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• MutWP1__CRUK_Grand_Challenge__normal_kidney_Nanoseq

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Non-tumour DNA is also studied for some cancer types. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001005451

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__head___neck

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Non-tumour DNA is also studied for some cancer types. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001005450

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified “more-is-better” and “one-size-fits-all” principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell “genomic instability” as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762

• Involvement of the FGF8/FGF Receptor Signaling Pathway in the Maintenance and Progression of Fusion-Positive Rhabdomyosarcoma

  In our previous work, we used a myoblast model of fusion-positive rhabdomyosarcoma (FP-RMS) to demonstrate that FGF8, a target of the PAX3-FOXO1 (P3F) transcription factor, is essential for tumorigenicity driven by P3F. When aberrantly expressed, FGF8 can also sustain tumorigenicity in recurrent tumors that are independent of P3F. In this study, we report that FGF8, along with its receptors FGFR1 and FGFR4, is often highly expressed in FP-RMS tumors. We found that high levels of FGF8 expression in FP-RMS cells correlate with increased sensitivity to an FGFR4 inhibitor and a pan-FGFR inhibitor. Conversely, downregulating FGF8 led to a loss of sensitivity to these inhibitors. Interestingly, when FGF8 was upregulated in myoblasts, it resulted in decreased FGFR4 expression and sensitized the cells to an FGFR1 inhibitor and a pan-FGFR inhibitor. The downregulation of FGFR4 expression mediated by FGF8 could be reversed by inhibiting FGFR1, MEK, or ERK, thereby defining a signaling pathway through which FGF8 exerts its regulatory effects. Additionally, we discovered that high FGF8 expression in P3F-independent recurrent tumors is due to a rearrangement of viral long terminal repeat (LTR) sequences into the 3' untranslated region (UTR) of FGF8, leading to increased stability of FGF8 mRNA. These findings indicate that FGF8 plays an oncogenic role in FP-RMS through FGFR4 and may also exert oncogenic effects in P3F-independent relapses via FGFR1. Our study highlights the functional significance of FGF8 in FP-RMS and supports the rationale for preclinical investigations of FGFR inhibitors in treating this type of cancer.

  Study phs004009

• Characterization of CNS Metastases

  Metastatic disease to the central nervous system (CNS) is devastating, with a poor prognosis. There are limited treatment options for patients with CNS metastases, and in particular with leptomeningeal carcinomatosis (LMD). In this study, we evaluated the molecular and cellular features of parenchymal brain metastases and LMD. We used single-cell RNA and cell-free DNA profiling of CSF from patients with LMD receiving immunotherapy to demonstrate shifts in the liquid LMD tumor microenvironment. We also characterize the tumor microenvironment of parenchymal brain metastases using single cell sequencing, before and after treatment with immunotherapy.

  Study phs002416

• 5- FU treated organoids

  5-Fluorouracil (5-FU) is a chemotherapeutic drug component that is commonly used for the treatment of solid cancers. The anticancer properties of 5-FU have been attributed to interference with nucleotide synthesis and through direct incorporation into the DNA as being a pyrimidine analog. As both mechanisms of action may have a mutational impact on surviving tumor cells, we performed three independent analyses to characterize the genomic consequences of 5-FU treatment: i) in vitro treatment of intestinal organoids with 5-FU followed by whole genome sequencing, ii) genome-wide mutation analyses in tumor samples from 5-FU treated patients with breast or colorectal cancer, and iii) analysis of paired biopsies from patients treated with 5-FU between biopsies. Our results demonstrate that both in vitro and in vivo 5-FU causes a mutational pattern that is dominated by T>G substitutions in a CTT context and with strong resemblance to COSMIC signature 17. Interestingly, this signature is also found in non 5-FU treated patients, most prominently in esophageal tumors, indicating that distinct endogenous and exogenous triggers can converge into highly similar mutational signatures. Furthermore, our results suggest that 5-FU may have adverse mutagenic effects on healthy cells and contributes to genetic variability in surviving cancer cells thereby contributing to tumor evolution.

  Study EGAS00001003592

• Childhood Cancer Data Initiative (CCDI): Integrating Longitudinal Clinical, Sociodemographic and Genomic Data into the NCCR

  The goal of this study is to contribute clinical and genomic data from a large institutional cohort of pediatric cancer patients who had tumor genomic profiling between 2013 and 2019 at Dana-Farber/Boston Children's Hospital Cancer and Blood Disorders Center. Clinical data include demographics, diagnosis (classified according to the International Classification of Diseases for Oncology (ICD-O-3.2), stage, and biospecimen associated data. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel of up to 447 cancer genes for detection of single-nucleotide variants (SNV), insertions, and deletions, and copy number alterations (CNA), as well as selected intronic regions for up to 60 genes for the detection of structural variants (SV). This dataset includes a patient and sample identifier (GENIE ID) that can be used to link the genomic data included in this dataset to additional longitudinal clinical cancer data on a subset of patients that was submitted to the National Childhood Cancer Registry (NCCR).

  Study phs002677

• Germline Genetics of Myelodysplastic Syndromes (MDS) and Acute Myeloid Leukemia (AML)

  Myelodysplastic syndromes (MDS) are part of a heterogeneous and overlapping group of clonal diseases that arise in the hematopoietic stem or progenitor cells and also include acute myeloid leukemia (AML), myeloproliferative neoplasms (MPN), and the hybrid MDS/MPN entities. Individuals with MDS have a high risk of progressing to leukemia, with approximately 30% expected to develop AML. This study evaluates genetic susceptibility to myeloid malignancy using data from population-based case control studies of myelodysplastic syndromes and acute myeloid leukemia in adults (ages 18-85 years) and pediatric MDS cases with banked samples at the Center for International Blood and Marrow Transplant Research (CIBMTR). Adult cases were identified through the Minnesota Cancer Reporting System and controls were recruited from the State Driver's License/Identification Card list. DNA samples were collected via mouthwash collection kits (AML cases and controls) or Oragene saliva collection kits (adult MDS cases and controls). Pediatric MDS samples were banked at CIBMTR prior to receipt of a transplant and DNA was extracted from isolated T cells or whole blood samples. Genotyping data were generated using the Illumina Global Diversity array and quality control and genotype calling was conducted using established best practices. Our primary analyses investigated the contribution of genetic variation to MDS risk and evaluated the role of the killer cell immunoglobulin receptors (KIR) on incidence and survival.

  Study phs002962

• MINCR is a MYC-induced lncRNA able to modulate MYC’s transcriptional network in Burkitt lymphoma cells

  Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long non-coding RNAs (lncRNAs), on the way MYC is able to influence cellular transcriptome. To this aim we have intersected RNA-sequencing data from two MYC-inducible cell lines and from a cohort of 91 mature B-cell lymphomas carrying, or not carrying, genetic variants resulting in MYC over-expression. By this approach, we identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them we focused on a lncRNA that we named MINCR, for MYC-Induced long Non-Coding RNA, showing a strong correlation with MYC expression in MYC-positive lymphomas and also in pancreatic ductal adenocarcinomas. To understand its cellular role we performed RNA interference (RNAi) experiments and found that MINCR knock-down is associated with a reduction in cellular viability, due to an impairment in cell cycle progression. Differential gene expression analysis following RNAi showed a strongly significant enrichment of cell cycle genes among the genes down-regulate following MINCR knock-down. Interestingly these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of MYC transcriptional program. Accordingly, following MINCR knock-down, we observed a reduction in the binding of MYC to the promoters of selected cell cycle genes. Finally we provide evidences that down-regulation of AURKA, AURKB and CTD1 may explain the reduction in cellular proliferation observed upon MINCR knock-down. We therefore suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  Dataset EGAD00001001441

• PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

  Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

  Study phs000963