10173 results for "cancer rna-seq"

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• WGS and Avenio Surveillance Panel data to previously submitted data under study number EGAS00001004276 of ALK-rearranged lung cancer

  Some data was previously submitted data under study number EGAS00001004276. In this new dataset we provide additional WGS and Avenio Surveillance Panel data. We utilized 43 ALK+ NSCLC patients receiving targeted ALK therapy to evaluate ctDNA levels based on matched panel-based targeted next generation sequencing (tNGS) and untargeted shallow whole genome sequencing (sWGS). For the Avenio panel the sequencing was done on Illumina NextSeq 550 paired end 150 bp, for WGS the sequencing was done on Illumina HiSeq 4000, partly with KAPA_Hyper_Prep_Kit. In this dataset there are 132 WGS tumor samples and 134 panel sequencing data of plasma.

  Dataset EGAD00001007818

• Clonal_selection_after_gene_therapy_in_SCD___Duplex_sequencing

  This study includes the targeted duplex sequencing data relating to this study. A custom targeted panel was used including 29 AML-associated genes, and a set of mutations from driver-containing clones that were sequenced during the WGS tree-building phase of the study. Targeted sequencing is performed on each of 6 individuals included at the study at at least 3 time points per individual: one prior to gene therapy, and two post-therapy time points.

  Study EGAS00001007253

• Correlative Genomic Analysis of Durvalumab plus Pazopanib Combination in Patients with Advanced Soft Tissue Sarcomas

  We conducted an open-label, phase 2 study to determine the activity of the anti-VEGF receptor tyrosine-kinase inhibitor, pazopanib, combined with the anti-PD-L1 immune checkpoint inhibitor, durvalumab, in unselected advanced sarcomas. In addition, we conducted whole exome and transcriptomic sequencing with pre-treatment tissue biopsy to correlate clinical outcomes with molecular and genomic biomarkers to identify patients who would most likely benefit from the combination treatment.

  Study EGAS50000000082

• Stand Up 2 Cancer (SU2C) Genomics-Enabled Medicine for Melanoma (GEMM) Trial

  The goal of the GEMM Trial is to ascertain if comprehensive and systematic interrogation of a patient's tumor molecular profile improves outcomes compared to the current practice of physician's choice for metastatic melanoma patients who have progressed following first line therapy. The data shared here includes tumor/normal exome and tumor RNAseq data for the trial patients, as well as archival data for a subset of patients.

  Study phs001786

• Cergentis FFPE-TLC sequencing of colorectal carcinoma

  In this study, formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing is used as a novel technology for targeted detection of tumor-specific genomic structural variants (SVs) in the primary tumor of 29 colorectal cancer patients with metastatic disease. The tumor region was macrodissected and sequenced for 29 patients, and the "normal" region of the same slide was macrodissected and sequenced for 8 of these patients. SVs were found in the common fragile site (CFS)-associated genes MACROD2, PRKN, FHIT and WWOX as well as SVs caused by three LINE transposable elements. Tumor-specificity of selected SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated. This dataset contains the hg19 reference alignment of the FFPE-TLC sequences for all 29 colorectal cancers and 8 adjacent normals.

  Dataset EGAD50000000618

• A genotype-phenotype study of tumors from patients with inherited mutations in DNA repair genes

  This study investigated the genomic landscape of tumors from patients with inherited mutations in DNA repair genes. The aim of this study was to determine the relationship between locus-specific loss of heterozygosity (LOH) and genomic signatures of homologous recombination-based DNA repair (HR) deficiency in tumors associated with pathogenic germline variants in DNA repair genes. Cohorts of pathogenic germline variant (PGV) carriers with different cancer types were identified via a cancer genetics registry and clinical practice at Penn Medicine and through our collaborator network. Tumors were analyzed with next generation sequencing (whole exome and/or targeted panel sequencing) with or without transcriptomic analyses. Sub-study #1 "Non-breast/ovarian tumors in germline BRCA1/2 carriers". This study investigated primary non-breast/ovarian tumors that arise in individuals with BRCA1/BRCA2 pathogenic germline variants (PGVs). Whole exome sequencing (WES) using Agilent All-Exon Kit v7 hybrid capture probes was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Individual WES data from DNA samples from tumor and normal are available. Sub-study #2: "Breast tumors in germline CHEK2 carriers". This study investigated primary breast tumors that arise in individuals with CHEK2 pathogenic germline variants (PGVs). Whole exome sequencing (WES) using Agilent All-Exon Kit v7 hybrid capture probes was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors. Individual WES data from DNA samples from tumor and normal and RNAseq data from tumor are available. Sub-study #3: "Breast tumors in germline TP53 carriers". This study investigated primary breast tumors that arise in individuals with TP53 pathogenic germline variants (PGVs). Whole genome sequencing (WGS) and/or custom panel targeted sequencing was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors and normal breast tissue. Individual WGS or targeted data from DNA samples from tumor and normal and RNASeq data from tumor and normal are available. Sub-study #4: "Prostate tumors in germline DNA repair carriers". This study investigated prostate tumors that arise in individuals with a variety of pathogenic germline variants (PGVs). Whole genome sequencing (WGS) and/or custom panel targeted sequencing was performed on matched tumor and blood germline normal DNA on an Illumina HiSeq. Whole transcriptome RNAseq was performed on tumors and normal prostate tissue. Individual WGS or targeted data from DNA samples from tumor and normal and RNASeq data from tumor and normal are available.

  Study phs003348

• scRNA-seq of LN and lymphoma stroma

  The activities of non-haematopoietic cells (NHCs), including mesenchymal stromal cells and endothelial cells, in lymphomas, reportedly underlie lymphomagenesis. However, understanding of lymphoma NHCs has been hampered by unexplained NHC heterogeneity, even in normal human lymph nodes (LNs). Here, we constructed a single-cell transcriptome atlas of >100,000 NHCs collected from 27 human samples, including LNs and various nodal lymphomas, revealing 30 distinct subclusters, including some that were previously unrecognized. Notably, this atlas was highly useful for comparative analysis with lymphoma NHCs, which revealed an unanticipated landscape of subcluster-specific changes in gene expression and interaction with malignant cells in follicular lymphoma NHCs, facilitating our understanding of stromal remodelling in lymphoma and potentially suggesting novel biomarkers. Our study largely updates NHC taxonomy in human LNs and pertains to analysis of disease status, providing a rich resource and deeper insights into LN and lymphoma biology and offering to advance lymphoma management and therapy.

  Study EGAS00001005732

• L1-Seq and Genome-Wide SNP Genotyping in a Multiethnic Asian Population

  Insertions of the human-specific subfamily of LINE-1 (L1) retrotransposon are highly polymorphic across individuals and can critically influence the human transcriptome. We hypothesized that L1 insertions could represent genetic variants determining important human phenotypic traits, and performed an integrated analysis of L1 elements and single nucleotide polymorphisms (SNPs) in several human populations. We found that a large fraction of L1s were in high linkage disequilibrium (LD) with their surrounding genomic regions and that they were well-tagged by SNPs. However, L1 variants were only partially captured by SNPs on standard SNP arrays, so that their potential phenotypic impact would be frequently missed by SNP array-based genome-wide association studies. We next identified potential phenotypic effects of L1s by looking for signatures of natural selection linked to L1 insertions; significant extended haplotype homozygosity (EHH) was detected around several L1 insertions. This suggests that some of these L1 insertions may have been the target of recent positive selection.

  Study phs000732

• SmMIP-tools:a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

  Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two major components of the software. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

  Study EGAS00001005359

• Comprehensive characterization of cell-free tumor DNA in plasma and urine of patients with renal tumors

  Cell-free tumour-derived DNA (ctDNA) allows non-invasive monitoring of various cancers but its utility in renal cell cancer (RCC) has not been well established. A combination of untargeted and targeted sequencing methods, applied to two independent cohorts of patients (n=90) with various renal tumour subtypes, were used to determine ctDNA content in plasma and urine. Our data revealed lower plasma ctDNA levels in RCC relative to other cancers, with untargeted detection of ~33% for both cohorts. A highly sensitive personalised approach, applied to plasma and urine from select patients (n=22), improved detection to ~50%, including in patients with early stage and even benign lesions. A machine-learning based model, applied to untargeted data, predicted this detection, potentially offering a means of triaging patient samples for personalised analysis. We observed that plasma, and for the first time, urine ctDNA may better represent tumour heterogeneity than a single tissue biopsy. Longitudinal sampling of >200 plasma samples revealed that ctDNA can track disease course. These data highlight low ctDNA levels in RCC but indicate potential clinical utility provided improvement in isolation and detection approaches.

  Study EGAS00001003530