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• Whole exome sequencing on primary retinoblastoma tissues and matching lymphocyte DNA.

  Retinoblastoma is a rare childhood cancer initiated by RB1 mutation or MYCN amplification, while additional alterations may be required for tumor development. However, the view on single nucleotide variants is very limited. To better understand oncogenesis, we determined the genomic landscape of retinoblastoma. We performed exome sequencing of 71 retinoblastomas and matched blood DNA. Next, we determined the presence of single nucleotide variants, copy number alterations and viruses. Aside from RB1, recurrent gene mutations were very rare. Only a limited fraction of tumors showed BCOR (7/71, 10%) or CREBBP alterations (3/71, 4%). No evidence was found for the presence of viruses. Instead, specific somatic copy number alterations were more common, particularly in patients diagnosed at later age. Recurrent alterations of chromosomal arms often involved less than one copy, also in highly pure tumor samples, suggesting within-tumor heterogeneity. Our results show that retinoblastoma is among the least mutated cancers and signify the extreme sensitivity of the childhood retina for RB1 loss. We hypothesize that retinoblastomas arising later in retinal development benefit more from subclonal secondary alterations and therefore, these alterations are more selected for in these tumors. Targeted therapy based on these subclonal events might be insufficient for complete tumor control.

  Study EGAS00001001690

• Host pathogen interaction long read transcriptome

  Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

  Study EGAS00001006779

• Integrative Multi-Omics and Drug Sensitivity Profiling Reveals Potential Predictive Biomarkers in Pediatric Solid Tumors from the INFORM Registry

  Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors (such as high-risk Group3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas and high-grade gliomas) and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities, biomarkers and unravel molecular mechanisms associated with drug response profiles for clinical translation. Here, we perform a multi-omics analysis using drug sensitivity profiles, genomic, and transcriptomic data of 81 pediatric solid tumor samples. The integrative analysis revealed two multi-omics signatures with high drug sensitivity predictivity. One signature highlighted neuroblastoma samples with sensitivity to navitoclax (a BCL-2 family inhibitor). A second signature was significantly specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation, which had high expression of MGAM, PTPN14, STAT4 and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis elucidated the potential biological mechanism of action between MEK inhibitors and the SIX1 mutation in n = 6 Wilms tumor samples.

  Study EGAS00001008249

• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• DAC for TFHL single-cell analysis project at Department of Hematology, University of Tsukuba

  DAC for study of tumor heterogeneity and immune-evasive microenvironment in T follicular helper cell lymphomas

  Dac EGAC50000000201

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• Additional Methylation files for Roussel-ATRT-TM

  Additional Methylation files for Roussel-ATRT-TM paper titled "Atypical teratoid/ rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities"

  Dataset EGAD00010002495

• Array data for oesophageal and related samples – kno_paper_methyl_release

  Array data for oesophageal and related samples – kno_paper_methyl_release

  Dataset EGAD00010001795

• Targeted sequencing analysis for MDS with HSCT

  Targeted capture sequencing for cases with MDS who were subjected to unrelated bone marrow transplantation via Japan marrow donor program

  Dataset EGAD00001003118

• Data files for CONSERTING

  Data files for CONSERTING (WGS)

  Dataset EGAD00001001352