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• Error-corrected flow-based sequencing at whole genome scale and its application to circulating cell-free DNA profiling

  Differentiating sequencing errors from true variants is a central genomics challenge calling for error suppression strategies that balance costs when sparse material or ultra-rare variants require high-accuracy methods. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), abundance of genomic material in samples, library preparation error rates and sequencing errors. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signal across the mutation landscape, but higher cost limits adoption compared with targeted panels, where ccfDNA abundance limits maximal coverage depths. Here we applied deep (~120x) lower-cost WGS (Ultima Genomics) with analytic error correction for tumor-informed ctDNA detection within the part-per-million range. We further developed high-coverage duplex error-corrected WGS of ccfDNA, achieving 7.7x10-8 error rates, to assess disease burden in melanoma and urothelial cancer patients without matched tumor sequencing. Together, we show that deeply sequenced error-corrected WGS accurately calls somatic variants, demonstrating the feasibility of WGS for tumor-informed and tumor-agnostic ctDNA detection.

  Study EGAS50000000844

• Whole-genome methylation profiling of menstrual stem cells identifies novel biomarkers for endometriosis

  Endometriosis is a highly prevalent condition that remains underdiagnosed and poorly managed due to the lack of clinically validated biomarkers and limited understanding of its underlying pathophysiology. Although menstrual blood–derived stem cells (MenSCs) have been implicated in disease pathogenesis, their potential as a diagnostic source has not been systematically explored. We conducted a clinical study including 42 women (19 with endometriosis and 23 controls) to evaluate whether DNA methylation profiles from freshly isolated MenSCs could identify disease-specific biomarkers. Whole-genome DNA methylation sequencing identified differentially methylated regions (DMRs) enriched in genes associated with key features of endometriosis, including inflammation, tissue remodelling, and developmental processes. These DMRs robustly discriminated cases from controls, independently of technical and clinical confounders. Machine learning models trained and validated on these regions demonstrated strong diagnostic performance (specificity 83%, sensitivity 79%). Integration with an independent single-cell RNA sequencing dataset suggested that the identified DMRs may influence gene expression, supporting their biological relevance. Collectively, these findings highlight MenSC DNA methylation profiling as a promising, non-invasive strategy for early diagnosis and personalised management of endometriosis. (PubMed IDs will be provided once the manuscript is published.)

  Study EGAS50000001640

• Development and first-in-human CAR T therapy targeting the pathognomonic MiT-fusion driven protein GPNMB

  Summary: CAR T therapy for solid tumors is constrained by the scarcity of safe, uniformly expressed cell-surface targets. Here we identify GPNMB, a MiT fusion-driven protein, as highly, homogeneously, and stably expressed in primary and relapsed translocation-positive alveolar soft part sarcoma (ASPS) and renal cell carcinoma (tRCC). We develop a GPNMB-directed CAR T cell product, GCAR1, which demonstrates potent activity against patient-matched cells, organoids and xenograft models. In a first-in-human treatment of two patients with relapsed/refractory, metastatic ASPS, GCAR1 is well tolerated and induces stable disease for up to 6 months, accompanied by resolution of many non-target lesions. GCAR1 T cells expand in peripheral blood as a polyclonal population and remain detectable for up to 6 months. Spatial transcriptomics identify multiple immunosuppressive niches adjacent to T cells infiltrating treatment-resistant lesions; biological PDL1 blockade or PD1 and TIGIT double knockout overcomes this resistance and shows synergistic activity with GCAR1 in xenograft models. Taken together, these data provide clinical proof-of-concept for treating solid tumors with CAR T cells targeting a surface antigen driven by an oncogenic gene fusion.

  Study EGAS50000001696

• The genomic basis of childhood T-lineage acute lymphoblastic leukemia

  T-lineage acute lymphoblastic leukemia (T-ALL) is a high-risk tumor that has eluded comprehensive genomic characterization, in part due to the high frequency of non-coding genomic alterations resulting in oncogenic dysregulation. Here we report integrated genome and transcriptome sequencing of T-ALL tumor and remission samples obtained from over 1300 uniformly treated children with T-ALL, coupled with epigenomic and single cell analysis of malignant and normal T cell precursors. Integrated analysis identified 15 subtypes with distinct genomic drivers, gene expression, developmental state and outcome. Integration with chromatin topology analyses enabled elucidation of multiple mechanisms of enhancer deregulation that involve enhancers and genes in a subtype-specific fashion. We show that the immunophenotypically-described, high-risk entity of early T-cell precursor ALL is superseded by a broader category of leukemias of variable immunophenotype with diverse genomic alterations of a core set of genes encoding regulators of hematopoietic stem cell development. Numerous genetic alterations and disease subtypes emerged as independent predictors of survival and treatment failure in univariable and multivariable outcome models. These findings provide a roadmap for the classification, risk stratification and mechanistic understanding of this disease.

  Study EGAS50000000016

• FLT3-targeting and places FLT3 as an ideal therapeutic target to selectively eradicate LSCs, while sparing HSC.

  CRISPR/Cas9 FLT3 knock-out (FLT3-KO) in human HSCs and LSCs followed by functional xenograft assays to test their ability to regenerate human hematopoiesis and leukemia, respectively. FLT3-KO in HSCs from human fetal liver, cord blood and adult bone marrow showed no impairment in multilineage hematopoiesis in primary and secondary xenografts. By contrast, FLT3-KO LSCs from 6 of 7 FLT3-ITD mutated AMLs were able to generate short-term engraftment but were completely exhausted by 12 weeks. Thus, FLT3 is essential for LSC long-term propagation. This dependency was unique to FLT3-ITD AML samples as non-FLT3-ITD AML samples generated leukemic grafts upon FLT3-KO. Transcriptomic analysis revealed that FLT3-KO induced downregulation of DNA repair and cell cycle checkpoints, uniquely in FLT3-ITD AML, but not in healthy HSCs or other AMLs. Our research highlights a critical distinction between healthy HSCs and LSCs: whereas healthy hematopoiesis proceeds unperturbed upon FLT3-KO, FLT3-ITD leukemogenesis is impaired through elimination of LSCs. This evidence underscores the necessity for more potent FLT3-targeting and places FLT3 as an ideal therapeutic target to selectively eradicate LSCs, while sparing HSC.

  Study EGAS50000000437

• Prediction of homologous recombination deficiency identifies colorectal tumors sensitive to PARP inhibition

  BRCAness is a well-established feature in breast, ovarian, prostate and pancreatic carcinomas, our recent findings indicate that up to 15% of colorectal cancers (CRC) also harbor defects in the HR pathway, presenting promising opportunities for innovative therapeutic strategies in CRC patients. We developed a new tool called HRDirect, which builds upon the HRDetect algorithm and is able to predict HRD from reference-free tumor samples. We validated HRDirect using matched breast cancer and CRC patient samples. Subsequently, we assessed its efficacy in predicting response to the PARP inhibitor olaparib by comparing it with two other commercial assays: AmoyDx HRD by Amoy Diagnostics and the TruSight Oncology (TSO) _500 HRD panel by Illumina NGS technology. While all three approaches successfully identified the most PARPi-sensitive CRC models, HRDirect demonstrated superior precision in distinguishing resistant models compared to AmoyDX and TSO500-HRD, which exhibited overlapping scores between sensitive and resistant cells. Furthermore, we propose integrating HRDirect scoring with ATM immunohistochemical analysis as part of our "composite biomarker approach" to enhance the identification of HRD tumors, with an immediate translational and clinical impact for CRC personalized treatment.

  Study EGAS50000000426

• Ischemia Reperfusion Responses in Human Lung Transplants at the Single Cell Resolution

  Ischemia reperfusion is an unavoidable step of organ transplantation. Development of therapeutics for lung injury during transplantation has proved challenging; understanding lung injury from human data at the single cell resolution is required to accelerate the development of therapeutics. Donor lung biopsies from six human lung transplant cases were collected at the end of cold preservation and 2-hour reperfusion and underwent single cell RNA sequencing. Donor and recipient origin of cells from the reperfusion timepoint were deconvolved. Gene expression profiles were (1) compared between each donor cell type between timepoints and (2) compared between donor and recipient cells. Inflammatory responses from donor lung macrophages were found after reperfusion with upregulation of multiple cytokines and chemokines, especially IL-1 and IL-1. Significant inflammatory responses were found in alveolar epithelial cells (featured by CXCL8) and lung endothelial cells (featured by IL-6 upregulation). Different inflammatory responses were noted between donor and recipient monocytes and CD8+ T cells. The inflammatory signals and differences between donor and recipient cells observed provide insight into the cellular and molecular mechanisms of ischemia reperfusion induced lung injury. Further investigations may lead to the development of novel targeted therapeutics.

  Study EGAS50000000490

• Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

  DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

  Study EGAS50000000541

• TDP43 proteinopathy leads to divergent cryptic splicing in the cortex and spinal cord

  Mislocalization of the nuclear TAR DNA-binding protein 43 (TDP43) is a hallmark of ALS and FTD which leads to de-repression and inclusion of cryptic exons, promising biomarkers of TDP43 pathology in a spectrum of neurodegenerative diseases. However, most cryptic exons to date have been identified from in vitro models or a single cortical FTD dataset, and little is known about cryptic splicing in the spinal cord, or within different neuronal subtypes. We meta-analyzed published bulk RNAseq datasets representing 1,778 RNAseq profiles of ALS and FTD post-mortem tissue, and in vitro models with experimentally depleted TDP43. We identified 142 cryptic splices, including 76 novel events. We found a novel pattern of spinal cord cryptic splicing, validated in an independent cohort by qPCR, which differed significantly from cortical and in vitro splicing. Finally, leveraging multiple public single-nucleus RNAseq datasets of ALS and FTD motor and frontal cortex, we confirmed the elevation of cortical-enriched splices in disease and localized them to layer-specific neuronal populations. This catalog of cryptic splices could inform efforts to develop biomarkers for tissue-specific and cell type-specific TDP43 pathology.

  Study EGAS50000000575

• Distinct immune cell infiltration patterns in PDAC exhibit divergent immune cell selection and immunosuppressive mechanisms

  Pancreatic ductal adenocarcinoma has a dismal prognosis. A comprehensive analysis of single-cell multi-omic data from matched tumour-infiltrated CD45+ cells and peripheral blood in 12 patients, and two published datasets, reveals a complex immune infiltrate. Patients have either a myeloid-enriched or adaptive-enriched tumour microenvironment. Lymphocyte enrichment is intrinsically linked with highly distinct B and T cell clonal selection, diversification, and differentiation. Using TCR data, we see the largest clonal expansions in CD8 effector memory, senescent cells, and highly activated regulatory T cells which are induced within the tumour from naïve cells. We identify pathways that potentially lead to a suppressive microenvironement, including targets of immunotherapy and checkpoints including TIGIT/PVR and SIRPA/CD47. PDAC patient tumors from the APACT clinical trial revealed that patients with myeloid enrichment had the shorter overall survival compared to those adaptive cell enrichment. We identify multiple therapeutic targets that should form the basis for rational design including boosting of B cell responses, targeting immunosuppressive macrophages, and specific Treg depletion approaches. The dataset is scRNA-seq data from PDAC patients.

  Study EGAS50000000726