7300 results for "canc*"

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• Bulk_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008282

• Spatial transcriptomics analysis of triple negative breast cancers

  While triple negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigated TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We performed an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures led to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identified nine TNBC ecotypes, further validated in external datasets. Several ecotypes were associated with disease outcome and characterized by potentially actionable features. In this work, we provideThis is the largest TNBC series providing a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. All the processed data needed to replicate the results from the publication (counts, images, clinical data, etc) are available on Zenodo: https://zenodo.org/records/14204217

  Study EGAS50000000475

• WGS and WES of 78 pairs Chinese gastric cancer

  Gastric Cancer (GC) is a highly heterogeneous disease. To identify potential clinically actionable therapeutic targets that may inform individualized treatment strategies, we performed whole-exome sequencing on 78 GCs of differing histologies and anatomic locations, as well as whole-genome sequencing on two GC cases, each with 3 primary tumours and 2 matching lymph node metastases. The data showed two distinct GC subtypes with either high-clonality (HiC) or low-clonality (LoC).

  Study EGAS00001001056

• Single cell transcriptomics to characterize the tumor microenvironment of prostate cancer fusion biopsies

  The primary objective of this study was to characterize the tumor microenvironment in fusion-guided transperineal biopsy samples from patients undergoing PC diagnosis. For each patient, one biopsy was taken from a suspected tumor region and another from a non-suspicious area, which were later classified as high- or low-tumorigenicity based on anatomopathological analysis. Using scRNA-seq data, we performed cancer-oriented cell annotation, differential expression analysis, and functional pathway enrichment studies across key cellular subpopulations. Additionally, differential abundance analysis was conducted to identify cell groups representative of different tumorigenicity levels. Finally, classification models were developed using gene expression data to differentiate high- vs. low-tumorigenicity samples, with the long-term goal of establishing a diagnostic classifier for PC stratification.

  Study EGAS50000000888

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• Emergence of oncofetal plasticity is ubiquitous in early colorectal cancers

  Metastasis formation is classically considered a late-stage event in colorectal cancer (CRC) evolution. Yet, the time and patterning by which metastatic competence is acquired remain poorly understood. Here, we show that metastasis-associated oncofetal cell states already emerge at the earliest stages of CRC, concurrent with invasive front formation. However, while necessary for metastasis, we detect them ubiquitously among early non-metastatic cancers, highlighting additional bottlenecks like immune evasion. To understand how oncofetal cells first emerge, we generated multiregional organoid models that reflect successive tumor progression stages within individual early-stage CRCs. Whole-genome sequencing and growth factor-dependency assays exclude tumor cell-intrinsic acquired traits. In contrast, single-cell spatial atlases of the tumor-microenvironment before and after malignant transformation revealed stereotypic patterning of fibroblast subtypes resembling normal tissue architecture, resulting in distinct regional microenvironments. At the onset of malignant growth into the submucosa, the first cancer-associated fibroblasts (CAFs) to appear strongly resemble submucosal trophocytes and colocalize with oncofetal cell states at invasive fronts. Functionally, fibroblast-organoid co-cultures confirm that these trophocyte-like CAFs induce plastic transitioning to oncofetal states. Thus, interactions between tumor and submucosal fibroblasts directly following malignant transformation dictate the timing and location at which oncofetal plasticity first occurs during CRC progression.

  Study EGAS50000001532

• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Using cancer cell fractions computed from single nucleotide variants and copy number alterations, we reconstructed the tumour phylogenies, which in turn allowed us to infer key molecular steps in the progression of prostate cancer in these individuals. We mapped the clonal composition of cancer sampled across the prostate in each individual and inferred the routes of spread of cancer cells within the prostate and to seminal vesicles and lymph nodes.

  Study EGAS00001007438

• V2_Colorectal_panel_test

  Targeted gene screen of cell line tumour samples for testing the new V2 Colorectal gene panel.

  Study EGAS00001001806

• A mathematical model of cell-free DNA fragment size reveals cancer-specific fragmentomic patterns

  This study aim to test a mathematical model of cfDNA length distribution across multiple biodiy flulids. It try to investigate biological mechanisms of cfDNA fragmentation and release.

  Study EGAS50000001560

• hereditary BrEAst Case CONtrol study

  The BEACCON study aimed to address the lack of power of previous studies to identify novel BC predisposition genes by performing extensive sequencing in 12,000 women (11,511 analysed following exclusions) and further enhancing power by using an ‘extreme phenotype’ design with enrichment of familial non-BRCA1 and BRCA2 cases, compared with a control population of older women with ongoing confirmation of cancer-free status at June 2019. Three-quarters of the 1303 candidate genes screened were selected based on empiric evidence from local (69 multi-case BC families) or international whole exome sequencing studies, and the remainder were included to provide detailed coverage of functional pathways with established associations with BC

  Study EGAS00001005043