7154 results for "canc*"

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• Clinical Cancer Genomic Profiling by Three-Platform Sequencing of Whole Genome, Whole Exome and Transcriptome

  To evaluate the potential of an integrated clinical test to detect diverse classes of somatic and germline mutations relevant to pediatric oncology, we performed three-platform whole-genome (WGS), whole exome (WES) and transcriptome (RNA-Seq) sequencing of tumors and normal tissue from 78 pediatric cancer patients in a CLIA-certified, CAP-accredited laboratory. Our analysis pipeline achieves high accuracy by cross-validating variants between sequencing types, thereby removing the need for confirmatory testing, and facilitates comprehensive reporting in a clinically-relevant timeframe. Three-platform sequencing has a positive predictive value of 97-99%, 99% and 91% for somatic SNVs, indels and structural variations, respectively, based on independent experimental verification of 15,225 variants. We report 240 pathogenic variants across all cases, including 84 of 86 known from previous diagnostic testing (98% sensitivity). Combined WES and RNA-Seq, the current standard for precision oncology, achieved only 78% sensitivity. These results emphasize the critical need for incorporating WGS in pediatric oncology testing.

  Study EGAS00001002217

• Sequencing of liver cancer cell lines

  Liver cancer is a dreadful disease with limited therapeutic options. How to translate genomic findings into biomarkers and precision treatment is challenging. A large cell line-based platform was established, termed as Liver Cancer Model Repository. Heterogeneities in patients were faithfully recapitulated by 81 liver cancer cell lines at genomic and transcriptomic levels. This platform provides a rich resource and models to study cancer drivers and drug responses in liver cancer.

  Study EGAS00001002237

• Kidney_tumour_DNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002486

• The molecular landscape of colorectal cancer （5 cases）

  We performed whole-exome sequencing of tumor samples and adjacent normal mucosae from 5 patients to characterize the genetic alterations in china.

  Study EGAS00001002374

• Drug screening and whole genome sequencing of primary cells and cell lines from ovarian cancer patients to associate genomic aberrations with in vitro drug sensitivities

  Identifying drugs for cancers with poor prognosis like ovarian cancer (OC) is hindered by inappropriate cell models and the limitations of current viability assays. We developed an automated confocal microscopy-based live cell assay (DeathPro) that robustly de-convolves cell death and proliferation over time by employing a specific image processing strategy. Using DeathPro, we screened nine OC patient-derived cell lines and one normal cell line (HOSEpiC) with 22 drugs or combinations. Whole genome was performed to analyze if the cell lines harbor OC-typical genomic aberrations and to relate genomic features to drug sensitivities. Commonly observed alterations in OC patients like TP53 mutations and MYC or PI3KCA amplifications were absent in the normal cell line but frequently detected in the OC cell lines. Moreover, genome-derived homologous recombination deficiency (HRD) scores of the OC cell lines correlated with their responses to carboplatin, olaparib and DNA demethylation drugs. Overall, we propose an imaging-based platform to guide drug development and genome-drug sensitivity analysis.

  Study EGAS00001002239

• Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma

  Background: Cancer patients with advanced disease exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates sequencing data with functional assay data to develop patient-specific combination cancer treatments. Methods: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient’s epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient’s primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. Results Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). Conclusions These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

  Study EGAS00001003564

• Analysis of four key cell types (epithelial, fbroblast, myeloid and T cells)

  Alterations of the normal prostate epithelial cell genome trigger the emergence of carcinoma, however cancer-only analyses of genomic aberrations have resulted in little clinical translation. A deep understanding of the tumor microenvironment is likely to inform on key drivers of disease progression and novel therapeutic opportunities. We investigated the role of key cell types along disease progression, profiling the RNA abundance of 52 samples from 13 patients enriched for one of four key cell types, spanning a wide CAPRA-S risk score range. Using a novel differential transcription Bayes method, TABI, we avoided a priori patient stratification, and mapped transcriptional alteration events to specific risk scores. The developmental and cell-type resolution yielded a landscape of concurrent transcriptional alterations from the tumour microenvironment, including key hallmarks. These transcriptional signatures permitted the identification of a “high survival” patient cluster in an independent prostate cancer dataset. Most importantly, together with our integrated transcriptional analysis, differential tissue composition analysis provided evidence for a key role for monocytes and macrophages in prostate cancer progression and disease recurrence.

  Study EGAS00001003579

• Infant Glioma Molecular Subtype

  Infant gliomas have completely different clinical behavior than gliomas in children and adults. Low-grade tumors are more aggressive with a higher mortality rate, while high-grade tumors are more benign. However, we have little understanding of their biology and so cannot explain this behavior and what constitutes optimal clinical management. To solve this enigma, we performed a comprehensive genetic analysis of the largest cohort to date of infantile gliomas. We uncovered several important findings which dramatically change the management of these cancers. Infant hemispheric gliomas harbor unique alterations in ROS, ALK, MET and other genes found in adult carcinomas. Unlike in adults, they are typically the only alteration present and some of these tumors regress from high- to low-grade partially explaining their favorable clinical outcome. Midline gliomas harbor RAS/MAPK pathway mutations, progress rapidly, and do not respond to current chemoradiation approaches, partially explaining their poorer outcome. These data suggest that infant gliomas require different therapeutic approaches including early use of targeted therapies.

  Study EGAS00001003714

• The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR_Custom

  We took a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We grew these up into colonies, then whole genome sequenced each colony. Somatic mutations act as a unique barcode for each clone. We have designed a panel for targeted resequencing of the mutations that we find. We are now looking for these mutations in the peripheral blood, to see the dynamics of how HSCs contribute to the peripheral blood in health.

  Study EGAS00001002257

• Genome-wide cell-free DNA fragmentation in patients with cancer

  Cell-free DNA (cfDNA) in the blood provides a noninvasive diagnostic avenue for patients with cancer. However, characteristics of the origins and molecular features of cfDNA are poorly understood. We developed an approach to evaluate fragmentation patterns of cfDNA across the genome and found that cfDNA profiles of healthy individuals reflected nucleosomal patterns of white blood cells, while patients with cancer had altered fragmentation profiles. We applied this method to analyze fragmentation profiles of 236 patients with breast, colorectal, lung, ovarian, pancreatic, gastric, or bile duct cancers and 245 healthy individuals. A machine learning model incorporating genome-wide fragmentation features had sensitivities of detection ranging from 57% to >99% among the seven cancer types at 98% specificity, with an overall AUC of 0.94. Fragmentation profiles could be used to identify the tissue of origin of the cancers to a limited number of sites in 75% of cases. Combining our approach with mutation based cfDNA analyses detected 91% of cancer patients. The results of these analyses highlight important properties of cfDNA and provide a proof of principle approach for screening, early detection, and monitoring of human cancer.

  Study EGAS00001003611

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Study EGAS00001003661

• Most HCCs in Taiwan show the mutational signature of aristolochic acid

  Plants in the genus Aristolochia contain the mutagen aristolochic acid (AA) and have been widely used in traditional medicines and for weight loss. AA binds covalently to genomic DNA and induces a highly distinctive mutational signature. While AA involvement in urinary-tract cancers in Taiwan is known, the possible role of AA in hepatocellular carcinomas (HCCs) in Taiwan has not been examined. Here, we whole-exome sequenced 98 unselected HCCs from Taiwan and analyzed the mutational signatures for evidence of AA mutagenesis. Remarkably, more than 78% of HCCs showed strong evidence of AA mutagenesis, often associated with high mutation burdens. Non-synonymous mutations in genes known to be HCC driver genes were detected. Importantly, we elucidated the potential of immunotherapy in this cohort of liver cancer patients.

  Study EGAS00001002301

• The Ovarian Cancer Association Consortium OncoArray genome-wide association study

  A custom Illumina genotyping array, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis as described in PMID:27697780.The array was used to genotype ovarian cancer cases and controls from multiple studies participating in the Ovarian Cancer Association Consortium, of which 54,747 passes QC.An initial principal components analysis was carried out using a method described in PMID:27697780 to assign subject to intercontinental ancestry groups: “European”, “African”, “Asian” and "Other". Within ancestry principal components analysis was carried using a set of ~33k unlinked markers. Subsequent analyses were adjusted for the ancestry specific PCs: 9 Eur, 10 Asian, 1 African and 6 Mixed. These PCs are included in the imputed dataset phenotypes file

  Study EGAS00001002305

• Multi-layered molecular characterization defines prognostic subtypes of lung adenocarcinoma in Asian never-smokers

  Multi-layered genomic studies such as the TCGA project have greatly advanced our understanding on molecular pathogenesis of lung cancer. For Asian nonsmoker patients, however, majority of studies have been limited to mutational analyses, emphasizing ethnic differences in driver mutations (e.g. more frequent EGFR mutations and ALK fusions). In essence, a comprehensive multi-layered characterization that could lead to molecular etiology and patient stratification scheme to be translated into clinical applications for this patient group is still missing. Here we report molecular profiling of tumor and matched normal tissues from 114 non-small-cell lung adenocarcinoma patients using whole exome sequencing, transcriptome sequencing, and array comparative genomic hybridization (CGH).

  Study EGAS00001003705

• Investigation_of_mutational_signatures_associated_with_DNMT3A_deficiency_

  Mutational signatures have been shown to be attributable to specific genetic contexts, such as mutations in DNA repair genes. DNMT3A is a DNA methyltransferase that helps maintain the DNA methylation pattern in a site-specific manner and may participate in DNA repair or the stress response. We have identified an adult individual who is a germline mosaic for a DNMT3A mutation. We have obtained clonal lymphoblastoid cells (LCLs) from the subject representing both WT and mutant lines grown in the same individual for >50 years. These clones represent a unique opportunity to examine the mutational impact of the DNMT3A mutation in a well-controlled setting. Our goal is to perform WGS on whole blood, representing the pool, as well as several WT and several mutant clones, in order to investigate the contribution of DNMT3A to mutation rates and signatures.

  Study EGAS00001002329

• whole genome sequence data of multifocal hepatocellular carcinoma

  Background & Aims: The differentiation of distinct multifocal hepatocellular carcinoma (HCC): multicentric disease vs. intrahepatic metastases, in which the management and prognosis varies substantively, remains problematic. We aim to stratify multifocal HCC and identify novel diagnostic and prognostic biomarkers by performing whole genome and transcriptome sequencing, as part of a multi-omics strategy Methods: A complete collection of tumour and somatic specimens (intrahepatic HCC lesions, matched non-cancerous liver tissue and blood) were obtained from representative patientswith multifocal HCC exhibiting two distinct postsurgical courses. Whole-genome and transcriptome sequencing with genotyping were performed for each tissue specimen to con-trast genomic alterations, including hepatitis B virus integrations, somatic mutations, copy number variations, and structural variations. We then constructed a phylogenetic tree to visualise individual tumour evolution and performed functional enrichment analyses on select differentially expressed genes to elucidate biological processes involved in multifocal HCC development. Multi-omics data were integrated with detailed clinicopathological information to identify HCC biomarkers, which were further validated using a large cohort of HCC patients (n = 174).Results: The multi-omics pro?ling and tumour biomarkers could successfully distinguish the two multifocal HCC types, while accurately predicting clonality and aggressiveness. The dual speci?city protein kinase TTK, which is a key mitotic checkpoint regulator with links to p53 signaling, was further shown to be a promising overall prognostic marker for HCC in the large patient cohort.Conclusions: Comprehensive multi-omics characterisation of multifocal tumour evolution may improve clinical decision-making, facilitate personalised medicine, and expedite identi?cation of novel biomarkers and therapeutic targets in HCC.

  Study EGAS00001002338

• Organoid_Derivation_Project__TGS

  Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

  Study EGAS00001002221

• Ongoing_mutagenesis_RNAseq

  One of the key questions to be explored is whether the biological processes generating specific mutational signatures continue to operate in the human cancer cell lines or simply reflect past mutagenic activity which is no longer operative. To address this question, we have extracted mutational signatures from 1,000 cancer cell lines of diverse cancer types. Several cell lines with mutational signatures of interest were selected, subcloned over a defined period of time and their genomes sequenced. The increased load of the mutations representative of a specific mutational signature within the genome of a subclone when compared to its parental clone was informative of the on-going mutational processes. To further study the recent observation that some of the clones belonging to a same cell line acquired differencet numbers of mutations over a set period of time, their RNA will be subjected to RNA-sequencing to study their differences.

  Study EGAS00001002364

• Comprehensive investigation of genome architecture of gastric adenocarcinoma with whole-genome sequencing in the Chinese population.

  In this study, we performed whole-genome sequencing (WGS) of 214 paired GC tumors and adjacent normal tissues to identify novel potential biomarkers. We extracted mutational signatures which induce somatic mutations and classified GC tumors into four groups with significantly different prognosis. Moreover, we observed copy number changes and structural variations frequently occurring in some cancer related genes. Our study covers a comprehensive genetic framework that can be used in clinical trials and treatment modalities in GC.

  Study EGAS00001002404

• Fibroblast heterogeneity and immunosuppressive environment in Human breast cancer

  Carcinoma-associated fibroblasts (CAF) are key players in the tumor microenvironment. Here, by combining 6 well-known stromal markers, we identify four CAF subsets (CAF-S1 to CAF-S4) in human breast cancer (BC) that exhibit distinct activation patterns and accumulate differently in BC subtypes.

  Study EGAS00001002508

• A dataset compiled as a resource a for orthogonal assessment of exon CNV calling in NGS data

  The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM and PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs the most difficult exon CNV to detect. The full dataset includes FASTQ files, target BED file, and MLPA results.

  Study EGAS00001002428

• Successful immune checkpoint blockade in a patient with advanced stage microsatellite unstable biliary tract cancer (H021)

  Cancers acquire multiple somatic mutations that can lead to the generation of immunogenic mutation-induced neoantigens. These neoantigens can be recognized by the host’s immune system. However, continuous stimulation of immune cells against tumor antigens can lead to immune cell exhaustion, which allows uncontrolled outgrowth of tumor cells. Recently, immune checkpoint inhibitors have emerged as a novel approach to overcome immune cell exhaustion and re-activate anti-tumor immune responses. In particular, antibodies blocking the exhaustion-mediating programmed death receptor (PD-1)/PD-L1 pathway have shown clinical efficacy. The effects were particularly pronounced in tumors with DNA mismatch repair deficiency and a high mutational load, which typically occur in the colon and endometrium. Here, we report on a 24-year old woman diagnosed with extrahepatic cholangiocarcinoma who showed strong and durable response to the immune checkpoint inhibitor pembrolizumab, although treatment was initiated at an advanced stage of disease. The patient’s tumor displayed DNA mismatch repair deficiency and microsatellite instability (MSI), but lacked other features commonly discussed as predictors of response towards checkpoint blockade, such as PD-L1 expression or dense infiltration with cytotoxic T cells. Notably, high levels of HLA class I and II antigen expression were detected in the tumor, suggesting a potential causal relation between functionality of the tumor’s antigen presentation machinery and the success of immune checkpoint blockade. We suggest determining MSI status in combination with HLA class I and II antigen expression in tumors potentially eligible for immune checkpoint blockade even in the absence of conventional markers predictive for anti-PD-1/PD-L1 therapy and in entities not commonly linked to MSI phenotype. Further studies are required to determine the value of these markers for predicting the success of immune checkpoint blockade. (H021)

  Study EGAS00001002441

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002509

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__Colorectal

  he Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute. Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003774

• TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

  We examined tumours from a large cohort of patients with metastatic urothelial bladder cancer (mUC) treated with an anti–PD-L1 agent (atezolizumab) and identified major determinants of clinical response and immune escape. Whole transcriptome profiles were generated for 368 patients using TruSeq RNA Access technology (Illumina). Somatic mutations were determined via whole exome sequencing for a subset of these patients. - Response was associated with CD8+ T effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden (TMB). On the other hand, lack of response was associated with a transforming growth factor β (TGF-β) signature, particularly in patients with CD8+ T cells preferentially residing in collagen-rich matrix surrounding tumours. Integration of these three independent biological features provided the best basis for understanding outcome in this setting. -

  Study EGAS00001002556

• Systematic kinase inhibitor profiling identifies CDK9 as a synthetic lethal target in NUT midline carcinoma

  Kinase inhibitors represent the backbone of targeted cancer therapy, yet only a limited number of oncogenic drivers are directly druggable. By interrogating the activity of 1,505 kinase inhibitors we found that BRD4-NUT-rearranged NUT midline carcinoma (NMC) cells are specifically killed by CDK9 inhibition (CDK9i) and exhibit a unique dependency on CDK9 and Cyclin-T1 expression. We show that CDK9i leads to robust induction of apoptosis and of markers of DNA damage response in NMC cells. While both CDK9i and bromodomain inhibition over time result in reduced Myc protein expression, only bromodomain inhibition induces cell differentiation and a p21-induced cell cycle arrest in these cells. Finally, RNA-Seq and ChIP-based analyses reveal a BRD4-NUT specific CDK9i-induced perturbation of transcriptional elongation. Thus, our data provide a mechanistic basis for the genotype-dependent vulnerability of NUT midline carcinoma cells to CDK9i that may be of relevance for the development of targeted therapies for NMC patients.

  Study EGAS00001002588

• Whole Genomes Define Concordance in Matched Primary, Xenograft, and Organoid Models of Pancreas Cancer

  Pancreatic ductal adenocarcinoma (PDAC) has the worst prognosis of any common solid epithelial tumour. Multiple failed clinical trials necessitate newer approaches to understand the molecular etiology of this disease. Patient-derived xenografts (PDX) and patient-derived organoids (PDO) may serve as pre-clinical disease models; however, characterization remains largely unaddressed at the whole genome level. We conducted a comprehensive assessment of the genetic landscape of tumours and matched PDX and PDO from patients with PDAC. Our data show that PDX and PDO recapitulate PDAC tumourigenesis with respect to simple somatic mutations and copy number changes, and capture major structural variation events.

  Study EGAS00001002597

• Res1_H23_exp1_MC_04_03_22

  1 sample is pure plasmid DNA and 8 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kozuke primers.

  Study EGAS00001006091

• Mutational spectrum of highly differentiated, fusion-negative rhabdomyosarcoma (set 1).

  Pediatric PAX-FOXO1 fusion-negative rhabdomyosarcoma represents a diverse spectrum of tumors. In this study, the mutational spectrum of 22 fusion-negative rhabdomyosarcomas with high, rhabdomyoma-like levels of differentiation was evaluated using OncoPanel v.2 (OPv2), an Agilent SureSelect custom designed bait set consisting of the coding regions of 504 cancer-relevant genes. Corresponding normal tissue was not available. Discarded normal human skeletal muscle, obtained from 7 donors without tumor history, were also included in the sequencing run.

  Study EGAS00001002630

• The evolutionary steps from primary to metastatic prostate cancer are largely uncharted, and the ability to use DNA present in body fluids as correlates of aggregate metastatic status is under-examined. We reconstructed phylogenies in ten prostate cancer patients with fatal disease using deep targeted sequencing of the prostate, adjacent and distant organs, as well as plasma, serum, and cerebrospinal fluid at various time points. A total of 163 samples are studied.

  The evolutionary steps from primary tumor to metastasis in prostate cancer are largely uncharted, and the ability to use serum, plasma, and cerebrospinal fluid as a correlate of aggregate metastatic tumor genomic status has not been tested. We used deep targeted sequencing to reconstruct tumor evolution in ten prostate cancer patients with fatal disease encompassing examination of the prostate and adjacent and distant organs, as well as plasma, serum, and cerebrospinal fluid at various time points. We show that there is substantial evolution from a common ancestor within the prostate that results in branching to multiple lineages which form an intermixed multi-clonal primary tumor mass. After the occurrence of key driver aberrations, one of these lineages will metastasize to multiple sites in a sequential fashion. These metastatic sites are then susceptible to being populated by cells from other intra-prostatic lineages or from other metastases. Genomic representation of metastases in body fluids is not uniform. Cerebrospinal fluid analysis can detect lineages not detected in circulating DNA, suggesting possible clinical utility.

  Study EGAS00001003848

• CancerDetector: Ultrasensitive and Non-Invasive Cancer Detection at the Resolution of Individual Reads using Cell-free DNA Methylation Sequencing Data

  The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed “CancerDetector”, using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation patterns of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor burden. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor DNAs. In addition, the predicted tumor burden showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1X to 10X). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.

  Study EGAS00001002728

• Sequencing of an organoid biobank for childhood kidney cancers that captures disease and tissue heterogeneity.

  Kidney tumors are among the most common solid tumors in children, comprising several distinct subtypes differing in many aspects, including cell-of-origin, genetics, and pathology. Pre-clinical cell models capturing the disease heterogeneity are currently lacking. Here, we describe the first pediatric cancer organoid biobank. It contains tumor and matching normal organoids from over 50 children with different subtypes of kidney cancer, including Wilms tumors, malignant rhabdoid tumors, renal cell carcinomas, and congenital mesoblastic nephromas. The malignant rhabdoid tumor organoids represent the first organoid model for tumors of non-epithelial origin. The tumor organoids retain key properties of native tumors, useful for revealing patient specific drug vulnerabilities. We further demonstrate that organoid cultures derived from Wilms tumors consist of multiple different cell types, including epithelial, stromal and blastemal-like. Our organoid biobank captures the cellular heterogeneity of pediatric kidney tumors, providing a representative collection of well-characterized models for basic cancer research, drug-screening, and personalized medicine.

  Study EGAS00001003853

• Identification of a Fumarate-Hydratase Deficient-like RCC Subtype with Convergent Pathway Alterations

  The development of molecularly targeted therapies builds upon the identification of tumor clades with shared molecular abnormalities. Hereditary leiomyomatosis and renal cell carcinoma (HLRCC) is a familial syndrome resulting from germline mutation of the two-hit tumor suppressor gene, Fumarate Hydratase (FH). HLRCC renal tumors present often in young adults, exhibit unique histological features and are particularly aggressive. HLRCC is uncommon and poorly understood, and whether there are sporadic renal tumors with similar characteristics, is unclear. Notably, FH can also be inactivated somatically in RCC, and should be included among FH-deficient (FHD) kidney tumors. We identified a tumor clade without FH mutations but with similar morphological and molecular characteristics as well as aggressive clinical behavior, which we name FHDL (FHD-like). We show that FHD/FHDL tumors represent a unique subtype of CIMP (CpG Island Methylator Phenotype) with the highest levels of overall genome methylation and CDKN2A silencing. FHD/FHDL tumors are characterized by convergent activation of the Hippo pathway as determined by frequent and mutually exclusive mutations in NF2 and PTPN14. AKR1B10, an NRF2 target, was upregulated in FHD/FHDL tumors as well as GATA3, which suggests a shared origin in the renal medulla and is consistent with topological studies. There is loss of 5-hydroxymethylcytosine in both FHD and FHDL tumors. These data define a group of particularly aggressive renal cancers with shared molecular features and potential targets for therapeutic intervention.

  Study EGAS00001002646

• Multisample genomic analysis of solid childhood cancers using high resolution SNP-arrays, Whole Exome Sequencing and Targeted Deep Sequencing.

  We mapped the prevalence of genetically distinct clones over 248 regions in 54 childhood cancers. This revealed that primary tumors can simultaneously follow up to four evolutionary patterns in different anatomic areas. The most common pattern consists of a fluctuating presence over anatomic space of subclones with very few mutations. The second most common is a surprisingly stable coexistence, over vast areas, of clones with different changes in chromosome numbers. This is contrasted by a third, less frequent, pattern where a novel clone harboring driver mutations or structural chromosome rearrangements completely replaces its progenitor. The fourth and rarest pattern is the local emergence of a myriad of clones with TP53 inactivation. Strikingly, death from disease was limited to tumors exhibiting the two latter, most dynamic patterns.

  Study EGAS00001002662

• WGS of 32 paired SRCC samples

  Signet-ring cell carcinoma (SRCC) has specific epidemiology and oncogenesis in gastric cancer, however with no systematical investigation for prognostic genomic features. We systematically investigated the clinical characteristics of 1,868 Chinese gastric cancer patients, and found that signet-ring cell content was significantly related to multiple clinical characteristics and treatment outcomes. Next, we performed whole genome sequencing for 32 SRCC patients with > 80% signet-ring cells in tumor, and identified frequent5 CLDN18-ARHGAP26/6 fusion (25%). With additional 797 patients for validation, we notice that prevalence of CLDN18-ARHGAP26/6 fusion is positively associated with signet-ring cell content (P = 4.1 x 10 -9 ), younger age at diagnosis (P = 4.2 x 10 -10 ), female/male ratio (P = 1.7 x 10 -9 ), and advanced TNM stage (P = 1.7 x 10 -5 ). Importantly, patients with CLDN18-ARHGAP26/6 fusion had a worse survival outcomes (P = 0.03), and got no benefit0 from platinum/fluoropyrimidines based chemotherapy (P = 0.92) compared to fusion-free patients (P = 0.001), which is consistent with the fact of oxaliplatin/fluoropyrimidine resistance acquired in CLDN18-ARHGAP26 introduced gastric cancer cell lines. Overall, this study provides new insights into the clinical and genomic features of SRCC, and highlights the importance of frequent CLDN18-ARHGAP26/6 fusions in chemotherapy response for SRCC.

  Study EGAS00001002668

• WGS of breast cancer diagnosed during pregnancy and matched control

  The aim of this study was to compare the mutational landscape of breast cancer diagnosed during pregnancy (BCP) and breast cancer from age/stage non-pregnant patients (controls). We present whole genome sequencing data (Illumina HiSeq X ten platform) of tumor and matched normal tissues from 35 BCP patients and 20 controls. This work provides important novel biological insights and a unique resource to study the biology of breast cancer in young women and how pregnancy could modulate tumor biology.

  Study EGAS00001002685

• Dynamics of neoantigen landscape during immunotherapy

  Immune checkpoint inhibitors have shown significant therapeutic responses against tumors containing increased mutation-associated neoantigen load. We have examined the evolving landscape of tumor neoantigens during the emergence of acquired resistance in non-small cell lung cancer patients after initial response to immune checkpoint blockade with anti-PD1 or anti-PD-1/anti-CTLA4 antibodies. Analyses of matched pretreatment and resistant tumors identified genomic changes resulting in loss of 7 to 18 putative mutation-associated neoantigens in resistant clones. Peptides generated from the eliminated neoantigens elicited clonal T cell expansion in autologous T cell cultures, suggesting that they generated functional immune responses. Neoantigen loss occurred through elimination of tumor subclones or through deletion of chromosomal regions containing truncal alterations and were associated with changes in T cell receptor clonality. These analyses provide insights into the dynamics of mutational landscapes during immune checkpoint blockade and have implications for development of immune therapies that target tumor neoantigens.

  Study EGAS00001002704

• Single cell RNA sequencing and Whole Genome Sequencing on different cells from the same sample for a triple negative patient derived xenograft and ovarian cancer cell lines.

  Measuring gene expression of genomically defined tumour clones at single cell resolution would associate functional consequences to somatic alterations, as a prelude to elucidating pathways driving cell population growth, resistance and relapse. In the absence of scalable methods to simultaneously assay DNA and RNA from the same single cell, independent sampling of cell populations for parallel measurement of single cell DNA and single cell RNA must be computationally mapped for genome-transcriptome association. Here we present clonealign, a robust statistical framework to assign gene expression states to cancer clones using single-cell RNA-seq and DNA-seq independently sampled from an heterogeneous cancer cell population. We apply clonealign to triple-negative breast cancer patient derived xenografts and high-grade serous ovarian cancer cell lines and discover clone-specific dysregulated biological pathways not visible using either DNA-Seq or RNA-Seq alone.

  Study EGAS00001003387

• Whole exome sequencing from early stage non-small cell lung cancer patients at MDACC

  The purpose of the study is to evaluate the mutational landscape and tumor mutational burden in tumor from patients with early stage non-small cell lung cancer. Mutational landscape was compared to the T cell repertoire to determine the relationship between somatic mutations and T cell response in early-stage NSCLC.

  Study EGAS00001004026

• HSC_population_dynamics___CB001_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003397

• Phase Ib of olaparib and capivasertib

  Background: Combining poly(ADP-ribose) polymerase (PARP) with phosphatidylinositol-3-kinase (PI3K) pathway inhibitors is supported by strong preclinical rationale. We sought to assess safety and a recommended phase 2 dose (RP2D) for the PARPi olaparib combined with the AKT inhibitor, capivasertib, and evaluate molecular markers of response and resistance. Methods: As part of a larger phase 1b trial, we performed a safety lead in of olaparib and capivasertib followed by expansion (n=24) in endometrial, triple negative breast, ovarian, fallopian tube, or peritoneal cancer. Olaparib 300mg orally twice daily and capivasertib orally twice daily on a 4 day on/3 day off schedule were evaluated. Two dose levels (DL) were planned: capivasertib 400mg (DL1); capivasertib 320mg (DL-1). Patients underwent biopsies at baseline and after 28 days.

  Study EGAS00001004930

• A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma

  Pancreatic cancer expression profiles largely reflect a classical or basal-like phenotype. The extent to which these profiles vary within a patient is unknown. We integrated evolutionary analysis and expression profiling in multiregion sampled metastatic pancreatic cancers, finding that squamous features are the histologic correlate of an RNA-seq defined basal-like subtype. In patients with coexisting basal/squamous and classical/glandular morphology, phylogenetic studies revealed that squamous morphology represented a subclonal population in an otherwise classical/glandular tumor. Cancers with squamous features were significantly more likely to have clonal mutations in chromatin modifiers, intercellular heterogeneity for MYC amplification, and entosis. These data provide a unifying paradigm for integrating basal-type expression profiles, squamous histology, and somatic mutations in chromatin modifier genes in the context of clonal evolution of pancreatic cancer.  

  Study EGAS00001003974

• Human genomic and phenotypic synthetic data for the study of rare diseases

  The purpose of this dataset is to facilitate development of technical implementations for rare disease data integration, analysis, discovery, and federated access. This synthetic dataset includes clinical and genomic data from 6 rare disease cases. It consists of 18 whole genomes (6 index cases with their parents) which have genetic background based on public human data sequenced in the context of the Illumina Platinum initiative (Eberle, MA et al. (2017)) and made available by the HapMap project (https://www.genome.gov/10001688/international-hapmap-project). In each of the cases, real causative variants correlating with the phenotypic data provided were spiked-in. The cases included in this synthetic dataset correspond to the following type of disorders: CASE 1- Congenital myasthenic syndrome (Autosomal Dominant -de novo variant) CASE 2- Macular dystrophy (Autosomal Dominant) CASE 3- Muscular dystrophy (Autosomal Recessive-compound heterozygous variants) CASE 4- Mitochondrial disorder (Autosomal Recessive-consanguineous case - homozygous variant) CASE 5- Breast cancer (Autosomal Dominant) CASE 6- Similar as case 1 for patient matchmaking tests: Congenital myasthenic syndrome (Autosomal Dominant-de novo variant) For each case you will be able to download the following data: clinical information (phenopackets per individual and pedigree per family), raw genomic data (FASTQ and BAMs) and processed genomic data (vcfs). When using the data, the following should be acknowledged: the RD-Connect GPAP (https://platform.rd-connect.eu/), EC H2020 project EJP-RD (grant # 825575), EC H2020 project B1MG (grant # 951724) and Generalitat de Catalunya VEIS project (grant # 001-P-001647).

  Study EGAS00001005702

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__pancreas

  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 (Illumina HiSeqX, 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 EGAS00001002726

• Somatic_mutation_and_clonal_evolution_in_premalignant_lung_disease___WGS

  Cancer is a genetic disease caused by an accumulations of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from the lung tissue of individuals with a variety of lung diseases (COPD, UIP, IPF, Emphysema, pulmonary hypertension). This will allow us to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. Smoking is a large risk factor for developing many of these lung diseases so we are particularly keen to determining whether there is evidence of a smoking signature in these patients.

  Study EGAS00001002747

• Benchmarking_CRISPR_Whole_genome_Drop_out_Screen___B_S

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries.

  Study EGAS00001002931

• Imaging metabolic heterogeneity in breast cancer using hyperpolarized 13C-MRI

  Higher 13C-lactate labeling was seen in the more aggressive tumors, including all triple negative breast cancers. There was a significant correlation between lactate labeling and expression of the monocarboxylate transporter (MCT1), which mediates tumor cell pyruvate uptake, and a weaker correlation with expression of LDHA, which catalyzes label exchange between the injected pyruvate and the endogenous lactate pool.

  Study EGAS00001004118

• Integrative genomic analysis reveals cancer-associated mutations at diagnosis of CML in patients with high risk disease

  Genomic events associated with poor outcome in chronic myeloid leukemia (CML) are poorly understood. We performed whole exome sequencing, copy number variation and/or RNA-Seq for 65 patients to discover mutations at diagnosis and blast crisis (BC). Forty-six chronic phase patients with the extremes of outcome were studied at diagnosis. Cancer gene variants were detected in 15/27 patients (56%) with subsequent BC or poor outcome and in 3/19 optimal responders (16%), P=.007. Frequently mutated genes at diagnosis were ASXL1, IKZF1 and RUNX1. The methyltransferase SETD1B was a novel recurrently mutated gene. A novel class of variant associated with the Philadelphia translocation was detected at diagnosis in 11/46 patients (24%) comprising fusions and/or rearrangement of genes on the translocated chromosomes, with evidence of fragmentation, inversion and imperfect sequence reassembly. These were more frequent at diagnosis in patients with poor outcome: 9/27 (33%) versus 2/19 optimal responders (11%), P=.07. Thirty-nine patients were tested at BC and all had cancer gene variants, including ABL1 kinase domain mutations in 58%. However, ABL1 mutations co-occurred with other mutated cancer genes in 89% of cases, and these predated ABL1 mutations in 62% of evaluable patients. Gene fusions not associated with the Philadelphia translocation occurred in 42% of patients at BC and commonly involved fusion partners that were known cancer genes (78%). Genomic analysis revealed numerous relevant variants at diagnosis in patients with poor outcome and all patients at BC. Future refined biomarker testing of specific variants will likely provide prognostic information to facilitate a risk-adapted therapeutic approach.

  Study EGAS00001003071

• Metastatic Adult Pancreatoblastoma: Multimodal Treatment and Molecular Characterization of a Very Rare Disease (NCT MASTER)

  Pancreatoblastoma is a rare malignant tumor that occurs predominantly in children. We identified four adult patients with metastasizing pancreatoblastoma at a high-volume German university cancer center which were treated with multimodal therapies between 2013 and 2018. In three cases, we performed a comprehensive molecular analysis that included whole-genome sequencing (WGS) or whole-exome sequencing (WES); transcriptome sequencing was performed in two cases, respectively. Subsequent recommendations of molecularly stratified treatment options were discussed within a dedicated molecular tumor board (MTB) embedded in a precision oncology program (NCT MASTER).

  Study EGAS00001004157