5735 results for "canc*"

in 22.47 milliseconds.

• Coverage bias and sensitivity of variant calling for four whole-genome sequencing technologies

  Massively parallel sequencing has revolutionized research in cancer genetics and genomics and enhanced our understanding of natural human genetic variation. Recently, Lam et al. have performed a detailed comparison of two next-generation sequencing technologies with respect to their sensitivity to call single nucleotide variants (SNV) and indels. Here, we sequenced two tumor/normal pairs obtained from two paedriatic medulloblastoma patients with Life Technologies’ SOLiD 4 and 5500xl SOLiD, Illumina’s HiSeq2000, and Complete Genomics’ technology. We then compared their ability to call SNVs with high confidence. As gold standard for SNV calling, we used genotypes determined by an Affymetrix SNP array. Additionally, we performed a detailed analysis of how evenly each technology covers the genome and how the reads are distributed across functional genomic regions. Finally, we studied how a combination of data from different technologies might help to overcome the limitations in SNV calling by any of the four technologies alone.

  Study EGAS00001000274

• Genetic_mechanisms_of_resistance_to_chemotherapy_in_breast_cancer

  Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is to identify genetic mechanisms causing some breastcancer patients not to respond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment.In the project we will perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where all patients have recievedtreatment with epirubicin monotherapy before surgical removal of a locally advanced breasttumour, and where all patients have been subjected to objective evaluation of the response tothe therapy.Subsequent to sequencing, we will analyse the data and compare with the clinical data foreach patient (object response to therapy). The main aim being to identify mutations that areassociated with resistance to epirubicin.Identification of mutations with strong predictive value, may have a direct impact on cancertreatment since it opens the possibility for genetic testing of a tumour, and desicion on whichdrug is likely to work best, prior to treatment start.

  Study EGAS00001000276

• Matched_Pair_Cell_Line_Tumour_RNAseq

  In this study we will sequence the transcriptome of Verified Matched Pair Cancer Cell line tumour samples. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000434

• Genentech Colon Cancer Screen

  Study EGAS00001000288

• Breast_cancer_sequential_sampling_study

  This study aims to whole genome sequence DNA derived from breast cancer patients who received neo-adjuvany chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved.

  Study EGAS00001000300

• Mutational context and diverse clonal development in early and late bladder cancer

  Bladder cancer shows multiple recurrences probably originating from a malignant field disease in the mucosa. Deep sequencing was used on a series of tumors to look into the clonal composition, mutational spectrum in non-aggressive tumors, and mutational context.

  Study EGAS00001000641

• WGS_skin_punches

  We wish to understand the degree of copy number alterations in normal human sun exposed skin. We have collected small punches of epithelia and using a bait set design have shown the these span a clone. WGS will provide copy number information on these.

  Study EGAS00001004465

• Immune and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 trials

  The identification of prognostic drivers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigated the complexity of B and T cell receptor (BCR and TCR) repertoires, reflecting antigen-specific immune response, in the context of two phase III trials, namely NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women affected by HER2-positive breast cancer. BCR/TCR features were heterogeneous, and BCR measures describing clonal expansion demonstrated independent prognostic value. A model developed in NeoALTTO and validated in CALGB 40601 predicted event-free survival (EFS) by integrating hormone receptor and clinical nodal status, treatment response (breast pCR)breast pathological complete response (pCR) as well as tumor-infiltrating lymphocytes and BCR evenness, measuring the equality of BCR clonal distribution. The HER2-EveNT score derived from the model allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

  Study EGAS00001007563

• Quantification of chromosomal copy number aberrations by shallow whole-genome sequencing

  Detection of DNA copy number aberrations by shallow whole-genome sequencing (WGS) faces many challenges including lack of completion and errors in the human reference genome, repetitive sequences, polymorphisms, variable sample quality, and biases in the sequencing procedures.Formalin-fixed paraffin-embedded (FFPE) archival material, the analysis of which is important for studies of cancer, presents particular analytical difficulties due to degradation of the DNA and frequent lack of matched reference samples. We present a robust, cost-effective WGS method for DNA copy number analysis that addresses these challenges more successfully than currently available procedures. In practice very useful profiles can be obtained with 0.1 fold genome coverage. We improve on previous methods by; first, implementing a combined correction for sequence mappability and GC content, and second, applying this procedure to sequence data from the 1000 Genomes Project in order to develop a blacklist of problematic genome regions. A small subset of these blacklisted regions were previously identified by ENCODE, but the vast majority are novel unappreciated problematic regions. Our procedures are implemented in a pipeline called QDNAseq. We have analyzed over 1,000 samples, most of which were obtained from the fixed tissue archives of over 25 institutions.We demonstrate that for most samples our sequencing and analysis procedures yield genome profiles with noise levels near the statistical limit imposed by read counting. The described procedures also provide better correction of artifacts introduced by low DNA quality than prior approaches, and better copy number data than high-resolution microarrays at substantially lower cost.

  Study EGAS00001000642

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Gastric_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003151