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• H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

  Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

  Study EGAS00001004301

• The spatio-temporal evolution of lymph node spread in early breast cancer

  Purpose: The most significant prognostic factor in early breast cancer is lymph node involvement. This stage between localised and systemic disease is key to understanding breast cancer progression, however our knowledge of the evolution of lymph node malignant invasion remains limited, as most currently available data derive from primary tumours. Experimental design: In 11 treatment-naïve node positive early breast cancer patients without clinical evidence of distant metastasis, we investigated lymph node evolution using spatial multi-region sequencing (n=78 samples) of primary and lymph node deposits and genomic profiling of matched longitudinal circulating tumour DNA (ctDNA). Results: Linear evolution from primary to lymph node was rare (1/11) whereas the majority of cases displayed either early divergence between primary and nodes (4/11), or no detectable divergence (6/11) where both primary and nodal cells belonged to a single recent expansion of a metastatic clone. Divergence of metastatic subclones was driven in part by APOBEC. Longitudinal ctDNA samples from 2 subjects taken peri-operatively reflected the two major evolutionary patterns and demonstrate that private mutations can be detected even from early metastatic nodal deposits. Moreover, node removal resulted in disappearance of private lymph node mutations in ctDNA.Conclusions: This study sheds new light on a crucial evolutionary step in the natural history of breast cancer, demonstrating early establishment of axillary lymph node metastasis in a substantial proportion of patients.

  Study EGAS00001002947

• ICU_transcriptomics__Assessing_the_role_of_the_host_immune_response_in_patients_with_ventilator_associated_pneumonia

  The aim of the proposed project is to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. The lung microbiome of these patients will be analysed in parallel by deep sequencing and 16S sequencing. These data will provide important information to the development of strategies aimed at improving patient outcomes, reducing the development of antimicrobial resistance and facilitating infection control measures in hospital. Specifically, the proposed work will be a proof of principle study of 100 patients. We will use transcriptomic data to define the host contribution to the symptoms of these critically ill patients diagnosed with pneumonia. The data will be correlated with cytokine/chemokine concentrations, routine microbiology analysis and pathogen genomic data from the same samples to determine the ecology of the lungs of these patients. We will look for associations between clinical features, host response and pathogen genomics in order to identify new diagnostic markers. This study should provide important information to improve the speed and accuracy of diagnosis - resulting in more targeted and successful treatment of critically ill patients in the ICU. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003074

• Exploiting evolutionary steering in cancer therapy

  Drug resistance, mediated by intra-tumour heterogeneity and clonal evolution, is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at the cost of increased sensitivity to another due to so-called evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, model systems able to recapitulate cancer evolution experimentally are lacking and current in vitro techniques based on small populations, re-plating and escalating dose, are unsuitable to develop evolutionary herding strategies. We present a novel methodology for evolutionary herding in vitro and ex vivo using patient-derived organoids. Our approach is based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, realistic high drug doses, time-course monitoring of cancer clones, and mathematical modelling of tumour evolutionary dynamics. We demonstrate evolutionary herding in non-small cell lung cancer in vitro and in patient-derived colorectal cancer organoids (PDO). We show that herding causes controlled evolutionary bottlenecks that lead to collateral sensitivity. Through genomic analysis, we were also able to determine the mechanisms that drive such sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can be translated into the clinic to control treatment resistance.

  Study EGAS00001003200

• Efficacy of JAK/STAT pathway inhibition in murine xenograft models of early T-cell precursor (ETP) acute lymphoblastic leukemia

  Early T-cell precursor (ETP) acute lymphoblastic leukemia (ALL) is a recently described subtype of T-ALL characterized by a unique immunophenotype and genomic profile as well as a high rate of induction failure. Frequent mutations in cytokine receptor and JAK/STAT signaling pathways led us to hypothesize that ETP-ALL is dependent on JAK/STAT signaling. Here we demonstrate aberrant activation of the JAK/STAT pathway in ETP-ALL blasts relative to non-ETP T-ALL. Moreover, ETP-ALL showed hyperactivation of STAT5 in response to IL7, an effect that was abrogated by the JAK1/2 inhibitor ruxolitinib. In vivo, ruxolitinib displayed activity in 6/6 patient-derived murine xenograft models of ETP-ALL, with profound single-agent efficacy in 5 models. Ruxolitinib treatment decreased peripheral blast counts relative to pre-treatment levels and compared to control (P<0.01) in 5/6 ETP-ALL xenografts, with marked reduction in mean splenic blast counts (P<0.01) in 6/6 samples. Surprisingly, both JAK/STAT pathway activation and ruxolitinib efficacy were independent of the presence of JAK/STAT pathway mutations, raising the possibility that the therapeutic potential of ruxolitinib in ETP-ALL extends beyond those cases with JAK mutations. These findings establish the preclinical in vivo efficacy of ruxolitinib in ETP-ALL, a biologically distinct subtype for which novel therapies are needed.

  Study EGAS00001001146

• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• Atypical 3q26/MECOM rearrangements genocopy inv(3)/t(3;3) in acute myeloid leukemia

  Acute myeloid leukemia (AML) with inv(3)/t(3;3)(q21q26) is a distinct WHO recognized entity, characterized by its aggressive course and poor prognosis. In this subtype of AML, the translocation of a GATA2 enhancer (3q21) to MECOM (3q26) results in overexpression of the MECOM isoform EVI1 and monoallelic expression of GATA2 from the unaffected allele. The full-length MECOM transcript, MDS1-EVI1, is not expressed as the result of the 3q26 rearrangement. Besides the classical inv(3)/t(3;3), a number of other 3q26/MECOM rearrangements with poor treatment response have been reported in AML. Here we demonstrate, in a group of 33 AML patients with atypical 3q26 rearrangements, MECOM involvement with EVI1 overexpression, but no or low MDS1-EVI1 levels. Moreover, the 3q26 translocations in these AML patients often involve super-enhancers of genes active in myeloid development (e.g. CD164, PROM1, CDK6 or MYC). In more than 50% of these cases allele specific GATA2 expression was observed, either by copy number loss or by an unexplained allelic imbalance. Altogether, atypical 3q26 recapitulate the main leukemic mechanism of inv(3)/t(3;3) AML, namely EVI1 overexpression driven by enhancer hijacking, absent MDS1-EVI1 expression and potential GATA2 involvement. Therefore, we conclude that both atypical 3q26/MECOM and inv(3)/t(3;3) can be classified as a single entity of 3q26-rearranged AMLs. Routine analyses determining MECOM rearrangements, EVI1 and MDS1-EVI1 expression are required to recognize 3q-rearranged AML cases.

  Study EGAS00001004325

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• Identification of the mutational consequences of precancerous liver disease (including alcohol abuse) on the genomes of human adult stem cells.

  Stem cells are believed to be the cells-of-origin cancer. Nevertheless, their genome remains remarkably stable during life. To increase insight into how these cells can drive tumorigenesis, we set out to determine the genomic integrity of human adult stem cells from patients with liver disease associated with increased cancer risk. To this end, we characterized genome-wide mutation profiles of single ASCs from livers of patients with alcoholic liver disease, non-alcoholic liver disease and primary sclerosing cholangitis. The patients included in our study received a liver transplant due to their liver disease. Strikingly, we found that ASCs in these livers maintain a stable genome and have comparable mutation rates as healthy human liver ASCs. We did observe more nonsense and nonsynonymous mutations in COSMIC cancer genes that are hit by dominant mutations in tumors in comparison to healthy ASCs (n.s.), including two ASCs in alcoholic liver disease patients with a nonsense mutation in PTPRK. Next, we sequenced 5 biopsies of an alcoholic tumour to identify the mutational patterns in the tumour-initiating ASC. We found that the mutational patterns are, again, similar to healthy liver, but the mutational load is slightly higher. This suggests that the increased cancer risk in the liver disease patients is not caused by an increased mutational load, but rather that the precancerous liver environment promotes outgrowth of cells that would normally be selected against.

  Study EGAS00001002983