6048 results for "canc*"

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• STM4 - Mouliere et al, 2018. Enhanced detection of circulating tumor DNA by fragment size analysis

  Study EGAS00001004418

• Genomic and transcriptomic determinants of therapy resistance and immune landscape evolution during anti-EGFR treatment in colorectal cancer

  Despite biomarker stratification, the anti-EGFR antibody cetuximab is only effective against a subgroup of colorectal cancers (CRC). This genomic and transcriptomic analysis of the cetuximab resistance landscape in 35 RAS wild-type CRCs identified associations of NF-1 and non-canonical RAS/RAF-aberrations with primary resistance and validated transcriptomic CRC-subtypes as non-genetic predictors of benefit. 64% of biopsies with acquired resistance harbored no genetic resistance drivers. Most of these had switched from a cetuximab-sensitive transcriptomic subtype pre-treatment to a fibroblast- and growth factor-rich subtype at progression. Fibroblast-supernatant conferred cetuximab resistance in vitro, confirming a major role for non-genetic resistance through stromal remodeling. Cetuximab treatment increased cytotoxic immune infiltrates and PDL1 and LAG3 immune-checkpoint expression, potentially providing opportunities to treat cetuximab-resistant CRCs with immunotherapy.

  Study EGAS00001003367

• Extreme intratumor heterogeneity and driver evolution in mismatch repair deficient gastro-esophageal cancer

  Study EGAS00001003434

• Detection of mutational patterns in cell free DNA (cfDNA) of colorectal cancer by custom amplicon sequencing

  Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell free (cf) DNA offers a non-invasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatics workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our method to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from 34 patients with advanced colorectal cancer. Our data demonstrates that recurrent and patient-specific mutational patterns can be reliably detected for the majority of patients. Furthermore, we show that the allele frequency of mutations in cfDNA correlates well with disease progression. Finally, we demonstrate that monitoring of cfDNA can outperform the predictive power of currently used tumor markers and reveal mechanisms of resistance to anti-EGFR antibody treatment.

  Study EGAS00001003382

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  Next generation sequencing (NGS) of circulating tumour DNA (ctDNA) supports blood-based genomic profiling but is not routinely implemented in the clinic. TARGET is a molecular profiling programme with the primary aim to match patients to early phase clinical trials based on analysis of both somatic mutations and copy number alterations (CNA) across a 641 cancer-associated gene panel in a single ctDNA assay. For the first 100 TARGET patients, ctDNA data showed good concordance with matched tumour and results were turned round within a clinically acceptable timeframe for Molecular Tumour Board (MTB) review. When applying a 2.5% Variant Allele Frequency (VAF) threshold actionable mutations were identified in 41/100 patients, with 11 of these patients going onto a matched therapy. These data support the application of ctDNA in an early phase trial setting where broad genomic profiling of contemporaneous tumour material enhances patient stratification to novel therapies and provides a practical template for bringing blood-based analyses to the clinic.

  Study EGAS00001003407

• Whole genome sequencing of Ewings Sarcoma

  Sarcomas are cancers of the bone and soft tissue often defined by their gene fusions. However, the timing, context, and processes by which these pathogenic fusions arise are unknown. We explored this in Ewing sarcoma, a cancer driven by EWSR1-ETS fusions, with very few cooperating mutations. Combining whole-genome sequencing with enhanced informatics, we found that the EWSR1-ETS fusion arose from striking rearrangement clusters in 42% of cases (52/124). Notably, these were organized in loops that universally contained the fusion at their center, while also weaving up to 18 genes together with it. We found the same pattern of rearrangements in three additional types of sarcoma. From these data, we define a new signature for sarcoma fusions that precedes other somatic changes, in the earliest replicating DNA of the genome. This dramatic, sudden process impinges on many genes – generating multiple coding changes that profoundly affect the transcriptome, with the disease-defining gene fusion at its core. These rearrangement loops emerge in an early ES clone from which both the primary tumor and the lethal relapse emerged, and then evolved in parallel until clinically detected.

  Study EGAS00001003385

• Sequencing Study in COPD cases and controls

  Since smokers with COPD have a higher risk of developing lung cancer than those without, we hypothesized that they carry more mutations in affected tissue. We called somatic mutations in airway brush samples from medium-coverage whole genome sequencing data from healthy never and ex-smokers (n=8), as well as from ex-smokers with variable degrees of COPD (n=4). Owing to the limited concordance of resulting calls between the applied tools we built a consensus, a strategy that was validated with high accuracy for cancer data.

  Study EGAS00001003406

• Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Most patients with late stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, thus making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft (PDX) models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the pro-apoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death and displayed synergy in vitro in most models. In vivo, the GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models – those with high BIM at baseline that was increased with MEK inhibition and those with low basal Bim and high pERK levels. Models with low BIM and low pERK were non-responsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

  Study EGAS00001003427

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Functional and genomic heterogeneity of long-term self-renewing compartment as the origin of treatment resistance in pancreatic tumors

  Adaptive drug-resistance mechanisms allow human tumors to evade treatment through selection and expansion of treatment-resistant clones. Here, studying clonal evolution of tumor cells derived from human pancreatic tumors, we demonstrate that in vitro cultures and in vivo tumors are maintained by a common set of tumorigenic cells that can be used to establish clonal replica tumors (CRTs), large cohorts of animals bearing human tumors with identical clonal composition. Using CRTs to conduct quantitative assessments of adaptive responses to therapeutics, we uncovered a multitude of functionally heterogeneous subpopulations of cells with differential degrees of drug sensitivity. High-throughput isolation and deep characterization of unique clonal lineages showed genetic and transcriptomic diversity underlying functionally diverse subpopulations. Molecular annotation of gemcitabine-naïve clonal lineages with distinct responses to treatment in the context of CRTs generated signatures that can predict the response to chemotherapy, representing a potential biomarker to stratify patients with pancreatic cancer. RNA-Seq data on these clones are available on EBI ENA, under accession number: PRJEB27735.

  Study EGAS00001003442