JAK tyrosine kinase family. These mutations were located in two adjacent codons of the pseudokinase domain (p.Pro760Leu and p.Gly761Val). In silico modeling revealed that both mutations affect the conformation of this auto-regulatory domain. Consistent with this notion, both germline mutations promote TYK2 autophosphorylation and activate downstream STAT family members, which could be blocked with the JAK kinase inhibitor I. These data indicate that germline activating TYK2 mutations predispose to the development of ALL.

  Study EGAS00001001889

• Combination_Immune_Checkpoint_Inhibition_in_Australian_Rare_Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Study EGAS00001005709

• Vento_Placental_Cell_Atlas

  The Human Cell Atlas initiative is an ambitious global research effort which aims to describe every cell in the human body across all developmental stages to generate a reference map to accelerate progress in science and medicine particularly relating to human development and disease. The initiative is led by investigators based at the Wellcome Sanger Institute and the Broad Institute of MIT and Harvard and funding support from the Wellcome and NIH. This specific project will assess human development. We aim to interrogate the cellular composition and molecular regulators underpinning development and maturation through single cell RNA-sequencing/spatial transcriptomics and computational algorithms to predict cellular developmental trajectories and cell-cell interactions. We will subsequent validate these findings in situ using allied imaging technologies e.g. immunohistochemistry and RNAscope and in vitro culture of human intestinal organoids (HIOs).

  Study EGAS00001004187

• Analysis of IDHwt-glioblastoma samples from paired primary and recurrent tumor samples

  IDHwt-glioblastomas rapidly recur after initial treatment. To study genetic evolution in glioblastoma, we analyzed whole genomes of 21 pairs of primary and recurrent tumor samples using next generation sequencing. In addition we sequenced RNA from 16 tumor pairs and a panel of 50 glioma-associated genes in tumor pairs from 43 patients (including 14 of the 21 patients included in the WGS discovery set). Glioblastoma subtypes were determined using 450k/EPIC methylation arrays. This study was supported within the e:med program of the German Ministry of Education and Research (BMBF) by the collaborative research project ‘SYS-GLIO - Systems-based prediction of the biological and clinical behavior of gliomas’ (https://www.sys-med.de/de/demonstratoren/sys-glio/) This study is part of the Heidelberg Center for Personalized Oncology - HIPO-043

  Study EGAS00001003184

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_Batch05

  Transcriptome Sequencing of Gingivo-buccal Cancer: ICGC-India ProjectAs a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Transcriptome sequencing of paired RNA samples – isolated from the tumor and adjacent normal tissues of 28 patients – have been performed. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from adjacent normal and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Sequencing is being performed at the National Institute of Biomedical Genomics, Kalyani.

  Study EGAS00001003285

• Forty-Five patient-derived xenografts capture the clinical and biological heterogeneity of Wilms tumor

  The lack of model systems has limited the preclinical testing of novel therapies for Wilms tumor (WT) patients who have poor outcomes. Herein, we established 45 heterotopic WT patient-derived xenografts (WTPDX) in CB17 scid-/- mice that capture the biological heterogeneity of Wilms tumor (WT). These WTPDX include 6 from patients with diffuse anaplasia, 9 from patients who later experienced disease relapse, and 13 from patients with bilateral disease. Early passage WTPDX showed enrichment of blastemal gene expression. Favorable histology WTPDX were chemosensitive, whereas unfavorable histology WTPDX were resistant to conventional chemotherapy with vincristine, actinomycin-D, and doxorubicin given singly or in combination. This WTPDX library is a unique scientific resource that retains the spectrum of biological heterogeneity present in WT and provides an essential tool to test novel targeted therapies in the era of precision medicine.

  Study EGAS00001003361

• Rare coding variants in lupus risk genes

  Systemic lupus erythematosus (SLE) is the prototypic systemic autoimmune disease. It is thought that many common variant gene loci of weak effect act additively to predispose to common autoimmune diseases, while the contribution of rare variants remains unclear. Here we describe that rare coding variants in lupus-risk genes are present in most SLE patients and healthy controls. We demonstrate the functional consequences of rare and low frequency missense variants in the interacting proteins BLK and BANK1, which are present alone, or in combination, in a substantial proportion of lupus patients. The rare variants found in patients, but not those found exclusively in controls, impair suppression of IRF5 and type-I IFN in human B cell lines and increase pathogenic lymphocytes in lupus-prone mice. Thus, rare gene variants are common in SLE and likely contribute to genetic risk.

  Study EGAS00001003548

• Short and long-read sequencing of Brugada syndrome samples

  Genome-wide association studies (GWAS) are instrumental in identifying loci with an impact on human traits and disease. Typically, however, most GWAS information is considered redundant as it is based on neighboring single-nucleotide variants (SNVs) in strong linkage disequilibrium (LD). In this context, besides the most significant hit (lead SNV) in every trait- or disease-associated locus, the rest of GWAS hits are often marginally reported, examined, or exploited. To interrogate the value of integrating the information provided by the full set of GWAS hits and fine-mapping haplotypes containing these SNVs, here we focused on a locus repeatedly associated with traits of the cardiac electrical conduction system and arrhythmia (SCN5A-SCN10A). We found that the same SNV can exhibit differing associations depending on haplotype. Thus, these analyses provide corroborative evidence that assuming redundancy among neighboring GWAS hits has the risk of missing critical disease-risk associations.

  Study EGAS00001004927

• Erythroid/megakaryocytic differentiation confers BCL-XL dependency and venetoclax resistance in acute myeloid leukemia

  Myeloid neoplasms with erythroid or megakaryocytic differentiation include pure erythroid leukemia (PEL), myelodysplastic syndrome (MDS) with erythroid features, and acute megakaryoblastic leukemia (FAB M7) and are characterized by poor prognosis and limited treatment options. Here, we investigate the drug sensitivity landscape of these rare malignancies. We show that acute myeloid leukemia (AML) cells with erythroid or megakaryocytic differentiation depend on the anti-apoptotic protein BCL-XL, rather than BCL-2, using combined ex vivo drug sensitivity testing, genetic perturbation, and transcriptomic profiling. Single-cell and bulk transcriptomics of patient samples with erythroid and megakaryoblastic leukemias identified high BCL2L1 expression compared to other subtypes of AML and other hematological malignancies, where BCL2 and MCL1 were more prominent. Our results suggest targeting BCL-XL as a potential therapy option in erythroid/megakaryoblastic leukemias and highlight an AML subgroup with potentially reduced sensitivity to venetoclax-based treatments.

  Study EGAS00001006819

• Genomic profiling of localized (lFL) and systemic follicular lymphoma (sFL) reveals novel insights into FL pathogenesis

  At diagnosis, the majority of FL presents with symptomatic disease in advanced/systemic stages of FL (sFL). In contrast only around 10 to 15% of cFL are diagnosed in localized stages (lFL). The biological knowledge is mainly based on data derived from global sFL analysis and only small cohorts of lFL were characterized intensively so far. It is well-known that the hallmark BCL2 translocation is less frequently observed in lFL. Furthermore, lFL differs from sFL concerning their gene expression and their N-glycosylation profiles. In consequence, comprehensive global analysis with CNA profiling and whole exome sequencing was performed in a large cohort of lFL. Additionally, the mutational profile as well as the CNA landscape of lFL and sFL, as well as for BCL2 translocation-positive and -negative was compared.

  Study EGAS00001006927

• Colorectal Microenvironment Spatial Mapping

  In colorectal cancer (CRC), interactions between tumor and immune cells within the tumor microenvironment are critical drivers of tumorigenesis, immune evasion, prognosis, and therapeutic response. Therefore, a deeper understanding of the spatial organization of cancer and immune cells within the CRC microenvironment is urgently needed. In this study, we aimed to characterize distinct cell populations and patterns of spatial gene expression associated with CRC tumorigenesis and immune infiltration. Spatial transcriptomics (ST) was performed on CRC and adjacent normal tissues to investigate the patterns of gene expression. Integrative ST data and publicly available single-cell RNA sequencing (scRNA-seq) data analysis tools were used for data integration, dimension reduction, clustering, and differential expression analysis. This study identified novel immunosuppressive cell populations and immune regulatory factors in CRC. Further functional validation of these findings will be essential to assess their potential as therapeutic targets.

  Study EGAS00001008254

• Whole genome sequencing data from tumor and normal samples

  Whole genome sequencing FASTQ files from tumor and normal samples from 202 patients. All experiments reported in this article were performed in the Clinical Laboratory Improvement Amendments (CLIA)-certified and College of American Pathologists (CAP)-accredited laboratories at Personalis Inc., as guided by the Association for Molecular Pathology (AMP) and CAP’s joint recommendations52. Preferred input material consisting of FFPE slides (enabling H&E and macrodissection which is part of the standard NeXT Personal process) was not available for the majority (94%) of tumor samples. Most tumor samples (72%) were processed from FFPE curls, with the remaining processed from pre-extracted DNA and fresh frozen material. Where FFPE material on slide was available, tumor sections were macrodissected to increase tumor content, with a minimum allowable cellularity threshold of 20% determined by pathological review. The tumor cellularity threshold of 20% was chosen based on prior work demonstrating that no significant correlation is observed between tumor purity and assay limit of detection (LOD) at this threshold31. Genomic DNA was isolated from tumor and normal samples and WGS libraries prepared as previously described31. Genomic DNA was isolated from matched tumor and normal samples using the Qiagen AllPrep DNA/RNA FFPE Tissue Kit or the QIAamp DNA Mini Kit (QIAGEN, Germantown, MD, USA) using internally optimized workflows. WGS sequencing libraries were prepared with 120-500 ng of acoustically sheared genomic DNA (Covaris LLC, Woburn, MA, USA) using the KAPA HyperPrep Kit (Roche Sequencing Solutions, Pleasanton, CA, USA) and customized methods. Libraries were cleaned-up using AMPure XP beads and then quantified using the KAPA Library Quantification Kit (Roche Sequencing Solutions, Pleasanton, CA, USA), before being sequenced to 30X depth of coverage using a NovaSeq 6000 instrument (Illumina, San Diego, CA, USA).

  Dataset EGAD50000001909

• Genome and transcriptome sequence data from a metastatic large cell neuroendocrine tumour of the lung patient

  Genome and transcriptome sequence data from a metastatic large cell neuroendocrine tumour of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003017

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002998

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002999

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003000

• Genome and transcriptome sequence data from a serous carcinoma of fallopian tube patient

  Genome and transcriptome sequence data from a serous carcinoma of fallopian tube patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003001

• Genome and transcriptome sequence data from a metastatic adult granulosa cell tumour patient

  Genome and transcriptome sequence data from a metastatic adult granulosa cell tumour patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003002

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003003

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003005

• Genome and transcriptome sequence data from a metastatic medullary thyroid cancer patient

  Genome and transcriptome sequence data from a metastatic medullary thyroid cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003006

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003007

• Genome and transcriptome sequence data from a metastatic adenocarcinoma presumably of ovarian origin patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma presumably of ovarian origin patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003008

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003009

• Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient

  Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003010

• Genome and transcriptome sequence data from a squamous cell carcinoma of the lung patient

  Genome and transcriptome sequence data from a squamous cell carcinoma of the lung patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003011

• Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient

  Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003012

• Genome and transcriptome sequence data from a metastatic gastric cancer patient

  Genome and transcriptome sequence data from a metastatic gastric cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003013

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003014

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003015

• Genome and transcriptome sequence data from a metastatic ductal carcinoma of the breast patient

  Genome and transcriptome sequence data from a metastatic ductal carcinoma of the breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003016

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003035

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003037

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003038

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003039

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003041

• Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient

  Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003018

• Genome and transcriptome sequence data from a metastatic uveal melanoma patient

  Genome and transcriptome sequence data from a metastatic uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003019

• Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

  Genome and transcriptome sequence data from a low grade serous ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003020

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003021

• Genome and transcriptome sequence data from a metastatic colorectal cancer patient

  Genome and transcriptome sequence data from a metastatic colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003022

• Genome and transcriptome sequence data from a metastatic renal cell carcinoma patient

  Genome and transcriptome sequence data from a metastatic renal cell carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003023

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003028

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003030

• Genome and transcriptome sequence data from a metastatic collecting duct kidney cancer patient

  Genome and transcriptome sequence data from a metastatic collecting duct kidney cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003031

• Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003032

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003033

• Genome and transcriptome sequence data from a metastatic colon cancer patient

  Genome and transcriptome sequence data from a metastatic colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003034

• Genome and transcriptome sequence data from a metastatic breast carcinoma patient

  Genome and transcriptome sequence data from a metastatic breast carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003042

• Genome and transcriptome sequence data from a metastatic breast cancer patient

  Genome and transcriptome sequence data from a metastatic breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001003044