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• RaScALL: Rapid screening of RNA-seq in acute lymphoblastic leukaemia

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accerelated risk-stratification and therapeutic triage.

  Study EGAS00001006460

• Medulloblastoma exome sequence analysis

  Medulloblastomas are the most common malignant brain tumors in children. Identifying and understanding the genetic events that drive these tumors is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma based on transcriptional and copy number profiles. Here, we utilized whole exome hybrid capture and Illumina sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas exhibit low mutation rates consistent with other pediatric tumors, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR, and LDB1, to our knowledge novel findings in medulloblastoma and all cancer. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant but not wild type beta-catenin. Together, our study reveals the alteration of Wnt, Hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and nominates the RNA helicase DDX3X as a component of pathogenic beta-catenin signaling in medulloblastoma. "Reprinted from 'MEDULLOBLASTOMA EXOME SEQUENCING UNCOVERS SUBTYPE-SPECIFIC SOMATIC MUTATION', with permission from Nature"

  Study phs000504

• Analysis of mutational and proteomic heterogeneity of gastric cancer to monitor post-treatment tumor burden using circulating tumor DNA

  It remains unclear whether complete spectrum of tumor heterogeneity is reflected in circulating tumor DNA (ctDNA). Here, we performed multi-regional target sequencing of primary tumors from 10 patients who underwent surgical resection for gastric cancer. A total of 126 non-synonymous mutations were identified from 30 samples from 10 tumors. Of these, 16 (12.7%) were likely mutations that occurred early in tumor development (i.e., present in all three regions) and were designated founder mutations. Among those validated with highly sensitive digital PCR (dPCR), 93% of non-founder mutations were found in all three regions. Variant allele frequencies (VAFs) of founder mutations were significantly higher than those of non-founder mutations. Phylogenetic analysis demonstrated that five of eight tumors (62.5%, excluding two hypermutator) had at least one identifiable truncal/founder mutation. These findings led us to prioritize founder mutations for ctDNA detection with individually-designed primer/probe sets for dPCR. Marked proteomic diversity was present across the tumor regions both within and between patients independent of mutational status. In preoperative plasma, the average ctDNA VAF of founder mutations was significantly higher than that of non-founder mutations (p = 0.039). Our present data demonstrated that high VAF mutations in the tumor likely represent founder or truncal mutations. However, mutation patterns alone appear insufficient to predict protein heterogeneity. These results suggest that, in practice, mutations having high VAF identified without multi-regional sequencing may be useful for ctDNA monitoring but are inadequate to fully predict proteomic heterogeneity of the tumor.

  Study JGAS000231

• Bladder cancer subtyping study across 4 atezo clinical trials

  Checkpoint inhibitors targeting the PD-1/PD-L1 interaction have revolutionized cancer therapy across many indications. In urothelial carcinoma (UC), several PD-1/PD-L1 inhibitors have been approved for treatment in localized and metastatic disease. While these agents provide durable clinical benefit in a number of patients, the majority do not respond. A better understanding of the molecular mechanisms underlying response and resistance is needed to tailor existing treatments and develop new therapeutics in UC. We profiled tumors from 2803 patients from four late-stage randomized clinical trials evaluating the PD-L1 inhibitor atezolizumab in metastatic UC and muscle-invasive bladder cancer by RNA-seq, a targeted DNA panel, immunohistochemistry, and digital pathology. A machine learning algorithm identified four UC transcriptional subtypes, representing luminal desert, stromal, immune, and basal tumors. Overall survival benefit from atezolizumab over standard-of-care was observed in immune and basal tumors (45% of patients). Digital pathology showed enrichment of human interpretable features in specific molecular subtypes, and a self-supervised approach could classify molecular subtypes from H&E slides with high accuracy, suggesting that machine-based image interpretation could accelerate tumor molecular profiling. Somatic alterations showed limited capacity to identify responders. Finally, mechanisms of benefit with PD-L1 blockade appeared different in immune and basal tumors, with immune tumors benefiting from B/plasma cell enrichment, while basal tumors benefited from granulocyte enrichment. This study represents the largest integration of UC molecular and curated clinical data in randomized clinical trials to date, paving the way for prospective clinical studies tailoring treatment regimens to specific tumor molecular subtypes in UC and other indications.

  Study EGAS50000000497

• Differentiation-associated ISG expression of NK cells in chronic viral hepatitis

  Little is known about the effects of ISGs on NK cell responses in chronic viral hepatitis. Here, we determined the expression, regulation and function of ISGs in NK cells with respect to phenotype and function, we performed high-throughput single cell RNA sequencing of circulating CD3-CD56+ NK cells from healthy donors (HD) and patients with chronic HBV or HCV infections.

  Dataset EGAD50000001623

• Deciphering Developmental Disorders (DDD)

  The Deciphering Developmental Disorders (DDD) study is a research collaboration between the Wellcome Trust Sanger Institute, the NHS clinical genetics services and families across the UK and Ireland. The project aims to improve the diagnosis of children with developmental disorders by using high-resolution microarray and massively parallel sequencing technologies on 12,000 children and their parents. Genetic changes that explain the child's symptoms will be displayed in the DECIPHER database (https://decipher.sanger.ac.uk). Extended datasets generated by the DDD project will be available in the European Genome-Phenome Archive with access carefully managed by a Data Access Committee.

  Study EGAS00001000775

• Mixture of 2 (closer mtDNA)

  Mixture of 2 unrelated individuals (of close mtDNA haplogroup) sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008727

• Multiple Myeloma ChipSeq data on six histone modifications

  The data contained in this dataset is ChipSeq BAM files aligned to reference genome hg38. The ChipSeq was based on a combination of six histone modifications as follows: H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K27Ac and H3K36me3. The samples are patient-derived xenografts generated by passaging primary patient CD138+ selected cells through the SCID-rab myeloma mouse model.

  Dataset EGAD00001008353

• Characterization of genomic landscape of Peripheral T-cell Lymphomas, not otherwise specified (PTCL-NOS) (2018-10-30)

  Peripheral T-cell lymphomas not otherwise specified (PTCL-NOS) represent a heterogeneous group of nodal and extra-nodal mature T-cell lymphomas, with a low prevalence in Western countries. PTCL-NOSs account for about 25% of all PTCLs and are currently diagnosed based on exclusion criteria, as this lymphomas lack unifying morphological, phenotypic and genomic features. Cytogenetic and FISH analysis of PTCL-NOS samples have not revealed recurrent pathogenetic abnormalities, while gene expression profiling has shown only partial ability to segregate cases representing homogeneous clinic-pathological entities. This underscores the need to look at PTCL-NOS with innovative and high-throughput approaches to identify recurrent genetic lesions that could further our understanding of the biology of this heterogeneous group of diseases, provide better diagnostic tools and perhaps new targets for innovative treatments. Our aim is to study ~15 patients affected by PTCL-NOS. Out study will be funded by a private, non-profit Italian cancer research fund (Associazione Italiana per la Ricerca sul Cancro, www.airc.it) based on a grant owned by Anna Dodero and Cristiana Carniti, hematologists at INT. Samples will be analysed by whole genome sequencing using Illumina X10 machines, on a 150bp-PE protocol. Data will be analysed using the pipeline available in Team 78, under the supervision of Peter Campbell, the WTSI faculty who will oversee the project, and by Francesco Maura, visiting scientist at the WTSI. . This dataset contains all the data available for this study on 2018-10-30.

  Dataset EGAD00001004428

• Mullighan - PAX5-driven Subtypes

  Using integrated genomic analysis of 1.988 childhood and adult cases, we describe a revised taxonomy of B-cell acute lymphoblastic leukemia, which incorporates 23 subtypes defined by chromosomal rearrangements, sequence mutations, or heterogeneous genomic alterations. Two subtypes have frequent alterations of the B lymphoid transcription factor gene PAX5. One, PAX5alt, has diverse PAX5 alterations, and a second subtype is defined by a single mutation, PAX5 P80R. We show that P80R impairs B lymphoid development and promotes the development of B-ALL in vivo. These results demonstrate the utility of transcriptome sequencing to classify B-ALL and reinforce the central role of PAX5 as a checkpoint in B lymphoid maturation and leukemogenesis.

  Study EGAS00001003266