7153 results for "canc*"

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• RESOLVE_trial_targeted_sequencing_data

  RESOLVE: Abemaciclib + Letrozole +/_- Metformin, Zotatifin, or Gedatolisib in Endometrial or Low-Grade Serous Ovarian Cancer

  Study EGAS50000001202

• 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

• 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

• R compatible Seurat's objetc .rds files with count data and metadata from single cell RNA seq analysis to characterize the prostate cancer tumoral microenviroment of 31 fusion biopses.

  Pre-processed Seurat objects with cellular and functional annotation information from the scRNAseq study on PC fusion biopsy samples. The data consists of rds files composed of normalised counts matrices, normalised and scaled counts, functional enrichment counts at the cellular level and metadata with patient grouping and cellular annotation variables. There are 3 .rds files, one with the total cells (SCP_data_analysis), with the selection of cells annotated as cancerous (selected_cancer_analysis) and cancer-associated fibroblasts (selected_caf_analysis).

  Dataset EGAD50000001298

• 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

• Division of Cancer Evolution National Cancer Center Research Institute Data Access Committee

  Data Access Committee for data from Division of Cancer Evolution, National Cancer Center Research Institute

  Dac EGAC50000000737

• WGS of oesophagogastric cancer

  Illumina short read WGS of 12 oesophagogastric cancer samples

  Dataset EGAD50000002239

• WGS of oesophagogastric cancer

  WGS of 12 oesophagogastric cancer samples WGS or 12 matched germline data.

  Dac EGAC50000000890

• HNSCC Patients Treated with Immune Checkpoint Blockade

  HNSCC Patients Treated with Immune Checkpoint Blockade

  Study EGAS50000001175

• CIAO Clinical Trial

  Whole exome and RNA sequencing for samples from CIAO (Checkpoint Inhibitors Assessment in Oropharynx cancer) (NCT03144778) clinical trial testing neoadjuvant anti-PD-L1 durvalumab with or without the anti-CTLA-4 tremelimumab in oropharynx cancer

  Study EGAS50000001174

• Identifying mutations in patient-derived melanoma DCC lines

  To identify mutations that cause resistance, we analyzed two patient-derived cell lines: Mel-DCC-11 (the parental line, sensitive to the BRAF inhibitor) and Mel-DCC-11-R (resistant to the BRAF inhibitor). We employed targeted-panel sequencing to examine the coding sequences of 410 cancer-associated target genes.

  Study EGAS50000001225

• Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade

  Following the pivotal Phase III IMpower133 study, atezolizumab (anti–PD-L1), combined with carboplatin and etoposide (CE), was the first immune checkpoint inhibitor approved for first-line treatment of extensive-stage small cell lung cancer (ES-SCLC) and is now a standard of care. A clearer understanding of therapeutically relevant SCLC subsets is needed to improve outcomes and to identify rational combination strategies. Transcriptomic analyses and nonnegative matrix factorization were conducted on 271 pre-treatment patient tumor samples from IMpower133 and four subsets with general concordance to previously reported SCLC subtypes were identified. Deeper investigation into the immune heterogeneity relevant to clinical outcomes uncover two subsets with differing neuroendocrine (NE) versus non-neuroendocrine (non-NE) phenotypes that demonstrated hallmarks of immune cell infiltration. The balance of tumor-associated macrophage (TAM) to T-effector signals distinguished these inflamed subsets. Tumors with low TAM but high T-effector signals had a NE phenotype and demonstrated longer overall survival with PD-L1 blockade and CE versus CE alone than did tumors with high TAM and high T-effector signal, which had a non-NE phenotype. The delineation of SCLC immune heterogeneity offers a clinically relevant approach to discriminate SCLC patients likely to benefit most from immunotherapeutic approaches and highlights the complex mechanisms underlying response and resistance to immune checkpoint blockade. 

  Study EGAS50000000138

• Dynamics of checkpoint receptors in γδ T cell subsets are associated with clinical responses during anti-PD-1 immunotherapies

  Gamma delta (γδ) T cells are innate-like lymphocytes with potent anti-tumor properties. Herein, we show that immune checkpoint receptors (ICRs) display differential expression and regulation by the JAK-STAT pathway in Vδ1 and Vδ2 cells and identify constitutive (e.g. TIGIT, PD-1) and inducible (e.g. TIM-3, LAG-3, CTLA-4) ICRs. In melanoma, all γδ T cell subsets downregulated AP-1 transcription factors, but Vδ1 cells specifically expressed high levels of ICR, TOX and inhibitory killer Ig-like receptor (KIR) transcripts, reminiscent of exhaustion. However, patient-derived cells were functionally competent, although induction of LAG-3 and CTLA-4 was impaired. During anti-PD-1 monotherapy, Vδ1 cells specifically bound high levels of therapeutic antibody but only in patients who responded to treatment, revealing a potential new prognostic marker for evaluating the efficacy of IC blockade (ICB) therapy. Finally, expression of KIR genes in Vδ1 cells was downregulated in response to successful ICB therapy. Collectively, our data indicate an intricate relationship between ICRs and γδ T cells and reveal novel approaches by which these cells can be harnessed in order to discern or improve cancer immunotherapy.

  Study EGAS50000001270

• Fasting-mimicking diet reshapes antitumor immunity in cancer patients

  Study EGAS00001004944

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Prior studies have suggested the biomarker potential of plasma circulating tumor DNA (ctDNA) in cancer patients treated with immune checkpoint inhibitors (ICIs). In order to characterize the potential role of ultrasensitive ctDNA detection in the management of these patients we have performed tumor whole-genome-informed, ultrasensitive ctDNA analysis—tracking approximately 1,800 tumor-specific mutations per patient—in a retrospective cohort (n=136) and a prospective validation cohort (n=66) across 24 cancer types treated with ICIs alone or in combination with bispecific antibodies or immune cell engagers. Analyzing 1,455 longitudinal samples, we found that ctDNA molecular response measured as early as 3 weeks after treatment initiation correlated with improved progression-free and overall survival, while ctDNA clearance at any time strongly correlated with radiological response and prolonged survival. Additionally, ctDNA dynamics distinguished true progression from pseudoprogression and predicted outcomes in patients receiving continued immunotherapy beyond initial progression. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities.

  Study EGAS50000001333

• Broad utility of ultrasensitive analysis of ctDNA dynamics across solid tumors treated with immunotherapy

  Plasma ctDNA sequencing data from samples collected from a pan-cancer cohort of patients with advanced-stage disease treated with IO therapies. This study highlights the broader applicability of ultrasensitive ctDNA as a biomarker across cancer types and immunotherapy modalities. Here, we applied a whole-genome, tumor-informed approach to study ctDNA in 202 advanced-stage cancer patients treated at VHIO. This study captures the plasma sequencing data from the project.

  Study EGAS50000001271

• Delineation of the heterogeneous molecular landscape of HRS cells and their biological contributions to forming comprehensive TME ecosystems.

  The tissue architecture of classic Hodgkin Lymphoma (CHL) is unique among cancers and characterized by rare malignant Hodgkin and Reed-Sternberg cells that are co-evolving in a complex ecosystem of immune cells in the tumor microenvironment. The lack of a comprehensive systems-level interrogation has hindered the description of disease heterogeneity and clinically relevant molecular subtypes. Here, we employed an integrative, multimodal approach to characterize CHL tumors using malignant cell sequencing, spatial transcriptomics and imaging mass cytometry. We identified four molecular subtypes (CST, CN913, STB, and CN2P) each characterized by distinct clinical features, mutational patterns, malignant cell gene expression profiles, and spatial architecture of immune cell populations. Functional modeling of CSF2RB mutations, a characteristic feature of CST, revealed dysregulated oncogenic signaling and changes in tumor microenvironment crosstalk. These findings highlight the significance of multi-dimensional profiling in elucidating patterns of molecular alterations that drive immune ecosystems and underlie therapeutically exploitable vulnerabilities.

  Study EGAS00001008064

• PROMETEO

  The SOLTI-1503 PROMETEO trial was a single-arm, preoperative, window-of-opportunity phase II study conducted at four sites in Spain between December 2018 and February 2022. It enrolled female patients with operable HER2-negative breast cancer (triple-negative or Luminal B-like) and residual disease after neoadjuvant chemotherapy. Tumor biopsies were collected at five time points (baseline, post-NAC screening, C2D1, C3D1, and surgery) for translational research. This dataset includes raw paired-end RNA sequencing data (~110M reads per library) generated from the 113 biopy samples, archived in FASTQ format.

  Study EGAS50000001499

• FASTQ Files from Breast Tumor Biopsies Collected Across Five Timepoints in the PROMETEO Phase II Trial

  The dataset contains RNA sequencing raw data from tumor biopsies collected at five time points during the SOLTI-1503 PROMETEO trial: baseline (pre-NAC), post-NAC screening, Cycle 2 Day 1, Cycle 3 Day 1, and surgery. The study intervention consisted of intratumoral injections of T-VEC followed by intravenous administrations of atezolizumab prior to surgery. The data is obtained from tumor samples of patients included in the study: female breast cancer patients with residual disease after neoadjuvant chemotherapy, including both triple-negative and Luminal B-like subtypes. Each sample includes raw paired-end RNAseq reads (~110 million reads per library) aligned to the GRCh38/hg38 reference genome

  Dataset EGAD50000002165

• Whole genome sequencing of patient derived cancer and normal organoids

  The dataset includes whole genome sequencing data generated from regional patient derived colorectal cancer (CRC) and adjacent normal tissue organoids. The dataset contains samples from a total of 10 different early CRC biobank patients from 2 different sequencing runs.

  Dataset EGAD50000002204

• The dataset of Detection and characterization of lung cancer using cell-free DNA fragmentomes on NovaSeq 6000 at 1-2x coverage

  The dataset contains 364 CRAM files from whole-genome next-generation sequencing on the Illumina NovaSeq 6000 at 1- 2x coverage. These are plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000001961

• Metabolic requirements of the metastasis-initiating tumour cell population using oral squamous cell carcinoma (OSCC) as a model system

  Study EGAS00001004765

• ecDNA copy number heterogeneity

  Neuroblastoma exhibits significant inter- and intra-tumour genetic heterogeneity and varying clinical outcomes. Here, we used DNA and RNA sequencing from the same single cells in cell lines and neuroblastoma patients to investigate these effects. We reveal extensive intercellular ecDNA copy number heterogeneity. We also provide direct evidence of how this heterogeneity influences the expression of cargo genes, including MYCN and its downstream targets, and the overall transcriptional state of neuroblastoma cells.

  Study EGAS50000000509

• Using RNA-sequencing to characterize the resistance to lirafugratinib

  In addition to Exome-sequencing, we used RNA-sequencing to also characterize resistance to lirafugratinib with whole exome sequencing in patients with FGFR2-driven cancers, treated in the phase 1/2 ReFocus trial (NCT04526106) and enrolled in the UNLOCK program at Gustave Roussy

  Study EGAS50000001370

• Using Exome-sequencing to characterize the resistance to lirafugratinib

  We characterized resistance to lirafugratinib with whole exome sequencing in patients with FGFR2-driven cancers, treated in the phase 1/2 ReFocus trial (NCT04526106) and enrolled in the UNLOCK program at Gustave Roussy

  Study EGAS50000001371