7794 results for "canc*"

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• Whole-exome sequencing data for breast cancer patients

  This datasets contains the FASTQ files sequenced by Illumina NovaSeqX Plus, and the variants called from the sequencing data.

  Dataset EGAD50000002800

• DAC for study of Zanidatamab in breast cancer patients

  This is the DAC for manuscript "Zanidatamab in Patients with Early Stage HER2-positive Breast Cancer: The NeoZanHER Phase 2 Single-Arm Open-Label Trial"

  Dac EGAC50000001059

• Single-molecule nanopore sequencing of plasma and cerebrospinal fluid cell-free DNA from paediatric patients with brain and extracranial solid tumours.

  Cell-free DNA (cfDNA) profiling enables minimally invasive cancer detection and monitoring. Here, we report single-molecule nanopore sequencing data generated using the SIMMA assay for 792 plasma and cerebrospinal fluid cfDNA samples from 277 paediatric patients with diverse brain and extracranial tumours. SIMMA is a low-input single-molecule sequencing approach that enables multimodal whole-genome and high-depth targeted sequencing of the same cfDNA sample for both tumour-agnostic and tumour-informed liquid biopsy analysis (Sauer et al. 2026).

  Study EGAS50000001839

• High-grade serous ovarian cancer is associated with increased TP53 mutation burden in uterine lavage

  High grade serous ovarian cancer (HGSC) has low survival partly due to the lack of methods for detection, diagnosis, and risk prediction. TP53 mutations, which drive HGSC, are found in gynecological tissues as the result of somatic evolution, but it is unknown whether an excess of mutations is linked to ovarian cancer. Here we investigate if TP53 mutation burden measured in uterine lavage, a minimally invasive gynecological liquid biopsy, can discriminate between patients with and without HGSC. We used ultradeep TP53 duplex sequencing (>15,000x duplex depth) to detect TP53 mutations in uterine lavage collected pre-operatively in 278 patients undergoing gynecological surgery for pelvic masses (average risk) or cancer risk-reduction (high risk). All lavages contained multiple TP53 mutant clones, which were used to quantify TP53 mutation burden frequency (MBF). Average risk patients with HGSC had significantly higher TP53 MBF independently of age and other risk factors (77% sensitivity, 89% specificity, AUC =0.88). Excluding tumor TP53 clonal mutations from the lavage MBF calculation maintains this association, suggesting that it is the overall TP53 somatic mutation burden (rather than the discovery of the specific tumor driver mutation) that identifies HGSC. These results demonstrate that TP53 somatic mutations are common in uterine lavage but more abundant in patients with HGSC, highlighting a connection between TP53 somatic evolution and ovarian cancer. Uterine lavage offers a minimally invasive approach that could be valuable to identify patients with HGSC.

  Study EGAS50000001910

• Detection of high-grade serous ovarian cancer using TP53 mutation burden in uterine lavage

  In total, 436 DNA samples from the 278 patients were processed for TP53 ultradeep duplex sequencing: 278 lavages, 86 tissue samples (some patients had multiple tissue samples), and 72 blood samples. Duplex sequencing was performed on an Illumina NovaSeq 6000 by TwinStrand Biosciences using a capture panel targeting the coding regions of the TP53 gene. Data were processed by TwinStrand Biosciences and .bam files were created for each sample.

  Dataset EGAD50000002776

• Carcinoma of Unknown Primary (CUP): A comparison across tissue and liquid biomarkers (CUP-COMP) study

  The Carcinoma of Unknown Primary (CUP): A comparison across tissue and liquid biomarkers (CUP-COMP) study (NCT: NCT04750109) was sponsored by The Christie NHS Foundation Trust and funded by Innovate UK.

  Study EGAS50000001821

• Single-cell RNA sequencing of liver metastasis-derived colorectal cancer organoids profiling cellular heterogeneity and lineage dynamics across time

  The objective of this analysis was to identify, at single-cell resolution, trasncriptionally distinct subpopulations in untreated metastatic colorectal cancer organoids with diverse genetic backgrounds and to investigate their temporal dynamics.

  Study EGAS50000001927

• Transcriptome profiling of liver metastasis-derived colorectal cancer organoids to dissect pro-differentiative effects of TGFB1 and IL-6

  Bulk RNA sequencing was performed on patient-derived xenograft (PDX)-derived organoid models of metastatic colorectal cancer (mCRC). The aim of this study was to test the effect of IL-6 and TGFbeta1 on mCRC organoid cell differentiation. Transcriptomic profiling was conducted following cytokine treatments to investigate molecular changes associated with treatments. Three biological replicates were included for each experimental condition (control, IL-6, and TGF-beta1 treatments).

  Study EGAS50000001914

• Bulk RNA sequencing of metastatic colorectal cancer PDX-derived organoids - untreated and treated with IL-6 or TGF-beta1

  Bulk RNA sequencing was performed on patient-derived xenograft (PDX)-derived organoid models of metastatic colorectal cancer (mCRC). The aim of this study was to test the effect of IL-6 and TGF-beta1 on mCRC organoid cell differentiation. Transcriptomic profiling was conducted following cytokine treatments to investigate molecular changes associated with treatments.

  Dataset EGAD50000002782

• Single-cell transcriptomic profiling of metastatic colorectal cancer organoids maintained in growth medium.

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from patient-derived xenograft (PDX) models. Organoids were seeded in 12-well plates, embedded in 200 µL of Matrigel or BME diluted 1:1 with culture medium, and maintained with EGF-supplemented growth medium. After 7 days (or 11 days) of growth, organoids were harvested, dissociated, and live single cells were sorted for single-cell RNA sequencing using the 10x Genomics platform.

  Dataset EGAD50000002797