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• Toxigenic Clostridium perfringens isolated from at-risk pediatric inflammatory bowel disease patients

  With the goal of studying mucosal-associated bacteria and products detrimental to inflammatory bowel disease (IBD) patients, we directly cultured bacterial communities from mucosal biopsies and examined for detrimental traits. Focusing on red blood cell lysis, a virulence trait, communities from 5 of 9 patients exhibited hemolytic activity. Clostridium perfringens was isolated from each hemolytic community, and whole-genome sequencing confirmed presence of hemolytic toxins – alpha toxin in all 5 strains, perfringolysin O (PFO) in 4 strains, alveolysin in 2 strains – and absence of enterotoxins. In vitro cytotoxicity experiments demonstrated strain supernatants were toxic to various cell types located beneath the intestinal epithelial barrier, including endothelial, neuroblasts, and neutrophils, while impact on epithelial cells was less pronounced. These findings suggest C. perfringens may be damaging particularly when intestinal barrier integrity is compromised, such as in IBD patients. Further characterization using purified toxins and genetic insertion mutants confirmed PFO toxin was sufficient for cell toxicity. C. perfringens supernatants also induced activation of neuroblast and dorsal root ganglion (DRG) neuron cells in vitro, suggesting C. perfringens in inflamed mucosal tissue may directly contribute to abdominal pain, a frequent IBD symptom. Strikingly, C. perfringens was detected in biopsies of 8 of 9 pediatric patients while not in all corresponding stool samples, and in other datasets, C. perfringens was in stool samples of IBD adults (18.7-27.1%) much more frequently versus healthy (5.1%). Our findings showcase C. perfringens may have an important pathogenic impact on IBD patients. Similar to Clostridioides difficile, routine monitoring of C. perfringens and PFO toxins in patients may be beneficial.

  Study EGAS50000000334

• Linking genes, genomic instability and molecular subgroups in medulloblastoma

  Brain tumors are the second most common pediatric cancer and carry the highest mortality rates in this age group. Medulloblastoma is the most frequent malignant brain tumor of childhood. Recent studies indicate that medulloblastoma comprises at least four sub-entities (SHH-signaling, WNT-signaling, Group-C, Group-D) that differ in molecular alterations, cell of origin, clinicopathological features and outcome. Further characterization of the entire spectrum of genomic alterations underlying the formation of these distinct groups is urgently needed to identify diagnostic and prognostic biomarkers for clinical management and uncover novel therapeutic targets.

  Study EGAS00001000085

• METABRIC: Data from Batra et al (2021); DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation

  DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, RRBS-based profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, the study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

  Study EGAS00001004327

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from cognitively healthy individuals exposed to traffic-related ultrafine particles (UFPs) for 24h and 72h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD00001011317

• Dynamics of sequence and structural cell-free DNA landscapes in small-cell lung cancer

  Patients with small-cell lung cancer (SCLC) have an exceptionally poor prognosis, calling for improved real-time non-invasive biomarkers of therapeutic response. We performed targeted error-correction sequencing on 171 serial plasmas and matched white blood cell (WBC) DNA from 33 patients with metastatic SCLC who received systemic treatment with chemotherapy or immunotherapy-containing regimens. Tumor-derived sequence alterations and plasma aneuploidy were evaluated serially and combined to assess changes in total cell-free tumor load (cfTL). Longitudinal dynamic changes in cfTL were monitored to determine circulating cell-free tumor DNA (ctDNA) molecular response during therapy. Combined tiered analyses of tumor-derived sequence alterations and plasma aneuploidy allowed for assessment of ctDNA molecular response in all patients. Molecular responses captured the therapeutic effect and long-term clinical outcomes in a more accurate and rapid manner compared to radiographic imaging. Patients with sustained molecular responses had longer overall (log-rank p=0.0006) and progression-free (log-rank p<0.0001) survival, with molecular responses detected on average 4 weeks earlier than imaging. ctDNA analyses provide a rapid approach for the assessment of early on-therapy molecular responses and have important implications for the management of patients with SCLC, including the development of improved strategies for real-time tumor burden monitoring.

  Study EGAS00001006831

• Admixture histories of São Tomé e Príncipe.

  Genotyping datasets 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 The genotype data corresponds to 2,104,148 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 97 volunteer participants sampled on São Tomé e Príncipe, family unrelated at the 2nd degree based on population genetics analyses. In particular, the dataset is composed of 95 individual samples collected on São Tomé and 2 collected on Príncipe. SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38.

  Dataset EGAD50000001348

• Novel driver variants in the histone 3.3 genes, H3F3A and H3F3B, define bone and cartilage cancer sub-types

  A selection of human cancers harbours somatic driver mutations in genes encoding histones, most notably childhood brain tumours with K27M substitutions of the histone 3.3 gene, H3F3A. We performed whole genome sequencing of the benign cartilage tumour, chondroblastoma, and targeted sequencing of histone 3.3 genes, H3F3A and H3F3B, in seven further skeletal tumour types. We identified an exceptionally high prevalence of novel histone 3.3 driver mutations at glycine 34 and at lysine 36. Histone 3.3 gene mutations were found in 91% in giant cell tumours of bone (48/53), mainly H3F3A G34W variants, and in 92% of chondroblastoma (73/79), predominantly K36M mutations in H3F3B. H3F3B is paralogous to the cancer gene H3F3A. However, H3F3B driver variants have not previously been reported in human cancer. Our observation demonstrate remarkable tumour-specificity of mutations, with respect to which histone 3.3 gene and residue is mutated, indicating that the advantage these mutations confer is tumour dependent. Moreover, tumour-specific mutation of H3F3A and H3F3B suggests, that although both genes encode identical proteins, they are likely non-redundant and employed differentially during skeletal development.

  Dataset EGAD00001000646

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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.

  Dataset EGAD00001006427

• Drug Signatures for Prediction and Mitigation of Toxicity

  The overall goal of the drug signatures for prediction and mitigation of toxicity study is to use genomic and proteomic high-throughput measurements as the basis for computational analysis that integrates network analyses with structural constraints and dynamical models in multiple cell types to identify signatures that predict toxicity induced by 55 FDA-approved chemotherapeutic drugs and potential mitigation of this toxicity. Specifically, we have recruited and pre-screened healthy individuals to be included in our study. Ninety six male and female individuals that satisfied the initial pre-screening for the study and their sex, age, race/ethnicity recorded through an enrollment questionnaire were consented. Eighty five underwent a formal and thorough medical health screening. The evaluation involved assessment of all inclusion and exclusion criteria, a full medical history, measurement of weight, height, waist and hip circumference, heart rate, blood pressure, respiratory rate, and oxygen saturation, a physical exam and an electrocardiograph (ECG). Blood was drawn for analysis of clinical relevant parameters. A pregnancy test was included for female participants. All blood draws and pregnancy tests were sent to a certified clinical laboratory for clinical analysis. Of the 85 subjects that were screened 42 (48.3%) were deemed eligible for final inclusion. Of these 42, one declined to undergo skin biopsy and/or venesection and one subject didn’t show up for the scheduled biopsy, leaving 40 clinically healthy subjects on which a skin biopsy and venesection was performed. Fibroblast lines were established from the skin biopsies. Induced pluripotent cells (iPSC) were generated from the established fibroblast lines of these 40 clinically healthy racially diverse male and female study participants who ranged in age from 22 and 61 years through reprogramming using either the mRNA or Sendai-virus methods. One clone from each of the 40 iPSC line was fully characterized for normal karyotype, short-tandem repeat matching to the original fibroblast line (authentication), pluripotency by select pluripotent marker expression via immunocytochemistry and by mRNAseq-based PluriTest analysis, and whole-genome sequencing.

  Study phs002088

• Osteosarcoma WGS on multiple tissue samples from six patients

  Osteosarcoma is a primary bone tumor that exhibits a complex genome characterized by gross chromosomal abnormalities. Osteosarcoma patients often develop metastatic disease, resulting in limited therapeutic options and poor survival rates. To gain knowledge on the mechanisms underlying osteosarcoma heterogeneity and metastatic process, it is important to obtain a detailed profile of the genomic alterations that accompany osteosarcoma progression. Therefore, in this study we performed WGS on multiple tissue samples from six patients with osteosarcoma, including the treatment naïve biopsy of the primary tumor, resection of the primary tumor after neoadjuvant chemotherapy, local recurrence and distant metastases.

  Dataset EGAD50000000475