5707 results for "canc*"

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• 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

• Resident memory CD8 T cell in human lung cancer

  Study EGAS00001004707

• 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

• Epigenome and transcriptome profiling of chronic lymphocytic leukemia patients

  Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

  Study EGAS00001001821

• QSEA – modelling of genome-wide DNA methylation from sequencing enrichment experiments

  We describe a new method, QSEA, for analyzing methylation enrichment data. We generated a benchmark experiment consisting of MeDIP-seq enrichment data, targeted BS-seq validation data, and RNA-seq data on five pairs of tumor and adjacent normal samples of non-small cell lung cancer patients. Details of the method and its performance on the data have been described in Lienhard et al. (2016).

  Study EGAS00001001822

• Mutation-specific non-canonical pathway of PTEN as a distinct therapeutic target for glioblastoma

  PTEN is one of most frequently altered tumor suppressor genes in malignant tumors. The dominant negative effect of PTEN alteration suggests that aberrant function of PTEN mutation might be more disastrous than deletion, the most frequent genomic event in glioblastoma (GBM). This study aimed to understand the functional properties of various PTEN missense mutations and to investigate their clinical relevance. The genomic landscape of PTEN alteration was analyzed using the Samsung Medical Center GBM cohort and validated via The Cancer Genome Atlas dataset. Several hot-spot mutations were identified, and their subcellular distributions and phenotypes were evaluated. We established a library of cancer cell lines that over-express these mutant proteins using the U87MG and patient-derived cell models lacking functional PTEN. PTEN mutations were categorized into two major subsets: missense mutations in the phosphatase domain and truncal mutations in the C2 domain. We determined the subcellular compartmentalization of four mutant proteins (H93Y, C124S, R130Q, and R173C) from the former group and found that they had distinct localizations; those associated with invasive phenotypes (‘edge mutations’) localized to the cell periphery, while the R173C mutant localized to the nucleus. Invasive phenotypes derived from edge substitutions were unaffected by an anti-PI3K/Akt agent but were disrupted by microtubule inhibitors. PTEN mutations exhibit distinct functional properties with regard to their subcellular localization. Further, some missense mutations (‘edge mutations’) in the phosphatase domain caused enhanced invasiveness associated with dysfunctional cytoskeletal assembly, thus suggesting it to be a potent therapeutic target.

  Study EGAS00001004753

• Identification of 19 novel loci reveals gene regulatory mechanisms determining susceptibility to testicular germ cell tumour

  Testicular germ cell tumour (TGCT) is the most common cancer in young men1,2, and is characterised by strong inherited genetic risk factors3. Here we have undertaken large-scale genome wide association study (GWAS) for TGCT, encompassing ~7,500 cases and ~23,000 controls, through the Oncoarray consortium. We identified 19 novel loci, approximately doubling the number of known TGCT risk loci to 44 (P<5x10-8)4-14 and conduct deep, high-throughput functional annotation of all risk loci. We establish a network of physical interactions for all risk SNPs to candidate casual genes in 3D space, using high-throughput chromosome conformation capture techniques (HiC) in TGCT cells. Firstly, functional evidence reveals widespread disruption of developmental transcriptional regulators, consistent with failed primordial germ cell differentiation as an initiating step in TGCT oncogenesis15. We secondly observe multiple risk loci associated with defective microtubule assembly, compatible with the high level of aneuploidy observed in TGCTs, suggesting gross chromosomal instability. Finally KIT-MAPK signalling features as a recurrently dysregulated pathway. In summary our findings substantially increase the number of known TGCT risk alleles, and provides a functional basis for disease susceptibility.

  Study EGAS00001001836

• Whole exome sequencing of Finnish hereditary breast cancer families

  A remarkable proportion of factors causing genetic predisposition to breast cancer (BC) are unknown in non-BRCA1/2 families. Exome sequencing was performed for 13 high-risk Finnish hereditary breast and/or ovarian cancer (HBOC) families to detect variants contributing to BC susceptibility

  Study EGAS00001001835

• 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

• CancerLocator: Non-Invasive Cancer Diagnosis and Tissue-of-Origin Prediction Using Methylation Profiles of Cell-Free DNA

  Background: The detection and characterization of cell-free DNA in plasma is one of the most promising new areas in cancer diagnosis. Liquid biopsy, unlike traditional tissue biopsy, has the potential to diagnose a variety of different malignancies. Results: Here we propose a probabilistic method, CancerLocator, which exploits the diagnostic potential of cell-free DNA by determining not only the presence but also the location of tumors. CancerLocator simultaneously infers the proportions and the tissue-of-origin of tumor-derived cell-free DNA in a blood sample using genome-wide DNA methylation data. We comprehensively evaluate CancerLocator with simulations and real data, and compare its performance with that of two established multi-class classification methods. We show that the predicted tumor burdens are highly consistent with the true values. In addition, when the proportion of tumor-derived DNAs in the cell-free DNAs is low, the two popular machine learning methods completely fail for cancer diagnosis, while CancerLocator successfully overcomes the challenge. CancerLocator also achieves promising results on patient plasma samples, despite the fact that the DNA methylation data from these samples has very low sequencing coverage. Conclusions: CfDNA methylation may be developed as an important approach for non-invasive early cancer diagnosis.

  Study EGAS00001002211

• Tumor HTG EdgeSeq from metastatic castrate resistant prostate cancer

  This dataset contains tumor bulk HTG EdgeSeq from patients with metastatic castrate resistant prostate cancer. RNA libraries were prepared following manufacturer's user guide (HTG Molecular Diagnostics). Each library was sequenced in HTG EdgeSeq system.

  Study EGAS00001004852

• 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

• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877

• EAC Genomic data

  Study EGAS00001004887

• Circulating Tumor DNA Analysis Detects Minimal Residual Disease and Predicts Recurrence in Patients with Stage II Colon Cancer

  Detection of circulating tumor DNA (ctDNA) after resection of stage II colon cancer may identify those at the highest risk of recurrence and help inform adjuvant treatment decisions. We used massively-parallel-sequencing–based assays to evaluate the ability of ctDNA to detect minimal residual disease in 1046 plasma samples from a prospective cohort of 230 patients with resected stage II colon cancer. In patients not treated with adjuvant chemotherapy, ctDNA was detected post-operatively in 14 of 178 (7.9%) patients, 11 (79%) of whom had recurred at a median follow-up of 27 months; recurrence occurred in only 16 (9.8 %) of the 164 patients with negative ctDNA (HR, 18; 95% confidence interval [CI], 7.9 to 36; P<0.001). In patients treated with chemotherapy, the presence of ctDNA following completion of chemotherapy was also associated with an inferior recurrence-free survival (HR, 11; 95% CI, 1.8 to 68; P=0.001). ctDNA detection after stage II colon cancer resection provides direct evidence of residual disease and identifies patients at very high risk of recurrence.

  Study EGAS00001001839

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Study EGAS00001004975

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005006

• RNA sequencing of PTCL-NOS

  Study EGAS00001005015

• Identification of novel fusion genes in lung cancer using breakpoint assembly of transcriptome sequencing data

  Genomic translocation events frequently underlie cancer development through generation of gene fusions with oncogenic properties. Identification of such fusion transcripts by transcriptome sequencing might help to discover new potential therapeutic targets. We developed TRUP (Tumor-specimen suited RNA-seq Unified Pipeline (https://github.com/ruping/TRUP), a computational approach that combines split-read and read-pair analysis with de-novo assembly for the identification of chimeric transcripts in cancer specimens. We apply TRUP to RNA-seq data of different tumor types, and find it to be more sensitive than alternative tools in detecting chimeric transcripts, such as secondaryrearrangements in EML4-ALK-positive lung tumors, or recurrent inactivating rearrangements affecting RASSF8.

  Study EGAS00001000659

• Stromal cell diversity associated with immune evasion in human triple‐negative breast cancer

  Study EGAS00001005061

• Subtype specific progression from DCIS to invasive breast cancer

  Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.

  Study EGAS00001001866

• Targeted next-generation sequencing of 13 chordoid gliomas of the third ventricle

  Study EGAS00001002733

• early-Duodenal Cancer sequencing study

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  Study EGAS00001006357

• H021-Master Umbrella study2 (not to be released)

  Study EGAS00001005145

• Multi-omics analysis of primary glioblastoma cell-lines shows recapitulation of pivotal molecular features of parental tumors

  Glioblastoma (GBM) is the deadliest primary brain cancer in adults. Emerging innovative therapies hold promise for personalized cancer treatment. Improving therapeutic options depends on research relying on relevant preclinical models. In this line we have established in the setting of the GlioTeX project (GBM and experimental therapeutics), a GBM-patient derived cell line library (GBM-PDCL). Multi-OMIC approach was used to determine the molecular landscape of PDCL and the extent to which they represent GBM tumors.

  Study EGAS00001001871