4955 results for "*oma"

in 23.10 milliseconds.

• 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

• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

  Blog the-last-addition-to-the-list-of-clonal-evolution-studies-in-the-ega

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

  Blog drug-development-for-pediatric-cancers

• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• Methylation Biomarkers can Distinguish Pleural Mesothelioma from Healthy Pleura and other Pleural Pathologies

  Pleural mesothelioma (PM) is a rare cancer type. This study developed a methylation-based biomarker assay to distinguish PM from healthy pleura and other pleural conditions. By analyzing methylation data, 744 hypermethylated CpG sites specific to PM were identified and validated with high accuracy. Using the bisulfite-free IMPRESS technique, the assay was further validated in a diverse cohort, showing strong performance in distinguishing tumoral from non-tumoral samples and PM from pleural metastases. These findings support the assay’s potential as a robust diagnostic tool for PM.

  Study EGAS00001008153

• Pineoblastoma Single-Nuclei RNA-seq Data Access Committee (St. Jude)

  Committee responsible for reviewing and approving external access requests to controlled-access pediatric brain tumor transcriptomic datasets from St. Jude Children's Research Hospital, ensuring alignment with patient consent and institutional ethics policies.

  Dac EGAC50000000839

• Androgen activity in the normal male embryonic hindbrain drives lethal PFA ependymoma

  PFA ependymoma is an unusual infantile brain tumor with few somatic mutations, thought to be driven by epigenetic mechanisms. PFA ependymomas have a markedly higher incidence, and a worse prognosis in males as compared to female infants. Here we show that the cellular hierarchy of male PFA is less differentiated than female PFA. Androgen supplementation promotes the growth of PFA ependymoma. We conclude that androgen signaling in both the normal developing hindbrain, and PFA ependymoma are both necessary and sufficient to promote growth and delay differentiation.

  Study EGAS50000000507

• Whole Exome Sequencing of Non-Hodgkin Lymphoma Patients in Tabuk, Saudi Arabia

  This study presents whole exome sequencing (WES) data from 20 Non-Hodgkin Lymphoma (NHL) patients. Samples represent diverse histopathological subtypes including Diffuse Large B-Cell Lymphoma (DLBCL), Follicular Lymphoma, and other NHL variants. Both nodal and extranodal disease origins are represented. Sequencing was performed to investigate the genomic landscape of NHL in a Saudi Arabian patient cohort.

  Study EGAS50000001776

• Plasma cell‐free transcriptome profiling in chronic liver disease

  RNAseq data from plasma samples corresponding to a Grand Challenge Programme project to find biomarkers for liver disease, including NAFLD, NASH, Cirrhosis and Hepatocelullarcarcinoma. A template of the DTA and DAA files is available in the following zenodo repository https://doi.org/10.5281/zenodo.19047046.

  Dac EGAC50000000360

• DAC for "H3K27me3-mediated epigenetic repression regulates neuroblastoma development and contributes to biological heterogeneity"

  Dac EGAC00001003620

• Single-cell bisulfite-seq analyses of 1-year-old prospermatogonia and adult spermatogonial stem cell

  To examine the timing of de novo methylation during human male germ cell development, single-cell bisulfite sequencing was carried out on human germ cells. FACS-purified Prospermatogonia from three teratoma patients (1-year-0-month, 1-year-5-months, and 1-year-8-months) and spermatogonial stem cells from a 29-year-old obstructive azoospermia patient with normal spermatogenesis were analyzed. The three 1-year-old prospermatogonia exhibited average methylation levels of 41.4% (23.1-54.4%, 1-year-0-month), 53.1% (32.0-62.4%, 1-year-5-months), and 32.6% (10.2-54.7%, 1-year-8-months). In contrast, adult spermatogonia showed an average level of 75.7% (73.3-76.8%). Although teratoma may have influenced the developmental timing of prospermatogonia within the same testes, prospermatogonia across all 1-year-old samples remained in an intermediate phase of DNA methylation establishment.

  Study JGAS000887

• Analysis of Large Cell Neuroendocrine Carcinoma Expressing POU2F3 Using WGS

  Lung LCNEC (Large Cell Neuroendocrine Carcinoma) has a poor prognosis, and no effective treatment has yet been established. We have found that the tuft-cell marker POU2F3 is specifically expressed in some LCNEC cases. By performing Whole Genome Sequencing (WGS) on samples from 10 LCNEC patients, we aim to identify changes characteristic of LCNEC expressing POU2F3 and explore new classifications and treatment options for LCNEC.

  Study JGAS000784

• Whole genome sequencing, single-cell RNA sequencing, and ATAC sequencing of mesothelioma (patient, patient-derived xenograft and cell line)

  Malignant pleural mesothelioma is an aggressive pleural tumor with a poor prognosis, and elucidating its molecular mechanisms is essential for improving diagnosis and treatment. This study investigates key genes and pathways involved in tumor progression, with particular attention to the involvement of neutrophils in the tumor ecosystem of mesothelioma. We performed whole-genome sequencing and single-cell RNA sequencing (scRNA-seq) of one pleural mesothelioma tumor specimen, scRNA-seq of matched patient-derived xenograft tumors, scRNA-seq of mesothelioma-free pleural tissues from three patients, and assay for transposase-accessible chromatin using sequencing (ATAC-seq) of a patient-derived cell line.

  Study JGAS000859

• Single-cell bisulfite-seq analyses of 29-year-old prospermatogonia and adult spermatogonial stem cell

  To examine the timing of de novo methylation during human male germ cell development, single-cell bisulfite sequencing was carried out on human germ cells. FACS-purified Prospermatogonia from three teratoma patients (1-year-0-month, 1-year-5-months, and 1-year-8-months) and spermatogonial stem cells from a 29-year-old obstructive azoospermia patient with normal spermatogenesis were analyzed. The three 1-year-old prospermatogonia exhibited average methylation levels of 41.4% (23.1-54.4%, 1-year-0-month), 53.1% (32.0-62.4%, 1-year-5-months), and 32.6% (10.2-54.7%, 1-year-8-months). In contrast, adult spermatogonia showed an average level of 75.7% (73.3-76.8%). Although teratoma may have influenced the developmental timing of prospermatogonia within the same testes, prospermatogonia across all 1-year-old samples remained in an intermediate phase of DNA methylation establishment.

  Study JGAS000888

• Genomic subtypes and cellular phenotypes of high-grade endometrial carcinoma

  Based on the mechanism of carcinogenesis, endometrial cancer (EC) is classified into two major types, Type I and Type II. Type I EC is characterized by G1/G2 histology, accounting for about 80% of all uterine carcinomas. On the other hand, Type II EC, which often develops after menopause, is estrogen-independent and consists of serous and clear cell carcinomas. G3 EC is often classified as a Type II EC, but the pathogenesis is thought to be a mixture of estrogen-dependent and estrogen-independent carcinogenesis. We will conduct an integrative genomic analysis to clarify the pathogenesis of Type II EC and redefine its classification by combining genomic status with cell phenotypes reflected in gene expression profiles.

  Study JGAS000753

• Whole-exome sequencing of uterine carcinosarcoma in a young woman with HBOC (tumor-normal pair)

  This study deposits controlled-access human genomic data (tumor-normal whole-exome sequencing) from a patient with uterine carcinosarcoma and hereditary breast and ovarian cancer (HBOC) syndrome, to support reproducibility of reported genomic findings.

  Study JGAS000883

• Molecular Characterization of Large Cell Neuroendocrine Carcinoma of the Lung by Multilayered Omics Analysis

  Large cell neuroendocrine carcinoma (LCNEC) is a rare lung cancer type with a very poor prognosis. The underlying molecular features remain unclear. Here, we conducted a multi-omics analysis of 27 LCNEC cases along with 7 small cell lung carcinoma and aimed to propose new classification by extracting genomic and transcriptomic features in LCNEC, leading to the elucidation of the therapeutic approaches.

  Study JGAS000832

• Whole exome and ChIP sequencing of external auditory canal squamous cell carcinoma (EACSCC)

  We performed whole exome sequencing of the primary tumor tissues, peripheral blood mononuclear cells from an EACSCC patient as well as the cell line established from the primary tumor tissues. We performed ChIP sequencing of primary tumor tissues and noncancerous ear skin tissues from EACSCC patients as well.

  Study JGAS000645

• Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing

  Chromosomal translocations with immunoglobin (IG) loci are the classic drivers in a large subset of B-cell lymphomas. Detection of these translocations is important for confirmation of diagnosis and for prognosis and therapy decisions. Currently, molecular diagnosis of translocations in lymphomas is not addressed well by Next Generation Sequencing (NGS). The standard method for detection of translocations is Fluorescence In Situ Hybridization (FISH), which is labor-intensive, and can be difficult to interpret. There is a need for a robust technology that can be standardized. Targeted Locus Capture (TLC) selectively enriches and sequences entire genes based on the crosslinking of physically proximal sequences, and thereby enables complete sequencing of genes of interest, including detection of large structural variants. Because the technology is based on the crosslinking and fragmenting of DNA, it has particular advantages in the analysis of Formalin-Fixed, Paraffin-Embedded (FFPE) samples, in which DNA is inherently crosslinked and fragmented. In order to validate the FFPE-TLC technology as a novel approach for translocation detection in lymphoma samples, we have developed a panel assay containing genes with frequent translocations (MYC, BCL2, BCL6, IG loci). With this assay we have analyzed >140 lymphoma and control FFPE samples of variable input amounts and qualities that had previously been analyzed with FISH, and a subset also with standard targeted NGS. Good concordance with FISH results was observed for both translocation positive and negative samples. In 10 cases for which FFPE-TLC detected a relevant fusion and FISH had been called negative, discordance could be explained by higher sensitivity of FFPE-TLC or by inconclusive FISH results. In a specific case, FFPE-TLC detected a small-distance rearrangement on chromosome 3 that caused a BCL6 fusion but led to insufficient and therefore undetectable break-apart with FISH. Secondly, the FFPE-TLC approach was tested on a set of 19 B-cell lymphoma FFPE samples that had previously been analyzed using standard targeted NGS and FISH and was enriched for discordant results between these methods. FFPE-TLC-based NGS enables more robust translocation calling as the detection relies on broad sequencing coverage across the translocation partner rather than on breakpoint sequences only. In 3 cases, FFPE-TLC could proof false negative calls in standard targeted NGS due to breakpoints located in regions difficult to capture or to sequence. In 1 case, standard targeted NGS had made a false positive call on a breakpoint sequence that was shown to be caused by a small insertion rather than a genuine translocation. This study shows that FFPE-TLC promises to be a robust alternative for FISH analysis and standard targeted NGS procedures in lymphoma diagnostics and possibly in other cancers with frequent structural variants. The FFPE-TLC approach enables a single, DNA-based NGS test detecting both small mutations and translocations.

  Study EGAS00001004760

• Single cell atlas of large B-cell lymphoma

  Large B-cell lymphomas (LBCL) are clinically and biologically heterogeneous lymphoid malignancies, shaped by complex tumor and microenvironments that play a critical role in disease progression. There has been no direct and comprehensive single-cell characterization of tumor microenvironment in LBCL that simultaneously captures lymphoid, myeloid, and stromal populations across a sufficiently large cohort to reveal reproducible and biologically meaningful patterns. Here, we performed single-nucleus multiome profiling, coupled with bulk DNA and RNA sequencing, on 232 tumor and control biopsies to comprehensively map cell subpopulations of LBCL. Through this integrative approach, we identified Lymphoma Microenvironment Archetype Profiles (LymphoMAPs)—distinct, reproducible patterns defined by the co-occurrence of functionally specialized cell subsets. We further characterized the cell-cell communication pathways that shape these transcriptional phenotypes within archetypes. Importantly, we discovered associations between specific LymphoMAPs and clinical and molecular features of LBCL, including response to CD19 CAR T-cell therapy. Our study provides a valuable resource of lymphoid, myeloid, and non-hematopoietic cell states in LBCL and offers a framework for understanding how the abundance and functional state of cells within the tumor microenvironment may drive inter-patient variability in therapeutic outcome.

  Study EGAS50000001022

• Evolution of an adenomacarcinoma in response to selection by targeted kinase inhibitors

  Background - Adenocarcinomas of the tongue are rare and represent the minority (20-25%) of salivary gland tumors affecting the tongue. We investigated the utility of massively parallel sequencing to characterize an adenocarcinoma of the tongue, before and after treatment. Results - In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain. 1,078 genes exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A recurring metastasis possessed 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumours and 9 new somatic protein coding mutations. The observed mutations and amplif ications were consistent with therapeutic resistance arising through activation of the MAPK and AKT pathways. Conclusions - We conclude that complete genomic characterization of a rare tumour has the potential to aid in clinical decision making and identifying therapeutic approaches where no established treatment protocols exist. These results also provide direct in-vivo genomic evidence for mutational evolution within a tumor under drug selection and potential mechanisms of drug resistance accrual.

  Study EGAS00000000074

• ARID1A Mutations in Endometriosis-Associated Ovarian Carcinomas

  We have sequenced the whole transcriptomes of 18 ovarian clear-cell carcinomas and 1 ovarian clear-cell carcinoma cell line and found somatic mutations in ARID1A (the AT-rich interactive domain 1A [SWI-like] gene) in 6 of the samples. ARID1A encodes BAF250a, a key component of the SWI–SNF chromatin remodeling complex. We sequenced ARID1A in an additional 210 ovarian carcinomas and a second ovarian clear-cell carcinoma cell line and measured BAF250a expression by means of immunohistochemical analysis in an additional 455 ovarian carcinomas

  Study EGAS00000000075

• Multiple Myeloma treated with BCL2 inhibitor based treatment

  Whole Genome Sequencing from patients with multiple myeloma treated with BCL2 inhibitor based treatment.

  Study EGAS50000001479

• Familial Melanoma Sequencing

  In this experiment we have sequenced the exome of 15 individuals from eight families who have familial melanoma. By sequencing the exome we hope to be able to identify new genes that are associated with this disease.

  Study EGAS00001000017