7361 results for "canc*"

in 18.52 milliseconds.

• Integrative_genome_profiling_in_AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Study EGAS00001000858

• Guardians_of_the_genome__protecting_DNA_from_endogenous_sources_of_damage_

  Analysis of mutational signatures caused by DNA repair defects in human induced pluripotent stem (iPS) cells. A reference human iPS cell line will be used for genetic manipulation to introduce homozygous knockouts of 100 genes known to be involved in or connected to DNA repair or DNA editing. Following a defined period of growth after homozygous knockout of each gene, sub clones will be generated and sequenced. The progenitor “parental” IPS cell line will be used to generate reference sequence data, in order to determine the mutational signature acquired due to the gene knockout. This is a pilot study to investigate the effects of oxygen conditions and growth period on mutations acquired

  Study EGAS00001000874

• 65 prostate cancer cases WGS and transcriptome sequencing project

  We obtained whole-genome and transcriptome sequencing of tumor-benign pairs from 65 Asian prostate cancer (PCa) patients. Taken together with the TCGA PCa cohort, our integration analysis provides the first comprehensive mutational landscape of PCas across major ethnics worldwide and reveals potential novel role of frequent altered chromatin remodeler genes in PCas without androgen receptor (AR) alteration and complex rearrangements derived from Chromoplexy. In addition, we identified 5 putative tumor suppressor genes (TSGs) chains including one on chromosome 13q with novel findings of PCDH9 (deletions in 15/65 tumors) which was implicated in aggressive progression of prostate cancer. Finally, the integrative pathway and co-expression network analysis followed by the functional study indicated the frequent altered genes, particularly focal amplifications of PLXNA1 (11/65), in semaphoring signaling of axon guidance pathway may interact with PI3K/AKT and AR signaling and also contribute to the aggressiveness and progression of prostate cancer.

  Study EGAS00001000888

• SeqControl: Process Control for DNA Sequencing

  As next-generation sequencing (NGS) continues to increase in speed and throughput, routine clinical and industrial application draws steadily closer. These “production” uses of NGS will require enhanced quality-monitoring and quality-control to optimize output and reduce costs. We therefore developed a framework called SeqControl for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, base-wise coverage and base-wise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references we derive multivariate models that predict sequencing quality and depth. SeqControl robustly predicts how much sequencing is required to reach a given coverage depth (AUC = 0.993), accurately classifies clinically relevant formalin-fixed paraffin-embedded samples and makes predictions from as little as 1/8 of a lane of sequencing data (AUC = 0.967). These techniques can be immediately incorporated into existing NGS pipelines to monitor data quality in real-time. SeqControl represents a first step towards statistical process-control for NGS.

  Study EGAS00001000899

• A Comparative Analysis of Algorithms for Somatic SNV Detection in Cancer

  Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer- normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterised and compared to investigate the strengths and weaknesses of each SNV calling algorithm.

  Study EGAS00001000927

• Cell_lines_with_telomere_fusion_induced_rearrangements

  Whole-genome somatic rearrangement and point mutation analysis in cell lines with induced telomere fusions.

  Study EGAS00001001059

• Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase-associated stress responses

  Background Single-cell RNA sequencing (scRNAseq) is a powerful tool for studying complex biological systems, such as tumour heterogeneity and tissue microenvironments. However, the sources of technical and biological variation in primary solid tumour tissues and patient-derived mouse xenografts for scRNAseq, are not well understood. Here, we used low temperature (6°C) protease and collagenase (37°C) to identify the transcriptional signatures associated with tissue dissociation across a diverse scRNAseq dataset comprising 128,481 cells from patient cancer tissues, patient-derived breast cancer xenografts and cancer cell lines.Results We observe substantial variation in standard quality control (QC) metrics of cell viability across conditions and tissues. From FACS sorted populations gated for cell viability, we identify a sub-population of dead cells that would pass standard data filtering practices, and quantify the extent to which their transcriptomes differ from live cells. We identify a further subpopulation of transcriptomically “dying” cells that exhibit up-regulation of MHC class I transcripts, in contrast with live and fully dead cells. From the contrast between tissue protease dissociation at 37°C or 6°C, we observe that collagenase digestion results in a stress response. We derive a core gene set of 512 heat shock and stress response genes, including FOS and JUN, induced by collagenase (37°C), which are minimized by dissociation with a cold active protease (6°C). While induction of these genes was highly conserved across all cell types, cell type-specific responses to collagenase digestion were observed in patient tissues. We observe that the yield of cancer and non-cancer cell types varies between tissues and dissociation methods.Conclusions The method and conditions of tumour dissociation influence cell yield and transcriptome state and are both tissue and cell type dependent. Interpretation of stress pathway expression differences in cancer single cell studies, including components of surface immune recognition such as MHC class I, may be especially confounded. We define a core set of 512 genes that can assist with identification of such effects in dissociated scRNA-seq experiments.

  Study EGAS00001003753

• Von Hippel-Lindau syndrome multi-region exome sequencing project from two patients undertaken at Cancer Research UK's London Research Institute

  Multi-region whole exome sequencing of tumours from patients with Von Hippel-Lindau syndrome reveals convergence of mutayional events upon the PI3L-AKT-mTOR signalling pathway.

  Study EGAS00001000907

• METABRIC: Data from Batra et al (2021); DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation

  DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, RRBS-based profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, the study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

  Study EGAS00001004327

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335