8432 results for "canc*"

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• Plasma CTCF ChIP-seq Reveals Cancer-Associated cfDNA Binding Profiles

  Cell-free DNA (cfDNA) in plasma predominantly exists as nucleoprotein complexes. Although circulating CTCF-bound cfDNA (cfCTCF-DNA) has previously been reported, the occupancy of individual CTCF binding sites in plasma has not been systematically characterised. This study describes the isolation of endogenous plasma cfCTCF-DNA by chromatin immunoprecipitation followed by next-generation sequencing (ChIP-seq) in samples obtained from cancer patients and healthy individuals. A two-step enrichment strategy was employed, combining physical removal of background cfDNA by immunoprecipitation with bioinformatic filtering to remove residual non-CTCF-derived sequences. Sequencing reads were aligned to the UCSC hg38 reference genome using BWA-MEM v0.7.17 and processed to generate CRAM files containing alignments restricted to the primary chromosomes (chr1–chr22, chrX, chrY and chrM). CTCF-associated cfDNA fragments were classified according to their similarity to a consensus CTCF binding motif, enabling discrimination between low-affinity and high-affinity CTCF binding sites. Comparative analyses identified quantitative and qualitative differences in plasma cfCTCF-DNA profiles between healthy individuals and patients with cancer. The deposited dataset comprises plasma cfCTCF-DNA ChIP-seq data from four clinical cohorts and includes both CTCF-enriched and total cfDNA samples where applicable. These data support the investigation of CTCF occupancy patterns as a novel class of liquid biopsy biomarkers for cancer detection and monitoring.

  Study EGAS50000001937

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• Machine Learning Uncovers Previously Undetectable Genetic Deletions in Cancer Panel Sequencing

  We developed a novel machine-learning pipeline for detection of genetic deletions and zygosity evaluation within MASTERsg, a precision oncology program using the TSO500 DNA gene panel to identify targetable alterations in advanced cancers. The TSO500 pipeline detects copy number variations (CNVs) through bin count averaging but may miss focal CNVs not meeting thresholds. As a proof-of-concept we used deletions in PTEN, which confer sensitivity to mTOR and Akt inhibition. An Extreme Gradient Boosting model trained on tumor samples with PTEN deletions and PTEN wild-type status enabled the correct identification of missed focal deletions, which were subsequently confirmed by immunohistochemistry. Additional cases of PTEN loss could be identified in 34 of 204 previously profiled, seemingly uneventful samples, which were validated in 75% of stainable cases. The findings underscore the substantial clinical potential of this method to uncover therapeutically relevant alterations beyond established diagnostic pipelines.

  Study EGAS00001008324

• Gene expression profiling in pregnancy-associated breast cancer

  Study EGAS00001008013

• Somatic mutations of non-malignant T cells

  Somatic mutations in T cells can cause cancer but also have implications for immunological diseases and cell therapies. The mutation spectrum in non-malignant T cells is unclear. Here, we examined somatic mutations in CD4+ and CD8+ T cells from 90 patients with hematological and immunological disorders and used T cell receptor (TCR) and single-cell sequencing to link mutations with T cell expansions and phenotypes. CD8+ cells had higher mutation burden than CD4+ cells. Notably, the biggest variant allele frequency (VAF) of non-synonymous variants was higher than synonymous variants in CD8+ T cells, indicating non-random occurrence. The non-synonymous VAF in CD8+ T cells strongly correlated with the TCR frequency, but not age. We identified mutations in pathways essential for T cell function and often affected in lymphoid neoplasia. Single-cell sequencing revealed cytotoxic Temra phenotypes of mutated T cells. Our findings suggest that somatic mutations contribute to CD8+ T cell expansions without malignant transformation.

  Study EGAS50000000237

• Spatial transcriptomic profiling of INSPIRE samples

  This study aimed t o define the spatial tumor microenvironment features associated with response to immune checkpoint blockade in recurrent/metastatic head and neck squamous cell carcinoma (RM-HNSCC). Spatial transcriptomic profiling was performed on tumor biopsies from ICB-naive patients to characterize malignant, stromal, and immune cell states and their spatial interactions. The study investigated how intratumoral heterogeneity, cancer-associated fibroblast programs, immune contexture, and tumor-microenvironment signaling relate to subsequent clinical response and progression-free survival following immunotherapy.

  Dataset EGAD50000003130

• MutWPX__CRUK_Grand_Challenge_Mutographs_of_Cancer__Effects_of_Chemotherapy_on_the_Somatic_Mutational_Landscape_in_Normal_Human_Tissue___Matched_Normals

  This study is investigating the effects of chemotherapy drugs used in cancer treatment on the somatic mutational landscape in normal human tissues. The samples used in this study have been taken from rapid autopsies of patients who have undergone chemotherapy using drugs thought to cause mutations in the DNA. Structures from a variety of tissues will be dissected using LCM and whole genome sequences will be produced in order to assess mutational burdens and signatures. This study contains the samples used as matched normals for each patient to remove germline mutations.

  Study EGAS00001004957

• SCLC ctDNA sequencing

  In this study we have sequenced the ctDNA of 28 Small Cell Lung Cancer patients in the TP53 gene, each sample has been sequenced twice.

  Study EGAS00001003984

• Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  Epithelial ovarian carcinoma of all subtypes has one of the worst outcomes of any human cancer. To improve our understanding of underlying biology and therapeutic possibilities in this disease, we performed whole genome sequencing, methylation, and expression analyses of a comprehensive set of 47 ovarian cancer cell lines representing different histologic tumor subtypes. Given the challenges of genomic analyses in tumors without matched normal samples, we developed novel approaches for detection of somatic alterations and used these to identify sequence, copy number, and rearrangement changes and integrated these with genome-wide epigenetic and expression alterations. Ovarian cancer cell lines had molecular changes in genes involved in cell cycle, PI3K, RAS, BRCA, chromatin regulating, and p53 pathways, and displayed global mutation and methylation changes similar to primary ovarian carcinoma. We identified alterations not previously implicated in ovarian cancer including amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and members of the TGF beta receptor pathway, including TGFBR2, SMAD3 and SMAD4, in-frame rearrangements of YAP1-MAML2 and IKZF2-ERBB4, and fusions involving MET, NF1, FBXW7 and CCND1. Integrating cell line alterations with dose-response data using three targeted therapies revealed novel molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, those with MYC amplifications to PARP inhibitor BMN673, and SMAD4 alterations to MEK inhibitor MEK162. Genome-wide analyses revealed intrachromosomal rearrangements as an improved measure of sensitivity to PARP inhibition compared to the homologous recombination defect (HRD) score. This study provides a comprehensive resource of molecular information for ovarian cancer cell line models and a pharmacogenomic platform for developing rational cancer therapeutic strategies.

  Study EGAS00001002998

• Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) to identify bivalently marked genes (H3K4me3 and H3K27me3 ChIP-seq), and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Epigenetic regulation of transcription plays a crucial role in lineage commitment of embryonic stem cells. Promoters of key lineage-specific differentiation genes are found in a repressed bivalent state, having both activating H3K4me3 and repressive H3K27me3 histone marks, making them poised for transcription upon loss of H3K27me3 in response to environmental cues. Whether the tumour-initiating, self-renewing, cancer-initiating cells (C-ICs) have similar epigenetic regulatory mechanism that prevent lineage commitment is unknown. In order to investigate bivalently marked and repressed promoters, we used a patient-derived CC-IC enriched model to identify the changes in transcriptome following inhibition of EZH2, the H3K27 methyltransferase. We also performed ChIP-seq for H3K27me3 and H3K4me3 at baseline in order to identify repressed and bivalently marked promoters.

  Study EGAS00001003003