7154 results for "canc*"

in 9.78 milliseconds.

• WXS of 147 lung cancer patients treated with immunotherapy

  We first attempted to predict MHC-binding neoantigens at high accuracy with convolutional neural networks. This prediction model outperformed previous methods in > 70% of test cases. Importantly, our method remarkably increased the predictive value of neoantigen load especially in combination with known resistance parameters. We then developed a classifier that can predict resistance from point mutations that are deleterious to protein function. Notably, genes involved in the adaptive immune response, cytokine signaling,and EGFR signaling held high explanatory power. Furthermore, when integrated with our neoantigen profiling, these anti-immunogenic mutations revealed significantly higher predictive power than known resistance factors.

  Study EGAS00001003781

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer RNA-Seq

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the patient matched RNA-Sequencing data.

  Study EGAS00001003307

• Patient-Derived Lung Cancer Organoid

  Lung cancer shows substantial genetic and phenotypic heterogeneity across individuals, driving a need for personalized medicine. Here we report lung cancer organoids and normal bronchial organoids established from patients tissues comprising five histological subtypes of lung cancer and non-neoplastic bronchial mucosa as in vitro models representing individual patient. The lung cancer organoids recapitulate the tissue architecture of the primary lung tumours and maintain the genomic alterations of the original tumours during long-term expansion in vitro. The normal bronchial organoids maintain cellular components of normal bronchial mucosa. Lung cancer organoids respond to drugs based on their genomic alterations: a BRCA2 mutant organoid to olaparib, an EGFR mutant organoid to erlotinib, and an EGFR mutant/MET amplified organoid to crizotinib. Considering the short length of time from organoid establishment to drug testing, our newly developed model may prove useful for predicting patient-specific drug responses through in vitro patient-specific drug trials.

  Study EGAS00001003786

• Cistrome-partitioning reveals convergence of somatic mutations and risk-variants on master transcription regulators in primary prostate tumors

  Thousands of noncoding somatic Single Nucleotide Variants (SNVs) of unknown function are reported in tumors. Partitioning the genome according to cistromes, reveals the enrichment of somatic SNVs in prostate tumors as opposed to adjacent normal tissue cistromes of master transcription regulators, including AR, FOXA1 and HOXB13. This parallels enrichment of prostate cancer genetic predispositions over these transcription regulators’ tumor cistromes, exemplified at the 8q24 locus harboring both risk-variants and somatic SNVs in cis-regulatory elements, upregulating MYC expression and altering the binding of transcription regulators to DNA. However, Massively-Parallel Reporter Assays reveal that few SNVs can alter the transactivation potential of individual CREs. Instead, SNVs accumulate, similarly to inherited riskvariants, in cistromes of master transcription regulators required for prostate cancer development. Difficulties in inferring the biological significance of noncoding mutations have limited their inclusion in precision genomics medicine pipelines. Most attempts to delineate a role for noncoding mutations relied on detecting evidence for positive selection within individual CREs, such as reported for the TERT gene promoter. By considering the enrichment of noncoding mutations in cistromes as opposed to individual CREs, we reveal their specificity towards master transcription regulators that promote prostate cancer development, a feature shared with inherited risk-variants. Overall, our work provides a blueprint for the functional interpretation of noncoding mutations in genomic tests relying on defining cis-regulatory units according to cistrome-partitioning to identify cancer driver transcription regulators.

  Study EGAS00001003928

• Rapid identification of somatic genome rearrangements as personalized biomarkers for blood-based cancer monitoring

  Increasing evidence shows the value of circulating tumour DNA (ctDNA) to detect cancer and monitor its progression. Somatic genomic structural variations (SVs) are promising personalized biomarkers for sensitive and specific detection of ctDNA in liquid biopsies. However, accurate, affordable, and fast identification of such SV biomarkers is challenging, which hinders routine use in the clinic. Here, we demonstrate a novel approach - termed SHARC - for rapid discovery of somatic SV breakpoints as personalized tumour biomarkers. SHARC combines low-coverage cancer genome sketching by using Oxford Nanopore portable sequencing with a random forest classification and a dedicated filtering pipeline to enrich for somatic SVs. Our method leverages the real-time and long-read capabilities of Nanopore sequencing to identify somatic SV breakpoints at nucleotide resolution from a tumour biopsy within two days. We applied SHARC to tumour samples of high-grade ovarian and prostate cancer and validated on average 10 somatic SVs per sample with the use of PCR mini-amplicons. Finally, we demonstrate that these somatic SV biomarkers can be used to detect tumour presence from liquid biopsies in a quantitative manner and we retrospectively monitored treatment response in patients with prostate cancer, demonstrating its potential benefit for clinical practice.

  Study EGAS00001003963

• SCLC ctDNA sequencing

  In this study we have sequenced the ctDNA of 28 Small Cell Lung Cancer patients in the TP53 gene, each sample has been sequenced twice.

  Study EGAS00001003984

• MutWP5__CRUK_Mutographs_of_Cancer__Lung__PD37920__Targeted_

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs.

  Study EGAS00001003321

• Exploiting evolutionary steering in cancer therapy

  Drug resistance, mediated by intra-tumour heterogeneity and clonal evolution, is arguably the biggest problem in cancer therapy today. However, evolving resistance to one drug may come at the cost of increased sensitivity to another due to so-called evolutionary trade-offs. This weakness can be exploited in the clinic using an approach called ‘evolutionary herding’ that aims at controlling the tumour cell population to delay or prevent resistance. However, model systems able to recapitulate cancer evolution experimentally are lacking and current in vitro techniques based on small populations, re-plating and escalating dose, are unsuitable to develop evolutionary herding strategies. We present a novel methodology for evolutionary herding in vitro and ex vivo using patient-derived organoids. Our approach is based on a combination of single-cell barcoding, very large populations of 108-109 cells grown without re-plating, realistic high drug doses, time-course monitoring of cancer clones, and mathematical modelling of tumour evolutionary dynamics. We demonstrate evolutionary herding in non-small cell lung cancer in vitro and in patient-derived colorectal cancer organoids (PDO). We show that herding causes controlled evolutionary bottlenecks that lead to collateral sensitivity. Through genomic analysis, we were also able to determine the mechanisms that drive such sensitivity. Our approach allows modelling evolutionary trade-offs experimentally to test patient-specific evolutionary herding strategies that can be translated into the clinic to control treatment resistance.

  Study EGAS00001003200

• Rapid response of APC/TP53/KRAS mutated stage IV colorectal cancer under FOLFIRI + Bevacizumab detected by liquid biopsy: a case report

  In our non-interventional liquid biopsy study, a male patient in his fifties diagnosed with stage IV colorectal cancer and polytope liver metastases rapidly progressed after completing chemotherapy and deceased 8 months after diagnosis. Retrospective cell free DNA testing showed that the APC/TP53/KRAS major clone responded quickly after 3 cycles of FOLFIRI + Bevacizumab. Retrospective exome sequencing of pre-chemotherapy and post-chemotherapy tissue samples including metastases confirmed that the APC/TP53/KRAS and other major clonal mutations (GPR50, SLC5A, ZIC3, SF3A1 and others) were present in all samples. After the last chemotherapy cycle,

  Study EGAS00001004088

• The_Little_Princess_Knowledge_Bank_

  We propose to build a genetic knowledge bank of Wilms tumour that integrates clinical outcome data with a genetic, epigenetic, and transcriptomic survey of 1,000 Wilms tumours.

  Study EGAS00001004237