5707 results for "canc*"

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• Evaluation of novel therapies using primary cultured gynecological cancer cells and search for predictors of efficacy

  The objective of this study is to establish an optimal method to evaluate the anti-tumor efficacy and biological activity of the novel therapies under investigation in our department using cancer tissues and cells derived from patients with gynecological malignancies in vitro and to evaluate them in practice. This research will contribute to the development of new treatments for gynecological cancer.

  Study JGAS000809

• Transcriptome sequencing of human colon organoid after co-cultivation with Bifidobacterium longum

  The large intestine has a dense milieu of indigenous bacteria, generating a complex ecosystem with crosstalk between individual bacteria and host cells. In vitro host cell modeling and bacterial interactions at the anaerobic interphase have elucidated the crosstalk molecular basis. Although classical cell lines derived from patients with colorectal cancer including Caco-2 cells are used, whether they adequately mimic normal colonic epithelial physiology is unclear. To address this, we performed transcriptome profiling of Caco-2 and Monolayer cells derived from healthy Human Colonic Organoid (MHCO) cultured hemi-anaerobically. Coculture with the anaerobic gut bacteria, Bifidobacterium longum subsp. longum differentiated the probiotic effects of test cells from those of physiologically normal intestinal and colorectal cancer cells. We cataloged non- or overlapping gene signatures where gene profiles of Caco-2 cells represented absorptive cells in the small intestinal epithelium, and MHCO cells showed complete colonic epithelium signature, including stem/progenitor, goblet, and enteroendocrine cells colonocytes. Characteristic gene expression changes related to lipid metabolism, inflammation, and cell-cell adhesion were observed in cocultured live Bifidobacterium longum and Caco-2 or MHCO cells. B. longum-stimulated MHCO cells exhibited barrier-enhancing characteristics, as demonstrated in clinical trials. Our data represent a valuable resource for understanding gut microbe and host cell communication.

  Study JGAS000740

• Application of targeted long-read methylation sequencing to dissected lung cancer tissues

  To investigate DNA methylation patterns within the tumor microenvironment, multiple regions were dissected from fresh-frozen sections of two lung adenocarcinoma specimens using the Millisect system. These regions were annotated based on spatial transcriptome data. DNA samples extracted from these regions were subjected to targeted long-read methylation sequencing using t-nanoEM. To establish a control dataset, short-read whole-genome sequencing (WGS) was performed on the tumor and normal parts, and long-read WGS was performed on the tumor part.

  Study JGAS000757

• Prevalence of rare pathogenic variants in cancer-predisposing genes among Japanese advanced prostate cancer patients.

  The prevalence of rare pathogenic variants in cancer-predisposing genes including those associated with DNA repair remains unknown among Japanese patients with advanced prostate cancer. This study was designed to elucidate the prevalence of pathogenic variants in 27 known cancer-predisposing genes and to explore the prognostic significance of the variants identified.

  Study JGAS000509

• Pilot study towards the development of a Companion/Complimentary Diagnosis platform using liquid biopsy with cfDNA for immune checkpoint inhibitor therapy in advanced urothelial cancer

  Preliminary analysis was conducted to develop a cfDNA-based platform capable of predicting gene mutation profiles, TMB, gene expression profiles (molecular subtype diagnosis), and immunohistochemical findings (PD-L1 expression) using the primary lesion tissue of bladder cancer and upper urinary tract epithelial cancer, verifying the feasibility of such development.

  Study JGAS000714

• CINECA_synthetic_cohort_ita_ingestion_test

  Please note: This synthetic data set (with cohort “participants” / ”subjects” marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk\n\nThis dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. \nThe genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.

  Dataset EGAD50000000369

• Aberrant EZHIP Expression Drives Tumorigenesis in Osteosarcoma

  Study EGAS00001007531

• CLL Genome

  The Chronic Lymphocytic Leukemia (CLL) Genome Project aims to identify genetic alterations involved in the development and progression of the CLL, which are still unknown, with the objective of generating a comprehensive catalogue of genetic alterations in 500 independent tumours. The CLL Genome Project, as a contributing member of the International Cancer Genome Consortium (ICGC), has the purposes of creating diagnostic tools, discovering therapeutic targets and developing new strategies that will allow a customized therapy for CLL in order to make it more precise and effective. This study consists of two datasets. EGAD00001000023 described in the Nature paper (2011), Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia, and the dataset EGA00001000044 & & EGAD00001000083 described in the Nature (2011) paper, Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia.Additional data generated within the ICGC-CLL genome project can be found in studies EGAS00001000374 and EGAS00001001306

  Study EGAS00000000092

• Genentech Small Cell Lung Cancer (SCLC) Screen

  Exome capture, RNA-Seq, whole genome sequencing of set of Small Cell Lung Cancer samples.

  Study EGAS00001000334

• Genomic and Transcriptomic Profiling of Colorectal Cancer in Swedish Patients

  My descriptionThis study investigates the genomic and transcriptomic landscape of colorectal cancer (CRC) in Swedish patients to identify molecular biomarkers associated with disease progression, treatment response, and survival outcomes. A total of 350 patients diagnosed with CRC between 2018 and 2023 were recruited from three Swedish hospitals: Lund University Hospital, Karolinska University Hospital, and Sahlgrenska University Hospital. Matched tumor tissue and blood samples were collected from all participants after obtaining informed consent. Whole-genome sequencing (WGS) was performed on blood-derived DNA to identify germline variants, while RNA-seq analysis of tumor tissues provided transcriptomic profiles. In addition, targeted panel sequencing was carried out for selected cancer-related genes to confirm findings from the WGS data.

  Study EGAS50000000158

• Whole-Genome and Transcriptomic Data from Colorectal Cancer Patients and Matched Healthy Controls in Sweden

  This dataset contains whole-genome sequencing (WGS) and RNA-seq data generated from tumor samples, matched blood samples, and healthy control samples collected from 350 Swedish individuals between 2019 and 2023. Tumor biopsies were obtained from colorectal cancer (CRC) patients, while control samples were collected from age- and sex-matched healthy volunteers with no history of CRC. For tumor samples, paired-end RNA-seq was performed to capture gene expression profiles, and WGS was carried out on DNA extracted from both tumor tissue and matched blood samples to identify somatic and germline variants. For controls, WGS was performed on peripheral blood DNA to provide baseline genomic profiles for comparison. The resulting dataset includes: RNA-seq files in FASTQ format (~2.8 TB total) WGS files in CRAM format (~4.2 TB total) Variant calls in VCF format (~150 GB) Clinical and sample metadata in CSV format Data are stored in FEGA Sweden under controlled access. Access requests will be reviewed by the Lund University RDO as the data controller. Ethical approval was obtained from the Swedish Ethical Review Authority (Dnr: 2023-01234).

  Dataset EGAD50000000155

• DNA Methylation and Microbiome Profiles from Colorectal Cancer Patients and Healthy Controls

  This dataset contains DNA methylation data and gut microbiome profiles derived from tumor biopsies, matched blood samples, and stool samples collected from 200 Swedish participants (150 colorectal cancer patients and 50 healthy controls) between 2020 and 2023. For DNA methylation profiling, genomic DNA was extracted from tumor tissues and blood samples using the Qiagen AllPrep DNA/RNA Kit and analyzed with the Illumina Infinium MethylationEPIC BeadChip. This approach captures more than 850,000 methylation sites across the genome. In parallel, stool samples were collected prior to treatment, and microbial DNA was extracted using the Qiagen QIAamp Fast DNA Stool Kit. 16S rRNA gene sequencing was performed on the Illumina MiSeq platform to characterize the gut microbiome composition in patients and controls. The resulting dataset includes: Methylation array data in IDAT format (~120 GB total) Normalized methylation matrices in CSV format (~15 GB) 16S rRNA microbiome data in FASTQ format (~250 GB total) Microbiome abundance tables in TSV format (~2 GB) All data are stored in FEGA Sweden under controlled access, and access requests will be reviewed by the Lund University RDO as the data controller. Ethical approval was obtained from the Swedish Ethical Review Authority (Dnr: 2023-04567).

  Dataset EGAD50000000156

• Personalized Onco-Genomic Project for pediatric and adolescent patients in British Columbia

  This is an extension of the BC Cancer Agency's Personalized Onco-Genomics (POG) project to children and adolescents treated at BC Children's Hospital. The project provides access to whole genome and transcriptome sequencing, and integrated bioinformatics analyses, of relapsed, refractory or poor prognosis cancers with an aim to identify actionable variants that can inform clinical decision making.

  Study EGAS50000000433

• Integrative genomic analyses reveal androgen-driven somatic alteration landscape in early-onset prostate cancer

  Early-onset prostate cancer (EO-PCA) represents the earliest clinical manifestation of prostate cancer. To compare the genomic alteration landscapes of EO-PCA with "classical" (elderly-onset) PCA, we performed deep sequencing-based genomics analyses in eleven tumors diagnosed at young age, and pursued comparative assessments with seven elderly-onset PCA genomes. Remarkable age-related differences in structural rearrangement (SR) formation became evident, suggesting distinct disease pathomechanisms. Whereas EO-PCAs harbored a prevalence of balanced SRs, with a specific abundance of androgen-regulated ETS gene fusions including TMPRSS2:ERG, elderly-onset PCAs displayed primarily non-androgen-associated SRs. Data from a validation cohort of >10,000 patients showed age-dependent androgen receptor levels and a prevalence of SRs affecting androgen-regulated genes, further substantiating the activity of a characteristic "androgen-type" pathomechanism in EO-PCA.

  Study EGAS00001000400

• Integrative sequencing reveals alterations in untreated and castration resistant prostate cancer

  We report the integrative sequencing of genomic, transcriptomic and DNA methylation changes in 28 untreated (PC) and 13 castration resistant prostate cancers (CRPC). AR, TGF-β and WNT signaling pathways were altered in CRPCs. We identified two new fusion genes, TMPRSS2-SKIL and DOT1L-HES6. Fusion analysis in an independent cohort validated SKIL as a recurrent 3’ fusion partner and oncogene in prostate cancer. The HES6 fusion was found in an AR-negative CRPC, and HES6 overexpression in vitro led to androgen independent growth. A distinct DNA methylation signature was found for CRPC. Transcriptome assembly uncovered 128 previously unannotated prostate cancer associated transcripts, including the ERG regulated transcript TPCAT-10-36067 whose knockdown had a dramatic effect on the growth, invasiveness, and rate of apoptosis of prostate cancer cells.

  Study EGAS00001000526

• Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue

  Diffuse Intrinsic Pontine Glioma (DIPG) is a fatal brain cancer that arises in the brainstem of children with no effective treatment. To understand what drives DIPGs we integrated whole-genome-sequencing with methylation, expression and copy-number profiling.

  Study EGAS00001000575

• Frequent mutations in chromatin-remodelling genes in pulmonary carcinoids

  Pulmonary carcinoids are rare neuroendocrine tumours of the lung. The molecular alterations underlying the pathogenesis of these tumours have not been systematically studied so far. Here we perform gene copy number analysis (n¼54), genome/exome (n¼44) and transcriptome (n¼69) sequencing of pulmonary carcinoids and observe frequent mutations in chromatin-remodelling genes. Covalent histone modifiers and subunits of the SWI/SNF complex are mutated in 40 and 22.2% of the cases, respectively, with MEN1, PSIP1 and ARID1A being recurrently affected. In contrast to small-cell lung cancer and large-cell neuroendocrine tumours, TP53 and RB1 mutations are rare events, suggesting that pulmonary carcinoids are not early progenitor lesions of the highly aggressive lung neuroendocrine tumors but arise through independent cellular mechanisms. These data also suggest that inactivation of chromatinremodelling genes is sufficient to drive transformation in pulmonary carcinoids.

  Study EGAS00001000650

• Integrative genomic profiling of large-cell neuroendocrine carcinomas reveals distinct subtypes of high-grade neuroendocrine lung tumors

  Large-cell neuroendocrine lung carcinomas (LCNEC) have similarities with other lung cancers, but their precise relationship has remained unclear. We conducted comprehensive genomic (n=60) and transcriptomic (n=69) analyses of 75 LCNECs and identified two molecular subgroups: “type I LCNECs” with bi-allelic TP53 and STK11/KEAP1 alterations (37%), and “type II LCNECs” enriched for bi-allelic inactivation of TP53 and RB1 (42%). Despite sharing genomic alterations with adenocarcinomas and squamous cell carcinomas, no transcriptional relationship was found; instead LCNECs form distinct transcriptional subgroups with closest similarity to SCLC. While type I LCNECs and SCLCs exhibit a neuroendocrine profile with ASCL1high/DLL3high/NOTCHlow, type II LCNECs bear TP53 and RB1 alterations and differ from most SCLC tumors with reduced neuroendocrine markers, a pattern of ASCL1low/DLL3low/NOTCHhigh and upregulation of immune-related pathways. In conclusion, LCNECs are comprised of two molecularly defined subgroups, and distinguishing them from SCLC may allow for stratified targeted treatments for high-grade neuroendocrine lung tumors.

  Study EGAS00001000708

• Combined targeting of BRD4-associated Promoter Activation and NFKB Immunomodulation in ARID1A-mutated Gastric Adenocarcinoma

  Study EGAS00001006397

• RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at multi-region RRBS data from the TRACERx cohort selected for quantity of material available and high tumour purity

  Study EGAS00001006523

• Follicular Lymphoma Whole Genome and Transcriptome Sequencing

  Study EGAS00001006646

• Characterization of MCSP+ melanoma DCC and MelDCC lines

  To dissect the sequence of genotypic and phenotypic progression during early metastatic colonization, we searched for the earliest detectable disseminated cancer cells (DCC) and identified MCSP+ melanoma cells as strong candidates for metastasis founder cells (MFC) in lymph nodes. We isolated MCSP+ DCC from various stages of metastatic colony-formation, performed scRNA-seq and unravelled their phenotypic progression. Further we performed bulk sequencing on patient-derived DCC models (MelDCC) and showed that they exhibit an immunosuppressive activity on CD8 T cells.

  Study EGAS00001006702

• Characterization of chromatin accessibility in metastatic prostate cancer

  The development of resistance to second-generation AR-signaling inhibitors (ARSIs) and progression to metastatic castrate-resistant prostate cancer (mCRPC) represents a huge obstacle to the improvement of patients’ clinical outcomes. Lineage plasticity is a common mechanism that drives the development of mCRPC by changing chromatin conformation at regulatory elements affecting downstream gene activity. ATAC-seq is a popular technique that measures accessible chromatin regions. To better understand of potential epigenomic mechanisms of ARSI resistance in prostate cancer, in this study, we performed ATAC-seq on 70 mCRPC tissue biopsies from the SU2C/PCF West Coast Dream Team (WCDT) cohort.

  Study EGAS00001006698

• Genomic profiling of subcutaneous patient derived xenograft models of solid childhood cancer

  Study EGAS00001006710

• Childhood B-cell acute lymphoblastic leukemia genomic and transcriptomic data

  Study EGAS00001006863

• The Landscape of N-6 Methyladenosine in Primary Localized Prostate Cancer

  Study EGAS00001006925

• Multi-region RNA sequencing of tumour regions and tumour-adjacent normal lung tissue

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Study EGAS00001006517

• Discovery of cancer prognostic markers based on comparison of gene expression in colorectal cancer samples.

  Here, we analyse bulk mRNA-seq data derived from normal tissues adjacent to tumors (NATs) and tumour tissues of colorectal cancer (CRC), including 80 NAT samples and 80 tumour samples.

  Study EGAS00001005068

• Tumor-intrinsic expression of the autophagy gene Atg16l1 suppresses anti-tumor immunity in colorectal cancer

  The vast majority of colorectal cancer (CRC) patients fail to respond to immune checkpoint inhibitors (ICI). Understanding tumor-intrinsic determinants of immunotherapy resistance is critical to improve CRC patient outcomes. Here, we demonstrate that transcript levels of the core autophagy gene ATG16L1 are prognostic of poor outcome and predictive of ICI resistance in late-stage CRC. Deletion of Atg16l1 in murine CRC organoids markedly inhibited tumor growth in primary and metastatic niches in syngeneic hosts. ATG16L1 deficiency rendered CRC organoids more responsive to interferon (IFN) signaling and enhanced programmed cell death while decreasing tumor stem-like populations. IFN hypersensitivity consequently promoted cytotoxic anti-tumor immunity in vivo. In IMblaze370, a large phase III clinical trial of anti-PD-L1 in advanced metastatic CRC, low ATG16L1 levels identified patients with increased lymphocyte infiltration and improved outcome in a KRAS mutant setting. This work reveals autophagy as a clinically relevant immunosuppressive mechanism in CRC and provides a rationale for autophagy inhibition to boost immunotherapy responses in the clinic.

  Study EGAS00001005952

• The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge

  Tumors are composed of many different cell types, ranging from the normal tissue micro-environment, infiltrating immune cells and tumour cells. This group of tumour cells is itself intrinsically highly heterogeneous, driven by the rapid mutation rate of cancer cells to become a mixture of different sub-populations. These different types of cells, called subclones, have different sets of mutations in their DNA. Because some subclones evolve from others, many subclones share mutations. While it is increasingly easy to determine what mutations are present in the tumor, it remains very difficult to determine which subclones have which mutations. The task of assigning mutations to subclones is called subclonal reconstruction.The ICGC-TCGA DREAM Somatic Mutation Calling - Tumour Heterogeneity Challenge (SMC-Het) is an international effort to improve standard methods for subclonal reconstruction: to quantify and genotype each individual cell population present within a tumor. The goal of this challenge is to identify the best subclonal reconstruction algorithms and to identify the conditions that affect their performance.

  Study EGAS00001002092

• Global Anaplastic Thyroid Cancer Initiative

  Thyroid cancer is the most common endocrine malignancy. Most thyroid cancers are of the well-differentiated (non-aggressive) phenotype, and are almost always cured with standard treatments. In contrast, anaplastic thyroid cancer (ATC) is rare, accounting for only 1% of thyroid cancers, however it is perhaps the most lethal human malignancy with an average survival of 3 to 6 months. ATC presents with dramatic and rapid onset of airway and esophageal blockage with frequent spread to the lungs. Interestingly, 21–79% of ATCs have coexisting areas or a previous history of well-differentiated cancers. Although this suggests a progression from well-differentiated cancers to ATC, to date there is little molecular conformation that such a progression exists versus de novo generation of ATC. As ATC is extremely rare and most cases are inoperable, there are a paucity of tissue samples for study at any one center. The Global Anaplastic Thyroid Cancer Initiative (GATCI) aims to unite international institutions in order to pool samples (ATC with or without a paired well-differentiated component) for a comprehensive analysis of the genomic landscape of this disease.

  Study EGAS00001002234

• Molecular Subtype-specific Biomarkers Improves Colorectal Cancer Prognostication

  Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC according to natural molecular subtypes, however, this strategy is not yet able to provide clinicians with improved tools for decision-making. We here present an extended framework for CRC stratification that specifically aims to improve patient prognostication. Using transcriptional profiles from 1,100 CRCs, including a novel set of >300 samples, we identify novel cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the microbiome. Notably, our subtyping strategy allowed identification of novel archetype-specific prognostic biomarkers that provided information beyond and independent of UICC-TNM staging, MSI-status and consensus molecular subtyping. The results illustrate that our extended subtyping framework, combining subtyping and subtype-specific biomarkers, could contribute to improved patient prognostication and may form a strong basis for future studies.

  Study EGAS00001002376

• 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

• The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  High-grade serous ovarian cancer exhibits extensive intratumoral heterogeneity coupled with widespread intraperitoneal disease. Despite this, metastatic spread of tumor clones is non-random, implying the existence of local microenvironmental factors that shape tumor progression. We interrogated the molecular interface between tumorinfiltrating lymphocytes (TIL) and cancer cells in 143 samples from 21 patients using whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T- and B-cell receptor sequencing. We identify 3 immunologic response categories, which frequently co-exist within individual patients. Furthermore, epithelial CD8+ TIL were inversely associated with malignant cell diversity, evidenced by subclonal neoepitope elimination and spatial tracking between tumor and T-cell clones. Intersecting mutational signatures and immune analysis showed that foldback inversion genomic aberrations lead to worse outcomes even in the presence of cytotoxic TIL (n=433). Thus, regional variation in immune contexture mirrors the pattern of intraperitoneal malignant spread, provoking new perspectives for treatment of this challenging disease.

  Study EGAS00001002839

• Combined gene expression and digital pathology identifies molecular mediators of T cell exclusion and immune suppression in ovarian cancer

  Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on a large ovarian tumour cohort, we develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFb and activated stroma. Furthermore, we identify TGFb as a key mediator of T cell exclusion. TGFb reduces MHC-I expression in ovarian cancer cells in vitro; TGFb also activates fibroblasts and induced extracellular matrix (ECM) production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFb may represent a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

  Study EGAS00001003487

• Genomic and transcriptomic landscape of aggressive thyroid cancer

  Molecular characteristics of anaplastic thyroid cancer (ATC) and advanced differentiated thyroid cancers (DTCs) have not been fully elucidated. In this study, we applied various types of massively-parallel sequencing technology to 113 advanced TCs, including 27 ATCs and 86 advanced DTCs, to reveal their genomic and transcriptomic characteristics.

  Study EGAS00001003540

• Cancer and germline exomes consisting of FASTQ paired-end reads from melanoma and lung cancer samples

  Efforts to precisely identify tumor human leukocyte antigen presented peptides (HLAp) capable of mediating T cell based tumor rejection still face important challenges. Recent reports suggest that non-canonical cancer HLAp could be immunogenic but their identification requires highly sensitive and accurate mass-spectrometry (MS)-based proteogenomics approaches. Here, we present a MS-based analytical pipeline that can precisely characterize the non-canonical HLAp repertoire, incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLAp. Albeit often at low levels and in distinct subpopulations of cells, numerous non-canonical HLAp are shared across tumors. This analytical platform holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.

  Study EGAS00001003723

• The WID-CIN test identifies women with, and at risk of, cervical intraepithelial neoplasia grade 3 and invasive cervical cancer (CIN3+)

  We analysed DNA methylation at >850,000 CpG sites across the genome using the Illumina EPIC array in a total of 1,254 cervical liquid-based cytology samples from cases of screen-detected histologically verified CIN1-3+ (98% hrHPV-positive) and population-based control women free from any cervical disease (100% hrHPV-positive). We developed the WID-CIN-test which is a DNA methylation signature consisting of 5,000 CpG sites.

  Study EGAS00001005078

• Immunogenomic landscape of hematological malignancies

  We integrated over 8,000 transcriptomes and over 2,000 samples with multilevel genomic data of hematological cancers to investigate how immunological features are linked to cancer subtypes, genetic and epigenetic alterations, and patient survival. For more detailed follow-up analyses in acute myeloid leukemia (AML), single-cell RNA sequencing was performed on 8 AML bone marrow samples at diagnosis to profile the phenotypes of blasts and infiltrating immune cells in different disease subtypes.

  Study EGAS00001004444

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  In many areas of oncology, we lack sensitive tools to track low burden disease. While cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low disease burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and post-operative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance, and empowering treatment optimization in low-disease burden oncology care

  Study EGAS00001004406

• The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

  Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

  Study EGAS00001004518

• Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer (NABUCCO Cohorts 1 and 2)

  Study EGAS00001004521

• Whole genome, transcriptome and methylome profiling enhances actionable target discovery in high-risk paediatric cancer

  Zero Childhood Cancer is a precision medicine program to benefit children with poor-outcome, rare, relapsed or refractory cancer. Utilising tumour and germline whole genome sequencing (WGS) and RNA sequencing (RNAseq) across 252 tumours from high-risk paediatric cancer patients, we identified 968 reportable molecular aberrations (39.9% in WGS and RNAseq, 35.1% WGS-only, 25.0% RNAseq-only). 93.7% of patients had at least one germline or somatic aberration, 71.4% had therapeutic targets and 5.2% had a change in diagnosis. WGS identified pathogenic cancer-predisposing variants in 16.2% of patients. In 76 CNS tumours, methylome analysis confirmed diagnosis in 71.1% and contributed to a change of diagnosis in two cases (2.6%). To date 43 patients have received a recommended therapy, 38 of whom could be evaluated. A small but encouraging proportion of 31% showed some evidence of clinical benefit. Comprehensive molecular profiling resolved the molecular basis of virtually all high-risk cancers, which in some cases has significant clinical impact.

  Study EGAS00001004572

• Patient-tailored design for selective co-inhibition of leukemic cell subpopulations

  The extensive primary and secondary drug resistance in many cancer types requires rational approaches to design personalized and selective combinatorial therapies that do not only show synergistic effect in overall cancer cell killing but also result in minimal toxic side effects on non-malignant cells. To address the combinatorial explosion in the number of relevant combinations, we implemented a machine learning approach that prioritizes patient-customized drug combinations with a desired synergy-efficacy-toxicity balance by combining single-cell RNA-sequencing with ex vivo single-agent testing in scarce patient-derived primary cells. When applied to two diagnostic and two refractory AML patient cases, each with a different genetic background, our integrated approach accurately predicted patient-specific combinations that were shown to result not only in synergistic cancer cell co-inhibition but were also capable of targeting specific AML cell subpopulations that emerge in differing stages of disease pathogenesis or treatment regimens. Our data-driven approach provides an unbiased means for systematic identification of personalized combinatorial regimens that selectively co-inhibit leukemic cells while avoiding inhibition of non-malignant cells, and highlight the relevance of considering cell heterogeneity for personalized cancer therapy.

  Study EGAS00001004614

• Plasma ctDNA is a tumor tissue surrogate and enables clinical-genomic stratification of metastatic bladder cancer

  Study EGAS00001004615

• Accurate detection and classification of pediatric sarcomas based on cell-free DNA fragmentation patterns

  Sequencing of cell-free DNA in the blood of cancer patients (“liquid biopsy”) provides attractive opportunities not only for early diagnosis, but also for minimally invasive monitoring of treatment response and disease courses. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we developed an integrated genetic/epigenetic analysis method and applied it to 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. We achieved sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. We evaluated different metrics for cell-free DNA fragmentation analysis and developed LIQUORICE, a bioinformatic tool for detecting circulating tumor DNA based on tumor-specific chromatin structure. Using machine learning methods, we combined several fragmentation-based metrics into an integrated approach for liquid biopsy analysis tailored to cancers with low mutation rates but widespread epigenetic deregulation. Clinical associations highlighted the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. Additionally, we performed low coverage whole-genome-sequencing on 43 tumor biopsy samples from patients with Ewing sarcoma, in order to compare copy number aberrations detected in cell-free DNA and biopsy samples of the same patients. For validation of the epigenetic signatures inferred from cell-free DNA, we further performed reduced representation bisulfite sequencing (RRBS) on 38 matched biopsy samples from patients with Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent somatic mutations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.

  Study EGAS00001005127

• Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

  This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

  Study EGAS00001004942

• The WID-EC test for the detection and risk prediction of endometrial cancer

  Study EGAS00001005033

• The DNA methylome of cervical cells and risk of ovarian cancer

  Study EGAS00001005045

• The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

  A surrogate marker based on the epigenome that captures these components in easily accessible epithelial tissue could potentially identify women at risk. The WID-BC-index identifies women with breast cancer based on a DNA methylation signature derived from cervical smear samples.

  Study EGAS00001005055