7147 results for "canc*"

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• Whole genome shotgun sequencing and somatic mutations data in Hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy.

  Study EGAS00001002578

• Multiregional sequencing of IDH-WT glioblastoma reveals high genetic heterogeneity and a dynamic evolutionary history

  Glioblastoma is the most common and aggressive primary brain malignancy in adults. In addi-tion to extensive inter-patient heterogeneity, glioblastoma shows intra-tumor extensive cellular and molecular heterogeneity, both spatially and temporally. This heterogeneity is one of the main reasons for the poor prognosis and overall survival. Moreover, it raises the important question of whether the molecular characterization of a single bioptic sample, as performed in standard di-agnostics, actually represents the entire lesion. In this study, we sequenced the whole-exome of nine spatially different cancer regions of three primary glioblastomas. We characterized their mutational profiles and copy number alterations, with implications for our understanding of tu-mor biology in relation to clonal architecture and evolutionary dynamics, as well as therapeuti-cally relevant alterations.

  Study EGAS00001005128

• Longitudinal profiling of circulating tumour DNA for tracking tumour dynamics in pancreatic cancer

  The utility of circulating tumour DNA (ctDNA) for longitudinal tumour monitoring in pancreatic ductal adenocarcinoma (PDAC) has not been explored beyond mutations in the KRAS proto-oncogene. We aim to characterise and track patient-specific somatic ctDNA variants, to assess longitudinal changes in disease burden and explore the landscape of actionable alterations.

  Study EGAS00001005981

• Whole genome characterisation of lung cancer organoids and tissue

  Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term expanding human airway organoids from broncho-alveolar biopsies or lavage material. The pseudostratified airway organoid epithelium consists of basal cells, functional multi-ciliated cells, mucus-producing goblet cells, and CC10-secreting club cells. Airway organoids derived from cystic fibrosis (CF) patients allow assessment of CFTR function in an organoid swelling assay. Organoid culture conditions also allow gene editing as well as the derivation of various types of lung cancer organoids. Respiratory syncytial virus (RSV) infection recapitulated central disease features and dramatically increases organoid cell motility, found to be driven by the non-structural viral NS2 protein. We conclude that human airway organoids represent versatile models for the in vitro study of hereditary, malignant, and infectious pulmonary disease.

  Study EGAS00001002899

• Neurodegenerative_TGS

  An investigation of clonal haematopoiesis in patients with neurodegenerative disease.

  Study EGAS00001002431

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Res1_HT29_exp2_MC_03_03_22

  1 sample is pure plasmid DNA and 10 samples are cell pellets for genomic DNA extraction. CRISPR PCR1 and PCR2 indexing - Please use standard Kozuke primers.

  Study EGAS00001006093

• 54 metastatic colorectal cancer patients from Schleswig-Holstein in North Germany

  Personalized treatment vs standard of care is much debated, especially in clinical practice. Here we investigated whether overall survival differences in metastatic colorectal cancer patients are explained by their tumor mutation profiles or by their treatment differences in real clinical practice.

  Study EGAS00001004108

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281