8255 results for "canc*"

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• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• Genomic Heterogeneity and the Small Renal Mass

  Tumor heterogeneity is believed to represent a barrier to pre-operative genomic characterization in kidney cancer. Previous studies of heterogeneity in clear cell renal cell carcinoma (ccRCC) evaluated only large and metastatic tumors. In small renal tumors in which multiple biopsies are not feasible, the extent of heterogeneity remains unknown. In this study, we evaluated how the extent of genomic heterogeneity in small and large ccRCC. A total of 23 small (<4cm ) and 24 large (>7cm ) ccRCC had 3 regions sampled for evaluation of copy number, clear-cell A/clear-cell B (ccA/ccB) classification, and cell cycle progression (CCP) score. Small tumors have less genomic complexity and significantly fewer subclonal events. Pre-treatment genomic characterization based on a single biopsy in small ccRCC can provide insight into biologic potential to make clinical decisions.

  Study EGAS00001002919

• Psoriatic_arthritis_WGS

  Whole genome sequencing of immune cells from patients diagnosed with psoriatic arthritis

  Study EGAS00001002822

• Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing - NGS targeted capture control cohort

  In routine diagnostic pathology, cancer biopsies are preserved by Formalin-Fixed, Paraffin-Embedding (FFPE) procedures for examination of (intra-) cellular morphology. Such procedures inadvertently induce DNA fragmentation, which compromises sequencing-based analyses of chromosomal rearrangements. Yet, rearrangements drive many types of hematolymphoid malignancies and solid tumors, and their manifestation is instructive for diagnosis, prognosis and treatment. Here, we present FFPE-Targeted Locus Capture (FFPE-TLC) for targeted sequencing of proximity-ligation products formed in FFPE tissue blocks, and PLIER, a computational framework that allows automated identification and characterization of rearrangements involving selected, clinically-relevant, loci. FFPE-TLC, blindly applied to 149 lymphoma and control FFPE samples, identifies the known and novel rearrangement partners. It outperforms fluorescence in situ hybridization (FISH) in sensitivity and specificity, and shows clear advantages over standard capture-NGS methods, finding rearrangements involving repetitive sequences which they typically miss. FFPE-TLC is therefore a powerful clinical diagnostics tool for accurate targeted rearrangement detection in FFPE specimens.

  Study EGAS00001005325

• Placental_genomics

  The aim of this study is to define the mutational landscape of placentas.

  Study EGAS00001003297

• Pancreatic Cancer Sequencing Initiative OICR

  Pancreatic Cancer Sequencing Initiative for the International Cancer Genome Consortium at the Ontario Institute for Cancer Research.

  Study EGAS00001000395

• A novel TP53-KPNA3 translocation defines a de novo treatment-resistant clone in osteosarcoma

  Osteosarcoma is the most common primary bone cancer. It can be cured by aggressive surgery and chemotherapy, but outcomes for metastatic or chemoresistant disease remain dismal. Cancer sequencing studies have shown that the p53 pathway is dysregulated in nearly every case, often by translocation; however, no studies of osteosarcoma evolution or intratumor heterogeneity have been done to date. We studied a patient with chemoresistant, metastatic disease over the course of three years. We performed exome sequencing on germline DNA and DNA collected from tumor at three separate timepoints. We compared variant calls and variant allele frequencies between different samples. We identified subclonal driver mutations in several different genes in the primary tumor sample and found that one particular subclone dominated subsequent tumor samples at relapse. This clone was marked by a novel TP53-KPNA3 translocation and loss of the opposite-strand wild-type TP53 allele. Future research must focus on functional significance of such clones and strategies to eliminate them.

  Study EGAS00001001805

• High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

  Lung adenocarcinoma is one of the most common cancer types with various treatment modalities. However, better biomarkers to predict therapeutic response are still needed to improve precision medicine. We utilized a consensus hierarchical clustering approach on 509 LUAD cases from TCGA to identify five robust LUAD expression subtypes. We then integrated genomic (patient and cell line) and proteomic data to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles.

  Study EGAS00001006461

• Ovarian cancer organoid biobank

  Ovarian cancer (OC) is a heterogeneous disease usually diagnosed at a late stage. Experimental in vitro models that faithfully capture the hallmarks and tumor heterogeneity of OC are limited and hard to establish. We present a novel protocol that enables efficient derivation and long-term expansion of OC organoids. Utilizing this protocol, we have established 56 organoid lines from 32 patients, representing the spectrum of ovarian neoplasms, including non-malignant borderline tumors, as well as mucinous, clear-cell, endometrioid, low- and high-grade serous carcinomas. OC organoids recapitulate histological and genomic features of the pertinent lesion from which they were derived, illustrating intra- and inter-patient heterogeneity, and can be genetically modified. We show that OC organoids can be used for drug screening assays and capture different tumor subtype responses to the gold standard platinum-based chemotherapy, including acquisition of chemoresistance in recurrent disease. Finally, OC organoids can be xenografted, enabling in vivo drug sensitivity assays. Taken together, this demonstrates their potential application for research and personalized medicine.

  Study EGAS00001003073

• Neoadjuvant chemotherapy alters the genomic landscape and immune microenvironment of breast cancers

  To characterize the effects of neoadjuvant chemotherapy (NAC) on the genome, transcriptome and tumor infiltrating leukocytes (TILs), we have conducted whole exome and whole transcriptome sequencing of a comprehensive, longitudinal breast cancer cohort consisting of 146 cases and 281 paired tumor samples. In total, 52 (38%) patients achieved pathologic complete response (pCR) while 85 patients (62%) had residual disease with standard chemotherapy regimen. Tumor biopsies were collected for each patient at three time points – pre-treatment, three weeks after the first cycle of anthracycline and cyclophosphamide (AC) and at the time of surgery after 3 more cycles of AC followed by 4 cycles of taxane or taxane plus Herceptin in case of HER2+ subtype.

  Study EGAS00001003354

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__BRCA_Carriers__Targeted_

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastectomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Targeted data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer.

  Study EGAS00001003315

• Pancreatic cancer organoids recapitulate disease and allow personalized drug screening

  We report derivation of 30 Patient-Derived Organoid lines (PDOs) from tumors arising in the pancreas and distal bile duct. PDOs recapitulate tumor histology and contain genetic alterations typical for pancreatic cancer. In vitro testing of a panel of 76 therapeutic agents revealed sensitivities currently not exploited in the clinic. The PRMT5 inhibitor EZP015556, shown to target MTAP negative tumors, was validated as such, but also appeared to constitute an effective therapy for a subset of MTAP+ tumors. Taken together, the work presented here provides a platform to identify novel therapeutics to target pancreatic tumor cells using PDOs.

  Study EGAS00001003369

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

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

  Study EGAS00001003723

• Infant_Spindle_Tumour_Study

  We aim to describe the transcriptomic landscape of infant spindle cell tumours.

  Study EGAS00001002935

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

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

  Study EGAS00001000526

• Genome-wide quantification of rare somatic mutations in normal human tissues using massively parallel sequencing

  We present Bottleneck Sequencing System (BotSeqS), a nextgeneration sequencing method that simultaneously quantifies rare somatic point mutations across the mitochondrial and nuclear genomes. BotSeqS combines molecular barcoding with a simple dilution step immediately prior to library amplification. We use BotSeqS to show age and tissue-dependent accumulations of rare mutations and demonstrate that somatic mutational burden in normal tissues can vary by several orders of magnitude, depending on biologic and environmental factors. We further show major differences between the mutational patterns of the mitochondrial and nuclear genomes in normal tissues. Lastly, the mutation spectra of normal tissues were different from each other, but similar to those of the cancers that arose in them. This technology can provide insights into the number and nature of genetic alterations in normal tissues and can be used to address a variety of fundamental questions about the genomes of diseased tissues.

  Study EGAS00001001838

• Tumor suppressor miR-133a modulates the prostate cancer epigenome by repressing BAZ2A

  Our study revealed a new subgroup of prostate tumors defined by the expression of a novel prognostic marker, BAZ2A, and the first time to show the establishment of CIMP via an microRNA-epigenetic interaction in prostate tumors.

  Study EGAS00001000568

• 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

• DNA Methylation loss coupled with mitotic cell division promotes immune evasion of tumours with high mutation load

  Mitotic cell division increases tumour mutation burden and copy number load with a positive and inverse correlation, respectively, with the clinical benefit of immunotherapy. Markers of cell division correlate also with genomic demethylation involving methylation loss in late-replicating partial methylation domains. Here we find that immunomodulatory pathway genes are concentrated in these domains and transcriptionally repressed in demethylated tumours with CpG island promoter hypermethylation. Global methylation loss correlated with immune evasion signatures independently of mutation burden and aneuploidy. Methylome data of our cohort (n = 60) and a published cohort (n = 81) in lung cancer and a melanoma cohort (n = 40) consistently demonstrated that genomic methylation alterations counteract the contribution of high mutation burden and increase immunotherapeutic resistance. Higher predictive power was observed for methylation loss than mutation burden. We also found that genomic hypomethylation correlates with the immune escape signatures of aneuploid tumours. Hence, DNA methylation alterations implicate epigenetic modulation as a combination regimens for precision immunotherapy.

  Study EGAS00001003731

• A system-wide approach to monitor responses to synergistic BRAF and EGFR inhibition in colorectal cancer cells

  Molecular heterogeneity of tumors, epigenetic changes and a diverse range of molecular mechanisms are main contributors to drug resistance, which represents one of the great challenges in cancer treatment. A deeper understanding of the molecular biology of cancer has resulted in better targeted therapies, where one or multiple drugs are adopted in novel therapies to tackle resistance. This beneficial effect of using combination treatments has to some extent also been observed in colorectal cancer (CRC) patients harboring the BRAF(V600E) mutation, whereby dual inhibition of BRAF(V600E) and EGFR increases antitumor activity. Notwithstanding this success, it is not clear whether this combination treatment is the only or most effective treatment to block resistance. Here, we investigate molecular responses upon single and multi-target treatments, over time, using BRAF(V600E) mutant CRC cells as a well-define model system. Through integration of transcriptomic, proteomic and phosphoproteomics data we obtain a comprehensive overview, revealing both well-known and novel responses. We primarily observe widespread upregulation of tyrosine kinases (RTKs) and and metabolic pathways. This points to by which the treated cells switch energy sources as a defensive response entering a quiescent like state, while activating signalling to re-activate the MAPK pathway.

  Study EGAS00001002654

• Chromothripsis in human breast cancer (HIPO K26K/H017/A017)

  Chromothripsis is a form of genome instability, by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosome(s). Widely assumed to be an early event in tumor development, this phenomenon plays a prominent role in tumor onset. We analyzed chromothripsis in 252 human breast cancers from two patient cohorts (149 metastatic breast cancers, 63 untreated primary tumors, 29 local relapses, 11 longitudinal pairs) using whole-genome and whole-exome sequencing. We showed that chromothripsis affects a substantial proportion of human breast cancers, with a prevalence over 60% in a cohort of metastatic cases and 25% in a cohort comprising predominantly luminal breast cancers (cohorts from HIPO K26K and H017 and A017). In the vast majority of cases, multiple chromosomes per tumor are affected, with most chromothriptic events on chromosomes 11 and 17 including, among other significantly altered drivers, CCND1, ERBB2, CDK12 and BRCA1. Importantly, chromothripsis generates recurrent fusions that drive tumor development. Chromothripsis-related rearrangements are linked with univocal mutational signatures, with clusters of point mutations due to kataegis in close proximity to the genomic breakpoints, and with the activation of specific signaling pathways. Analysis of the temporal order of events in tumors with and without chromothripsis as well as longitudinal analysis of chromothriptic patterns in tumor pairs revealed important insights on the role of chromothriptic chromosomes in tumor evolution.

  Study EGAS00001004662

• Kings_Hepatoblastoma_Behjati_Nanoseq_Managed_Access

  A study of the development of liver based tumours.

  Study EGAS00001006877

• Organoid_Derivation_Project___GRCh38___RNAseq

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001004677

• Tissue and plasma RNA from esophageal cancer and precursor lesions

  In the past decades, the incidence of esophageal adenocarcinoma has increased dramatically in Western populations. Better understanding of disease etiology along with the identification of novel prognostic and predictive biomarkers are urgently needed to improve the dismal survival probabilities. Here, we performed comprehensive RNA (both coding and non-coding) profiling in various samples from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were included. In total, this comprehensive dataset consists of 102 RNA-seq libraries from 51 samples. This unique resource allows for discovery of novel biomarkers and disease mechanisms, comparison of tissue and liquid biopsy profiles, integration of coding and non-coding RNA patterns, and can serve as a validation dataset in other RNA landscaping studies. Moreover, structural RNA differences can be identified in this dataset, including protein coding mutations fusion genes, and circular RNAs.

  Study EGAS00001004939