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• Duplexseq_of_the_interstrand_crosslinks_WGS

  One of the most dangerous forms of DNA damage are interstrand crosslinks (ICLs), which covalently crosslink the two strands of the DNA double helix. The repair of these lesions is crucial for cellular survival due to their ability to block transcription and DNA replication. Initially, the major pathway that has been described in ICL repair involves a network of 22 genes that are mutated in a severe human genetic disease known as Fanconi Anemia (FA). Using synthetic lethality screens in the near-haploid human HAP1 cell line, we recently identified two potentially novel regulators of ICL repair, C1orf112 and THAP12. Loss of C1orf112 and THAP12 causes hypersensitivity to ICL-inducing DNA damaging agents, such as Mitomycin C (MMC). Additionally, C1orf112-depleted cells show elevated levels of micronuclei and accumulation of DNA damage in S-phase. To better understand how C1orf112 and THAP12 mediate the repair of ICLs, we want to perform mutational signature analysis, using the BotSeq method. Therefore, WT, C1orf112 and THAP12 knockout cells were cultured in vehicle or MMC treated conditions for 10 days and the genomic DNA was isolated. FANCA and FANCD2 knockout cells are taken along as controls in this experimental setting.

  Study EGAS00001006545

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__organoid_control_WGS

  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, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure 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 EGAS00001005449

• Spatial multi-omic map of human myocardial infarction

  Myocardial infarction is a leading cause of mortality worldwide 1 . While advances have been made in acute treatment, an incomplete understanding of remodelling processes has limited the effectiveness of therapies to reduce late-stage mortality 2 . Here, we generate an integrative high- resolution map of human cardiac remodelling after myocardial infarction using single-cell gene expression, chromatin accessibility, and spatial transcriptomic profiling of multiple physiological zones at distinct time points in myocardium from myocardial infarction and control patients. Multimodal data integration allowed us to evaluate cardiac cell-type compositions at increased resolution, yielding insights into changes of the cardiac transcriptome and epigenome through the identification of distinct tissue structures of injury, repair and remodelling. We identified and validated disease-specific cardiac cell-states of major cell-types and analysed them in their spatial context, evaluating their dependency on other cell-types. Our data elucidates molecular principles of human myocardial tissue organisation, recapitulating a gradual cardiomyocyte and myeloid continuum following ischemic injury. In total, our study provides an integrative molecular map of human myocardial infarction and represents an essential reference for the field and paves the way for advanced mechanistic and therapeutic studies of cardiac disease.

  Study EGAS00001006330

• Profiling_the_Microbiome_of_Early_Life_Gut_Samples

  The human gut microbiome (GM), defined as the microorganisms that reside in the human gastrointestinal tract, has been identified as critical for normal intestinal development and physiology. However, to-date, the majority of studies characterizing the gut microbiome has relied on stool samples, thereby limiting insights into the regionality of the gut and how its microbiota differs along its length. As a result, this project seeks to profile the adjacent microbiota of various regions along the intestinal tract from pediatric intestinal tissue and their associated mucosal washes, enabling insights into tissue-specific microbiomes. Due to the expected low microbial biomass of these samples, donor stool (when available) will also be metagenomically profiled as positive controls, which will enable us to benchmark our low-biomass processing methods with existing protocols. By sampling pediatric patients of diverse ages and health statuses, this metagenomic data will also be valuable for understanding the gut microbiome of the developing human gut across time and space. 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 please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001008081

• noninvasive lung cancer subtyping

  Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.

  Study EGAS00001007717

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Mutagen_treated_organoids

  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, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure 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 EGAS00001004873

• Risk and modifying factors in Frontotemporal Dementia

  Understanding the molecular mechanisms underlying frontotemporal dementia (FTD) is essential for the development of successful therapies. Here, we present Phase 1 of a multi-omics, multi-model data resource for FTD research which will allows in-depth molecular research into these mechanisms. We have integrated and analysed data from the frontal lobe of FTD patients with mutations in MAPT, GRN and C9orf72 and detected common and distinct dysregulated cellular pathways. Our results highlight that excitatory neurons are the most vulnerable neuronal cell type and that vascular aberrations are a common hallmark in FTD. Via integration of multi-omics data, we detected several transcription factors and pathways which regulate the strong neuroinflammation observed in FTD-GRN. Finally, using small RNA-seq data and verification experiments in cellular models, we identified several up-regulated miRNAs that inhibit cellular trafficking pathways in FTD and lead to microglial activation. In this work we shed light on novel mechanistic and pathophysiological hallmarks of FTD. In addition, we believe that this comprehensive, multi-omics data resource will further mechanistic FTD research by the community.

  Study EGAS00001004895

• Single cell RNA sequencing of synovial B cells in early Rheumatoid Arthritis

  Rheumatoid Arthritis (RA) is a prevalent autoimmune disease characterized by inflammation of the peripheral joints and occurence of autoantibodies, i.e. Rheumatoid Factor (RF) and anti-citrullinated protein antibodies (ACPA), in circulation. Previous studies have shown that there are memory B cells and autoantibody producing plasma cells present in the joint tissue of patients with long-standing RA. However, it has remained unclear, whether these B cell populations are already present in the joint tissue of patients at the disease onset and whether these are autoreactive. Here, we used a single cell RNA sequencing approach to dissect the B cell repertoire at this early timepoint. We found evidence for B and T cell interaction and presence of memory and plasma cell pools in ACPA- and ACPA+ RA. Our results demonstrated clonal relationships between the memory and plasma cell compartments and autoreactivity within the plasma cell pool. These findings challenge our understanding of the local adaptive immune response in the joints of ACPA- and ACPA+ RA patients with direct implications for B and T cell targeting therapy in both patient subgroups.

  Study EGAS00001005144

• Circulating tumor cells Exome sequencing from breast cancer

  Single cell technologies allow interrogating the extent of tumor heterogeneity, providing novel insights into tumor evolution and treatment resistance mechanisms. Here, we investigated the level of genetic heterogeneity among circulating tumor cells (CTCs) at the single nucleotide variation and copy number aberration (CNA) levels and compared it to synchronous matched primary tumor/metastatic lesion from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive (HER2+) and estrogen-receptor-positive (ER+) tumors. Whole exome sequencing was performed on 3 synchronous bulk tumor tissue and 21 single/pooled CTC samples. When comparing bulk tissue with CTCs from the same patient, we found similar CNA profiles and the same patient-specific driver mutations for the HER2+ and TNBC tumors. Different CNA profiles and driver mutations were found for the ER+ tumor, with two distinct clones being identified in the CTCs, one harboring an activating ESR1 mutation, the other one bearing a TP53 mutation. These data suggest that tumor tissue and CTCs provide in a subset of patients complementary clinically relevant information to map tumor heterogeneity and monitor tumor evolution. Further validation is needed.

  Study EGAS00001005228

• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877