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• Cell-free DNA sequencing using newly developed single-strand DNA library preparation

  We performed whole genome sequencing of cell-free DNA that was collected from human plasma using an improved cfDNA purification protocol and DNA library prepared with newly developped protocol of our own.

  Study JGAS000257

• Subclonal diversification of primary breast cancer

  Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

  Dataset EGAD00001000898

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Pancreatic Organoids (2021-02-02)

  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. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006933

• Long read whole genome sequencing data from brain postmortem tissue

  Dataset consisting of 172 whole genome sequencing runs from healthy controls and Parkinson's disease patients. The data was sequenced on Oxford Nanopore (PromethION) platform. The data has been mapped to T2T-CHM13v2.0 reference genome. The data processing pipeline is available on the following link: [https://zenodo.org/records/13385065](https://zenodo.org/records/13385065). The data is in CRAM format and subet of donors also have information on C (hydroxy)methylation (MM and ML tag). The reads are also phased (HP tag).

  Dataset EGAD50000001349

• Non-coding RNAs Activated by the Wnt/Beta-catenin Signaling Pathway in Hepatoblastoma

  Hepatoblastoma (HB) is the most common pediatric liver tumor, affecting mostly children under 3 years of age. This rare tumor represents 1% of all pediatric cancers. Genetic studies have shown that HB is characterized by high frequency mutations of the CTNNB1 gene encoding beta-catenin (around 75%) and relative genomic stability. Here we have analyzed the transcriptional profile of 21 HBs compared to matched non-tumor livers by Cap Analysis of Gene Expression (CAGE), which provides accurate and quantitative profiling of all transcripts. CAGE analysis revealed strong upregulation of known Wnt target coding genes in most tumors analyzed, consistent with previous transcriptomic studies. To better define the Wnt-dependent transcriptional landscape of HB, we integrated CAGE data with TCF4 ChIP-seq data from a CTNNB1-mutated cancer cell line and with the FANTOM5 genomic coordinates of TCF/LEF binding motifs. Both TCF/LEF binding motifs and ChIP-seq peaks were strongly enriched in the immediate upstream region, not only for protein-coding genes, but also for non-coding transcripts. Among the selected 112 top Wnt target genes at FDR<1.0E-6 and fold change>8, we found clear over-representation (66%) of distant transcription start sites (TSSs) representing lncRNAs and enhancer RNAs, which raises the question of their role in HB pathogenesis. Analysis of the 112 promoters using CAGEd-oPOSSUM confirmed the predominant involvement of Tcf/Lef transcription factors, together with HNF4G, GATA2, Sox3 and Ets-related genes. Finally, the 112 Wnt target signature defined 3 tumor subclasses, T1, T2 and T3, characterized by progressive alteration of the non-coding part of the transcriptome and significant differences in clinical behavior.

  Study phs001433

• WGS and WES of 78 pairs Chinese gastric cancer

  Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

  Study EGAS00001001056

• Integration of genomics and metabolomics in acute myeloid leukemia

  Although targeting of cell metabolism is a promising therapeutic strategy in acute myeloid leukemia (AML), metabolic dependencies are largely unexplored. We aimed to classify AML patients based on their metabolic landscape and map connections between metabolic and genomic profiles. The intracellular metabolome distinguished three AML clusters, correlating with distinct genomic profiles: NPM1-mutated(mut), chromatin/spliceosome-mut and TP53-mut/aneuploid AML that were confirmed by biofluid analysis.

  Study EGAS00001005422

• Profiling of 27 type 2 diabetes GWAS loci using next-generation (NG) capture C in a human beta-cell model

  Most type 2 diabetes association signals are due to variants that impact gene regulation but identifying the genes they impact is challenging. We generated interaction profiles at 27 T2D GWAS loci using next-generation (NG) capture C in a human beta-cell model ( EndoC-betaH1) and contrasted our maps with public Hi-C/promoter capture Hi-C maps in EndoC-betaH1 cells or human islets.

  Study EGAS00001006105

• RNA sequencing of 20 intra/extra hepatic bileduct organiods

  This dataset contains RNA sequencing data for 20 intra/extra hepatic bileduct organiods. Data is in BAM format and was processed by STAR.

  Dataset EGAD00001005225

• Analysis of AR Gene Rearrangements in Prostate Cancer

  Molecularly-targeted therapies for advanced prostate cancer include castration modalities that suppress ligand-dependent transcriptional activity of the androgen receptor (AR). However, persistent AR signaling undermines therapeutic efficacy and promotes progression to lethal castration-resistant prostate cancer (CRPC), even when patients are treated with potent second-generation AR-targeted therapies abiraterone and enzalutamide. Here we define diverse AR genomic structural rearrangements (AR-GSRs) as a class of molecular alterations occurring in one third of CRPC-stage tumors. AR-GSRs occur in the context of copy-neutral and amplified AR and display heterogeneity in breakpoint location, rearrangement class, and sub-clonal enrichment in tumors within and between patients. Despite this heterogeneity, one common outcome in tumors with high sub-clonal enrichment of AR-GSRs is outlier expression of diverse AR variant species lacking the ligand binding domain and possessing ligand-independent transcriptional activity. Collectively, these findings reveal AR-GSRs as important drivers of persistent AR signaling in CRPC.

  Study phs001223