7345 results for "canc*"

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• Single-cell RNA sequencing of human omental tissue in benign and metastatic ovarian cancer

  To elucidate the cellular and molecular mechanisms underlying omental homeostasis and its transformation during ovarian cancer metastasis, a human omental cell atlas was generated encompassing both benign and metastatic conditions. Single-cell RNA sequencing was performed on freshly dissociated omental tissue samples from patients with newly diagnosed benign and malignant disease. Samples collected during diagnostic surgery covered distinct anatomical regions, enabling comparison between non-metastasized omentum and sites along the metastatic gradient, including distant, peritumoral, and tumor core areas.

  Study EGAS50000001465

• 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

• PTEN homozygous deletion is a negative prognostic factor in Tumor Treating Fields-treated glioblastoma, IDH wildtype patients

  This study investigates genomic determinants of outcome in glioblastoma, IDH-wildtype patients treated with Tumor Treating Fields (TTFields) in addition to standard radiochemotherapy. Tumor tissue from primary glioblastoma at initial diagnosis was profiled using the Illumina TruSight Oncology 500 (TSO500) targeted sequencing panel to characterise somatic alterations. The overarching goal is to provide exploration of genomic determinants of survival and treatment response in TTFields-treated glioblastoma, IDH-wildtype.

  Study EGAS50000001469

• Single cell sequencing: Capturing the origin and dynamics of chromosomal copy-number heterogeneity

  Study EGAS00001003812

• Whole-exome sequencing and RNA-seq data of paired normal-tumour samples from MMR-proficient early-onset colorectal cancer patients

  This study aims to identify novel hereditary colorectal cancer predisposition genes by performing whole-exome sequencing and RNA-seq of paired normal colonic mucosa and colorectal cancer samples from 19 patients diagnosed with MMR-proficient colorectal cancer at an age of 50 years or younger. Both whole-exome and RNA sequencing were performed on the Illumina platform.

  Study EGAS50000001296

• Genome- and epigenome-driven evolutionary dynamics of tumour-immune coevolution within primary colorectal cancers

  This data includes targeting sequencing of the immunopeptidome from 94 samples, usually individual laser microdissected cancer glands, from 11 cases of colorectal cancer. The data were used to test for evidence of immunoediting (antigen depletion) in colorectal cancers. The full data description is provided in the original manuscript https://pmc.ncbi.nlm.nih.gov/articles/PMC10888923/. The 11 colorectal cancers had been previously multiomic profiled with data described in the parts of this disposition.

  Study EGAS50000001154

• RNA sequencing of in vitro generated suppressive myeloid cells using parental and Sialidase expressing A549 cancer cell lines

  Study EGAS00001007618

• Cell-free DNA methylome and fragmentome analysis for disease relapse monitoring in patients with Ewing Sarcoma

  We conducted whole-genome and methylome sequencing of cfDNA from 87 serial samples of 23 patients with EwS and 3 patients with CIC-rearranged sarcoma (CIC). With EwingSign, a new machine learning model, we identified EwS or CIC in a test set for 11 out of 16 patients at diagnosis and 15 out of 18 clinically confirmed relapse events. 0 out of 24 non-cancer controls were detected positive with EwingSign.

  Study EGAS50000001415

• Intrapatient tumor heterogeneity and clonal evolution in metastatic salivary gland cancer: an autopsy study

  This data contains DNA sequencing data of an autopsy study in patients with salivary gland cancer. Whole-genome sequencing was performed on multiple spatially separated tumor samples per patient (4-7 per patient) and healthy control samples.

  Study EGAS50000001420

• RNA seq data of 2 lung cancer samples prepared using 2 different RNA-seq library preparation protocols

  Raw data used for generation of the results in the Vardetector manuscript – “.bam” files of RNA-seq data of tumor samples of 2 patients prepared with 2 different library preparation protocols (exome-capture and ribodepletion –> 4 “.bam” files in total). The submission also contains the somatic mutations “.vcf” files (4 in total, however 2 unique). Moreover, also an output of the Vardetector module (“.csv” file with the number of reads above the mutations of interest) is present in the submission (4 “.csv” files in total).

  Study EGAS50000001419

• Molecular evolution and clinical trajectories of prostate cancer identifies novel markers for risk stratification - additional data

  Study EGAS00001004884

• Discovery and validation of an ancillary genomic test of malignancy for primary melanocytic tumors

  Background:Pathological diagnosis of melanocytic tumors can be difficult and prone to error. More accurate and reliable ancillary investigations than those currently available are required to improve diagnostic accuracy. Goals: (1) to generate a genomic model for distinguishing benign (nevi) from malignant (melanoma) melanocytic skin tumors, developed from a customized gene panel evaluated on a cohort of 250 nevi and melanomas. (2) To evaluate the performance of the genomic model in melanocytic tumors of uncertain diagnosis/behavior. Details: The cohort of 250 melanomas and naevi was split into a discovery set and a validation set. Our genomic model obtained an area under the curve of 95% in the discovery cohort and 96% for the validation cohort. Based on a Youden index threshold, the resulting classifier shows high specificity (>95% in the discovery and validation cohorts), with sensitivities >80% in the discovery and validation cohorts. Evaluation of the genomic model on a cohort of 110 melanocytic tumors identifies key driver mutations in agreement with the likely pathway of origin of the tumors. The probability of melanoma (p=0.02) from the genomic model was significantly associated with pathology-based estimates of malignancy for melanocytic tumors lacking pathway-defining genomic aberrations (conventional tumors). The genomic model identified 8/36 (22%) conventional tumors with unresolved malignancy to have a high probability of melanoma, with 7/8 of these cases showing negative/non-aberrant results with either fluorescent in-situ hybridization, PRAME and/or p16 immunostains. Furthermore, no evidence of malignant behavior based on the genomic model was seen in 4 conventional borderline tumors with more than 1 year follow-up. Conclusion: This genomic model can become a clinically useful ancillary tool that is highly specific for differentiating melanomas from nevi.

  Study EGAS50000000887

• Tumor Profiler Ovarian Study

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. Technologies used are digital pathology, targeted NGS, single-cell RNA, single-cell DNA, bulk RNA, bulk proteotyping, single-cell CyTOF, imaging mass cytometry, pharmacoscopy, 4i Drug Response Profiling, and cell-free DNA. These technologies were applied to 240 tumor samples collected over 3 years across three cancer indications: metastatic melanoma, metastatic epithelial ovarian cancer, and acute myeloid leukemia (AML). Here, we publish the scRNA and scDNA data of the ovarian cancer cohort.

  Study EGAS50000000885

• Clonal Evolution and Transcriptional Plasticity Shape Metastatic Dissemination Routes in Prostate Cancer

  This study provides comprehensive insights into the genetic and transcriptomic landscape of prostate cancer, highlighting significant clonal heterogeneity, transcriptional plasticity, and metastatic spread patterns. We examined the clonal evolution and metastatic dissemination of prostate cancer by integrating single-nuclei RNA sequencing (snRNA-seq) and low-pass whole-genome sequencing (WGS) data from 43 spatially distinct tumour samples in five patients with locally advanced disease. By reconstructing the evolutionary trajectories of each tumour, we identified distinct patterns of tumour evolution, including both monophyletic and polyphyletic metastatic dissemination, as well as ongoing primary tumour clonal evolution after metastatic spread. We observed converging changes leading to metastatic potential, such as androgen receptor independence and increased activity in the estrogen, WNT, and JAK/STAT pathways in identified seeding areas. These findings enhance our understanding of the disease's progression and may inform future therapeutic strategies.

  Study EGAS50000000927

• High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. These tumors were profiled using whole-genome sequencing (WGS) or whole-exome sequencing (WES) to identify somatic mutations, WGS or low-pass WGS to detect copy number alterations, targeted capture sequencing to assess MYC and BCL2 structural variants, and RNA sequencing. The genetic features of HGBCL-NOS were compared to those of diffuse large B-cell lymphoma (DLBCL-NOS) and EBV-negative adult Burkitt lymphoma (BL). DLBCL-NOS tumors underwent targeted capture sequencing using a panel of 125 genes recurrently mutated in aggressive B-cell lymphomas. BL biopsies were drawn from the Burkitt Lymphoma Genome Sequencing Project and had available WGS (dbGaP Study Accession: phs000527.v18.p6).

  Study EGAS50000000932

• Sequencing data of tumor tissue obtained from GANNET53 study patients

  The GANNET53 clinical trial evaulated novel treatment options for ovarian cancer patients with platinum-resistant relapse. Archival fresh-frozen paraffin embedded tissue was available from 131 of the 133 enrolled patients. NGS sequencing aimed at assessing the mutational spectrum of key ovarian cancer genes (with a focus on TP53), and their relevance for therapy resistance. From available FFPE samples, DNA was extracted and NGS sequenced using the SureSeq™ Ovarian Cancer Panel and the NGS Library Preparation kit covering all exons of 7 key ovarian cancer genes BRCA1, BRCA2,TP53, PTEN, ATM, ATR, NF1 for single nucleotide variants (SNV) and indels. Finally, sequence data from 118 individual FFPE tumor tissue samples were generated.

  Study EGAS50000000935

• 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

• Genomic landscape of poorly differentiated thyroid carcinoma

  Poorly differentiated thyroid carcinoma (PDTC) is a rare and aggressive subtype of thyroid cancer with limited molecular characterization. This study aims to define the somatic mutational landscape of PDTC using whole-genome sequencing. Paired tumour and matched normal blood samples were collected from six patients undergoing surgery. The overarching goal is to identify recurrent mutations, structural variants, and other genomic alterations associated with tumour aggressiveness and poor clinical outcomes.

  Study EGAS50000001134

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting.

  Study EGAS50000001595

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Genomic and transcriptomic analysis of thymic epithelial tumors

  Thymic epithelial tumors (TETs), comprising various histologic types of thymomas and thymic carcinomas, originate from thymic epithelial cells. Each histologic type is typically associated with a distinct immune cell composition and clinical manifestation. A better understanding of the cellular origins and molecular pathways underlying this heterogeneity is needed to improve patient stratification and treatment. Here, we conducted an integrated genomic and transcriptomic analysis of 124 thymomas and 13 thymic carcinomas, including 20 newly sequenced cases combined with 117 cases from publicly available datasets. This approach stratified TETs into three subgroups with different possible origins: GTF2I-mutant (GTF2I-type) thymomas, copy number-altered (CN-type) thymomas, and thymic carcinomas.

  Study EGAS00001004227

• Activation of IL7RA signalling in human B-lymphoid precursors induces pre-leukemia

  Study EGAS00001003979

• ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium.

  The telomeric amplicon at 8p12 is common in oestrogen receptor-positive (ER+) breast cancers. Array-CGH and expression analyses of 1172 primary breast tumours revealed that ZNF703 was the single gene within the minimal amplicon and was amplified predominantly in the Luminal B subtype. Amplification was shown to correlate with increased gene and protein expression and was associated with a distinct expression signature and poor clinical outcome. ZNF703 transformed NIH 3T3 fibroblasts, behaving as a classical oncogene, and regulated proliferation in human luminal breast cancer cell lines and immortalized human mammary epithelial cells. Manipulation of ZNF703 expression in the luminal MCF7 cell line modified the effects of TGFβ on proliferation. Overexpression of ZNF703 in normal human breast epithelial cells enhanced the frequency of in vitro colony-forming cells from luminal progenitors. Taken together, these data strongly point to ZNF703 as a novel oncogene in Luminal B breast cancer.

  Study EGAS00000000082

• METABRIC

  Solid tumors are complex tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Normal cell contamination can dilute cancer cell information and tissue architecture is generally not reflected in molecular assays. To address these challenges, we developed a computational approach based on standard Haematoxylin and Eosin-stained sections and demonstrated its power in a discovery cohort of 323 breast tumors and an independent validation cohort of 241 tumors. First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.

  Study EGAS00000000098

• METABRIC miRNA landscape

  MicroRNAs (miRNAs) are key players in cancer pathogenesis1. They display differential expression across breast cancer subtypes, and play oncogenic and tumor-suppressive roles2-6. A systematic study of the global miRNA landscape in breast cancer and the factors shaping it has not been undertaken. Here we report the results of profiling miRNA expression in 1,302 breast tumors with detailed clinical annotation and long-term follow-up, and for which matching genomic and mRNA expression data were available7. This provides a comprehensive view of the quantity, distribution and variation of the miRNA population and dissects how much genomic, transcriptional and post-transcriptional events contribute to miRNA expression architecture. The key clinical parameters and cellular pathways related to the miRNA landscape are identified, exemplified by context-dependent interaction with cell adhesion and Wnt signaling. Strikingly, in breast cancer miRNAs appear to act as modulators of mRNA-mRNA interactions rather than molecular switches. We demonstrate an important modulatory role for miRNAs in the biology of breast tumors devoid of somatic copy number aberrations, a common subtype where immune response is prominent. Remarkably, prognostic miRNA signatures derived in this subtype are consistently prognostic across several other subtypes and validate in external cohorts. These findings represent a new framework to study the biology of miRNA in human cancer.

  Study EGAS00000000122