12312 results for "cancer rna-seq"

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• Whole-exome sequencing of human pancreatic cancers and characterization of genomic instability caused by MLH1 haploinsufficiency and complete deficiency

  Whole-exome sequencing (Exome-Seq) has been successfully applied in several recent studies. We here performed Exome-Seq of 15 pancreatic tumor-normal pairs. We captured 162,073 exons of 16,954 genes and sequenced the targeted regions to a mean coverage of 56 folds. This study identified a total of 1,517 somatic mutations and validated 934 of them by transcriptome sequencing. We detected recurrent mutations in 56 genes. Among them, 41 have not been described. The mutation rates varied widely among tumors. The diversity of mutation rates was significantly correlated with the distinct MLH1 copy-number status. Exome-Seq revealed intensive genomic instability in a tumor with MLH1 homozygous deletion, indicated by a dramatically elevated mutation rate of somatic substitutions, small insertions/deletions (indels), as well as indels presented at microsatellites. Notably, we detected MLH1 allelic loss in 4 tumors. MLH1 expression was decreased by nearly half in these cases. While they were negative in the conventional microsatellite instability assay, they showed a 10.5-fold increase in the mutation rate of somatic indels, e.g. truncating indels in TP53 and TGFBR2, indicating MLH1 haploinsufficiency in correction of DNA indel errors. We further analyzed the exomes of 15 renal cell carcinomas (RCCs) and confirmed MLH1 haploinsufficiency. We observed a significant increase in the mutation rate of somatic indels in affected cases and identified recurrent truncating indels in several cancer genes such as VHL, PBRM1 and JARID1C. Together, our data suggest that MLH1 hemizygous deletion, through increasing the mutation rate of somatic indels, could drive the development and progression of sporadic cancers.

  Study EGAS00001000149

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• PCNSL single-cell dataset

  This dataset includes 4 samples with scRNA-seq and 3 sample with CITE-seq, scTCR-seq and scBCR-seq.

  Study EGAS50000000474

• Evolution of Chromatin Architecture and Transcriptional Regulation in Mammals

  Changes in gene expression are a critical force driving the evolution of form and function. As a result, the mechanisms by which gene expression evolves have become a subject of intense interest. A number of investigators have measured evolutionary changes in gene expression at the chromatin, mRNA, and protein levels, leading to new insights about how species evolve. However, studies of different stages in gene expression have not always been in agreement. For example, the extremely rapid rates of evolutionary changes that have been widely observed at enhancers appear to conflict with the slower rates observed in mRNA abundance. We recently completed a major comparative study in primates showing that this disparity between enhancer and mRNA evolution, in part, reflects extensive compensation at enhancers that jointly determine transcription at target genes. Likewise, related findings have demonstrated that post-transcriptional changes buffer protein abundance to relatively more common differences in mRNA expression. Together, these recent findings demonstrate that evolutionary changes affecting multiple stages of transcriptional regulation often have interdependent effects on gene expression. Here we propose to determine how stages early during transcriptional regulation work in concert, either to conserve gene expression through compensatory changes across stages, or, in rare cases, to change mRNA in ways that alter organism phenotypes. Our central hypothesis is that interactions between stages are common, especially at long evolutionary time-scales. To test this hypothesis we propose an ambitious plan to collect rich genomic data profiling distinct stages of gene expression in two cell types and three tissues from nine mammalian species. We have focused our study on several early rate-limiting steps in mRNA production, using molecular assays selected to provide orthogonal sources of information about chromatin architecture (Hi-C/Hi-ChIP), accessibility (ATAC-seq), transcription (PRO-seq), and mRNA levels (RNA-seq). This project will produce the largest resource of genomic data uniformly collected across mammals to date. We will integrate genomic data using a suite of new computational tools, which together will provide a new understanding of how distinct regulatory stages work in concert during regulatory evolution.

  Study phs002146

• Human omentum cell atlas

  This dataset contains single-cell RNA sequencing data derived from freshly dissociated human omental tissue. The study investigates the transcriptomic landscape of the omentum by comparing samples from patients with benign conditions against those with ovarian cancer metastasis. To capture the heterogeneity of the metastatic niche, sampling was performed across distinct anatomical sites, including non-metastasized tissue, distant omental regions, peritumoral zones, and the tumor core. This comprehensive profiling aims to define the cellular remodeling associated with malignant transformation

  Dataset EGAD50000002110

• ICARUS-BREAST01 Dataset

  A phase II clinical trial (NCT04965766) of patritumab deruxtecan in 99 breast cancer patients. Whole-exome sequencing (WES) is available for 43 tumor samples and 43 blood samples collected at entry into the trial. RNA-squencing is available for 44 samples comprising 22 samples collected at entry into the trial and 22 samples collected during treatment (cycle 1 day 3, cycle 1 day 19, or cycle 2 day 3) from 22 patients.

  Dataset EGAD50000000773

• Dataset Plasma-seq

  We performed low coverage whole genome sequencing of plasma DNA from prostate cancer patients to establish copy number profiles on both a genome-wide and a gene-specific level. The data include plasma samples from prostate cacner patients (n=13), non-malignant controls (males, n=10 and females, n=9), plasma samples from pregnancies with aneuploid and euploid fetuses (n=4). Furthermore, we sequenced different tumor samples (n=6) of one patients and a serial dilution of HT29 in a background of normal DNA (n=9).

  Dataset EGAD00001000364

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Whole genome sequencing of tumour-normal pairs in eight patients with clinically localised disease undergoing prostatectomy. A bespoke DNA capture and amplification panel against the highest prevalence, highest confidence aberrations for each individual was designed and used to interrogate ctDNA isolated from plasma prospectively obtained pre- and post- (24 hours and 6 weeks) surgery. Tagged-amplicon deep sequencing (TAm-Seq) across the TP53 gene in ctDNA in a cohort of 189 individuals.

  Dataset EGAD00001006369

• National Cancer Institute (NCI) Primary Human Melanocyte QTL Study

  In order to create a melanocyte-specific QTL resource, we obtained primary human melanocyte cultures isolated from foreskin of 106 healthy newborn males predominantly of European descent. Melanocytes were cultured in lot-matched culture medium in randomized batches to minimize variability that could be introduced by culturing conditions. RNA sequencing and direct SNP genotyping of these samples produced an average of ~87.9 million reads (paired-end, stranded, 126bps), and ~713,000 SNP genotypes, respectively. Illumina 450K methylation array covered over 485,000 CpGs distributed genome wide.

  Study phs001500

• Childhood Cancer Data Initiative (CCDI): Single-Cell Atlas of NF1 Nerve Sheath Tumors

  The worst outcome of NF1 is the development of the aggressive and highly metastatic malignant peripheral nerve sheath tumors (MPNST), which transform from benign plexiform neurofibroma (PN) and lack effective treatment. In this study, we performed single-cell RNA sequencing of 63 clinically annotated NF1-associated peripheral nerve sheath tumors, including 24 PN, 34 premalignant atypical neurofibromas, and 5 MPNSTs. These results improve the ability of identifying high-risk neurofibromas and provide a unique opportunity for early detection of MPNST.

  Study phs003519