10463 results for "cancer rna-seq"

in 54.90 milliseconds.

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• Reliable detection of somatic mutations in solid tissues by laser-capture microdissection and low-input DNA sequencing

  Somatic mutations accumulate in healthy tissues as we age, giving rise to cancer and potentially contributing to ageing. To study somatic mutations in non-neoplastic tissues, we developed a series of protocols to sequence the genomes of small populations of cells isolated from histological sections. Here, we describe a complete workflow that combines laser-capture microdissection (LCM) with low-input genome sequencing, whilst circumventing the use of whole-genome amplification (WGA). The protocol is subdivided broadly into 4 steps: tissue processing, LCM, low-input library generation and mutation calling and filtering. The tissue processing and LCM steps are provided as general guidelines which may require tailoring based on the specific requirements of the study at hand. Our protocol for low-input library generation utilises enzymatic rather than acoustic fragmentation to generate WGA-free whole-genome libraries. Finally, the mutation calling and filtering strategy has been adapted from previously published protocols to account for artefacts introduced via library creation. To date, we have used this workflow to perform targeted and whole-genome sequencing of small populations of cells (typically 100-1,000 cells) in thousands of microbiopsies from a wide range of human tissues. The low-input DNA protocol is designed to be compatible with liquid handling platforms and make use of equipment and expertise standard to any core sequencing facility. However, obtaining low-input DNA material via LCM requires specialized equipment and expertise. The entire protocol from tissue reception through whole-genome library generation can be accomplished in as little as a week, though 2-3 weeks would be a more typical turnaround time.

  Dataset EGAD00001006088

• META-PRISM

  A pan-cancer cohort of 1031 patients resistant to systemic therapies or with no approved therapeutic options. It includes whole-exome sequencing of 571 tumor and matched-normal samples, and transcriptome sequencing of 947 tumor samples. Biopsies were taken at entry into precision medicine trials, often after diagnosed resistance. Comprehensive clinical information is available for all patients and include patient age at biospy, tumor primary site and histological subtype, biopsy site, treatments received prior to biopsy, blood assessment results at biopsy, metastatic sites at biopsy, and survival time from the biopsy date.

  Dataset EGAD00001009684

• hereditary BrEAst Case CONtrol study (BEACCON)

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC.

  Dataset EGAD00001007025

• sWGS of core biopsies from localized breast cancer patients

  Paired end shallow whole genome sequencing (sWGS) data for the identification of genomewide somatic copy number alterations (SCNA) and the estimation of tumor fractions.

  Dataset EGAD00001008397

• Distinct evolutionary trajectories of primary high grade serous ovarian cancers revealed through spatial mutational profiling

  High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to the emergence of treatment-resistant subclones. We sought to measure the degree of genomic diversity within primary, untreated HGSCs to examine the natural state of tumour evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on 31 spatially and temporally separated HGSC tumour specimens (six patients), including ovarian masses, distant metastases and fallopian tube lesions. We found widespread intratumoural variation in mutation, copy number and gene expression profiles, with key driver alterations in genes present in only a subset of samples (eg PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range 10.2 to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole-genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology, with common aetiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating that diversity arises at early stages of tumourigenesis. Our results revealed that HGSCs exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug-resistance mechanisms

  Dataset EGAD00001000669

• Distinct evolutionary trajectories of primary high grade serous ovarian cancers revealed through spatial mutational profiling

  High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to emergence of treatment-resistant sub-clones. We sought to measure the degree of genomic diversity within primary, untreated HGSC to examine the natural state of tumor evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on thirty-one spatially and temporally separated HGSC tumor specimens (six patients) including ovarian masses, distant metastases, and fallopian tube lesions. We found widespread intra-tumoral variation in mutation, copy number, and gene expression profiles, with key driver alterations in genes present in only a subset of samples (e.g. PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range: 10.2% to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology with common etiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating diversity arises at early stages of tumorigenesis. Our results reveal that HGSC exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug resistance mechanisms.

  Dataset EGAD00001000974

• CNS Embryonal tumors

  The dataset represents a total of 58 DNA samples from 16 male and 12 female pediatric patients affected with embryonal central nervous system tumors. The samples were subject to whole genome sequencing, WGS, [48 samples, (representing 12 male and 11 female individuals)] and whole exome sequencing, WES, [10 samples, (representing 4 male and 1 female individuals)]. One tumor tissue sample and one peripheral blood sample were analyzed from each of 26 patients, whereas two tumor tissue samples and one peripheral blood sample were analyzed from two patients. The WGS samples were sequenced 2x150 bp paired-end on an Illumina HiSeqX v2.5 instrument, and the WES samples were sequenced 2x100 bp paired-end on an Illumina HiSeq 2500 instrument. The FASTQ files generated were aligned to the human reference genome sequence GRCh38/hg38 using bwa-mem, with the ALT-aware option turned on. Sorting of reads and marking of PCR duplicates was performed with GATK. Base quality score recalibration and joint realignment of reads around insertions and deletions (indels) were conducted using GATK tools. The dataset consists of 58 files in the CRAM format (lossless compression) with a total file size of ~8,8 TB. All CRAM files but one, are derived from one sequence run and one sample. P4551_227N_P4552_112N is a CRAM file where 2 sequence runs (P4551_227N and P4552_112N) from peripheral blood samples from the same individual, P019, were aligned into one single CRAM file. Additional genomic and molecular data (FASTQ, BAM, IDAT, and VCF files) and limited clinical data can be requested by ethically approved projects conducting research in the field of pediatric cancer.

  Dataset EGAD50000000298

• Identification of RNA biomarkers in Parkinson's disease patients

  Parkinson?s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of dopaminergic neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. By analyzing the transcriptome of early-stage PD patients, this study aims to identify genes (including important non-coding RNAs) and pathways altered at disease onset that may be used as novel biomarkers for PD diagnosis as well as potential new drug targets. The study consists of three main sources of data: first year blood transcriptomes, second year blood transcriptome and matched neural stem cell (NSC)/neuron transcriptomes. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38), processed CAGE tags were clustered ready for differential expression analyses. First year blood sequencing consisted of 22 PD patients and 10 healthy controls across four lanes. In the second year, a further four lanes were sequenced containing 17 PD patients (12 patients from the first year and 5 new patients) along with 10 healthy controls and 5 first year blood samples matching the new second year patients.

  Study JGAS000119

• LCLF1.0 Data

  In this study, we investigated ad libitum food intake of 20 healthy adult volunteers who each completed a 4-week stay at the National Institutes of Health (NIH). During their stay, they consumed a low-carbohydrate, high-fat (LCHF) diet and a low-fat, high-carbohydrate (LFHC) diet for 2 weeks each, in random order. We collected information about energy intake and metabolic changes in response to the two test diets. The test diets were presented to subjects in amounts exceeding their daily energy requirements, and subjects were instructed to eat as much or as little of each diet as desired. This study implemented 7-day rotating menus for each test diet. The diets were matched for presented calories and protein, but the LCHF diet was low in carbohydrate (~10% of calories) and high in fat (~75% of calories) whereas the LFHC diet was high in carbohydrates (~75% of calories) and low in fat (~10% of calories). The two test diets had a common foundation of vegetables with low amounts of digestible carbohydrates such as lettuce, spinach, kale, cabbage, cauliflower, zucchini, tomato, asparagus, broccoli, peppers, brussels sprouts, and green beans. The LCHF diet included meat, poultry, fish, eggs, dairy, and nuts. The LFHC diet included legumes, rice, root vegetables, soy products, corn, lentils, peas, whole grains, bread, and fruit. The test diets were designed using a standard computerized nutrition database, and blood samples were collected from the subjects.

  Study phs003187