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• Maturation of Human Intestinal Epithelial Cell Layers Fortifies the Apical Surface against Salmonella Attack

  Pathogen invasion of intestinal epithelial cells (IECs) is a key gut infection event. The dynamics of this process in intact epithelia and the factors governing IEC susceptibility remain underexplored. We present a resource for live-cell infection imaging in human enteroid-/colonoid-derived IEC layers, across maturation states and in the presence or absence of soluble mucus production. Utilization of this resource shows how human IEC maturation fortifies the apical surface against invasion by Salmonella Typhimurium (S.Tm). Immature IEC layers appear permissive to S.Tm invasion, but maturation towards an enterocyte/colonocyte phenotype reduces the susceptibility by up to tenfold. This shift couples to downregulated expression of actin regulatory proteins exploited by the pathogen, an increased dependence on the S.Tm effector SipA, and the build-up of the apical IEC glycocalyx linked to surface-attached mucins like MUC13 and nullifiable by StcE-enzyme treatment. This underscores how the maturation state of human IECs governs susceptibility to bacterial invasion.

  Study EGAS50000001241

• WGS analysis of Japanese liver cancer

  Liver cancer is prevalent worldwide, mainly associated with virus infection, and its underlying etiology and genomic structure are heterogeneous. Here we provide a whole-genome landscape of somatic alterations in 300 Japanese liver cancers. Our comprehensive analysis elucidated point mutations in non-coding regions, structural variants (SVs), and virus integrations, in addition to coding mutations, and demonstrated new mutational signatures related with liver carcinogenesis, novel recurrently mutated coding and non-coding regions such as lincRNA NEAT1/MALAT1, promoters, CTCF binding sites, and regulatory regions. SV analysis found a significant association with replication timing, and revealed that known cancer genes (CDKN2A, CCND1, APC, and TERT) and new cancer genes (ASH1L, NCOR1, MACROD2) were recurrently affected by SVs, leading to altered expression of nearby genes. These results emphasize the value of whole genome sequencing analysis to discover cancer driver mutations and to understand comprehensive molecular profiles of liver cancer, especially for SVs and non-coding mutations.

  Study JGAS000151

• Molecular Profiling and Sequential Somatic Mutation Shift in Hypermutator Tumors Harboring POLE Mutations

  Defective DNA polymerase ? (POLE) proofreading leads to extensive somatic mutations that exhibits biased mutational properties; however, the characteristics of POLE-mutated tumors remain unclear. In present study, we described a molecular profile using whole exome sequencing based on the transition of somatic mutations in 10 POLE-mutated solid tumors that obtained from 2,42 Japanese patients. The bias of accumulated variations in this mutant was quantified to follow a pattern of somatic mutations, thereby classifying the sequential mutation shift into three periods. During the period prior to occurrence of the aberrant POLE, no accumulation of mutations in cancer-related genes was observed, whereas PTEN was highly mutated in conjunction with or subsequent to the event, suggesting that POLE and PTEN mutations were responsible for the development of POLE-mutated tumors. Furthermore, homologous recombination was restored after occurring PTEN mutations. Our strategy for estimation of the footprint of somatic mutations may provide new insight toward the understanding of mutation-driven tumorigenesis.

  Study JGAS000130

• Sequencing cancer mutations in various types of lung cancer using the long-read, portable sequencer

  In this study, we used a long-read and portable sequencer MinION to identify cancer mutations in lung adenocarcinoma cells. We performed cDNA amplicon sequencing for various types of mutations such as point mutations in EGFR and KRAS and oncogenic fusion transcripts in ALK and RET. Using the long reads of MinION, we also conducted mutation phasing of EGFR TKI-sensitive and resistant mutations, which would provide useful information to next thrapeutic approaches for cancers. We applied this method to identify mutation genotypes of eight clinical samples from Japanese lung adenocarcinomas. This method could provide new sequencing-based diagnostic approaches for lung cancers. Additinally we also performed cancer mutation identification of risk-dependent unique samples. Usual interstitial pneumonia (UIP) is a risk factor for lung carcinogenesis. This study was performed to characterize mutagenesis and mutational target genes underlying lung carcinogenesis in patients with UIP.We performed whole exome sequencing of lung adenocarcinoma with usual interstitial pneumonia.

  Study JGAS000065

• Fragmentation signatures in cancer patients are similar to those in patients with vascular and autoimmune diseases

  The analysis of fragmentation patterns in plasma cell-free DNA (cfDNA) has been shown to distinguish individuals with cancer from healthy controls in multiple case-controlled studies. However, there have been few studies that investigate various types cfDNA fragmentomics patterns in individuals with other diseases. For this purpose, we developed a comprehensive metric, called fragmentation signatures, that integrated the distributions of fragment positioning, fragment length, and fragment end-motifs. Using this metric, we found that individuals with venous thromboembolism, systemic lupus erythematosus, dermatomyositis, or scleroderma had cfDNA fragmentation signatures that closely mimicked those found in individuals with advanced cancers. Furthermore, these signatures were highly correlated with increases in inflammatory markers in the blood. Though these data put substantial limitations on the specificity of fragmentomics-based tests for cancer diagnostics, they also offer ways to improve the interpretability of such tests. Moreover, they should lead to a better understanding of the cells – most likely inflammatory cells - from which plasma cfDNA is derived.

  Study EGAS00001008004

• STimage: Robust and interpretable prediction of gene markers and cell types from spatial transcriptomics data

  Spatial transcriptomics (ST) links tissue morphology with gene expression values, opening new avenues for digital pathology. Deep learning models are used to predict gene expression or classify cell types directly from images, offering significant clinical potential but still requiring improvements in interpretability and robustness. We present STimage as a comprehensive suite of models to predict spatial gene expression and classify cell types directly from standard H\&E images. STimage enhances robustness by estimating gene expression distributions and quantifying both data-driven (aleatoric) and model-based (epistemic) uncertainty using ensemble approach with foundation models. Interpretability is achieved through attribution analysis at single-cell resolution integrated with histopathological annotations, functional genes, and latent representations. We validated STimage across diverse datasets, demonstrating its performance across various platforms. STimage-predicted gene expression can stratify patient survival and predict drug response. By enabling molecular and cellular prediction from routine histology, STimage offers a powerful tool to advance digital pathology.

  Study EGAS50000001503

• Data Use Ontology (DUO) at EGA

  For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

  Blog data-use-ontology

• Somatic mutations in ALS genes in the motor cortex of sporadic ALS patients

  Several lines of evidence suggest that amyotrophic lateral sclerosis (ALS) pathology starts focally and spreads within the central nervous system (CNS). We leveraged DNA and RNA sequencing data from ALS autopsy tissue to explore the presence of somatic mosaic variants in sporadic ALS (sALS) cases. Deep targeted sequencing of known ALS disease genes from motor cortex tissue revealed enrichment of somatic variants in sALS compared to familial ALS (fALS) with a monogenic cause and an increased pathogenicity of mosaic mutations in known ALS mutational hot spots. Experimental validation of the variants identified that the somatic FUS variant p.E516X leads to nucleo-cytoplasmic mislocalization and aggregation. Additionally, somatic variant calling from single-cell RNA-sequencing data of sALS tissue showed an accumulation of somatic variants in excitatory neurons. Collectively, using a multi-modal approach, our findings suggest that somatic mutations within the motor cortex, especially in excitatory neurons, may contribute to the development of sALS.

  Study EGAS00001008104

• Genetic Basis of Hepatosplenic T Cell Lymphoma (HSTL)

  Hepatosplenic T cell lymphoma (HSTL) is a rare and lethal lymphoma; the genetic drivers of this disease are unknown.  Through whole exome sequencing of 68 HSTLs, we define recurrently mutated driver genes and copy number alterations in the disease. Chromatin modifying genes including SETD2, INO80 and ARID1B were commonly mutated in HSTL, affecting 62% of cases. HSTLs manifest frequent mutations in STAT5B (31%), STAT3 (9%), and PIK3CD (9%) for which there currently exist potential targeted therapies. In addition, we noted less frequent events in EZH2, KRAS and TP53. SETD2 was the most frequently silenced gene in HSTL. We experimentally demonstrated that SETD2 acts as a tumor suppressor gene. In addition, we found that mutations in STAT5B and PIK3CD activate critical signaling pathways important to cell survival in HSTL. Our work thus defines the genetic landscape of HSTL and implicates novel gene mutations linked to HSTL pathogenesis and potential treatment targets.

  Study EGAS00001002182

• Orthotopic Patient-Derived Xenografts of Pediatric Solid Tumors

  Pediatric solid tumors arise from endodermal, ectodermal, or mesodermal lineages. Although the overall survival of children with solid tumors is 75%-80%, that of children with recurrent disease is below 30%. To capture the complexity and diversity of pediatric solid tumors and establish new models of recurrent disease, we developed a protocol to produce orthotopic patient-derived xenografts (O-PDXs) at diagnosis, recurrence, and autopsy. Tumor specimens were received from 168 patients, and 64 O-PDXs were established for 12 types of pediatric solid tumors. The origins of the O-PDX tumors were reflected in their gene-expression profiles and epigenomes. Genomic profiling of the tumors, including detailed clonal analysis, was performed to determine whether the clonal population in the xenograft recapitulated the patient’s tumor. We identified several drug vulnerabilities and showed that the combination of a WEE1 inhibitor (AZD1775), irinotecan, and vincristine can lead to complete response in multiple rhabdomyosarcoma O-PDX tumors in vivo.

  Study EGAS00001002528