4955 results for "*oma"

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• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015712

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015713

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Acral Melanoma PDXs from the admixed Brazilian Population - Tumour and unfiltered PDX sample CRAM files - Whole exome sequencing data

  CRAM files containing the whole exome data for Tumours, and unfiltered Patient Derived Xenograft samples mapped to build GRCh38. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015740

• Acral Melanoma PDXs from the admixed Brazilian Population - Tumour VCF files with somatic SNV and INDELs - Whole exome sequencing data

  Raw, flagged and annotated VCF files with somatic calls made with CavEMan and Pindel for Acral Tumours. Variant effect prediction was run with Ensembl VEP v103.Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015741

• Acral Melanoma PDXs from the admixed Brazilian Population - Tumour and unfiltered PDX sample CRAM files - RNAseq

  Patient Derived Xenograft RNAseq sample CRAM files mapped to build GRCh38. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015742

• Acral Melanoma PDXs from the admixed Brazilian Population- Tumour RNA expression data - htseq count files

  Files containing the read counts obtained with obtained with HTSeq for all the genes in Ensembl v103 annotation for GRCh38 human reference genome. This dataset contains the files for all Tumour samples. Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015745

• Ancestry and somatic profile predict acral melanoma origin and prognosis – WXS

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015755

• Ancestry and somatic profile predict acral melanoma origin and prognosis – RNA

  Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, we characterise the genome and transcriptome of 123 acral melanoma tumours from 92 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower median number of structural variants. The tumours with activating BRAF mutations have a transcriptional profile more similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and quadruple wild-type samples (non BRAF/NRAS/NF1/KIT) differed from mutated samples in their structural genomic profile and overall and recurrence-free survival patterns. Transcriptional profiling defined three expression clusters; these characteristics were associated with recurrence-free and overall survival. We highlight potential novel low-frequency drivers, such as PTPRJ, NF2 and RDH5. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

  Dataset EGAD00001015756

• Genomics Define Malignant Transformation in Myeloma Precursor Conditions

  Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

  Dataset EGAD00001015768

• CcRCC_metabolic_heterogeneity

  Heterogeneity is a hallmark of clear cell renal cell carcinoma (ccRCC). In this study, hyperpolarized [1-13C]pyruvate MRI (HP-13C-MRI) was used to probe metabolic heterogeneity non-invasively in 6 ccRCC patients from which 58 tumor and healthy tissues biopsies were acquired postoperatively. MRI parameters were correlated with 146 metabolite concentrations and the expression of 2523 metabolic genes across 34 metabolic pathways. Using metabologram projections and pathway consensus scoring, several metabolic pathways were correlated with the metabolic MRI, including glycolysis, pentose phosphate pathway, and the TCA cycle. A simple thresholding approach applied to the imaging metrics was sufficient to provide meaningful metabolic pathway information. We also show that tissue metabolic heterogeneity increases in regions with higher pyruvate-to-lactate conversion on imaging. These results provide validation of the biological relevance of HP-13C-MRI and support the possibility of its clinical use to improve disease characterization, stratification, targeting of biopsies, and providing novel methods to monitor treatment response.

  Dataset EGAD00001015780

• A developmental cell atlas of the human thyroid gland

  Thyroid hormones are essential for health, but human thyroid development and cellular heterogeneity are poorly understood. We generated a high-resolution, spatiotemporal transcriptional atlas of human fetal thyroid, and examined its perturbations in trisomy 21 (T21), where aberrant thyroid development is associated with congenital hypothyroidism, and in papillary thyroid carcinoma (PTC). Normal tissue revealed two functional follicular cell states (fTFC1, fTFC2) with divergent PAX8 expression levels, persisting into adulthood. Additionally, the rare C-cell population was comprehensively profiled at single-cell resolution for the first time. T21 fetal thyroid was hypoplastic, with disrupted follicular morphology and altered expression of genes mediating cellular topology and extracellular matrix interactions. Finally, the transcriptional signals of both fetal follicular cell states were found to be perturbed in PTC. Overall, we defined a reference atlas for normal human fetal thyrocyte heterogeneity and provided novel insights into thyroid disorders.

  Dataset EGAD00001015783

• Dataset for ChIP and Transcriptomic sequencing of neuroblastoma tumor samples(hipo)

  This dataset contains ChIP and Transcriptomic sequencing of 32cneuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 4000 respectively.

  Dataset EGAD00001015808

• Dataset for H3K27me3 ChIP-seq data for neuroblastoma cell lines (Neuroblastoma_CL)

  Dataset for H3K27me3 ChIP-seq data of 31 neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015809

• Dataset for Transcriptomic sequencing data for neuroblastoma tumor samples

  Dataset Transcriptomic sequencing data of 42 neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 4000. The sequencing was always paired.

  Dataset EGAD00001015812

• Dataset for ChIP-seq data for neuroblastoma tumor samples(NB,Neuroblastoma)

  Dataset for H3K27me3 ChIP-seq data of neuroblastoma tumor samples. The sequencing was performed on Illumina HiSeq 2000 and Illumina HiSeq 2500

  Dataset EGAD00001015813

• Dataset for "Characterizing the cfDNA fragmentome in patients with hepatocellular carcinoma"

  The dataset includes 63 BAM files from Oxford Nanopore PromethION whole-genome sequencing, generated by base calling POD5 files with Dorado (super-accurate, modified base model v5.0.0_5mCG_5hmCG@v3) and aligning reads to the hg19 reference genome.

  Dataset EGAD00001015823

• Orphan_Tumour_Study___familial_neuroblastoma

  The aim of this study is to study the genomes of ultra rare childhood tumours

  Study EGAS00001002171

• Serial assessment of measurable residual disease in medulloblastoma liquid biopsies

  Nearly one-third of children with medulloblastoma, a malignant embryonal tumor of the cerebellum, succumb to their disease. Conventional response monitoring by imaging and cerebrospinal fluid (CSF) cytology remains challenging and a marker for measurable residual disease (MRD) is lacking. Here, we show the clinical utility of CSF-derived cell-free DNA (cfDNA) as a biomarker of MRD in serial samples collected from children with medulloblastoma (123 patients, 476 samples) enrolled on a prospective trial. Using low-coverage whole-genome sequencing, tumor-associated copy-number variations (CNVs) in CSF-derived cfDNA are investigated as an MRD surrogate. MRD is detected at baseline in 85% and 54% of patients with metastatic and localized disease, respectively. The number of MRD-positive patients decline with therapy, yet those with persistent MRD have significantly higher risk of progression. Importantly, MRD detection precedes radiographic progression in half who relapse. Our findings advocate for the prospective assessment of CSF-derived liquid biopsies in future trials for medulloblastoma.

  Study EGAS00001005592

• A tumor-associated photoreceptor signature unifies distinct central nervous system malignancies

  Pineoblastoma is a clinically aggressive childhood brain tumor composed of distinct molecular subgroups with divergent driver genes, demographics, and clinical outcomes. To identify developmental origins and mechanisms governing disease pathogenesis, we derive single-cell transcriptomes from pineal parenchymal tumors, aligning malignant cells with our atlas of pineal gland development to retrace cellular origins. Integrative computational analyses maps pineoblastoma origins to transient cycling pinealocyte progenitors during development. Lineage-specific perturbation of suspected drivers in the early pineal gland yields preclinical models representative of consensus molecular subgroups. Multi-omic characterization of patient tumors and these models uncovers a tumor-associated photoreceptor signature common to pineoblastoma, retinoblastoma, and Group 3 medulloblastoma. Transcriptional activity of this signature within respective cellular origins establishes a developmental basis for molecular similarities between entities. Photoreceptor signature constituents are selective dependencies across these anatomically distinct central nervous system malignancies, motivating future studies evaluating developmentally encoded programs of malignancy as potential therapeutic liabilities.

  Study EGAS50000001457

• Phased whole genome sequencing of 10 melanoma samples

  We have sequenced 10 melanoma samples using 10X linked reads technology to obtain phased whole genome sequence data. Using this data, we created diploid personalized genomes for each sample and aligned functional genomics data obtained from the same samples in order to find allele specific events (such as allele-specific binding and allele-specific chromatin accessibility).

  Study EGAS00001004136

• Genomic characterization of Malignant Pleural Mesothelioma.

  Genomic characterization of Malignant Pleural Mesothelioma using RNA-seq, Exome and Illumina 2.5 M array.

  Study EGAS00001001563

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• Bulk RNAseq gene expression of baseline tumors from metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)

  We examined tumors from a large cohort of patients with metastatic urothelial bladder cancer (mUC) and metastatic renal cell carcinoma (mRCC) treated with an anti-PD-L1 agent (atezolizumab) and found that high tumor IL8 gene expression was associated with worse overall survival (OS). We further identified the tumoral immune presence based on Teff signature. We found that high tumor IL8 expression continued to be associated with worse OS even in inflamed tumors in mUC and mRCC.

  Study EGAS00001004386

• Single cell RNA sequencing of relapsed/refractory multiple myeloma

  Study EGAS00001004805

• Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma

  Atezolizumab (anti–programmed death-ligand 1 [anti-PD-L1]) and bevacizumab (anti-vascular endothelial growth factor [anti-VEGF]) combination therapy has become the new standard of care in patients with unresectable hepatocellular carcinoma. However, potential predictive biomarkers and mechanisms of response and resistance remain less understood. We report integrated molecular analyses of tumor samples from 358 patients enrolled in the GO30140 phase 1b or IMbrave150 phase 3 trials who were treated with atezolizumab combined with bevacizumab, atezolizumab alone, or sorafenib. Pre-existing immunity assessed by high expression of CD274 (PD-L1 mRNA), T-effector signature, and intratumoral CD8+ T cell density were associated with response and better clinical outcomes with the combination treatment. Less clinical benefit was associated with high regulatory T cell (Treg) to effector T-cell ratio and high expression of oncofetal genes such as GPC3 and AFP. Improved outcomes from the combination vs atezolizumab alone appeared to be associated with high expression of KDR (VEGFR2), Treg, and myeloid inflammation signatures, indicating anti-VEGF may contribute by targeting these axes. These findings were further validated by transcriptome analysis of paired pre- and post-treatment biopsies, in situ analysis by multiplex IHC and digital pathology, and in vivo study of an immunogenic hepatocellular carcinoma mouse model. Our findings highlight that anti-VEGF therapy might augment antitumor immunity and enhance anti–PD-L1 immunotherapy by targeting VEGF-mediated angiogenesis, Treg proliferation, and myeloid cell inflammation. Furthermore, our study identified candidate biomarkers for predicting response and resistance to anti–PD-L1 and anti-VEGF combination therapy.

  Study EGAS00001005503

• Comprehensive Genomic Characterization of Refractory Multiple Myeloma Reveals a Complex Mutational and Structural Landscape Associated with Drug Resistance (H067)

  Outcome of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs) is still very poor. To elucidate the genetic landscape of relapsed/refractory MM (RRMM) we performed whole genome and transcriptome sequencing of 39 heavily pretreated RRMM patients with at least double refractoriness revealing complex structural changes and a high mutational load (H067/K08K). We found a median of 67 structural variants and 116 nonsynonymous exonic mutations per patient. Assessment of oncogenic drivers showed NRAS, BRAF, TP53, KRAS, SLC4A7, FAM46C, DIS3, RB1, KMT2C, MLLT4, EWSR1, HCFC2, and COPS3 as significantly mutated. We found multiple genomic regions with bi-allelic events affecting known tumor suppressor genes, most frequently TP53, RB1, and TRAF3. Supervised analysis of mutational signatures showed a major contribution of Cosmic signature 6 associated with deficiency in DNA mismatch repair and the ‘BRCAness’ signature which coincided with mutations in genes known to confer PARP inhibitor sensitivity. Recurrently mutated gene networks included genes with relevance for PI and IMiD activity, the latter including in particular members of the Cereblon and the COP9 signalosome complex. In conclusion, this comprehensive genomic characterization revealed a complex mutational and structural landscape in RRMM and highlights potential implications for therapeutic strategies.

  Study EGAS00001004363

• ENCORAFENIB COMBINED WITH BINIMETINIB FOR BRAFV600E-MUTATED RELAPSED/REFRACTORY MULTIPLE MYELOMA: THE PHASE II GMMG-BIRMA TRIAL (Hipo_K08K)

  Activating BRAF mutations are rare events in multiple myeloma but have been shown to be promising therapeutic targets in small case studies. This multicenter phase II trial assessed the efficacy and safety of the BRAF/MEK inhibitors, encorafenib and binimetinib, in patients with relapsed/refractory multiple myeloma (RRMM) carrying an activating BRAFV600E mutation. Twelve RRMM patients with a median of five prior lines of therapy were enrolled. The study met its primary endpoint with 10 patients achieving at least a partial response according to IMWG criteria (overall response rate 83.3%). Responses occurred rapidly within the first cycle and deepened over time. The median progression-free survival (PFS) was 5.6 months and overall survival was 55% at 24 months. Genomic profiling revealed RAS mutations and structural variants involving the BRAF locus to be drivers of resistance to BRAF/MEK inhibition in RRMM. This trial demonstrates the value of translationally driven clinical trials in selected patient populations.

  Study EGAS00001005973

• Failure of Differentiation of the Rhombic Lip Constitutes Medulloblastoma

  We used single-cell transcriptomics to study cells from the developing human cerebellum, and show that different molecular subgroups of medulloblastoma resemble distinct glutamatergic progenitors.

  Study EGAS00001005826

• Single-cell multi-omics of relapse/refractory multiple myeloma patients (Hipo K08K/H067/K43R)

  Therapy resistance in cancers is ingrained in complex clonal dynamics. While the major clonal population in a tumour might respond well to the employed intervention, minor clones will eventually mutate, consequently acquiring a selective advantage and drug resistance. Hence, to improve cancer therapy, it is crucial to understand the mechanisms behind clonal evolution. Here, we applied single-cell transcriptomics and epigenomics, as well as whole-genome sequencing to 15 patients with relapsed/refractory multiple myeloma (RRMM). By profiling longitudinal samples throughout varying treatment regimens, we were able to interrogate patterns of evolution across patients. In particular, by defining clones based on copy number aberrations (CNAs), we found evidence for the majority of clones being diminished but not fully eradicated during treatment.

  Study EGAS00001006538

• Whole-exome sequencing of HPV-negative HNSCC to identify pathway alterations

  This study applies whole-exome sequencing (WES) to characterize genomic alterations in HPV-negative head and neck squamous cell carcinoma. Tumors were analyzed to derive pathway-level alteration scores, enabling stratification into Hedgehog-high and Hedgehog-low groups. The genomic data were integrated with imaging, transcriptomic, and functional analyses to investigate tumor-intrinsic Hedgehog signaling. The study aims to identify molecular features associated with biologically distinct tumor subgroups.

  Study EGAS50000001550

• Multi-omics datasets (WES, RNA-seq) of mesothelioma MIST2 study, a phase II CDK4/6 (abemaciclib) clinical trial

  This study comprises 26 mesothelioma patients with whole exome and RNA sequencing, to to assess potential sensitivity to CDK4/6 inhibition in p16ink4A-negative mesothelioma.

  Study EGAS50000001823

• Multi-omics datasets (WES, RNA-seq) of mesothelioma NERO study, a phase II PARP inhibitor clinical trial

  Niraparib Efficacy in Patient With Unresectable Mesothelioma, NERO, this randomised phase II trial is designed to evaluating the efficacy of the PARP inhibitor Niraparib versus active symptom control.

  Study EGAS50000001825

• Comprehensive Characterization of Early Relapse and End-Stage Relapsed Refractory Multiple Myeloma (HIPO K08K/H067/H021+nonHIPO)

  Study EGAS00001007469

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

  In this project, genomic analyses of pediatric medulloblastoma samples, obtained through the international medulloblastoma consortium, will be performed. RNA and miRNA expression profiles of 1000 samples, representing all four subgroups (Wnt, Shh, Group C, and D), will be studied to identify novel subtypes within each subgroup. The resulting subtype-specific expression profiles will support the development of reliable and robust biomarkers to more accurately and reliably classify medulloblastomas for treatment in clinical trials. For that purpose, two assays will be developed: an antibody-based immunohistochemical assay and an orthogonal nucleic acid-based hybridization assay. Additional genomic DNA analysis of the 300 high risk subgroup cases will support the discovery of subgroup specific somatic mutations in order to inform current clinical trials of targeted therapies, and to identify genes and pathways already targeted in other diseases. Such therapies could be rapidly transitioned to Phase II trials in medulloblastoma. Furthermore, the discovery of somatic mutations could be used for developing as well as validating specific biomarkers. The project team will also try to identify risk factors that predispose children to this type of cancer.

  Study EGAS00001000273

• RNA sequencing dataset of of explants treated with PRX3 inhibitor thiostrepton in mesothelioma

  This dataset includes 66 RNA sequences datasets of mesothelioma explants under three conditions: baseline, untreated control and thiostrepton treatment.

  Dataset EGAD50000002650

• Transcriptome profiling of HNSCC treated with PD1/PDL1

  Immune checkpoint inhibitors have improved survival in several solid tumors, including head and neck squamous cell carcinoma (HNSCC). However, current use of PD-1/PD-L1 inhibitors relies on PD-L1 expression, which does not reliably predict patient response. Therefore, better predictive biomarkers are needed to identify which patients benefit from immunotherapy. Previous studies suggest that genomic and transcriptomic features may help predict treatment response. This study aims to integrate genomic, transcriptomic, and methylomic data from 31 patients with recurrent/metastatic HNSCC to identify new biomarkers of resistance to anti-PD-1/PD-L1 therapy.

  Dataset EGAD50000002506

• Whole genome sequencing of primary and metastatic Melanoma cases in an Australian cohort.

  Melanoma is the fourth most common cancer in Australia and the leading cause of cancer death in young adults. The Australian Melanoma Genome Project (AMGP) is analysing whole genomes from melanomas. We include the results of whole genome sequencing (WGS) for a number of datasets that include cutaneous, acral and mucosal melanoma subtypes.

  Study EGAS00001001552

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  Study EGAS00001007404

• Transcriptomic profiling of Hedgehog-high and Hedgehog-low HPV-negative HNSCC

  This study investigates transcriptomic differences between Hedgehog-high and Hedgehog-low HPV-negative head and neck squamous cell carcinoma (HNSCC). Tumors were stratified based on pathway-level genomic alteration scores and imaging-associated Hedgehog activity. RNA sequencing was performed on archival FFPE tumor samples to assess pathway activation and transcriptional programs associated with Hedgehog signaling. The dataset supports integrative radiogenomic and functional analyses of tumor-intrinsic signaling pathways.

  Study EGAS50000001549

• Neuroblastoma and adrenal gland single-cell study

  Neuroblastoma is a pediatric tumor of the developing sympathetic nervous system. However, the cellular origin of neuroblastoma remains to be defined. Here, we study single-cell transcriptomes of neuroblastomas and normal human developing adrenal glands at various stages of embryonic and fetal development. We define normal differentiation trajectories during adrenal medullary development and identify the cellular origin of neuroblastoma. Importantly, adrenergic and mesenchymal neuroblastomas with varying clinical phenotypes match different temporal states along normal differentiation trajectories, with the degree of differentiation corresponding to clinical prognosis.

  Study EGAS00001004388

• Anaplastic Large Cell Lymphoma Tumor Gene Expression Profiling

  Anaplastic large cell lymphoma tumor RNA-Seq

  Study EGAS50000001011

• Anaplastic Large Cell Lymphoma Gene Expression

  Anaplastic Large Cell Lymphoma Gene Expression Study

  Dataset EGAD50000001478

• Mayo Anaplastic Large Cell Lymphoma Gene Expression

  Dac EGAC50000000633

• Development of actionable molecular targets and/or biomarkers for prognostication and patient stratification in gynecological cancer based on whole-exome sequencing and epigenomic analysis

  We collected 157 oral MPA-treatment samples from 66 cases (53 endometrial hyperplasia from 31 cases, 19 atypical polypoid adenomyoma from 14 cases, 1 normal endometrium from 1 case, and 84 endometrial carcinoma from 53 cases) and matched normal tissues/whole blood. The purpose of this study is to develop actionable molecular targets and/or biomarkers for prognostication and patient stratification.

  Study JGAS000813

• Whole-genome sequencing of the parental tumor and established organoids from a patient with gastric-type cervical adenocarcinoma

  This study aims to evaluate the genetic characteristics of patient-derived organoids established from gastric-type cervical adenocarcinoma and to assess their similarity to the parental tumors using whole-genome sequencing.

  Study JGAS000796

• Pharmacogenomic landscape of patient-derived cells informs precision oncology therapy

  Outcomes of anticancer therapy vary dramatically among patients, which may be caused by the specific molecular alterations in each patient’s tumor. Precision oncology aims to apply optimal therapies for each tumor based on its molecular characteristics. We have established a resource reporting the genomic and transcriptomic profiles of 462 patient tumor-derived cells (PDCs) across 14 cancer types, together with responses to 60 targeted agents. Compared with long-term cultured cancer cell lines, PDCs better recapitulate the molecular profiles of the original tumors. Among other unreported associations, we identify molecular factors inducing resistance to EGFR inhibitors in glioblastoma, and we suggest repurposing ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, using a retrospective clinical study, we find that PDC-derived sensitivities can be used to predict patient responses.

  Study EGAS00001002515

• ICGC Oesophageal adenocarcinoma - pilot samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett's oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000559

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Oesophageal_adenocarcinoma

  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 (40X and 20X depth respectively). 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.

  Study EGAS00001003702