14982 results for "cancer studies using rna-seq"

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• Asian Immune Diversity Atlas (AIDA) sQTL

  Current efforts within the Human Cell Atlas (HCA) are largely focused on defining reference human cell types using a relatively small number of samples of predominantly European origin. However, the next phase of the HCA is likely to address the topic of human diversity by comprehensively characterizing variation in cell states across age, sex, population groups, diseases and environments. To spur this next phase, and also expand the geographical scope of the HCA, we propose an HCA-Asia seed network to generate an Asian Immune Diversity Atlas (AIDA). AIDA will generate transcriptome variation datasets from 5 major Asian population groups (Chinese, Japanese, Korean, Indian, Malay), define an atlas of Asian cell types and states, and characterize their variation associated with ethnicity, age and sex. We will also formalize a study design based on common controls that can in principle reduce technical artifacts in a broad range of comparative single cell studies. This study design will be complemented with novel algorithms designed to normalize datasets of interest against the common controls, to increase the robustness of biological inferences. In addition to providing new tools and resources to the HCA, this seed network will serve as a template for future comparative studies in the single cell field.The AIDA dataset consists of scRNA-seq (10x 5′ v2 scRNA-seq) and genotype (Illumina Infinium Global Screening Array v.3) data. In the AIDA splicing quantitative trait loci (sQTL) project, we identified 11,577 independent cis-sQTLs, 607 trans-sQTLs, and 107 dynamic sQTLs. The post-imputation genotype for the Japanese and Korean cohort will be available through dbGaP. The Singaporean (ethnically Chinese, Indian and Malay) genotypes require a data access application to the HELIOS Data Access Committee (helios_science@ntu.edu.sg). European samples are used as control.

  Study phs003848

• Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas

  Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents and ranges on the spectrum of malignancy from low-grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF. However, in approximately 50% of cases, no genetic driver has been established. Clinical whole genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine−threonine kinase that activates MEK. The patient who had exhausted all other therapeutic options was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1-8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements - uncovered by comprehensive clinical sequencing of a single case - are the most common genetic event in spitzoid melanoma, are present in adult melanomas, and could be amenable to MEK inhibition.

  Study EGAS00001003430

• A Genomic Approach to Improved Diagnosis and Treatment of Neuroendocrine Tumors

  These are RNA-Seq samples from patients undergoing surgery for small bowel and pancreatic neuroendocrine tumors. Normal tissue, primary tumors, lymph nodes, and liver metastases were collected at surgery and stored in RNAlater until RNA extraction was carried out for RNA-Seq.

  Study phs001772

• Cancer Risk Estimates Related to Susceptibility Genes (CARRIERS)

  The CARRIERS study utilized custom amplicon-based variant screening of known cancer predisposition genes in germline DNA from breast cancer cases and age matched unaffected controls taken from predominantly cohort-based breast cancer case-control studies to establish the risks of breast cancer associated with pathogenic variants in these genes.

  Study phs002820

• RNA sequencing and Illumina 2.5M SNP array data collected from 675 commonly used human cancer cell lines.

  Tumor-derived cell lines have served as vital models to advance our understanding of oncogene function and therapeutic response1. Although substantial effort has been directed to defining the genomic constitution of cancer cell line panels2–4, the transcriptome – which represents the active program of a cell – remains understudied. Here, we describe RNA sequencing and SNP array analysis of 675 commonly used human cancer cell lines. We explore numerous transcriptome features including coding and non-coding gene expression, transcribed mutations, gene fusion and expression of non-human sequences. Aside from many known aberrations we find new surprising characteristics, including more than 2200 unique fusion gene pairs representing a vast, testable repertoire of oncogenic fusions, many of which have analogs found in primary human tumors. We show that a combination of multiple genome and transcriptome features in a novel pathway-based approach enhances prediction of response to various targeted therapeutics. Our results provide valuable new insights into these critical pre-clinical models and provide added context for interpreting the numerous studies that employ these widely used cell lines.

  Study EGAS00001000610

• Kidney Two-Hit Mapping

  Germ-line genetic variants identified thus far generally account for only part of the genetic risk predicted for most cancers. A component of the remaining risk may be explained by functionally consequent genetic variants that are individually very rare (or private to that individual's family). While their identification may be highly informative for cancer etiology and biological knowledge, strategies that allow for agnostic (genome-wide) identification of such genes are not straight forward. This is particularly true for rare cancers where sufficient numbers of patients may simply not be available for appropriate statistically powered studies. In this project we have explored a study design based around the concept of "two-hit mapping" using the co-occurrence of germ-line and somatic mutations in the same gene to assist in the identification of susceptibility genes. The dataset includes 54 kidney cancer patients selected for enrichment of genetic disease, that is patients with: early age of onset and/or family history and/or bilateral disease. Germ-line and somatic (kidney cancer) tumor sequencing was carried out. These data may improve our understanding of kidney cancer.

  Study phs001971

• RNA-seq analysis of human primary keratinocytes and skin

  Bulk and single cell RNA-seq analysis of human keratinocyte and human skin

  Study EGAS00001002981

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Study EGAS00001003973

• Pooled Single-Cell RNA-Seq of iPSC-Derived Neural Stem Cells from ADHD and Control Individuals

  This dataset contains FASTQ files from pooled single-cell RNA sequencing (scRNA-seq) of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs). The iPSCs were reprogrammed using the non-integrative Sendai virus system (CytoTune-iPS 2.0), introducing OCT3/4, SOX2, KLF4, and cMYC. Donor somatic cells included keratinocytes, PBMCs, and lymphoblastoid cell lines from individuals with ADHD and age-matched healthy controls (6–18 years). iPSCs underwent standard quality control, including immunocytochemistry, qRT-PCR, mycoplasma testing, and SNP genotyping. NSCs were produced via neural induction and validated by qRT-PCR and immunostaining for PAX6, SOX2, NESTIN, TUJ1, and FOXG1. Sequencing was performed on the Illumina NovaSeq 6000.

  Dataset EGAD00001015644

• Genomic and Transcriptomic Profiling of Patients with Malignant Pleural and Peritoneal Mesothelioma: The NCI Cohort

  Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. Better understanding of mesothelioma genomics and transcriptomics could advance novel therapies. We performed whole-exome sequencing (WXS) of germline and tumors of 122 patients, and RNA-sequencing (RNA-Seq) of tumor samples of 100 patients with pleural, peritoneal, and tunica-vaginalis mesothelioma.The biospecimens used in this study were collected as a part of the Mesothelioma Natural History Protocol (https://clinicaltrials.gov/ct2/show/NCT01950572), wherein, samples were collected from subjects with malignant mesothelioma as listed in the eligibility criteria below and written consent from each participant was obtained before sample acquisition.

  Study phs002207

• BMP4 and temozolomide synergize in the majority of patient derived glioblastoma cultures

  The poor prognosis of patients with glioblastoma is partly due to resistance to standard treatment, which combines chemoradiation using temozolomide (TMZ). The concept of cancer stem cells provided new insight into tumor resistance and management, and isolated Glioblastoma stem-like cells (GSCs) which contribute to this therapy resistance. Bone morphogenetic protein 4 (BMP4) is a differentiation factor that stimulates astroglial differentiation of such GSCs, thereby reducing their self-renewal. Exposing GSCs to BMP4 could therefore sensitize them to chemotherapy with TMZ, but previous studies with various treatment paradigms have produced contradictory results in this matter. Therefore, we re-defined the optimal treatment paradigm for the combination of TMZ and BMP4 and subsequently re-assessed the inter-tumoral variability in response to co-treatment with TMZ+BMP4 in vitro. First, the simultaneous treatment was found more effective than sequential therapy. Second, after application of our optimized treatment protocol, 70% of a total of 20 patient-derived glioblastoma cultures showed synergy when the treatments were combined. The synergistic effect was a result of increased cellular apoptosis and not of decreased proliferation. Comparative RNA-sequencing suggested that combination treatment results in decreased MAPK signaling. We conclude that addition of BMP4 to standard therapy with TMZ could enlarge the group of patients with good therapeutic response.

  Study EGAS00001007095

• Molecular Subtype-specific Biomarkers Improves Colorectal Cancer Prognostication

  Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC according to natural molecular subtypes, however, this strategy is not yet able to provide clinicians with improved tools for decision-making. We here present an extended framework for CRC stratification that specifically aims to improve patient prognostication. Using transcriptional profiles from 1,100 CRCs, including a novel set of >300 samples, we identify novel cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the microbiome. Notably, our subtyping strategy allowed identification of novel archetype-specific prognostic biomarkers that provided information beyond and independent of UICC-TNM staging, MSI-status and consensus molecular subtyping. The results illustrate that our extended subtyping framework, combining subtyping and subtype-specific biomarkers, could contribute to improved patient prognostication and may form a strong basis for future studies.

  Study EGAS00001002376

• Assessment of RNA-Seq Sample Preparation Methodology

  The goal of this study was two-fold, to determine if common purification techniques have any effect on downstream differential expression analysis and to evaluate combinations of alignment and differential expression software for reliability. To this end, blood was collected from three individuals and pooled during and after extraction. After pooling and mixing was completed, samples were divided into three aliquots for testing. The first aliquot was a control and not purified or concentrated. It was diluted to produce samples of varying concentrations for testing. The second aliquot was diluted to 20 ng/μL and used to test six different variations on the AMPure XP bead purification procedure. The last aliquot was also diluted to varying concentrations of 60, 30, and 9.6 ng/μL and purified using MinElute columns. Samples were submitted for total RNA-Seq library preparation and sequencing. Library preparation was performed using the TruSeq Stranded Total RNA with Ribo-Zero Globin kit (20020612, Illumina Inc.), and 2x150 bp PE sequencing was done on an Illumina NovaSeq 6000 with the S4 reagent kit. Comparisons were made between methods (AMPure vs. unpurified, AMPure vs. MinElute, MinElute vs. unpurified) to assess the effects of purification method on downstream differential expression. Comparisons were also made within methods using the varying concentrations tested for unpurified samples and for MinElute purified samples to assess the effects of concentration on differential expression. Variations of the AMPure procedure were also compared to assess the effectiveness of the variations tested in comparison to the unmodified procedure. A subset of samples was selected for use with alignment and differential expression package comparison. Unpurified high concentration samples eluted in RNAse-free water were compared to unpurified high concentration samples eluted in BR5, a buffer from the PAXgene blood miRNA kit, with the expectation that there should be no or very few differentially expressed genes. Unpurified high concentration samples eluted in RNAse-free water were also compared to unpurified low concentration samples also eluted in RNAse-free water, with possibly a small number of differentially expressed genes anticipated. A third dataset of simulated RNA-seq data was created with a known rate of differential expression. These files were aligned using Bowtie2, HISAT2, kallisto, RSEM, Rsubread, Salmon, and STAR. Results were then analyzed for differential expression using ALDEx2, baySeq, DEGseq, DESeq2, edgeR, limma, NOISeq, PoissonSeq, and SAMseq. Differential expression results of all three comparisons were evaluated to determine which combinations provided the most reliable results for both real and simulated data.

  Study phs003001

• Dataset for Ewing_sarcoma_PNET-RNA

  Rare cancer sequencing data of 28 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008845