6052 results for "canc*"

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• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer

  Study EGAS00001007372

• Berlin Neuroblastoma Dataset Update 2021

  Study EGAS00001005604

• H021-Master Umbrella study2 (not to be released)

  Study EGAS00001005145

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  Study EGAS00001006905

• Genomic characterization of retinoblastoma

  Study EGAS00001005248

• ATAC-seq data in normal colon mucosa

  This dataset includes ATAC-seq data generated in normal colon mucosa obtained in four healthy volunteers during colonoscopy indicated for colorectal cancer screening. Subjects had no lesions in the colon. Also includes one frozen sw480 colon adenocarcinoma cell line sample for piloting the protocol

  Study EGAS00001005281

• DAC - Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  Dac EGAC00001002549

• Identification of early disease progression in ALK-rearranged lung cancer using circulating tumor DNA analysis (hipo_K34R)

  Study EGAS00001005327

• Evaluating CRISPR-based Prime Editing for cancer modeling and CFTR repair in organoids

  Study EGAS00001005358

• The Institute of Cancer Research - Endocrinology Team

  Dac EGAC00001000532

• SmMIP-tools:a computational toolset for processing and analysis of single-molecule molecular inversion probes derived data

  Single-molecule molecular inversion probes (smMIPs) provides a modular and cost-effective platform for high-multiplex targeted next-generation sequencing (NGS). Nevertheless, translating the raw smMIP-derived sequencing data into accurate and meaningful information currently requires proficient computational skills and a large amount of computational work, prohibiting wide-scale adoption of smMIP-based technologies. To enable easy, efficient, and accurate interrogation of smMIP-derived data, we developed SmMIP-tools, a computational toolset that combines the critical analytic steps for smMIP data interpretation into a single computational pipeline. Here, we describe in detail two major components of the software. The first is a read processing tool that performs quality control steps, generates read-smMIP linkages and retrieves molecular tags. The second is an error-aware variant caller capable of detecting single nucleotide variants (SNVs) and short insertions and deletions (indels). Using a cell-line DNA dilution series and a cohort of blood cancer patients, we benchmarked SmMIP-tools and evaluated its performance against clinical sequencing reports. We anticipate that SmMIP-tools will increase accessibility to smMIP-technology, enabling cost-effective genetic research to push personalized medicine forward.

  Study EGAS00001005359

• PELICAN33 longitudinal clinical and autopsy phenomic assessment in lethal metastatic prostate cancer

  Objective: To identify novel phenotypes and features associated with metastatic prostate cancer (mPC) outcome, and to identify biomarker and data requirements to be tested in future precision oncology trials. Design, Setting, and Participants: We analyzed deep longitudinal clinical, neuroendocrine expression, and autopsy data of 33 men who died from mPC between 1995 and 2004 (PELICAN33), and related findings to mPC biomarkers reported in the literature. Intervention: 33 men prospectively consented to participate in an integrated clinical-molecular rapid autopsy study of mPC.

  Study EGAS00001005399

• WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, here we aim at performing WGS of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005559

• Identifying transcriptional programs underlying anti-EGFR small molecule response and resistance with TraCe-seq

  Genetic and non-genetic heterogeneity within cancer cell populations represents a major challenge to anti-cancer therapies. We currently lack robust methods to determine how pre-existing and adaptive features affect cellular responses to therapies. Here, by conducting clonal fitness mapping and transcriptional characterization using expressed barcodes and single-cell RNA-sequencing, we have developed TraCe-seq, a method that captures at clonal resolution the origin, fate, and differential early adaptive transcriptional programs of cells in a complex population in response to distinct treatments. We used TraCe-seq to benchmark how next-generation dual EGFR inhibitors-degraders compare to standard EGFR kinase inhibitors in EGFR-mutant lung cancer cells. To QC the TraCe-seq strategy, single-cell RNA-seq libraries were generated from a variety of human cancer cell lines transduced with the TraCe-seq library to validate the TraCe-seq strategy. Specifically, 5 different cell lines (PC9, MCF-10A, MDA-MB-231, NCI-H358, and NCI-H1373) were each transduced with a unique TraCe-seq barcode. The transduced cells were selected with puromycin only, dissociated to single cell suspensions, and then mixed together. The complex mixture of the 5 cell lines was profiled by 10X scRNA-seq. Furthermore, transduced NCI-H1373 cells were sorted by FACS to enrich for the top 50% of eGFP positive cells, and sorted cells were cultured briefly and used to construct scRNA-seq libraries and profiled by 10x scRNA-seq. To carry out the full TraCe-seq experiment, ~600 PC9 cells carrying unique TraCe-seq barcodes were expanded over 12 doublings to establish the barcoded population. A subset of the barcoded PC9 population was used to generate scRNA-seq libraries and profiled by 10x scRNA-seq prior to treatment to establish a baseline transcription profile for each barcoded clone. The rest of the cells were then treated for four days with 1 µM erlotinib, 1 µM GNE-069, or 1 µM GNE-104 respectively. scRNA-seq libraries were then generated form the treated cells and profiled by 10x scRNA-seq.

  Study EGAS00001005405

• Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized controlled trial AGITG-MAX

  Patients and methods: We analyzed tumor samples of 256 patients enrolled in the AGITG-MAX 3-arm randomized controlled trial (RCT) who were randomly assigned to receive either capecitabine, or capecitabine and bevacizumab with- or without mitomycin. Chromosome 18q11.2-q12.1 copy number status was measured and correlated with PFS according to a predefined analysis plan with marker-treatment interaction as the primary end-point.Results: Chromosome 18q11.2-q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the non-randomized study, significant PFS benefit of bevacizumab was observed in chromosome 18q11.2-q12.1 loss patients (P=0.009), and not in 18q no-loss patients (P=0.67). Although significance for marker-treatment interaction was not reached (Pinteraction = 0.28), hazard ratio and 95% confidence interval (HRinteraction 0.72, CI 0.39 - 1.32) show striking overlap with the non-randomized study cohorts (HRinteraction 0.41, CI 0.32 - 0.8) supported by a non-significant Cochrane chi-squared (P=0.11) for heterogeneity. Conclusions: PFS characteristics for marker positive- and negative patients randomized for treatment with- or without bevacizumab were consistent with those of the non-randomized discovery study, though the number of AGITG-MAX samples fell short to reach significance for marker-treatment interaction. Post-hoc analysis of the AGITG-MAX RCT provides supportive evidence for chromosome 18q11.2-q12.1 as a clinically relevant predictive marker for mCRC patients.

  Study EGAS00001005453

• Germline variants in patients with rare cancers and their implications for precision cancer medicine: experiences from the Multicenter MASTER Trial by the German Cancer Consortium (HIPO_021)

  The era of precision oncology entails an increasing amount of molecular data from tumor sequencing in research and diagnostics. In this setting, germline variant analysis may add clinical benefits for patients and family members. In this study, we evaluated germline variants from genome/exome matched tumor-blood sequencing in 1.485 advanced cancer patients within a prospective observational study carried out by the German Cancer Consortium. Included patients had cancers of rare entities (79.2%) or were under the age of 51 at first diagnosis (76.6%). Ten percent of the patients harbored pathogenic germline variants in 35 tumor predisposition genes with autosomal-dominant inheritance such as BRCA1, BRCA2, TP53, RB1, CHEK2, ATM, PALB2, SDHB etc., while 4.6% of the patients were carriers of pathogenic germline variants in 18 genes with autosomal-recessive inheritance of tumor predisposition. Based on pathogenic germline variants, 14% of the patients received genetic counselling recommendations in the molecular tumor board report. Forty five percent of pathogenic germline variants supported a molecular treatment recommendation, which was implemented for 28 patients. Furthermore, we compared our approach and results to previous studies, broadening the insight into pan cancer germline findings but also revealing differences between studies on various levels, such as cohort demographics, tumor entities, gene nominations, variant detection and variant interpretation. Our data support the importance of germline variant interpretation in precision oncology studies for patients and their families, if applicable. However, guidelines for evaluation and reporting of germline variants in the context of genetic tumor profiling need to be established and further research on the relevance of germline mutations as biomarkers for treatment recommendations is needed.

  Study EGAS00001005537

• Multiregion Whole-Exome Sequencing Uncovers the Genetic Evolution and Mutational Heterogeneity of Early-Stage Metastatic Melanoma.

  Study EGAS00001004320

• Cell-free DNA sequencing data of healthy control, atrophic gastritis, and gastric cancer patients’ blood

  Study EGAS00001007308

• Translation of non-canonical open reading frames as a cancer cell survival mechanism in childhood medulloblastoma

  A hallmark of high-risk childhood medulloblastoma is the dysregulation of RNA translation. Currently, it is unknown whether medulloblastoma dysregulates the translation of putatively oncogenic non-canonical open reading frames. To address this question, we performed ribosome profiling of 32 medulloblastoma tissues and cell lines and observed widespread non-canonical ORF translation. We then developed a step-wise approach to employ multiple CRISPR-Cas9 screens to elucidate functional non-canonical ORFs implicated in medulloblastoma cell survival. We determined that multiple lncRNA-ORFs and upstream open reading frames (uORFs) exhibited selective functionality independent of the main coding sequence. One of these, ASNSD1-uORF or ASDURF, was upregulated, associated with the MYC family oncogenes, and was required for medulloblastoma cell survival through engagement with the prefoldin-like chaperone complex. Our findings underscore the fundamental importance of non-canonical ORF translation in medulloblastoma and provide a rationale to include these ORFs in future cancer genomics studies seeking to define new cancer targets.

  Study EGAS00001007426

• Human lymphoma plasma cfRNA - raw data

  This study contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma patients, 13 primary mediastinal large B-cell lymphoma patients and 22 cancer-free controls.

  Study EGAS00001007127

• Complex patterns of genomic heterogeneity identified in 42 tumor samples and ctDNA of a pulmonary atypical carcinoid patient

  Study EGAS00001006530

• Defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Germline structural variants (SVs) are challenging to identify by conventional genetic testing assays. Long-read sequencing has improved the global characterization of SVs, but its sensitivity at genetic loci associated with high- and moderate-penetrance cancer susceptibility has not been reported. This study used long-read genome sequencing performed on the Oxford Nanopore Technologies' PromethION to resolve variants underlying breast cancer susceptibility in sixteen individuals with pathogenic germline SVs in BRCA1, BRCA2, CHEK2 or PALB2.

  Study EGAS00001005872

• Sequencing of an organoid biobank for childhood soft tissue sarcoma.

  Rhabdomyosarcomas are diverse tumors of mesenchymal origin and the most common childhood soft tissue sarcoma. Patients receive intense treatment with a nevertheless poor prognosis for high-risk patients. New therapy would benefit from additional preclinical models and their rapid establishment. Tumor organoid models (tumoroids) have so far only been established from epithelial cancers. Here, we describe generation and characterization of a collection of pediatric RMS tumoroids comprising all major subtypes.

  Study EGAS00001005912

• Single-cell RNA sequencing of chemotherapy-resistant muscle-invasive urothelial bladder cancer

  All single-cell mRNA sequencing data were acquired from a single patient (BC159-T#3) and patient-derived xenografts (BC159-T#3-PDX-vehicle and BC159-T#3-PDX-tipifarnib).

  Study EGAS00001004233

• Specific BRCA and immune configurations determine optimal response to platinum-based chemotherapy in triple negative breast and ovarian carcinomas (COH_TNBC_RNAseq)

  To determine the trascriptional profiles of Triple Negative Breast Cancers (COH cohort)

  Study EGAS00001006002