14989 results for "cancer studies using rna-seq"

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• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• IMMUcan Lung NSCLC2 cohort

  The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

  Study EGAS50000001558

• Myelodysplastic_Syndrome_Follow_Up_Series

  Agilent whole exome hybridisation capture was performed on genomic DNA derived from MDS and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to discover the prevalence of our findings using bespoke pulldown methods and sequencing the products from a larger set of patient DNA.

  Study EGAS00001000224

• Genome-wide DNA methylation profiles of NSCLC xenograft and primary lung tissues for the identification of epigenetic predictive biomarkers.

  Non-small cell lung cancers (NSCLC) are the most common cause of cancer-related deaths worldwide and primarily treated with platinum-based drugs like cisplatin and carboplatin, radiation and surgery. The major challenge in the management of NSCLC are intrinsic or acquired resistance mechanisms with only few published molecular markers which can predict the outcome of the patients. On the other side, changes in DNA methylation are observed in nearly all cancer types making them suitable as biomarker. Here genome-wide methylation profiles from MeDIP-Seq and gene expression profiling data of 22 primary NSCLC, adjacent normal tissue and PDX samples are provided. For each PDX tumor growth rates were measured in absence or presence of chemotherapy.

  Study EGAS00001002479

• Discovery of Colorectal Cancer Susceptibility Genes in High-Risk Families

  Colorectal cancer remains one of the most common cancers in the US with 146,970 new diagnoses and 49,920 deaths estimated for 2009. Colon cancer is also one of the most familial of cancers. Individuals with a first-degree relative with colon cancer have a 2- to 3-fold increased risk, and those with more than one first-degree relative with colon cancer, or a single first-degree relative affected at age 50 years, have a 3- to 6-fold greater risk than those with no family history. The most prominent high-risk colorectal cancer susceptibility genes, APC, MLH1, MSH2, MSH6, and PTEN, were all discovered more than a decade ago. Currently, mutation screening of these genes, plus a short list of additional genes that are responsible for a very small fraction of colorectal cancer, plays an important role in the clinical management of individuals with a strong family history of the disease or syndromic evidence for the presence of a gene mutation. At the other end of the risk spectrum, genome-wide association studies have identified a number of common alleles with very modest effects on colorectal cancer risk; their clinical utility has yet to be established. However, taken together, the known spectrum of genetic effects only explain about one quarter of the overall familial excess of colorectal cancer. It should be emphasized that, at present, the vast majority of individuals seen at familial cancer clinics are counseled on the basis of their family history alone because they do not have mutations in the known susceptibility genes. Accordingly, the long-term objective of this project is to identify the majority of genes responsible for the unexplained component of inherited colorectal cancer risk. Nextgen DNA sequencing is well suited for application to research questions in genetic susceptibility for which linkage analysis is confounded by extensive genetic heterogeneity. Taking advantage of unparalleled familial cancer genetics resources available through the Utah Population Database, candidate genes have been identified by sequencing all of the gene exons in the human genome from a series of colorectal cancer cases with a very strong family history of colorectal cancer not explained by one of the currently known high-risk susceptibility genes.

  Study phs001787

• UCL Centre for Longitudinal Studies

  Dac EGAC00001001041

• snMultiome Studies of University of Copenhagen

  Dac EGAC50000000924

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• Duplex sequencing of selected breast cancer patients

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primaty tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000769

• WES of breast cancer patients and controls

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primary tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000770

• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• TIGER-LC High-Throughput Sequencing

  Intrahepatic cholangiocarcinoma (CCA) and hepatocellular carcinoma (HCC) are clinically disparate primary liver cancers with etiological and biological heterogeneity. We performed sequencing on multiple data levels of Thai CCA and HCC among the Thailand Initiative in Genomics and Expression Research for Liver Cancer (TIGER-LC) cohort using targeted OncoVar platform, whole exome, whole transcriptome, and whole genome metagenomic sequencing.

  Study phs001199

• Exploration of predictive biomarkers for postoperative recurrence of stage II/III colorectal cancer using genomic sequencing

  To identify biomarkers that can predict treatment outcomes, we compared the mutational profiles of surgically resected specimens from patients with recurrent cancer with those from patients with non-recurrent cancer. Target sequencing, whole-exome sequencing (WES), or whole-genome sequencing (WGS) was perfomed.

  Study JGAS000335

• Bacterial SNPs in the human gut microbiome associate with host BMI

  Genome-wide association studies (GWAS) have revolutionized the field of genetics, providing numerous associations between human SNPs and health traits. Likewise, metagenome-wide association studies (MWAS) between bacterial SNPs and human traits can suggest mechanistic links between the microbiota and its host. However, very few such studies have been done to date, in part due to the large number of samples required to address the variable coverage of bacteria across samples and the fact that most bacteria are present in only a subset of the population. Here, we devised an MWAS framework to detect SNPs and associate them with host phenotypes systematically. We recruited and obtained gut metagenomic samples from a cohort of 7,190 healthy individuals and discovered 1,358 statistically significant associations between a bacterial SNP and host body mass index (BMI). To address the possible effects of population structure and linkage disequilibrium, we applied a clumping procedure, and found 40 independent associations between SNPs and host BMI. We uncovered BMI-associated SNPs in the genomes of 27 bacterial species, even though the relative abundance of 12 of these species was not associated with the phenotype. We separated genome-wide sub-species variations from local associations in individual SNPs, and demonstrated how this framework can highlight specific bacterial functions of interest. Our results demonstrate the importance of considering nucleotide-level diversity in microbiome studies and pave the way toward a better understanding of interpersonal gut microbiome differences and their health implications.

  Study EGAS00001007204

• WXS and RNA-seq raw sequence data for TG project

  WXS sequence data from 112 samples, RNA-seq sequence data from 117 samples, all sequence data are raw sequence data in fastq format, sequenced by Illumina platform.

  Dataset EGAD00001007989

• Gastrointestinal Cancer Treatment Responders

  Comprehensive genomic profiling of colon adenocarcinomas has revealed multiple recurrent alterations that may inform new treatment strategies. Clinical trials of these agents are ongoing, although the mechanisms of response and resistance to these agents are not well characterized. The goal of this study is to perform comprehensive profiling of pre-treatment and post-resistance tumor and germline samples obtained from patients with colon cancer who receive these agents by carrying out whole exome sequencing and RNA sequencing, and to use these data to identify mechanisms of response and resistance.

  Study phs000803

• Acquired Cross-Resistance in Small Cell Lung Cancer Patient-Derived Xenografts

  Here we present whole genome sequencing and RNA sequencing of patient-derived xenograft (PDX) models of small cell lung cancer (SCLC). These models were derived at a variety of clinical time points from either biopsy/resection samples, malignant effusions, or circulating tumor cells (CTCs), and grown in the subcutaneous flank of NSG (NOD.Cg-Prkdcscid Il2rgtm1Wjl /SzJ) mice. The first analysis published with these data was to determine the genomic and transcriptomic features of PDX models derived after relapse that demonstrated in vivo resistance to multiple chemotherapy regimens (cross-resistance).

  Study phs003486

• ChIP-seq data in MSC_Pat and EWIma1 (FLI1 & H3K27ac)

  Ewing sarcoma is characterized by pathognomonic translocations fusing most frequently EWSR1 with FLI1 (EF1). In addition, Ewing sarcoma can also display alterations in STAG2, TP53 and CDKN2A (SPC). Starting from Ewing sarcoma derived human mesenchymal stem cells (MSCpat), we recapitulated this translocation and SPC alterations using a CRISPR/cas9 approach and generated a bona fide Ewing sarcoma model (EWIma1) displaying transcriptomic and epigenetic hallmarks of EwS.

  Study EGAS50000001172

• WNT-dependent interaction between inflammatory fibroblasts and FOLR2+ macrophages promotes fibrosis in chronic kidney disease

  Chronic kidney disease (CKD) is a public health problem driven by myofibroblast accumulation, leading to interstitial fibrosis. Heterogeneity is a recently recognised characteristics in kidney fibroblasts in CKD, but the role of different populations is still unclear. Here, we characterize a proinflammatory fibroblast population (named CXCL-iFibro), which corresponds to an early state of myofibroblast differentiation in CKD. By performing immunofluorescence studies and spatial transcriptomics analysis on 2 patients, we demonstrate that CXCL-iFibro co-localize with macrophages in the kidney and participate in their attraction, accumulation, and switch into FOLR2+ macrophages from early CKD stages on. In vitro, we cultured primary inflammatory fibroblasts that we characterized by using bulk RNAseq. We show that macrophages promote the switch of CXCL-iFibro into ECM-secreting myofibroblasts through a WNT/-catenin-dependent pathway, thereby suggesting a reciprocal crosstalk between these populations of fibroblasts and macrophages. Finally, the detection of CXCL-iFibro at early stages of CKD is predictive of poor patient prognosis, which shows that the CXCL-iFibro population is an early player in CKD progression and demonstrates the clinical relevance of our findings.

  Study EGAS50000000101