14312 results for ""Pennsylvania+German"+ACS+study+'Socius'+open+access"

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• RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

  Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

  Study EGAS00001000761

• A Comprehensive Catalogue of Somatic Mutations from a Human Cancer Genome

  We have carried out complete sequencing of the genome of the human male maligant melanoma cell line COLO-829 using the Illumina Genome Analyzer II. We generated a sequencing library with a median insert size of ~200 bp following random fragmentation and gel fractionation of the genomic DNA. We sequenced 75 bases from both ends of these templates to cover the COLO-829 genome to an average depth of more than 40x. We have carried out purity-filtering (PF) to remove mixed reads, where two or more different template molecules are close enough on the surface of the flow-cell to form a mixed or overlapping cluster. No other filtering of the data has been carried out prior to submission. We have also submitted sequence data for a lymphoblastoid control cell line COLO-829BL from the same individual.

  Study EGAS00000000052

• Massive Genomic Rearrangment Acquired in a Single Catastrophic Event During Cancer Development

  Cancer is driven by mutation. Using Agilent exome hybridisation capture and Illumina GA massively parallel sequencing technology, we aim to sequence ~1600 microRNAs plus the protein coding genome of 25 matched human renal cancer samples. Bespoke algorithms are being developed to identify the somatically acquired point mutations, insertions and deletions in these samples. This project will give unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with renal cancer development.Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00000000029

• Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts

  MicroRNAs (miRNAs) are regulatory noncoding RNAs that affect the production of a significant fraction of human mRNAs via post-transcriptional regulation. Interindividual variation of the miRNA expression levels is likely to influence the expression of miRNA target genes and may therefore contribute to phenotypic differences in humans, including susceptibility to common disorders. The extent to which miRNA levels are genetically controlled is largely unknown. In this report, we assayed the expression levels of miRNAs in primary fibroblasts from 180 European newborns of the GenCord project and performed association analysis to identify eQTLs (expression quantitative traits loci). We detected robust expression for 121 miRNAs out of 365 interrogated. We have identified significant cis- (10%) and trans- (11%) eQTLs. Furthermore, we detected one genomic locus (rs1522653) that influences the expression levels of five miRNAs, thus unraveling a novel mechanism for coregulation of miRNA expression

  Study EGAS00000000056

• Clonally heritable gene expression imparts a layer of diversity within cell types

  Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high coverage single cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging and disease.

  Study EGAS50000000161

• SCANDARE MACARON

  Among gynecological cancers, high-grade serous ovarian cancer has the highest prevalence and more than 75% of patients have advanced stage at diagnosis with a 5-year survival of 40%. When the initial complete surgical removal is not possible (60% of patients), an interval surgery can be considered after three to four cycles of neoadjuvant chemotherapy to reduce the tumor mass. However, in approximately 50% of cases the tumor has little or no response to neoadjuvant chemotherapy. Therefore, identification of potential drug targets, biomarkers and/or pathways whose modulation can help in the prevention, interception, or curing of the disease is essential to address the unmet need. Therefore, MACARON project aims to address these issues through the identification of shared neoantigens arising out of somatic alterations and aberrant transcriptional programs in ovarian cancer DNA/RNA datasets.

  Study EGAS50000000145

• Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

  Small cell lung cancer (SCLC) is one of the deadliest human cancers with a five-years survival rate of less than 7%. The standard of care for extensive-stage SCLC consists of systemic treatment with platinum and etoposide, recently combined with PD-L1 immune checkpoint inhibitors (ICI). SCLC patients show high sensitivity to platinum-based chemotherapy, followed by rapid recurrence, which distinguishes SCLC from most human cancers. Unfortunately, second-line treatment with other chemotherapeutics or immunotherapy is only marginally effective, and patients ultimately succumb to their disease. We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC. We determined tumor phylogenies at diagnosis and throughout chemotherapy and immunotherapy by multi-region sequencing of 160 tumors from 65 patients, to thus decipher the evolutionary processes underlying the remarkable sensitivity of small cell lung cancer (SCLC) to chemotherapy.

  Study EGAS50000000169

• RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

  RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dataset EGAD50000000333

• UK Biobank whole cohort directly genotyped and imputed data (~500,000 participants)

  Genotype data is available for all 500,000 participants in the UK Biobank cohort. Genotyping has been performed using the Affymetrix UK BiLEVE Axiom array on an initial 50,000 participants and the remaining 450,000 participants have been genotyped using the Affymetrix UK Biobank Axiom® array. The two arrays are extremely similar (with over 95% common content).Quality control and imputation (to over 90 million SNPs, indels and large structural variants) has been performed by a collaborative group headed by the Wellcome Trust Centre for Human Genetics.The following data are available:* A clean set of QC’ed genotype calls* Confidence values that a genotype call is correct* Intensity data to generate cluster plots* Extensive QC information regarding SNPs and samples including SNP metrics, batch effects, population structure and relatedness* Imputed dataFor further information, please refer to the UK Biobank website

  Study EGAS00001002399

• ARST17B2-Q Germline and Somatic Genetic Landscape of Pediatric Rhabdomyosarcoma

  Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. While these malignancies display aberrant myogenic differentiation, relatively little is known about genetic susceptibility to RMS, or how genetic variants influence subsequent somatic events and may be used in risk stratification strategies. A small percentage of cases are associated with mutations in TP53 (Li-Fraumeni syndrome), HRAS (Costello syndrome), and PTCH1 (nevoid basal cell carcinoma syndrome/Gorlin syndrome), suggesting the genetic origins of childhood RMS. In spite of this, little work has been done to characterize genetic susceptibility to this malignancy. We plan to leverage samples collected as part of D9902 to conduct one of the largest germline genomic studies of RMS. We anticipate that once genetic associations are identified, researchers can use the information to develop better strategies to detect, treat, and prevent childhood RMS.

  Study phs003192