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• HG_Retroduplications_in_Neurodevelopmental_Disorders

  Mobile genetic Elements (MEs) are pieces of DNA which, through an RNA intermediate, can generate new copies of themselves elsewhere in the host genome. Additionally, MEs can facilitate the duplication of non-ME transcripts, typically genes, through the mechanism of retroduplication. In humans, several disorders have been directly attributed to ME-derived mutagenesis but not to retroduplication events. We propose to whole genome sequence the 7 individuals with putative de novo gene retroduplications in order to identify the site of insertion. This sequencing will serve two primary purposes: 1.) Identify the first documented case of a de novo retrogene insertion event causing a disease in humans 2.) provide additional whole genome sequencing of undiagnosed probands recruited into the DDD 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 EGAS00001002907

• Spatial profiling of hepatocellular carcinoma identifies distinct tumor and immune micro-ecosystems related to patient outcomes

  Hepatocellular carcinoma (HCC) shows substantial intra-tumor heterogeneity that remains poorly understood. Using spatial transcriptomics, we identified 13 recurrent tumor and stromal micro-ecosystems (MES) and mapped their spatial organization and biological functions. One immune-enriched MES containing Kupffer cell–like macrophages was strongly associated with improved disease-free survival and response to atezolizumab–bevacizumab. Our findings demonstrate the value of spatial profiling for revealing rare but clinically meaningful cellular communities.

  Study EGAS50000001474

• Institut National pour la Recherche Biomedicale Comite d'Access aux Donnees

  Dac EGAC00001001539

• AREP(Association pour la Recherche et l’Enseignement en Pathologie) Data Access Commitee

  Dac EGAC00001001196

• Botensilimab, an Fc-enhanced Anti-CTLA-4 Antibody, is Effective Against Tumors Poorly Responsive to Conventional Immunotherapy

  This study explores the genomic landscape associated with a novel Fc-engineered anti-CTLA-4 antibody (botensilimab) in advanced solid tumors. We seek to understand if enhancing the Fc-region affinity of anti-CTLA-4 antibodies can improve anti-tumor efficacy and expand clinical benefit to tumors poorly responsive to conventional immunotherapy. As part of an ongoing open-label, Phase 1, multicenter study, we conducted an exploratory sub-analysis of genomics data. The primary study evaluates the safety, tolerability, pharmacokinetics, and pharmacodynamics of botensilimab monotherapy and in combination with an anti-PD-1 antibody (balstilimab) in participants with advanced solid tumors. RNA from formalin-fixed paraffin-embedded (FFPE) tumor biopsies and matched normal blood samples were isolated and subjected to RNA-sequencing using the Personalis ImmunoID NeXT Platform. We demonstrated that anti-CTLA-4 engineered for enhanced FcγR affinity leverages FcγR-dependent mechanisms to potentiate T cell responsiveness, reduce intratumoral Tregs, and enhance antigen presenting cell activation. This genomic analysis contributes to our understanding of the molecular mechanisms underlying patient responses to Fc-engineered anti-CTLA-4 therapy and may inform future strategies to expand the clinical benefit of immune checkpoint blockade in cancer immunotherapy.

  Study phs003704

• Fgl2 Regulates FcγRIIB+ CD8+ T Cell Responses during Infection

  While the inhibitory receptor FcγRIIB has been shown to be upregulated on activated CD8+ T cells in both mice and humans, its impact on T cell fate during infection has not been fully elucidated. We identified an increase in FcγRIIB-expressing CD8+ T cells in COVID patients relative to healthy controls, and in mouse models of viral infection. Despite its well-known role as an Fc receptor, FcγRIIB also ligates the immunosuppressive cytokine Fgl2, resulting in CD8+ T cell apoptosis. Both chronic LCMV infection in mice and COVID in humans resulted in a significant increase in plasma Fgl2. Further, plasma Fgl2 was directly proportional to CD8+ T cell lymphopenia in COVID patients. To further understand the association of Fgl2 and CD8+ T cell lymphopenia following COVID infection, we assessed the transcriptomic profiles of PBMCs with high (≥ 9.153 ng/ml) vs low (defined as

  Study phs003870

• Data Access Committee KCL FC

  Dac EGAC00001000386

• Identification of HER2-positive breast cancer molecular subtypes with potential clinical implications in the ALTTO clinical trial

  In HER2-positive breast cancer, clinical outcome and sensitivity to HER2-targeted therapies are influenced by both tumor and microenvironment features. However, we are currently unable to depict the molecular heterogeneity of this disease with sufficient granularity. Here, by performing gene expression profiling in HER2-positive breast cancers from patients receiving adjuvant trastuzumab in the ALTTO clinical trial, we identified and characterized five molecular subtypes associated with the risk of distant recurrence: immune-enriched (IM), proliferative/metabolic-enriched (P/Met), mesenchymal/stroma-enriched (Mes/S), luminal (LUM), and ERBB2-enrichedERBB2-dependent (ERBB2-EERBB2-D). We next validated the biological profiles of the subtypes and explored their prognostic/predictive value in external cohorts, namely the NeoALTTO trial, SCAN-B, I-SPY2, METABRIC and TCGA. IM tumors presented better survival outcomes, in contrast to Mes/S and P/Met tumors, while LUM tumors and ERBB2-EERBB2-D were characterized by low and high rates of pathological complete response, respectively. Of note, these molecular subtypes provide the rationale for treatment approaches leveraging the heterogeneous biology of HER2-positive breast cancer.

  Study EGAS50000000525

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• MCF10A 12h IL6 classical signaling

  Gene expression after cell culture, 12h IL6+sgp130-Fc stimulated

  Dataset EGAD00010001970