15020 results for "cancer studies using rna-seq"

in 14.10 milliseconds.

• Circular RNA characterization in functionally distinct brain regions

  RNA extracted from middle temporal gyrus (MG) brain region of healthy elderly controls. Three pairs of samples were generated, each pair consisting of one sample that was enriched for circular RNAs using RNase R, and a second sample that was not enriched (total N=6). Remaining samples in the study from other functionally distinct brain regions are currently under process and will be released soon.

  Dataset EGAD00001004211

• RNAseq_pituitary_adenoma

  Total RNA was extracted using RNAble (Eurobio), cleaned-up with RNeasy columns (Qiagen) and sequenced. The libraries were prepared at the Genomics Platform of the Cochin Institute, following the TruSeq Stranded mRNA protocol (Illumina), starting from 1 µg of high quality total RNA. Paired end (2 × 75 bp) sequencing was performed on a Nextseq 500 platform (Illumina). FASTQ sequences were aligned on hg19 (GRCh37) human reference genome with STAR (v.2.5.2a)

  Dataset EGAD00001004996

• oncogenic gene fusions in primary colon cancers

  This dataset represents RNA-sequencing data from 278 primary colon cancers obtained from fresh-frozen tumor sections. RNA-sequencing was performed using TruSeq library preparation and samples were sequenced on Illumina NextSeq and HiSeq. The data are available as Illumina NextSeq and HiSeq fastq files (_R1.fastq and _R2.fastq for each tumor sample, 556 files in total).

  Dataset EGAD00001003291

• Multicenter AIDS Cohort Study (MACS)

  The Multicenter AIDS Cohort Study (MACS) - now part of the MACS-WIHS Combined Cohort Study (MWCCS) investigates the epidemiology of human immunodeficiency virus (HIV) infection among men who have sex with men. Over 7,000 participants volunteered for semiannual interview, physical examination, and laboratory testing across the 325 years of the study, in four metropolitan areas of Los Angeles, Chicago, Baltimore/Washington (DC) and Pittsburgh. The study aimed to identify risk factors for occurrence and clinical expression of the HIV infection, and to establish a repository of biologic specimens for future study. Study visits included detailed questions covering HIV-related symptoms and utilization of health services, demographic and psychosocial characteristics, a quality of life survey, a physical examination, a detailed form on medications used as prophylaxis and/or treatment, a neuropsychological screening and examination, blood samples to do measure hematologic variables including enumeration of T-cell subsets and HIV viral load and evaluate genetic risk factors via genome wide association studies using data generated using the Infinium Multi-Ethnic Global BeadChip genotyping array in all participants. Men who have sex with men, with and without HIV infection were enrolled in the MACS. MACS data continues to be available through the merged MWCCS cohort.

  Study phs002226

• Botswana 15 autosomal unlinked microsatellites

  Population structure was investigated in 990 Botswana individuals according to ethno-linguistics, Bantu and Khoisan, and geography (the nine administrative districts) using the AmpFLSTR Identifiler autosomal microsatellite markers. Genetic diversity and forensic parameters were calculated for the overall population, and according to ethno-linguistics and geography. The overall combined power of exclusion (CPE) was 0.9999965412 and the combined match probability 6,28 x 10-19. CPE was highest for the Khoisan Tuu ethnolinguistic group and the Northeast District at 0.9999582029 and 0.9999922652 respectively. CMP ranged from 6.28 x 10-19 (Khoisan Tuu) to 1,02 x 10-18 (Northwest district). Using pairwise genetic distances (FST), analysis of molecular variance (AMOVA), factorial correspondence analysis (FCA), and the unsupervised Bayesian clustering method found in STRUCTURE and landscape genetics software TESS, ethno-linguistics were found to have a greater influence on population structure than geography. FCA showed clustering between Bantu and Khoisan, and within the Bantu. This Bantu sub-structuring was not seen with STRUCTURE and TESS, which detected clustering only between Bantu and Khoisan. The patterns of population structure revealed highlight the need for regional reference databases that include ethno-linguistic and geographic location information. These markers have important potential for bio-anthropological studies as well as for forensic applications.

  Study EGAS00001002380

• Presence of rare potential pathogenic variants in subjects under 65 years old with very severe or fatal COVID‑19

  Rare variants affecting host defense against pathogens could be involved in COVID‑19 severity and may help explain fatal outcomes in young and middle‑aged patients. Our aim was to report the presence of rare genetic variants in certain genes, by using whole exome sequencing, in a selected group of COVID‑19 patients under 65 years who required intubation or resulting in death (n = 44). To this end, different etiopathogenic mechanisms were explored using gene prioritization‑based analysis in which genes involved in immune response, immunodeficiencies or blood coagulation were studied. We detected 44 different variants of interest, in 29 different patients (66%). Some of these variants were previously described as pathogenic and were located in genes mainly involved in immune response. A network analysis, including the 42 genes with candidate variants, showed three main components, consisting of 25 highly interconnected genes related to immune response and two additional networks composed by genes enriched in carbohydrate metabolism and in DNA metabolism and repair processes. In conclusion, we have detected candidate variants that may potentially influence COVID‑19 outcome in our cohort of patients. Further studies are needed to confirm the ultimate role of the genetic variants described in the present study on COVID‑19 severity.

  Study EGAS00001006372

• PREDICT

  PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics.

  Study EGAS00001000094

• An Empirical Approach Leveraging Tumorgrafts to Dissect the Tumor Microenvironment in Renal Cell Carcinoma Identifies Missing Link to Prognostic Inflammatory Factors

  We undertook an empirical approach to dissect the tumor microenvironment by developing a bulk tumor dissection algorithm, DisHet, and leveraging RNA-Seq data of tumorgrafts (patient-derived tumors implanted in mice), in which only the tumor cell component expands. We found that approximately 65% of previously defined immune signature genes are not abundantly expressed in the Renal Cell Carcinoma (RCC) microenvironment, and we identified more than two times as many novel immune/stromal transcripts. By using refined immune/stroma-specific genes and genomics, electronic medical record data and imaging data of 1084 RCC patients, we discovered a highly-inflamed pan-RCC subtype enriched for Treg cells, NK cells, Th1 cells, neutrophils, macrophages, B cells, and CD8+ T cells. This inflamed subtype (IS) is enriched for aggressive RCCs, including BAP1-deficient clear-cell and type 2 papillary tumors. Interestingly, IS is correlated with systemic manifestations of inflammation in patients such as thrombocytosis and anemia, whose pathogenesis were poorly defined and have been predictors of poor prognosis in RCC. Indeed, we discovered that IS is a strong predictor of poor survival. Lastly, our analyses show that tumor cells may drive stromal immune response. Overall, these data provide a missing link between the tumor cells, the tumor microenvironment, and systemic factors.

  Study EGAS00001002786

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  The 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.

  Dataset EGAD00001006427

• Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

  Here, we applied single-cell RNA-sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same cHL tumors. This allowed us to identify genes of cell surface proteins that are consistently overexpressed in HRS cells and can potentially be used as targets for antibody-drug conjugates or CAR T cells. Finally, we identify potential interactions by which HRS cells inhibit T cells, among which the Galectin-1/CD69 and HLA-DRA/LAG3 interactions. However, high levels of inter-patient heterogeneity of the interaction strength were observed. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets.

  Study EGAS50000000432