7147 results for "canc*"

in 10.08 milliseconds.

• WGS of clonal organoids, bulk-tumor tissues, and matched blood samples derived from metastatic colorectal cancer patients

  This dataset consists of WGS fastq files from 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients with matched blood control samples from each patient. After DNA extraction from each sample using DNeasy Blood and Tissue Kit (Qiagen), library preparation was done using TruSeq DNA PCR-free kit. Then, paired-end fastq files were generated using Illumina NovaSeq 6000.

  Dataset EGAD50000001493

• Molecular profiles in early onset prostate cancer

  Paired germline (blood) and tumour samples were collected from prostate cancer cases <65 years at diagnosis to identify genetic changes in early onset prostate cancer.  Whole exome sequencing was performed on these samples. The aim was to determine if these changes are associated with more aggressive disease and to identify targets for treatment and screening by identifying associations with family history, DNA repair germline mutations, and clinical features.

  Study EGAS50000001467

• 46 WES paired FASTQ germline/tumour samples from 23 early-onset prostate cancer donors from the Bob Champion Cancer Trust

  The dataset contains 46 samples: a germline and tumour sample from each of 23 donors. Donors are men diagnosed with prostate cancer at a young age, from the Bob Champion Cancer Trust. The data consists of 92 whole exome sequenced paired FASTQ files, compressed with bgzip. Exome sequences were enriched using Agilent SureSelect XT2 Human All Exon V5 baits, and sequenced with Illumina HiSeq 2500.

  Dataset EGAD50000002112

• 16S rRNA Rectal Mucus

  16S rRNA sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001262

• Profiling the genomic landscape and evolutionary history of polyploid giant cancer cells in undifferentiated pleomorphic sarcomas

  Polyploid giant cancer cells (PGCCs), characterised by multi-nucleation and atypical nuclear morphology, are a common feature of undifferentiated pleomorphic sarcomas. While PGCCs may be a critical substrate for cancer evolution, their formation pathways and the genomic consequences of PGCCs remain relatively under explored. In this study, we characterise PGCCs in undifferentiated pleomorphic sarcomas, as well as their histological mimics, and use topographic single-cell DNA sequencing (scDNA-seq) to investigate their genomic landscape. We selected PGCCs based on their nuclear morphology, including mono-nucleated or multi-nucleated bizarre, misshapen nuclei and analysed them at single-cell resolution. Our findings highlight PGCCs as a highly heterogeneous and evolutionarily dynamic component of undifferentiated pleomorphic sarcomas.

  Study EGAS50000001445

• Profiling the genomic landscape and evolutionary history of polyploid giant cancer cells in undifferentiated pleomorphic sarcomas

  In this study, we characterise PGCCs in ten pleomorphic sarcomas and use topographic single-cell DNA sequencing (scDNA-seq) to investigate their genomic landscape. We selected PGCCs based on their nuclear morphology, including mononucleated or multinucleated bizarre, misshapen nuclei, and analysed them at single-cell resolution. Histopathological analysis showed that PGCCs were often randomly distributed throughout the tumour and did not appear in clusters, suggesting that they arise de novo rather than through clonal expansion. scDNA-seq revealed that PGCCs originate from the dominant tumour population and exhibit extensive copy number heterogeneity, either due to subsequent or ongoing chromosomal instability. Both clonal and subclonal chromothripsis-like events were identified in PGCCs, indicating that chromothripsis is a key driver of heterogeneity in these cells and is linked to multinucleation rather than mononuclear PGCC formation.

  Dataset EGAD50000002084

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Single-cell RNA sequencing was performed on a cetuximab-sensitive metastatic colorectal cancer (mCRC) patient-derived xenograft (PDX) model. The objective of this analysis was to assess whether the transcriptional patterns identified in the single-cell RNA-seq data of matched organoids were preserved in the in vivo context.

  Study EGAS50000001459

• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from a cetuximab-sensitive patient-derived xenograft (PDX) model. The objective of this analysis was to investigate, at single-cell resolution, the transcriptional changes previously identified in bulk RNA-seq analyses of PDX models exposed to anti-EGFR therapeutic pressure.

  Study EGAS50000001460

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Tumor implantation and expansion were performed in two 6-week-old NOD/SCID mice. Once tumors reached an average volume of approximately 700 mm³, mice were randomly assigned to one of two treatment arms: vehicle (physiological saline, intraperitoneally, twice weekly) or cetuximab (20 mg/kg, intraperitoneally, twice weekly). After 1 week of treatment, mice were sacrificed, and tumors were harvested and preserved in sCelLiVE® Buffer for downstream single-cell RNA sequencing analysis.

  Dataset EGAD50000002103

• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Organoids were seeded in 12-well plates at a density of 5 × 10⁴ cells per well, embedded in 200 µL of Matrigel diluted 1:1 with culture medium, and maintained under EGF-deprived conditions. After four days of growth, organoids were either left untreated or treated with cetuximab (20 µg/mL). Following 72 hours of treatment, organoids were harvested, dissociated, and live single cells were sorted for single-cell RNA sequencing using the 10x Genomics platform.

  Dataset EGAD50000002104

• RNAseq for 208 patients with medulloblastoma cancer (MB_COMICS cohort)

  This dataset contains 208 paired fastq files sequenced with Illumina HiSeq 2500.

  Dataset EGAD50000000600

• Berlin Neuroblastoma Dataset

  Study EGAS00001004022

• Sequence data to study genomic CNVs that drive apoptotic resistance and relapses on immune checkpoint inhibitors

  This project investigates the genomic mechanisms underlying acquired resistance to immune checkpoint inhibitors (ICIs) across tumor types, addressing the critical clinical problem of treatment relapses where the molecular basis remains poorly understood. Through integrative genomic analyses of longitudinal clinical melanomas, functional CRISPR-Cas9 screens, and human and murine melanoma models, the study demonstrates that copy-number variant (CNV)-driven subclonal evolution is a primary driver of clinical relapses. The research identifies resistance-driver genes targeted by CNVs, including pro-apoptotic gene deletions and anti-apoptotic gene amplifications, which collectively downregulate apoptotic priming in resistant cells. The findings establish that modulating the apoptotic threshold can prevent or reverse ICI resistance, positioning CNV evolution as a key driver of acquired resistance and identifying apoptotic regulation as a therapeutic target to combat resistance evolution.

  Study EGAS50000001055

• Shallow whole genome sequencing of ctDNA samples from DETECT study

  A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival from the paper "A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival", by Beddowes et al. Mol.Onc.

  Study EGAS50000000911

• Development and validation of multivariate predictors of primary endocrine resistance to tamoxifen and aromatase inhibitors in luminal breast cancer reveal drug-specific differences

  Background: Endocrine therapy is highly effective in blocking the estrogen receptor pathway in HR+/HER2- early breast cancer (EBC). However, up to 40% of patients experience relapse during or after adjuvant endocrine therapy. Here, we investigate molecular mechanisms associated with primary resistance to endocrine therapy and develop predictive models. Results: TP53 mutations were prominently associated with primary resistance to both tamoxifen (TAM) and aromatase inhibitors (AI), with AI non-responders exhibiting resistance in up to 32% of cases. Additionally, we identified distinct DNA methylation patterns in TAM and AI non-responders, with TAM non-responders showing global DNA methylation loss, associated with KRAS signaling, apical junctions and epithelial-mesenchymal transition (EMT). Conversely, we observed methylation gain in AI non-responders affecting developmental transcription factors, hypoxia and estrogen signaling. TAM or AI resistance was associated with increased methylation-inferred proportions of immune cells and decreased proportions of endothelial cells. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI stratified NR and R cases in both treatment groups and cohorts with high accuracy (ROC AUC TAM discovery 93.9%, validation 83%; AI discovery 98.6%, validation 76.9%). A simplified PERCI efficiently predicted progression-free survival in the TCGA-BRCA sub-cohort (Kaplan-Meier log-rank p-value = 0.03 between low and high PERCI groups). Conclusions: We identified genomic and epigenomic features associated with primary resistance to TMA and AI. By combining information on genomic alterations, patient age, differential methylation and tumor microenvironment (TME) composition, we developed PERCI TAM and PERCI AI as novel predictors of primary resistance, with potential additional prognostic value. Applying PERCI in a clinical setting may allow patient-specific drug selection to overcome resistance.

  Study EGAS50000001102

• Whole exome sequencing of patients with esophageal squamous cell carcinoma receiving chemoradiotherapy

  We performed multi-region whole exome sequencing (WES) of pre-treatment and recurrent esophageal cancer receiving chemoradiotherapy in order to characterize clonal evolution of treatment resistant clones. Furthermore, additional solitary pre-treatment tumor samples were subjected to WES to detect biomarkers predicting clinical outcome.

  Study JGAS000227

• Genome sequencing of biliary tract cancers

  Biliary tract cancers (BTCs) are clinically and pathologically heterogeneous with poor response to treatments. Genomic profiling can offer a clearer understanding of their carcinogenesis, classification and treatment strategy. We performed genome sequencing analyses for a large scale samples of BTCs to investigate their somatic and germline driver events and characterize their genomic landscape.

  Study JGAS000109

• A study on personalized medicine in genitourinary cancers using genetic biomarkers

  We present a patient with MSI-high castration-resistant PC who showed a remarkable and durable response to pembrolizumab. Whole exome sequencing revealed approximate tumor mutation burden of 61 mutations/Mb as well as biallelic loss of MSH2.

  Study JGAS000510

• Research for biological features by gene expression analysis and biomarkers at diagnosis/therapeutics in lung cancer

  WGS, WES, ATAC-seq and methylation analysis with DNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients. RNA-seq analysis with RNA harvested from lung cancer organoids established from surgery, biopsy, pleural effusion, sputum and blood samples of patients.

  Study JGAS000610

• Whole genome sequence analysis in patients with primary central nervous system lymphomas

  We performed target amplicon sequencing analysis in 28 patients with primary central nervous system lymphomas using target capture technology (NGS) on Cancer Panel to explore molecular targets.

  Study JGAS000258

• Phylogenetic analysis of combined lobular and ductal carcinoma of the breast

  Breast cancer manifests in diverse forms, with particular reference to various cell types harboring different mutations and gene expression profiles. To elucidate the clonal relationship between cancer cells in tumors composed of both ductal and lobular phenotypes, we analyzed two combined lobular and ductal carcinoma (CLDC) cases, including one mixed ductal-lobular carcinoma (MDL) lesion, by next generation sequencing.

  Study JGAS000300

• Common and rare germline variants in Japanese prostate cancer patients

  Study JGAS000487

• Identification of genetic mutations characteristic for recurrence and metastasis of lymphoma.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent B cell lymphoma, and the purpose of this study is to find the characteristics of recurrent B cell lymphoma by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000087

• Target sequencing of ROS1-rearranged lung cancer patients

  We performed target capture sequencing of ROS1-rearranged non-small cell lung cancer patients to develop and examine the efficacy of new molecular targeted drug against ROS1 tyrosine kinase.

  Study JGAS000189

• exploration of biomarkers discriminating squamous cell carcinoma from other lung cancers

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we initially performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). We furhter expanded the transcriptome profiling to cover additional 48 malignant neoplasm of bronchus and lung, including mesothelioma and metastatic lung cancers derived from other tissues.

  Study JGAS000488