9295 results for "cancer rna-seq"

in 26.81 milliseconds.

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD43291_Novaseq__Exome_

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003503

• Human_Colorectal_Cancer_Exome_Sequencing

  In this experiment we sequenced a collection of genes identified as being mutated in a Sleeping Beauty Screen in a mouse colorectal Cancer Model in human tumours collected from patients with germline mutations in APC and also other familial CRC predisposition syndromes. We also sequenced the germline of these patients allowing us to identify somatically mutated genes. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000077

• Spatially resolved antigen receptor and gene expression data from breast cancer patients

  The dataset includes spatially-resolved and single-cell antigen receptor, as well as gene expression, data from two different HER2+ breast cancer patients. The tumor piece obtained during surgery from each patient was divided into several regions and tissue sections were used for spatial transcriptomics (Visium, 10x genomics). As indicated, some tissue sections were analyzed by a new method (Spatial VDJ) to spatially resolve antigen receptor sequences (target capture), which was developed in our publication. In parallel, tissue pieces from the same tumor were dissociated for single-cell gene expression analysis (10x genomics GEX, VDJ, and feature barcoding/Hash Tag Oligonucleotide). The deposited data is in the form of fastq files. All processed data, metadata, micrographs of the tissue sections (of those used for spatial transcriptomics), and scripts used for the analysis are publicly available at Zenodo (DOI: 10.5281/zenodo.7961605). Final libraries were sequenced on NextSeq2000 (Illumina) or NovaSeq6000 (Illumina) and analyzed with Cell Ranger, Seurat, Space Ranger, and STutility pipelines.

  Dataset EGAD00001011061

• DNA Methylation-based diagnostic biomarkers for ESCC in Han Chinese population

  DNA methylation-based biomarkers were suggested to be promising for early cancer diagnosis. However, DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC), especially in Chinese Han populations have not been identified and evaluated quantitatively. To identify the candidate DNA-methylation based biomarkers for ESCC diagnosis, we performed the targeted bisulfite sequencing analysis in this study. Based on these 94 pairs of ESCC tumors and adjacent normal tissues, we found out that ADHFE1, EOMES, SALL1 and TFPI2 could be an effective methylation-based assay for ESCC diagnosis.

  Study EGAS00001003158

• DO NOT USE - Whole genome sequencing of SI-NETs from six patients

  Small intestine neuroendocrine tumor (SI-NET), the most common cancer of the small bowel, often displays a curious multifocal phenotype with several intestinal tumors centered around a regional lymph node metastasis, yet the typical path of evolution of these lesions remains unclear. Here, we determined the complete genome sequences of 24 tumor and 3 adjacent normal tissue samples with their paired normal blood samples (totally 33 whole genomes) from 6 patients with multifocal SI-NETs, allowing elucidation of phylogenetic relationships between multiple intestinal tumors and metastases in individual patients.

  Study EGAS00001005009

• Pediatric tumor in a single child of three large nuclear families

  We identify three nuclear families in which a pediatric tumor had been diagnosed in a single child and neither parent had been diagnosed with cancer. These families had 4, 5, and 7 children, respectively. Diagnoses included Wilms tumor, low-grade astrocytoma, and Burkitt’s lymphoma, respectively. We used whole-genome sequencing to profile normal cells from each family member and a linked-read technology for genomic phasing, which enabled us to identify compound-heterozygous and de novo variants in addition to simple-heterozygous and homozygous-alternate variants.

  Study EGAS00001005321

• Familial breast cancer targeted sequencing with ONT

  A large cohort of 600 cases with familial breast cancer as classified by the Spanish Society of Medical Oncology (SEOM) Clinical Guidelines Update that were recruited during 6 years at Hospital Universitario Morales Meseguer (Murcia, Spain) were retrospectively evaluated to select 16 cases with no positive finding in NGS analysis of 20 genes implicated in this disease. These 16 cases were selected for further investigation using nanopore sequencing. This method involved the use of adaptive sampling enrichment, targeting a panel of 18 human genome regions, which contained the 20 genes (PTEN, ATM, BRCA2, PALB2, CDH1, TP53, NF1, RAD51D, BRCA1, RAD51C ,BRIP1, STK11, CHEK2, EPCAM, MSH2, MSH6, BARD1, MLH1, PMS2, NBN). In 5 samples (P1, P2, P4, P15 and P16) no selection of long reads was performed. Additionally, in 3 samples (P7, P9 and P10), both procedures were performed in two independent runs, and for the second run of P7, the DNA was previously fragmented using g-TUBE Covaris® (ref 520079) according to the protocol for 6 kb fragments.

  Dataset EGAD00001011106

• High-resolution lung adenocarcinoma expression subtypes identify tumors with dependencies on MET, CDK4, CDK6, and PD-L1

  Lung adenocarcinoma is one of the most common cancer types with various treatment modalities. However, better biomarkers to predict therapeutic response are still needed to improve precision medicine. We utilized a consensus hierarchical clustering approach on 509 LUAD cases from TCGA to identify five robust LUAD expression subtypes. We then integrated genomic (patient and cell line) and proteomic data to help define biomarkers of response to targeted therapies and immunotherapies. This approach defined subtypes with unique proteogenomic and dependency profiles.

  Study EGAS00001006461

• Oral Microbiome in Esophageal Adenocarcinoma

  The purpose of our study was to assess the influence of oral microbiota on the development of esophageal cancer. Our preliminary case-control studies reported a global alteration of foregut microbiome in esophageal adenocarcinoma with the strongest changes found in the oral microbiome. We hypothesise that commensal oral bacteria are capable of activating or degrading carcinogens in cigarette smoke and therefore may contribute to esophageal carcinogenesis. We conducted a prospective study nested in two large US cohorts, to determine whether oral microbiota are associated with subsequent esophageal adenocarcinoma.

  Study phs001527

• Genomic Analysis of Bevacizumab-induced Hypertension

  Bevacizumab use in the treatment of cancer can lead to the development of hypertension in some patients, and high-grade toxicity can limit therapy or lead to cardiovascular complications. The factors that contribute to interindividual variability in blood pressure rise during bevacizumab treatment are not well understood. In the present study, whole exomes and flanking regulatory regions of candidate genes associated with vasodilation and blood pressure were sequenced in bevacizumab-treated subjects with the objective of identifying genes harboring multiple variants associated with severe, early-onset bevacizumab-induced hypertension.

  Study phs001597