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• PCGP Ph-like ALL

  Background: BCR-ABL1-like, or Ph-like acute lymphoblastic leukemia is characterized by a gene expression profile similar to BCR-ABL1 positive ALL, genetic alterations of lymphoid transcription factor genes, and poor outcome. Sequencing of small numbers of Ph-like ALL cases has identified genetic alterations activating kinase signaling suggesting Ph-like ALL may be amenable to treatment with tyrosine kinase inhibitors. However, the spectrum of genetic alterations in childhood and adult Ph-like ALL is incompletely understood. Methods: We performed genomic profiling of 1736 B-ALL cases and next-generation sequencing for 160 Ph-like cases. We examined the functional effects of chimeric fusion proteins in mouse cell lines. Results: The frequency of Ph-like ALL rose from 11% in children to 26% in young adults, and was associated with very poor outcome. Kinase-activating alterations were identified in 90% of Ph-like cases, most commonly fusions involving 10 kinase or cytokine receptor genes (ABL1, ABL2, CRLF2, CSF1R, EPOR, JAK2, NTRK3, PDGFRB, PTK2B and TYK2), and mutations involving FLT3, IL7R and SH2B3. Expression of ABL1, ABL2, CSF1R and JAK2 fusions resulted in cytokine-independent proliferation of cell lines and activation of pSTAT5. Cells expressing ABL1, ABL2, CSF1R and PDGFRB fusions were sensitive to dasatinib, and JAK2 fusions to ruxolitinib. Conclusions: Ph-like ALL is characterized by a diverse range of genomic alterations that converge on a limited number of kinase signaling pathways amenable to inhibition with currently available tyrosine kinase inhibitors. Trials identifying Ph-like ALL and testing the efficacy of tyrosine kinase inhibitor therapy are warranted

  Study EGAS00001000654

• Genetic characterization of B-cell prolymphocytic leukemia: a hierarchical prognostic model involving MYC and TP53 abnormalities - RNA-seq

  B-cell prolymphocytic leukemia (B-PLL) is a rare disease, whose molecular pathology is largely unknown. We report here the cytogenetic and molecular findings in a large series of 34 B-PLL. Karyotype (K) was complex (≥3 abnormalities) in 73%, and highly complex (HCK≥5) in 45%. The most frequent chromosomal aberrations were: translocation targeting the MYC gene [t(MYC)] (62%), 17p deletion including TP53 gene (38%), trisomy 18/18q (30%), 13q14 deletion (29%), trisomy 3 (24%), trisomy 12 (24%) and 8p deletion (23%). Whole-Exome Sequencing performed in 16 patients revealed recurrent mutations in TP53 (6/16, 38%), MYD88 (n=4), BCOR (n=4), MYC (n=3), SF3B1 (n=3), FAT1 (n=3), SETD2 (n=2), CHD2 (n=2), CXCR4 (n=2) and BCLAF1 (n=2). The main group of patients (21/34, 62%) had a t(MYC) associated with a higher percentage of prolymphocytes (p=0.03), CD38 expression (p<0.001), lower K complexity (p=0.0004), mutations in MYC and in genes involved in RNA metabolism and chromatin remodeling. Principal component analysis of gene expression data showed that patients with t(MYC) clustered together. A second group with MYC gain (5/34, 15%), was associated with HCK≥5 (p=0,01) and trisomy 3 (p=0,008). Altogether, 26/34 patients (76%) had a MYC activation, translocation or gain, that were mutually exclusive. We identified 3 distinct cytogenetic prognostic groups (p=0.0006): lower risk: absence of MYC activation (median not reached); intermediate risk: MYC activation without del17p (125 months); high risk: MYC activation + del17p (11 months). Our results show that cytogenetic analysis is a useful diagnostic tool in B-PLL that improves prognostic stratification.

  Study EGAS00001003274

• single cell RNA-seq of peripheral blood from analysis in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  This dataset contains two experiments. 1) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with SORT-seq (see cell systems, 2016, doi:10.1016/j.cels.2016.09.002). For some of the patients, multiple indipendent plates were produced (each plate is a sample). Barcode-well correspondence can be found here: https://bitbucket.org/princessmaximacenter/sharq/src/master/data/celseq2_bc384-v4.csv . 2) Single cell RNA-seq of peripheral blood diagnostic samples from patients with MLL-rearranged infant ALL that underwent relapse or not (samples ending in R relapsed, samples ending in N did not), sequenced with10x Genomics Version 2.

  Dataset EGAD00001007752

• Characterization of the molecular signature of human monocytes in aging and myelodysplastic syndrome

  Deep immunophenotypic profiling of peripheral blood immune cells from young and older control subjects as well as patients with MDS was initially performed, using mass cytometry to identify monocyte subpopulations. Abundance of monocyte subpopulations separated the samples from patients with MDS from elderly control subjects was identified. Therefore, targeted immunophenotyping of monocytes was also performed with flow cytometry and RNA sequencing from isolated CD14+ peripheral blood longitudinally in 26 subjects, six young healthy individuals, nine older healthy individuals and eleven patients with MDS.

  Study EGAS00001007676

• Whole Exome Sequencing of Human Gastro-esophageal Cancer PDXs

  The current study investigates biomarkers of response to anti-EGFR therapies in gastro-esophageal cancer. Whole exome sequencing was performed on 26 tumors to explore potential factors influencing treatment outcomes. As part of the analysis, somatic mutations in EGFR, ERBB2, and key downstream signaling genes (KRAS and PIK3CA) were examined to exclude the presence of known mutations conferring sensitivity/resistance. The study aims to contribute to the identification of patients who may benefit from lower-toxicity regimens, improving treatment personalization and minimizing adverse effects.

  Study EGAS50000000966

• Datasets of RNA-seq of tumor samples from clear cell renal cell carcinoma patients included in the Translational Program of the NIVOREN GETUG-AFU-26 trial

  RNA-seq analyses were performed on tumor tissue samples of 115 advanced clear cell renal cell carcinoma patients who participated in the NIVOREN GETUG-AFU-26 trial. The samples were obtained prior to treatment initiation. RNA-seq was performed to evaluate previously published gene expression signatures. These included: the IMmotion T effector (CD8A, EOMES, PRF1, IFNG and CD274) and the IMmotion Myeloid (IL-6, CXCL1, CXCL2, CXCL3, CXCL8, and PTGS2) gene signatures represent gene expression patterns associated with T effector cells and myeloid cells, respectively, while JAVELIN Renal 101 Immuno (T-cell receptor signaling: CD3G, CD3E, CD8B, THEMIS, TRAT1, GRAP2, CD247; T-cell activation, proliferation, and differentiation: CD2, CD96, PRF1, CD6, IL7R, ITK, GPR18, EOMES, SIT1, NLRC3; Natural killer cell mediated cytotoxicity: D2, CD96, PRF1, CD244, KLRD1, SH2D1A; Chemokine: CCL5, XCL2; and Other immune response genes: CST7, GFI1, KCNA3, PSTPIP1) represents gene expression patterns associated with both innate and adaptive immune response.

  Dataset EGAD50000001541

• Wilm's tumor sequencing data

  No. of samples: 80 (28 ULP-WGS, 26 WES, 26 RNA-SEQ) File types: FASTQ (28 ULP-WGS, 19 WES, 18 RNA) and BAM (7 WES, 8 RNA) Technology used: Sequencing - Illumina Novoseq 6000; Map/Align - Illumina DRAGEN v3.7.5; Genome assembly - GrCh38p13 Filename nomenclature: - SampleName_Passage_SampleType_TissueType_SequencingType - Passage of: PX = unknown; PZ = from patient; P0 = first passage from patient on plastic; P1 = first passage from plastic/PDX/organoid - SampleType: STN = normal; STT = tumor - SampleType STN: 00 = tissue unknown; 01 = adjacent normal; 02 = fibroblast; 03 = germline blood; 21 = cell line from patient tissue; 22 = cell line from PDX; 23 = cell line from patient fibroblast - SampleType STT: 00 = tissue unknown; 01 = primary tumor; 21 = cell line from patient; 22 = cell line from PDX - TissueType: WT = Wilm's tumor; 00 = kidney unknown; 01 = kidney left; 02 = kidney right - SequencingType: 00 = unknown; 02 = ultra-low pass whole-genome sequencing; 20 = whole-exome; 61 = bulk RNA-sequencing

  Dataset EGAD00001011111

• Sequencing data for oesophageal and related samples - ICGC DCC release 26 (WGS)

  WGS sequencing for 303 cases (620 samples) from the ICGC ESAD-UK project Tumours 50x Normals 30x HiSeq X BAM files These samples are all available in ICGC release 26

  Dataset EGAD00001003580

• 3/7 Psychiatric Genomics Consortium: Finding Actionable Variation

  The goal of this study was to generate new therapeutic hypotheses by targeted sequencing of 161 genes most likely to harbor schizophrenia (SCZ) causal variants in multi-ancestry schizophrenia case-control cohorts. The gene panel was intended to contain putative SCZ risk genes, from within which, the majority of new discoveries from additional WES/WGS would come. To this end, we integrated current knowledge of the genetic architecture of SCZ (results from The Schizophrenia Exome Sequencing Meta-Analysis Consortium, or SCHEMA) and gene membership in gene sets that have been implicated in SCZ using a Bayesian framework. A total of 23,352 individuals selected to be non-overlapping with SCHEMA, as well as other previous and ongoing sequencing efforts in the field, were identified from over 20 individual study sites. Sequencing of the exonic regions of 161 prioritized genes was performed on the Ion Torrent platform in between June 2018 and April 2019. Sequencing plates were matched with respect to ancestry and case/control composition whenever possible. The average sequencing depth across all samples was 224x. Single sample calling was performed using Torrent Variant Caller v5.8.0, which is specially optimized to exploit the underlying flow signal information generated by the Ion Torrent sequencing. The schizophrenia case-control status was obtained from each original study site.

  Study phs003138

• Alzheimer's Disease Genetics Consortium (ADGC) Genome Wide Association Study -NIA Alzheimer's Disease Centers Cohort

  The National Institute on Aging (NIA) Alzheimer's Disease Centers (ADCs) cohort includes subjects ascertained and evaluated by the clinical and neuropathology cores of the 29 NIA-funded ADCs. Data collection is coordinated by the National Alzheimer's Coordinating Center (NACC). NACC coordinates collection of phenotype data from the 29 ADCs, cleans all data, coordinates implementation of definitions of AD cases and controls, and coordinates collection of samples. The ADC cohort consists of autopsy-confirmed and clinically-confirmed AD cases, and cognitively normal elders (CNEs) with complete neuropathology data who were older than 60 years at age of death, and living CNEs evaluated using the Uniform dataset (UDS) protocol who were documented to not have mild cognitive impairment (MCI) and were between 60 and 100 years of age at assessment. ADCs sent frozen tissue from autopsied subjects and DNA samples from some autopsied subjects and from living subjects to the National Cell Repository for Alzheimer's Disease (NCRAD). DNA was prepared by NCRAD for genotyping and sent to the genotyping site at Children's Hospital of Philadelphia. ADC samples were genotyped and analyzed in separate batches. [Reprinted from AC Naj et al. Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease. Nature Genetics 43, 436-441 (2011). doi:10.1038/ng.801. PMID: 21460841.]

  Study phs000372