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• Development of New Diagnostics, Therapeutics, and Prevention Methods for Personalized Medicine Based on Comprehensive Cancer-Related Gene Exome Analysis and Information Analysis Using Cancer Specimens Stored in TMDU Biobank.

  Biobanked tumor samples are a valuable resource in real-world solid tumor research. Panel-based genomic profiling enables the identification of clinically significant alterations that inform personalized diagnostic and treatment decisions. This study aimed to characterize the genomic landscape of solid tumors collected through the TMDU Biobank by summarizing mutational, copy number, and gene fusion alterations in a large and diverse patient cohort. This dataset contains summary-level genomic information from 1,996 tumor samples analyzed by ACT Genomics and ACT med using the ACTOnco Comprehensive 440-Gene Cancer Panel. Data provided includes (1) gene-level mutation counts, (2) a summary of copy number alterations, and (3) a summary of detected fusion events. Clinical attributes such as ICD-10 codes, age group, sex, tumor mutational burden (TMB), and microsatellite instability (MSI) status were included at the aggregate level. Summary statistics were generated from three source tables (gene, sample, and copy number data) using standardized processing rules. Due to contractual and ethical considerations, individual-level mutation locations and raw sequence data are not included; only summary-level information is provided. This dataset will support future research in tumor-type-specific genomic patterns, molecular characterization of solid malignancies, and precision oncology.

  Study JGAS000863

• LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma

  Diffuse large B-cell lymphoma (DLBCL) is a biologically heterogeneous disease. Two genomic classification systems, LymphGen and DLBclass, are capable of reproducibly classifying single tumors into subtypes with prognostic relevance in the context of standard-of-care R-CHOP chemoimmunotherapy. Preliminary data from subgroup analyses of clinical trials suggest that the distinct biological features are targetable with drugs that exploit subtype-specific vulnerabilities, and large clinical trials are being designed to test this hypothesis. Although whole exome sequencing (WES) remains the gold standard for each of these classification systems, many laboratories may opt for smaller targeted sequencing panels that reduce costs associated with sequencing, data storage, and processing. Here, we describe the design and validation of a targeted sequencing panel (LySeqST) that captures the genomic features required specifically for LymphGen classification. We perform in silico and real-world validation vs. WES data and demonstrate that LySeqST can be used to accurately classify DLBCL tumors. In an unselected population-based cohort, we determine the real-world proportions and validate the prognostic relevance of LymphGen subtypes, confirming that only tumors expressing the dark zone gene expression signature are consistently associated with inferior outcomes. Our results support the use of LySeqST for accurate genomic classification of DLBCL.

  Study EGAS50000001601

• Whole-Genome Sequencing Suggests Schizophrenia Risk Mechanisms in Humans with 22q11.2 Deletion Syndrome

  Chromosome 22q11.2 microdeletions impart a high but incomplete risk for schizophrenia. Possible mechanisms include genome-wide effects of DGCR8 haploinsufficiency. In a proof-of-principle study to assess the power of this model, we used high-quality, whole-genome sequencing of nine individuals with 22q11.2 deletions and extreme phenotypes (schizophrenia, or no psychotic disorder at age >50 years). The schizophrenia group had a greater burden of rare, damaging variants impacting protein-coding neurofunctional genes, including genes involved in neuron projection (nominal P = 0.02, joint burden of three variant types). Variants in the intact 22q11.2 region were not major contributors. Restricting to genes affected by a DGCR8 mechanism tended to amplify between-group differences. Damaging variants in highly conserved long intergenic noncoding RNA genes also were enriched in the schizophrenia group (nominal P = 0.04). The findings support the 22q11.2 deletion model as a threshold-lowering first hit for schizophrenia risk. If applied to a larger and thus better-powered cohort, this appears to be a promising approach to identify genome-wide rare variants in coding and noncoding sequence that perturb gene networks relevant to idiopathic schizophrenia. Similarly designed studies exploiting genetic models may prove useful to help delineate the genetic architecture of other complex phenotypes.

  Study EGAS00001002344

• Host whole genome variations are associated with neurocognitive outcome in survivors of pediatric medulloblastoma

  Host whole genome analysis is a promising source of predictive information for long-term morbidity in cancer survivors. However, studies on genetic predictors of long-term outcome, particularly neurocognitive function following chemoradiation in pediatric oncology are limited. In the present study, we evaluated variations in host whole genome single nucleotide polymorphisms (SNPs) and their association with cognitive outcome. Whole-genome SNP analysis of host peripheral blood was conducted on 22 medulloblastoma long-term survivors, of whom 18 completed neuropsychological testing. First, unsupervised consensus clustering of the most variable SNPs within 409 genes involved in DNA repair was performed. Discrete variant groups were identified, although they were not associated with cognitive outcome, suggesting that variations in genes corresponding to a single functional group may be insufficient to predict long-term outcome alone. In support of this interpretation, unsupervised hierarchical clustering analysis using disease-associated gene variants by cognitive impairment status yielded two distinct variant clusters comprised of 36 variants, 34 of which were in noncoding regions. These findings illustrate for the first time that cognitively impaired survivors have a distinct variant profile compared to other medulloblastoma survivors. Future research in larger cohorts is needed to validate host genome predictors of cognitive impairment that may impact clinical management.

  Study EGAS00001002996

• Host pathogen interaction long read transcriptome

  Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

  Study EGAS00001006779

• DAC Admixture histories of São Tomé e Príncipe

  Contacts: Paul Verdu +33144057317 paul.verdu@mnhn.fr CNRS-MNHN-Université de Paris UMR7206 Eco-anthropology Jorge M. Rocha jrocha@cibio.up.pt CIBIO Short description The Data Access Committee for acess to genotype and sample information used in the article "Nested admixture during and after the Trans-Atlantic Slave Trade in the island of Sao Tome" by Ciccarella M et al.2025 ensures that data-access requests comply with the Informed Consent provided by donors, and with ethical and deontological guidelines with respect to privacy. Research sampling protocols followed the Declaration of Helsinki guidelines and written informed consent was obtained from all volunteer participants involved in the sampling in São Tomé e Príncipe. The study of the São Tomé e Príncipe sample was undertaken with the support and permission of the Provincial Government of the Ministry of Health of the Democratic Republic of São Tomé e Príncipe, and the Provincial Government of Príncipe. Research sampling protocols also followed the French laws of scientific research deontology (Loi n° 2016-483 du 20 avril 2016) and were approved by the French ethics committees and CNIL (Declaration n°1972648).

  Dac EGAC50000000437

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Dataset EGAD00001011048

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - SCC_CALRmutated ET

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016068

• Genomic evolution and natural history of myeloproliferative neoplasms on therapy - triple-negative-ET

  Philadelphia-negative myeloproliferative neoplasms are chronic blood neoplasms. Treatments control blood counts but disease can progress to myelofibrosis or acute myeloid leukaemia. We performed longitudinal whole-genome and targeted sequencing in 30 patients, integrating clonal dynamics with 7,986 blood counts and clinical histories. Distinct evolutionary patterns distinguished stable from progressive disease, with leukaemic transformation arising via TP53 loss, stepwise driver mutation acquisition within complex clones, or emergence of independent leukaemic clones. In contrast, stable disease showed long-term clonal equilibrium without new drivers. Phylogenetic analysis using 203 whole-genomes of haematopoietic colonies revealed age-appropriate polyclonal haematopoiesis in triple-negative essential thrombocythaemia and germline predisposition to thrombocytosis, supporting non-neoplastic origins. Therapy-associated mutagenesis was observed, including C>G mutations following azacitidine and characteristic T>A/T>G after hydroxycarbamide exposure in blood cells, although not in skin where UV damage predominated. These findings demonstrate progression is genomically encoded years in advance and support serial monitoring and further study of treatment-related mutagenesis.

  Dataset EGAD00001016066

• Whole Exome Sequencing of Chronic Lymphocytic Leukemia

  The somatic genetic basis of chronic lymphocytic leukemia (CLL), a common and clinically heterogenous adult leukemia, remains poorly understood. Massively parallel sequencing technology now provides a method for systematic discovery of genetic alterations that underlie disease, and for uncovering new therapeutic targets and biomarkers. In study version 2 we presented a dataset consisting of DNA sequencing from 169 CLL samples (with matched germline controls). Samples were collected from patients displaying a wide range of characteristics representing the broad clinical spectrum of CLL. Understanding the mutational landscape of CLL provides a starting point for systematic analyses to address fundamental questions in CLL, including how mutated genes alter cellular networks and phenotypes, and thereby contribute to disease heterogeneity. Intratumoral heterogeneity plays a critical role in tumor evolution. To define the contribution of DNA methylation to heterogeneity within tumors, we performed genome-scale bisulfite sequencing of >100 primary chronic lymphocytic leukemias (CLLs; data presented in study version 3). Compared with 26 normal B cell samples, CLLs consistently displayed higher intrasample variability of DNA methylation patterns across the genome, which appears to arise from stochastically disordered methylation in malignant cells. Transcriptome analysis of bulk and single CLL cells revealed that methylationdisorder was linked to low-level expression. Disordered methylation was further associated with adverse clinical outcome. We therefore propose that disordered methylation plays a similar role to that of genetic instability, enhancing the ability of cancer cells to search for superior evolutionary trajectories.

  Study phs000435