11976 results for "cancer rna-seq"

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• Melbourne Collaborative Cohort Study DNA Methylation Studies

  This dataset contains raw Illumina 450K blood DNA methylation data from a subset of participants in the Melbourne Cohort Study (MCCS), a prospective study of 41,513 healthy adult volunteers (24,469 women) aged between 27 and 76 years when recruited between 1990 and 1994. Nested case-control studies: DNA methylation data were generated as part of cancer case-control studies nested in the MCCS. Participants were cancer-free at blood draw; blood samples were taken at baseline (1990-1994) for 97% of participants; and for 3% of participants at the second wave of follow-up (2003-2007). Eight separate studies were conducted of breast, prostate, colorectal, lung, kidney, urothelial and gastric cancer and B-cell lymphoma, for a total of > 3,500 cancer cases. Controls were individually matched to cases on age, sex, and country of birth using incidence density sampling. Additional matching on smoking history was made for the study of lung cancer. Longitudinal study: For a subset of 1,100 participants with baseline DNA methylation measures (from dried blood spots) who were selected as controls in the nested case-control studies, repeated methylation measures were made using wave 2 follow-up samples (also from dried blood spots) to study longitudinal DNA methylation changes. Project aims: 1. Nested case-control studies: To assess prospective associations between peripheral blood DNA methylation and risk of eight cancer types (breast, prostate, colorectal, lung, kidney, urothelial cell and gastric cancer, and mature B-cell neoplasms). 2. Longitudinal study: To assess associations between lifestyle changes and changes in peripheral blood DNA methylation.

  Study phs003213

• Benchmarking for alignment and variant calling

  Background: Lung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and six structural variant callers comprised of four generic callers (Sniffles2, cuteSV, SVIM and DELLY in generic mode) and two somatic callers (nanomonsv and DELLY in somatic modes). Results: Different combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short read sequencing. When compared to somatic structural variants detected with short read sequencing, more events were detected with long read sequencing. The mean recall of somatic variant events identified by short read sequencing was higher for the somatic callers (64%) than generic callers (52%), with nanomonsv (69%) showing the best performance. Conclusion: Long read sequencing can identify somatic structural variants. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

  Study EGAS00001007819

• MSI-Exome-DAC Team Microsatellites Instability and Cancer, INSERM Hospital Saint-Antoine, Paris 12, France Carte d'identité des tumeurs, French league against cancer, Paris France

  Dac EGAC00001000665

• CLL cancer Sample Sequencing

  CLL cancer Sample Sequencing

  Dataset EGAD00001000004

• Various Cancer Fusion Gene Sequencing

  Various Cancer Fusion Gene Sequencing

  Dataset EGAD00001000005

• Methylation profiles in blood (breast cancer cases)

  Raw methylation data from blood samples in breast cancer cases.

  Dataset EGAD00010002470

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  Study EGAS00001007299

• WES in Angolan and Cape Verdean triple-negative breast cancer samples

  WES in 23 Angolan and 7 Cape Verdean triple-negative breast cancer samples

  Dac EGAC50000000486

• atrial appendage RNA-seq in non-, paroxysmal and persistent atrial fibrillation

  Understanding the interconnectedness of structural remodelling processes atrial fibrillation (AF) in patients could identify targets for future therapies. These data include transcriptome sequencing of atrial tissues of patients without AF, with paroxysmal AF and persistent AF (total n=64). In AF patients, epicardial cell gene expression decreased, contrasting with an upregulation of epithelial to mesenchymal transition (EMT) and mesenchymal cell gene expression. Immunohistochemistry demonstrated thickening of the epicardium and an increased proportion of (myo)fibroblast-like cells in the myocardium, supporting enhanced EMT in AF. We furthermore report an upregulation of endothelial cell proliferation, angiogenesis and endothelial signalling. EMT and endothelial cell proliferation concurred with increased interstitial (myo)fibroblast-like cells and extracellular matrix gene expression including enhanced tenascin-c, thrombospondins, biglycan and versican. Morphological analysis discovered increased and redistributed glycosaminoglycans and collagens in the atria of AF patients. Signalling pathways, including cell-matrix interactions, PI3K-AKT and Notch signalling, that could regulate mesenchymal cell activation, were upregulated. These dynamic processes may provide targets to prevent or reverse structural remodelling.

  Study EGAS00001005295

• RNA-seq of M-CSF differentiated human peripheral monocyte-derived macrophages (MDMs) - Validation macIDR

  Macrophages represent multifunctional leukocytes defined by their stimulus-specific transcriptional reprogramming. As in vivo macrophages are often difficult to obtain, in vitro macrophage models are often used. We aggregated public expression data to define consensus expression profiles for eight commonly-used in vitro macrophage models and built the classifier macIDR, capable of distinguishing macrophage subsets with high accuracy (>0.95). Classification of in vivo macrophages suggested that alveolar macrophages resembled interleukin-10 activated macrophages in general whereas chronic obstructive pulmonary disease patients displayed decreased similarity to interferon-γ stimulated macrophages. Adipose tissue-derived macrophages were classified as unstimulated macrophages, but would resemble LPS-stimulated macrophages more in diabetic-obese patients. Rheumatoid arthritic synovial macrophages were similar to macrophages stimulated with interleukin-10 or interferon-γ. Altogether, our results suggest that macIDR is capable of identifying in vitro macrophages. By projecting in vivo macrophages onto the in vitro macrophages, we were capable of elucidating macrophage-specific changes as a result of tissue and disease.

  Study EGAS00001003451

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• Dual targeting of polyamine synthesis and uptake in diffuse intrinsic pontine gliomas

  Bulk RNA-seq data of tumour data.

  Dataset EGAD00001006794

• H3K27ac ChIP-seq in TMPRSS2:ERG positive and negative prostate cancer tissue samples

  The TMPRSS2:ERG (T2E) structural rearrangements typifies ~50% of prostate tumors and results in overexpression of the ERG transcription factor. Using chromatin data collected in T2E and non-T2E primary prostate tumors, we show a distinct cis-regulatory landscape between T2E and non-T2E, inclusive of Cluster Of Regulatory Elements (COREs). This is mediated by ERG co-option of HOXB13 and FOXA1 implementing a T2E-specific transcriptional profile. We also report a T2E-specific CORE on the structurally rearranged ERG locus arising from spreading of the TMPRSS2 locus pre-existing CORE, assisting in its overexpression. Finally, we show that the T2E-specific cis-regulatory landscape reveals a vulnerability against the NOTCH pathway. Taken together, our work shows that overexpressed ERG co-opts master transcription factors to deploy a unique cis-regulatory landscape inducing a druggable dependency on NOTCH signaling in T2E prostate tumors.

  Study EGAS00001002496

• Use of Whole Genome Sequencing for Diagnosis and Discovery in the Cancer Genetics Clinic

  Despite the potential of whole-genome sequencing (WGS) to improve patient diagnosis and care, the empirical value of WGS in the cancer genetics clinic is unknown. We performed WGS on members of two cohorts of cancer genetics patients: those with BRCA1/2 mutations (n = 176) and those without (n = 82). Initial analysis of potentially pathogenic variants (PPVs, defined as nonsynonymous variants with allele frequency < 1% in ESP6500) in 163 clinically-relevant genes suggested that WGS will provide useful clinical results. This is despite the fact that a majority of PPVs were novel missense variants likely to be classified as variants of unknown significance (VUS). Furthermore, previously reported pathogenic missense variants did not always associate with their predicted diseases in our patients. This suggests that the clinical use of WGS will require large-scale efforts to consolidate WGS and patient data to improve accuracy of interpretation of rare variants. While loss-of-function (LoF) variants represented only a small fraction of PPVs, WGS identified additional cancer risk LoF PPVs in patients with known BRCA1/2 mutations and led to cancer risk diagnoses in 21% of non-BRCA cancer genetics patients after expanding our analysis to 3209 ClinVar genes. These data illustrate how WGS can be used to improve our ability to discover patients' cancer genetic risks. "Reprinted from doi:10.1016/j.ebiom.2014.12.003, with permission from EBioMedicine."

  Study phs000942

• Geriatric Oncology Database of genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients to establish truly effective treatment strategy

  Owing to the advent of super-aged society, cancer mortality in Japan is forecasted to become an all-time high. The management of elderly patients with cancer is a serious health issue and the need for specific care guidelines for this population is critical in Japan. The significant individual differences in comorbidity, physical and mental functioning, and social problems among aging individuals are obstacles to the progress. The response to cancer treatment varies significantly among patients, even in the same stage of the same type of cancer. Older aged patients are still less likely to be offered participation in clinical trials, thus the number of clinical evidences is limited. The molecular mechanisms regulating the physiological process of ageing and senescence, and cancer are far from understood. To establish a truly effective treatment algorithm, we attempted to develop a geriatric oncology database for genotypes and methylation, gene expression, clinical data, and survey results on psychosocial and physical conditions in Japanese elderly cancer patients in this retrospective study. The genomic analysis was performed in 62, 106, and 173 cases, respectively for gastric, colon and lung cancers. The clinical data and survey results on psychosocial and physical conditions were collected from 166, 313, and 344 patients respectively for gastric, colon and lung cancers, and also collected from 357, 49, and 300 benign cases respectively for cardiovascular disorder, respiratory dysfunction, diabetes and nephropathy as the analysis control.

  Study JGAS000061

• Long read mRNA sequencing of human neural retinal samples

  Long-read (PacBio) RNA sequencing dataset of three neural retinal samples. Files are raw BAM format files generated by a Sequel II machine. Additionally, the ccs3 BAM format files are included.

  Dataset EGAD50000000101

• Transcriptomic sequencing of early and late passage of mCRC tumoroids

  Dataset of 46 mCRC tumoroids from different passages (23 early-passage 3, 23 late-passage 8-12). FASTQ files of paired sequencing of PolyA-enriched total RNA

  Dataset EGAD50000000153

• RNAseq of samples from CLL patients treated with idelalisib in vivo

  The dataset contains RNA sequencing data from 18 paired samples of 9 CLL patients treated with idelalisib in vivo (median time on therapy 4 weeks; range 2-5 weeks).

  Dataset EGAD50000000878

• Single-cell genotype-to-phenotype (scG2P) of normal esophageal epithelium

  Single-cell genotype-to-phenotype (scG2P) of normal esophageal epithelium, based on targeted DNA genotyping of mutation hot spots and targeted RNA capture.

  Dataset EGAD50000002066

• single cell RNAseq data of lung adenocarcinoma

  Single-cell RNA sequencing was performed for cells from five early-stage LUADs and fourteen multi-region normal lung tissues of defined spatial proximities from the tumors.

  Dataset EGAD00001006936

• Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

  Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

  Dataset EGAD00001005987

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  This dataset contains BAM files for RNA-sequencing of stage I lung adenocarcinomas from Asian patients. In total, there are 107 patients and 107 tumor samples.

  Dataset EGAD00001006187

• anti-SARS-CoV-2 IgG and Fostamatinib treated human primary IL10-M2 macrophages

  RNA sequencing data of anti-SARS-CoV-2 spike IgG (monoclonal or patient serum), poly(I:C) and Fostamatinib treated human primary IL10-M2 macrophages

  Dataset EGAD00001007512

• Human tumor single-cell mutiome

  We profiled 1 patient neuroblastoma-FOXR2 tumor sample by single-cell multiome RNA + ATAC. The raw fastqs are provided.

  Dataset EGAD00001010902

• m6A profiling in Lung Adenocarcinoma

  Applying a refined m6A RNA immunoprecipitation method, we profiled the m6A epitranscriptome on 10 non-neoplastic lung (NL) tissues and 53 lung adenocarcinoma tumors.

  Dataset EGAD00001008026