5707 results for "canc*"

in 97.30 milliseconds.

• Methylome sequencing of cell-free DNA and RRBS of solid tissue

  Early cancer detection by cell-free DNA (cfDNA) faces multiple challenges: low fraction of tumor cfDNA, molecular heterogeneity of cancer, and sample sizes not sufficient to reflect diverse patient population. We develop a cancer detection approach to address these challenges. It consists of an assay, cfMethyl-Seq, for cost-effective sequencing of cfDNA methylome (with >12-fold enrichment over whole genome bisulfite sequencing in CpG islands), and a computational method to extract methylation information and diagnose patients. Applying our system to 408 colon, liver, lung, and stomach cancer patients and controls, at 97.9% specificity we achieve 80.7% and 74.5% sensitivity in detecting all-stage and early-stage cancer, and 89.1% and 85.0% accuracy for locating tissue-of-origin of all-stage and early-stage cancer, respectively. Our approach cost-effectively retains methylome profiles of cancer abnormalities, thereby permitting the classification models to learn new features as training cohorts grow, and expanding their scope to other cancer types.

  Study EGAS00001006020

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  Study EGAS00001006161

• Whole-Exome Sequencing analyses in tamoxifen-associated endometrial cancer

  An increased incidence of endometrial cancer has been described for patients that have received tamoxifen to treat breast cancer. Using samples from endometrial tumors, isolated from surgivcal specimens of patients who previously received tamoxifen treatment for breast cancer, we aimed to identify whether there are specific somatic mutations enriched in this population, relative to endometrial tumors from the general population. For this, WES was performed on matched endometrial tumors and healthy tissue (n=21).

  Study EGAS00001006453

• Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

  We developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 94 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for high levels of a mutational signature associated with HRD in an additional MyBrCa TNBC validation cohort (this EGA study) as well as in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

  Study EGAS00001006518

• PELICAN45 RNAseq Dataset

  To better understand the biology of prostate cancer, we performed RNAseq in cancerous (primary and metastatic) and noncancerous tissues in the PELICAN45 cohort. The PELICAN45 RNAseq samples include androgen-deprived metastasis samples from the PELICAN33 consenting rapid autopsy study participants, whose identifiers are A1, A2, etc. The PELICAN45 RNAseq dataset also includes data from non-androgen deprived metastases in an additional 12 men. These samples are identified as PB50, PB133, etc.

  Study EGAS00001006959

• LOGGIC Core BioClinical Data Bank: Added clinical value of RNA-Seq in an international molecular diagnostic registry for pediatric low-grade glioma patients

  Study EGAS00001007072

• Melanoma_Til_Study_RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Study EGAS00001000251

• Genentech Colon Cancer Screen

  Study EGAS00001000288

• Analysis of DNA methylation in normal B cells and chronic lymphocytic leukemia

  Charting differences between tumors and normal tissue is a mainstay of cancer research. However, clonal tumor expansion from complex normal tissue architectures potentially obscures cancer-specific events, including divergent epigenetic patterns. Using whole-genome bisulfite sequencing of normal B cell subsets, we observed broad epigenetic programming of selective transcription factor binding sites coincident with the degree of B cell maturation. By comparing normal B cells to malignant B cells from 268 patients with chronic lymphocytic leukemia (CLL), we showed that tumors derive largely from a continuum of maturation states reflected in normal developmental stages. Epigenetic maturation in CLL was associated with an indolent gene expression pattern and increasingly favorable clinical outcomes.As second study using these samples focued on evolution and resulting intra-tumor heterogeneity in CLL. We used 450k bead-chip arrays to study DNA methylomes in 68 chronic lymphocytic leukemia (CLL) cases, including 28 serial cases. The result establishs linked evolution of epigenetic and genetic alterations in progressive disease, revealing an important aspect of the biology of epigenetics in cancer.

  Study EGAS00001000534

• Genomic consequences of aberrant DNA repair mechanisms stratify ovarian cancer histotypes

  Aberrant DNA repair processes are a hallmark of human tumours. How these deficiencies variously impact the genomes of ovarian cancer between and within histotypes remains unknown. We studied the whole genome pointmutation and structural variation patterns of 133 tumours (59 high grade serous (HGSC), 35 clear cell (CCOC), 29 endometrioid (ENOC), and 10 adult granulosa cell tumours (GCT)) as a substrate for class discovery in ovarian cancer. Ab-initio clustering of integrated point mutation and structural variation signatures revealed seven novel subgroups, comprising between and within histotype stratification. Prevalence of fold-back inversions (FBI) co-localised with high level amplification events divided HGSC into two prognostically significant subgroups. This finding was recapitulated in two additional independent cohorts (total n=576 cases), and transcended gene based mutation status and gene expression as prognostically relevant features of HGSC. CCOC were divided into one group harbouring a signature reflective of active genome editing via APOBEC enzymes (26%) and a complementary group with an age-relatedmutational signature. ENOC were divided intomicrosatellite instable (MSI) cases (28%) with a distinctmismatch repairmutation signature and an outlying mutation rate, with the remainder of cases distributed amongst the remaining six groups. We suggest the FBI, MSI, and APOBEC groups represent biologic strata that could direct treatment strategies. Taken together, our work establishes the efficacy of the somatic genome as a biomarker to stratify ovarian cancers, simultaneously identifying patients that may benefit from emerging therapeutics and distinct subgroups within classic ovarian cancer histotypes.

  Study EGAS00001002390

• Control samples, breast cancer clinical samples and matched patient-derived tumour xenografts (PDTXs) to develop and test a computational approach to discriminate human and mouse sequences in PDTXs

  Patient-Derived Tumour Xenografts (PDTXs) have emerged as the pre-clinical models that best represent clinical tumour diversity and intra-tumour heterogeneity. The molecular characterization of PDTXs using High-Throughput Sequencing (HTS) is essential; however, the presence of mouse stroma is challenging for HTS data analysis. Indeed, the high homology between the two genomes results in a proportion of mouse reads being mapped as human. In this study we generated Whole Exome Sequencing (WES) and RNA sequencing (RNA-seq) data from samples with known mixtures of mouse and human DNA or RNA.

  Study EGAS00001002445

• The_mutational_landscape_of_recurrent_Glioblastome_multiforme

  Targeted gene screen of approx 120 patients with primary GBM and recurrent samples.

  Study EGAS00001001764

• The_Causes_of_Clonal_Blood_Cell_Disorders_Study___SCOR

  We will take 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 will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health.

  Study EGAS00001002132

• Automated image-based profiling of complex drug induced phenotypes in patient-derived organoids

  We established a platform for high-throughput confocal fluorescence microscopy and automated image analysis to perform large-scale drug response profiling with patient derived organoids (PDOs). Using PDO lines newly established from colorectal cancer patients with a standardized workflow, we performed chemical perturbations with more than 500 experimental and clinically used compounds. Subsequently, we captured approx. six million images by confocal microscopy. To analyze drug-induced PDO re-organization on a single organoid level we developed SCOPE, a software framework for automated PDO high-throughput image analysis. We observed a rich variety of divergent and reoccurring compound induced phenotypes in organoids. Perturbation of cellular processes, including signaling by MEK, GSK3β, cyclin dependent kinases (CDKs) and others, led to recurring and distinct architectural changes. Highlighting the clinical relevance, PDO viability was heterogeneous after perturbation with anticancer drugs and matched clinical response of corresponding colorectal cancer patients. Our work opens new avenues for image-based profiling for accelerated drug discovery and clinical decision-making.

  Study EGAS00001003140

• SCAT_osteosarcoma_sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 osteosarcoma cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes

  Study EGAS00001000196

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746

• Acute_Lymphoblastic_Leukemia_Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 Acute Lymphoblastic Leukemia samples and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped build 37 of the human reference genome to facilitate the identification of novel cancer genes. In addition, 500bp, NO_PCR total genomic libraries will be prepared from the same samples and five lanes of Illumina GA sequencing will be analysed to characterise genome wide, somatically acquired structural variation.

  Study EGAS00001000058

• Melanoma_TIL_Study_Exomes

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of teh samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Study EGAS00001000216

• 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

• HKU Gastric Cancer Genomics study - WGS, DNA genotyping array, expression and methylation profiling

  HKU Gastric Cancer Genomics study - Whole Genome Sequencing, DNA genotyping array, Expression profiling and Methylation profiling

  Study EGAS00001000597

• Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Study EGAS00001007941

• Single-cell RNA sequencing of 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes

  Hodgkin lymphoma (HL) is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of non-cancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding crosstalk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 HL tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the HL-specific immune microenvironment at single-cell resolution. Library preparation was performed using the 10x Genomics Chromium system, and Illumina sequencing was used to generate 3' gene expression data for every cell. Downstream analysis was performed in R to identify HL-specific microenvironment patterns and identify novel cell populations.

  Study EGAS00001004085

• Unraveling mutagenic processes influencing the tumor mutational patterns of individuals with Constitutional Mismatch Repair Deficiency

  Constitutional mismatch repair deficiency (CMMRD), caused by bi-allelic germline variants in one of the mismatch repair (MMR) genes, is a childhood cancer predisposition syndrome that often results in the development of multiple tumors early in life. A better understanding of mutational processes driving subsequent CMMRD tumors could advance optimal treatment. Therefore, we performed a genomic characterization of 41 tumors from 17 individuals with CMMRD. Mutational patterns in these tumors were found to be influenced by multiple factors, including the affected MMR genes, tumor types and somatic polymerase proofreading mutations. Temozolomide treatment left prominent mutational signatures in two second primary hematologic malignancies. Furthermore, a novel indel signature was found in 54% of the tumors, characterized by one base pair cytosine insertions in cytosine homopolymers. In conclusion, the analysis of sequential tumors in individuals with CMMRD reveals diverse mutational patterns influenced by the underlying mutated MMR gene, tumor type and treatment history.

  Study EGAS00001007660

• S_CORT_Stratification_in_COloRecTal_cancer_

  Colorectal cancer samples will be submitted for Illumina sequencing using a custom capture of 116 genes implicated in colorectal tumourigenesis. Driver mutations will be detected and ultimately correlated with phenotypic data.

  Study EGAS00001001521

• Buccal Sample Methylation for Breast Cancer Detection

  This study encompasses buccal sample DNA methylation (IlluminaMethylationEPIC array) from breast cancer cases and healthy age-matched controls.

  Study EGAS00001007658

• Kidney_tumour_DNA

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

  Study EGAS00001002486

• Comprehensive Genomic and Transcriptomic Analysis of Rare Cancers for Guiding of Therapy (H021)

  Here we analyzed the molecular profiles and clinical outcomes of 1,310 patients (proportion of rare cancers, 75%) enrolled in a prospective observational study by the German Cancer Consortium that applies whole-genome/exome and RNA sequencing to inform the care of adults with incurable cancers. Based on 472 single and six composite biomarkers, a cross-institutional molecular tumor board provided evidence-based management recommendations, including diagnostic reevaluation, genetic counseling, and experimental treatment, in 88% of cases. Recommended therapies were administered in 362 of 1,138 patients (31.8%) and resulted in significantly improved response and disease control rates (23.9% and 55.3%, respectively) compared to previous therapies, translating into a progression-free survival ratio >1.3 in 35.7% of patients.

  Study EGAS00001004813

• RNA-seq consisting of FASTQ paired-end reads from 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 EGAS00001003724

• ctDNA to predict risk of progression and death after trifluridin/tipiracil therapy

  Background. Late-line treatment in metastatic colorectal cancer (mCRC) can improve the prognosis. However, not every patient has a benefit and may experience severe side effects. Thus, predictive/prognostic biomarkers are urgently needed. Despite many promising results, the role of circulating tumor DNA (ctDNA) analysis in trifluridin/tipiracil (FTD/TPI) treated mCRC patients is so far still elusive. Study design. This prospective non-interventional translational biomarker phase II study enrolled 30 metastatic CRC patients treated with FTD/TPI. The primary study aim was to identify a molecular biomarker to predict overall survival (OS) benefit upon FTD/TPI treatment. Methods. mCRC patients (60% male, 40% female) with FTD/TPI therapy were included. Molecular profiling in cell-free DNA from plasma was performed prior to treatment and on average 4, 8 and 12 weeks after FTD/TPI initiation. Tumor levels were assessed as the highest variant allele frequency (hVAF) and correlated with OS. Uni- and multivariate analyses for survival were performed with clinical variables. Multivariate analyses for survival and treatment efficacy were adjusted to age, gender and ECOG performance status. Results. Compared to previous data, our disease control rate of 30% was lower with a median OS of 8.1 months and a median PFS of 3.2 months. At baseline (BL) and the first two follow-ups (FU), a hVAF cut-off of 7.5% was most discriminative (BL HR 0.39 95% CI 0.16 - 0.98 P=0.0212, FU1 HR 0.30 95% CI 0.12 -0.77 P=0.0021, FU2 HR 0.23 95% CI 0.08-0.70 P=0.0004) whereas at the last follow-up the stratification was most pronounced at a 15% cut-off. An elevated hVAF trajectory over time was associated with a higher risk of death. Conclusion. ctDNA is detectable in a high proportion of mCRC patients. Changes in ctDNA levels are associated with survival among FTD/TPI therapy and may identify patients who benefit most from treatment in these late-stage disease.

  Study EGAS00001006883

• Gene expression-based prediction of pazopanib efficacy in sarcoma (HIPO, H021)

  The multi-receptor tyrosine kinase (RTK) inhibitor pazopanib is approved for the treatment of advanced non-adipocytic soft-tissue sarcoma and has also shown activity in other sarcoma subtypes. However, its clinical efficacy is highly variable, and no reliable predictors exist to date to select patients who are most likely to benefit from this drug. We analyzed the molecular profiles and clinical outcomes of pazopanib-treated sarcoma patients enrolled in a prospective observational study by the German Cancer Consortium, DKTK MASTER, that employs whole-genome/exome sequencing (WGS/WES) and transcriptome sequencing to inform the care of adults with advanced cancer across histologies who are younger than 51 and patients with rare tumors, including rare subtypes of more common entities, regardless of age.​ Among a total of 109 patients with available WGS/WES data, there was no correlation between clinical parameters, specific genetic alterations, or mutational signatures and clinical outcome. In contrast, analysis of a subcohort of 62 patients who underwent molecular analysis before pazopanib treatment and had transcriptome sequencing data available showed that mRNA levels of NTRK3 (hazard ratio [HR]=0.53, p=0.021), IGF1R (HR=1.82, p=0.027), and KDR (HR=0.50, p=0.011) were independently associated with progression-free survival (PFS). Based on the expression of these RTK genes, i.e., the features NTRK3-high, IGF1R-low, and KDR-high, we developed a pazopanib efficacy predictor (PEP) that stratified patients into three groups with significantly different PFS (p<0.0001). Application of the PEP to an independent cohort of pazopanib-treated sarcoma patients from DKTK MASTER (n=43) confirmed its potential to separate patient groups with significantly different PFS (p=0.02), whereas no such association was observed in sarcoma patients from DKTK MASTER (n=77) or The Cancer Genome Atlas sarcoma cohort (n=256) who were not treated with pazopanib. A score based on the combined expression of NTRK3, IGF1R, and KDR allows identification of sarcoma patients with good, intermediate, and poor outcome following pazopanib therapy and warrants investigation as a predictive tool in prospective studies to optimize the use of this drug in the clinic.

  Study EGAS00001005836

• METABRIC: Data from Pereira et al (2016), The somatic mutation profiles of 2433 breast cancers refine their genomic and transcriptomic landscapes. Nat Comms 7.

  The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2433 primary breast tumours that have copy number aberration (CNA), gene expression, and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters, and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intratumour heterogeneity using mutant allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intratumour heterogeneity are in general associated with worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intratumour heterogeneity. These results emphasise the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

  Study EGAS00001001753

• Genomics-based characterization and personalized treatment in pleural and peritoneal mesothelioma

  Study EGAS00001007294

• GBM stem cell lines and PRMT5 inhibitor

  Study EGAS00001004397

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• DEREGULATION OF PRE-mRNA SPLICING IN MISMATCH REPAIR DEFICIENT COLORECTAL CANCER

  Study EGAS00001004863

• Therapeutic Targeting of Ependymoma as Informed by Oncogenic Enhancer Profiling

  Genomic sequencing has driven precision-based oncology therapy; however, genetic drivers remain unknown or non-targetable for many malignancies, demanding alternative approaches to identify therapeutic leads. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Here, we mapped active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts. Enhancer regions revealed novel oncogenes, molecular targets, and pathways, which when subjected to small molecule inhibitor or shRNA treatment, increased survival and slowed proliferation in mouse and neurosphere patient-derived models of ependymomas. This study represents one of the largest enhancer mapping study of any cancer type to date, and provides a framework for target and drug discovery for other cancers recalcitrant to therapeutic development because of their lack of known genetic drivers.

  Study EGAS00001002696

• 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

• A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer

  Background Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. Methods We combined immunohistochemistry (IHC) with RNA-sequencing and whole genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Further, we explored transcriptional features of immune archetypes, T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions, and assessed common adult biomarkers such as neoantigen load and TMB. Results A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. Conclusions Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.

  Study EGAS00001007029

• Single-cell RNA sequencing of 6 follicular lymphoma tumors

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Study EGAS00001005257

• Spatiotemporal Genomic Profiling of Intestinal Metaplasia Reveals Clonal Dynamics of Gastric Cancer Progression

  Intestinal metaplasia (IM) is a pre-malignant condition of the gastric mucosa associated with increased gastric cancer (GC) risk. We analyzed 1256 gastric samples (1152 IMs) from 692 subjects from a 10-year prospective study. We identified 26 IM driver genes in diverse pathways including chromatin regulation (ARID1A) and intestinal homeostasis (SOX9), largely occurring as subclonal events. Analysis of clonal dynamics between and within subjects, and also longitudinally across time, revealed that IM clones are likely transient but increase in size upon progression to dysplasia, with eventual transmission of genetic events to paired GCs. Single-cell and spatial profiling highlighted changes in tissue ecology and lineage heterogeneity in IM, including an intestinal stem-cell dominant cellular compartment linked to early malignancy. Expanded transcriptome profiling revealed expression-based molecular subtypes of IM, including a body-resident “pseudoantralized” subtype associated with incomplete histology, antral/intestinal cell types, ARID1A mutations, inflammation, and microbial communities normally associated with the healthy oral tract. We demonstrate that combined clinical-genomic models outperform clinical-only models in predicting IMs likely to progress. Our results raise opportunities for GC precision prevention and interception by highlighting strategies for accurately identifying IM patients at high GC risk and a role for microbial dysbiosis in IM progression.

  Study EGAS00001007067

• ExomeSeq Neoantigen Immunogenicity Landscapes

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007508

• RNASeq Neoantigen Immunogenicity Landscape

  Immune checkpoint blockade (ICB) therapy is a cornerstone of oncologic treatment for patients with advanced stage non-small cell lung cancer (NSCLC) and other malignancies. Neoantigen immunoediting drives ICB efficacy, yet the fundamental physiochemical characteristics of neoantigens and how neoantigen immunogenicity shapes treatment response remains poorly understood. To help address these questions, a prospective clinical trial of NSCLC patients treated with nivolumab was conducted. We assessed genomic alterations in tumors from 58 patients and performed large-scale neoepitope immunogenicity analyses, before and during treatment (CheckMate153, CA209-153). Tumors were analyzed by whole-exome and transcriptome sequencing. In responding patients, loss of mutation and neoantigen burden early during therapy associated with clinical benefit. We evaluated the immunogenicity of 1,453 candidate neoantigens and identified 502 neopeptides that bound to MHC I and 196 neopeptides that were immunogenically recognized by T cells in the setting of nivolumab treatment. These T cell reactive neoantigens were differentially present in clonal populations that underwent distinctive evolutionary trajectories across responders and nonresponders. Mapping these neoantigens to tumor clonal dynamics and clinical response revealed strong selection against immunogenic neoantigen harboring clones compared to non-immunogenic clones. Using this large collection of neoantigens, we identified position specific amino acid features related to immunogenicity, which we used to develop and validate an immunogenicity score. Changes in the genomic and neoantigen immunogenicity landscapes were accompanied by temporal changes in the tumor microenvironment. Nivolumab-induced microenvironmental evolution in NSCLC shared some similarities with that in melanoma, yet critical differences in immunologic programs were apparent from comparative network analysis between tumor types. This study provides unprecedented molecular portraits of the neoantigen landscapes underlying nivolumab’s mechanism of action.

  Study EGAS00001007509

• Breast Cancer PDTX Encyclopaedia

  Molecular data from the collection of PDTX breast cancer models described in Bruna et al, 2016. Cell. It includes whole exome sequencing, shallow whole genome sequencing, expression arrays and reduced bisulfite representation sequencing (RRBS).

  Study EGAS00001001913

• Stratifying and Targeting Pediatric Medulloblastoma through Genomics

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

  Study EGAS00001000273

• Clonal_architecture_of_pre_malignant_and_malignant_tumours

  Single cells have been isolated from normal and pre-invasive lung cancer lesions from one patient. These have been grown into colonies that will then be whole genome sequenced. This will reveal the mutational burden in normal and premalignant tissues, and the heterogeneity between different cells.

  Study EGAS00001001676

• Comprehensive molecular profiling of high-grade serous ovarian cancer

  The diversity and heterogeneity within high-grade serous ovarian cancer (HGSC) is not well understood. Here, we performed comprehensive molecular analysis, including high-pass whole genome sequencing, targeted deep sequencing, RNA sequencing, reverse phase protein arrays and immune assessment, on primary and metastatic sites from highly clinically annotated HGSC samples. Samples were obtained pre-treatment based on a laparoscopic triage algorithm from patients who underwent R0 tumor debulking, or received neoadjuvant chemotherapy (NACT) with excellent or poor response.

  Study EGAS00001003804

• Inference of transcription factor binding from cell-free DNA enables tumor subtype prediction and early detection

  Deregulation of transcription factors (TFs) is an important driver of tumorigenesis, but non-invasive assays for assessing transcription factor activity are lacking. We Here we developed and validated a minimally invasive method for assessing TF activity based on cell-free DNA sequencing and nucleosome footprint analysis. We analyzed whole genome sequencing data for >1,000 cell-free DNA samples from cancer patients and healthy controls using a newly developed bioinformatics pipeline developed by us that infers accessibility of TF binding sites from cell-free DNA fragmentation patterns. We observe patient-specific as well as tumor-specific patterns, including accurate prediction of tumor subtypes in prostate cancer, with important clinical implications for the management of patients. Furthermore, we show that cell-free DNA TF profiling is capable of detection of early-stage colorectal carcinomas. Our approach for mapping tumor-specific transcription factor binding in vivo based on blood samples makes a key part of the noncoding genome amenable to clinical analysis.

  Study EGAS00001003206

• Studying the single cell characteristics of pancreatic cancer

  Pancreatic cancer is a dangerous malignancy in the pancreas. In this study we use single-cell RNA sequencing technique to help understand the transcriptome characteristics of pancreatic tumor cells. This study help understands the complex microenvironment of pancreatic tumors and will likely to benefit clinical research of pancreatic cancer treatments.

  Study EGAS00001003889

• 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

• Single-cell analysis for metastatic gastric adenocarcinoma

  Intra-tumoral heterogeneity (ITH) is the fundamental property of cancer, however, the origins of ITH remain poorly understood. Here we performed single-cell RNA sequencing of peritoneal carcinomatosis (PC) from patients with advanced gastric adenocarcinoma (GAC), constructed a transcriptome map of 45,048 PC cells, profiled the transcriptome states of diverse tumor cell lineages and types, incisively explored ITH of PC tumor cells, and identified significant correlates with patient survival.

  Study EGAS00001004443