5731 results for "canc*"

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• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877

• Targeted next-generation sequencing of 13 chordoid gliomas of the third ventricle

  Study EGAS00001002733

• Single-cell multi-omics defines the cell-type-specific impact of splicing aberrations in human hematopoietic clonal outgrowths

  Study EGAS00001007402

• Circulating Tumor DNA Analysis Detects Minimal Residual Disease and Predicts Recurrence in Patients with Stage II Colon Cancer

  Detection of circulating tumor DNA (ctDNA) after resection of stage II colon cancer may identify those at the highest risk of recurrence and help inform adjuvant treatment decisions. We used massively-parallel-sequencing–based assays to evaluate the ability of ctDNA to detect minimal residual disease in 1046 plasma samples from a prospective cohort of 230 patients with resected stage II colon cancer. In patients not treated with adjuvant chemotherapy, ctDNA was detected post-operatively in 14 of 178 (7.9%) patients, 11 (79%) of whom had recurred at a median follow-up of 27 months; recurrence occurred in only 16 (9.8 %) of the 164 patients with negative ctDNA (HR, 18; 95% confidence interval [CI], 7.9 to 36; P<0.001). In patients treated with chemotherapy, the presence of ctDNA following completion of chemotherapy was also associated with an inferior recurrence-free survival (HR, 11; 95% CI, 1.8 to 68; P=0.001). ctDNA detection after stage II colon cancer resection provides direct evidence of residual disease and identifies patients at very high risk of recurrence.

  Study EGAS00001001839

• checup

  Sequencing data from a phase II study of nivolumab and ipilimumab in recurrent or refractory cancer of unknown primary (CheCUP trial)

  Study EGAS00001007403

• Therapeutic Targeting of Ependymoma as Informed by Oncogenic Enhancer Profiling

  Genomic sequencing has driven precision-based oncology therapy; however, genetic drivers remain unknown or non-targetable for many malignancies, demanding alternative approaches to identify therapeutic leads. Ependymomas are chemotherapy-resistant brain tumours, which, despite genomic sequencing, lack effective molecular targets. Here, we mapped active chromatin landscapes in 42 primary ependymomas in two non-overlapping primary ependymoma cohorts. Enhancer regions revealed novel oncogenes, molecular targets, and pathways, which when subjected to small molecule inhibitor or shRNA treatment, increased survival and slowed proliferation in mouse and neurosphere patient-derived models of ependymomas. This study represents one of the largest enhancer mapping study of any cancer type to date, and provides a framework for target and drug discovery for other cancers recalcitrant to therapeutic development because of their lack of known genetic drivers.

  Study EGAS00001002696

• Genomic evolution and transcriptional changes in the evolution of prostate cancer into neuroendocrine and ductal carcinoma types

  Prostate cancer is typically of acinar adenocarcinoma type but can occasionally present as neuro-endocrine and/or ductal type carcinoma. These are associated with clinically aggressive disease and the former often arises on a background of androgen deprivation therapy, although it can al-so arise de novo. Two prostate cancer cases were sequenced by exome capture from archival tis-sue. Case 1 was de novo small cell neuroendocrine carcinoma and ductal adenocarcinoma with 3 longitudinal samples over 5 years. Case 2 was a single time point after development of treatment related neuroendocrine prostate carcinoma. Case 1 showed whole genome doubling in all sam-ples and focal amplification of AR in all samples except the first time point. Phylogenetic analysis revealed a common ancestry for the ductal and small cell carcinoma. Case 2 showed 13q loss (involving RB1) in both adenocarcinoma and small cell carcinoma regions, and 3p gain, 4p loss, 17p loss (involving TP53) in the latter. By using highly curated samples, we demonstrate for the first time that small cell neuroendocrine and ductal prostatic carcinoma can have a common an-cestry and the process of evolution over time. We highlight whole genome doubling in a patient with prostate cancer relapse, reinforcing its poor prognostic nature.

  Study EGAS00001007412

• Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

  Study EGAS00001004975

• Clinical outcomes in ctDNA-positive urothelial carcinoma patients treated with adjuvant immunotherapy

  Minimally invasive approaches to detect residual disease after surgery are urgently needed to select patients at highest risk for metastatic relapse for additional therapies. Circulating tumour DNA (ctDNA) holds promise as a biomarker for molecular residual disease (MRD) and relapse,1-3 but its clinical value has yet to be demonstrated in a randomised clinical trial. We evaluated outcomes in post-surgical ctDNA-positive (+) patients in a randomised phase III trial of adjuvant atezolizumab versus observation. IMvigor010 enrolled 809 patients with muscle-invasive urothelial carcinoma and did not meet its primary endpoint of disease-free survival (DFS) in the intent-to-treat population. Within the study, an exploratory planned analysis of prospectively collected plasma was performed, which tested the utility of ctDNA to identify patients who may benefit from adjuvant atezolizumab treatment. ctDNA was measured at the start of therapy (cycle 1 day 1; C1D1) and at week 6 (cycle 3 day 1; C3D1), and 581 patients were evaluable for ctDNA. The prevalence of ctDNA positivity at C1D1 was 37% (n=214), and ctDNA positivity identified patients with poor prognosis (observation arm DFS HR= 6.19 (4.29, 8.91), p<0.0001). Here we show that ctDNA(+) patients had improved DFS and overall survival (OS) with atezolizumab versus observation (DFS HR= 0.56 (0.41-0.77); p=0.0003 and OS HR= 0.58 (0.4-0.86); p=0.0063). No difference in DFS or OS between arms was noted for ctDNA-negative patients. The rate of ctDNA clearance was higher with atezolizumab (18%) versus observation (4%) (p=0.0041). Transcriptomic analysis revealed that tumours from ctDNA(+) patients had higher expression of cell cycle and keratin genes. Within the ctDNA(+) patient population in the atezolizumab arm, non-relapsing patients were further enriched in prominent immune response signatures including PD-L1, IFNG, CXCL9, and high tumour mutational burden, whereas relapse was associated with angiogenesis and fibroblast-transforming growth factor-beta signatures (F-TBRS). TCGA molecular subset analysis revealed increased efficacy of atezolizumab in patients with basal-squamous tumours, consistent with underlying tumour-immune contexture. Together these findings suggest that adjuvant atezolizumab may be associated with improved outcomes compared with observation in this high-risk ctDNA(+) population. These findings, if validated in other settings, would shift approaches to post-operative cancer care.

  Study EGAS00001004997

• Genome-wide cell-free DNA biological patterns in patients with cancer

  The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

  Study EGAS00001007400

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005006

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005010

• CancerDetector: Ultrasensitive and Non-Invasive Cancer Detection at the Resolution of Individual Reads using Cell-free DNA Methylation Sequencing Data

  The detection of tumor-derived cell-free DNA in plasma is one of the most promising directions in cancer diagnosis. The major challenge in such approach is how to identify the tiny amount of tumor DNAs out of total cell-free DNAs in blood. Here we propose an ultrasensitive cancer detection method, termed “CancerDetector”, using the DNA methylation profiles of cell-free DNAs. The key of our method is to probabilistically model the joint methylation patterns of multiple adjacent CpG sites on an individual sequencing read, in order to exploit the pervasive nature of DNA methylation for signal amplification. Therefore, CancerDetector can sensitively identify a trace amount of tumor cfDNAs in plasma, at the level of individual reads. We evaluated CancerDetector on the simulated data, and showed a high concordance of the predicted and true tumor burden. Testing CancerDetector on real plasma data demonstrated its high sensitivity and specificity in detecting tumor DNAs. In addition, the predicted tumor burden showed great consistency with tumor size and survival outcome. Note that all of those testing were performed on sequencing data at low to medium coverage (1X to 10X). Therefore, CancerDetector holds the great potential to detect cancer early and cost-effectively.

  Study EGAS00001002728

• Single-cell roadmap of immune cell responses in chronic myeloid leukemia

  To study the innate and adaptive immune responses in CML, we profiled 25 samples from CML patients including samples at diagnosis (n = 7, N = 9, where n is the number of subjects and N the number of samples if different from n) and before and after TKI-cessation with imatinib (n = 6, N = 15) with paired single-cell RNA and T cell receptor (TCR) αβ chain sequencing (scRNA+TCRαβ-seq) and compared our data to different cancers (n = 29) and healthy donors (n = 7). This dataset contains the samples from before and after TKI-cessation, please see the manuscript for info related to the other datasets.

  Study EGAS00001005044

• Stromal cell diversity associated with immune evasion in human triple‐negative breast cancer

  Study EGAS00001005061

• Subtype specific progression from DCIS to invasive breast cancer

  Breast cancer consists of at least five main molecular “intrinsic” subtypes, which are reflected in both pre-invasive and invasive disease. Although previous studies have suggested that many of the molecular features of invasive breast cancer are established early, it is unclear what mechanisms drive progression, and whether the mechanisms of progression are dependent or independent of subtype. We have generated mRNA, miRNA and DNA copy number profiles from a total of 59 in situ lesions and 85 invasive tumors, in order to comprehensively identify those genes, signaling pathways, processes, and cell types that are involved in breast cancer progression. Our work provides evidence that there are molecular features associated with disease progression that are unique to the intrinsic subtypes. We additionally establish subtype-specific signatures that are able to identify a small proportion of pre-invasive tumors with expression profiles that resemble invasive carcinoma, indicating a higher likelihood of future disease progression.

  Study EGAS00001001866

• Finding structural variation and functional consequences from primary acute myeloid leukemia cells with complex karyotype (CK-AML) at the single-cell level

  Study EGAS00001007436

• CRISPR transduction of iPS cells

  Genome engineering using CRISPR/Cas9 technology enables simple, efficient and precise genomic modifications in human cells. Conventional immortalized cell lines can be easily edited or screened using genome-wide libraries with lentiviral transduction. However, cell types derived from the differentiation of induced Pluripotent Stem Cells (iPSC), which often represent more relevant, patient-derived models for human pathology, are much more difficult to engineer as CRISPR/Cas9 delivery to these differentiated cells can be inefficient and toxic. Here, we present an efficient, lentiviral transduction protocol for delivery of CRISPR/Cas9 to macrophages derived from human iPSC with efficiencies close to 100%. We demonstrate CRISPR/Cas9 knockouts for three non-essential proof-of-concept genes - HPRT1, PPIB and CDK4. We then scale the protocol and validate for a genome-wide pooled CRISPR/Cas9 loss-of-function screen. This methodology enables, for the first time, systematic exploration of macrophage involvement in immune responses, chronic inflammation, neurodegenerative diseases and cancer progression, using efficient genome editing techniques.

  Study EGAS00001005102

• CUPiD, a cfDNA methylation-based tissue-of-origin classifier for Cancers of Unknown Primary

  Study EGAS00001007445

• Chemotherapy accelerates genomic aging of normal blood in children treated for cancer

  Whole genome sequencing (WGS) data obtained from clonally expanded hematopoietic stem and progenitor cells (HSPCs) from pediatric cancer patients before and after therapy exposure. In addition, WGS data of cord-blood derived HSPCs clones exposed to various chemotherapeutics and radiation was obtained.

  Study EGAS00001005141

• Multi-omics analysis of primary glioblastoma cell-lines shows recapitulation of pivotal molecular features of parental tumors

  Glioblastoma (GBM) is the deadliest primary brain cancer in adults. Emerging innovative therapies hold promise for personalized cancer treatment. Improving therapeutic options depends on research relying on relevant preclinical models. In this line we have established in the setting of the GlioTeX project (GBM and experimental therapeutics), a GBM-patient derived cell line library (GBM-PDCL). Multi-OMIC approach was used to determine the molecular landscape of PDCL and the extent to which they represent GBM tumors.

  Study EGAS00001001871

• The Genetic Landscape of Ocular Adnexa MALT Lymphoma Reveals Frequent Aberrations in NFAT and MEF2B Signaling Pathways

  A comprehensive constellation of somatic non-silent mutations and copy number (CN) variations in ocular adnexa marginal zone lymphoma (OAMZL) is unknown. By utilizing whole-exome sequencing in 69 tumors we define the genetic landscape of OAMZL. Mutations and CN changes in CABIN1 (30%), RHOA (26%), TBL1XR1 (22%), and CREBBP (17%) and inactivation of TNFAIP3 (26%) were among the most common aberrations. Candidate cancer driver genes cluster in the B-cell receptor (BCR), NFkB, NOTCH and NFAT signaling pathways. One of the most commonly altered genes is CABIN1, a calcineurin inhibitor acting as a negative regulator of the NFAT and MEF2B transcriptional activity. CABIN1 deletions enhance BCR-stimulated NFAT and MEF2B transcriptional activity, while CABIN1 mutations enhance only MEF2B transcriptional activity by impairing binding of mSin3a to CABIN1. Our data provide an unbiased identification of genetically altered genes that may play a role in the molecular pathogenesis of OAMZL and serve as therapeutic targets.

  Study EGAS00001006631

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  Papillary thyroid carcinoma (PTC) is the most common malignancy amongst adolescent and young adult women. Clinical and genomic features of PTC in children differ from those in adults. Historically, a substantial proportion (~50%) of pediatric PTC (PPTC) lack any of the common driver mutations typical of adult PTC. Thus, molecular diagnostics developed for adults may not be valid in children. We applied novel bioinformatic pipelines to RNASeq analysis of pediatric thyroid tumors to identify known and novel fusion oncogenes as drivers of tumorigenesis and to define gene expression patterns among tumors. Analysis of 38 samples resulted in identification of 16 previously reported oncogenic fusions and three novel candidate fusions. In conducting these analyses, we reduced the proportion of cancers with unknown drivers from approximately 50% to 6%. Gene expression analysis identified three distinct categories of tumors. These studies represent the first unbiased genomic approach to childhood PTC. Novel bioinformatic pipeline. GEC Identified 3 distinct classes. DICER1, PTEN segregated with benign tumors. >90% of PPTC carry identifiable ongognic driver variants, however, the landscape differs from that in adults and existing tools for tumor genotyping in adults may not be applicable to pediatric tumors. BACKGROUND: Papillary thyroid carcinoma demonstrates clinically distinct behaviour in pediatric patients when compared to adults, with increased regional and distal metastases, more frequent recurrence, yet overall highly favourable prognosis. Recent tumor genotyping has demonstrated that in pediatric tumors, ***-*** do not carry the most common genomic variants found in adult PTC, leaving a substantial proportion of driver-unknown or “dark matter” tumors. METHODS: We established a cohort of 52 pediatric PTC and performed quantitative-PCR genotyping followed in a subset by whole exome and whole transcriptome (RNASeq) sequencing using a novel, robust bioinformatic pipeline to identify oncogenic fusion transcripts. Gene expression analysis was used to derive distinct clusters. RESULTS: In 52 pediatric PTC, genotyping identified BRAFV600E(21%), NRASQ61R(2%), RET/PTC1 (21%), RET/PTC3 (17%) or PAX8-PPAR in 33 (63%) of tumors. Among the remaining 19 tumors, oncogenic variants were identified in /19 (%). The variants included SNVs in DICER1, ETV6-NTRK3, PTEN and 9 additional oncogenic fusions including two previously-undescribed fusion transcripts, *** and ***. CONCLUSIONS: The genomic landscape of PTC differs between children and adults. In children, there is a substantial fraction of tumors that are unexplained by variants typical of adult PTC. This discrepancy is explained largely by uncommon oncogenic fusions which can be identified by whole-transcriptome analysis.

  Study EGAS00001005182

• WES of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007301

• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  A growing number of druggable targets and national initiatives for precision oncology necessitate broader genomic profiling for many cancer patients. Whole exome sequencing (WES) offers unbiased analysis of the entire coding sequence, segmentation-based detection of copy number alterations (CNAs), and accurate determination of complex biomarkers including tumor mutational burden (TMB), homologous recombination repair deficiency (HRD), and microsatellite instability (MSI). To assess the inter-institution variability of clinical WES, we performed a comparative pilot study between German Centers of Personalized Medicine (ZPMs) from five participating institutions. Tumor and matched normal DNA from 30 patients were analyzed using custom sequencing protocols and bioinformatic pipelines. Calling of somatic variants was highly concordant with a sensitivity between 91-95% and a positive predictive value (PPV) of 82-95% compared with a three-institution consensus and full agreement for 16 of 17 druggable targets. Deviations were observed for cases with low VAF or coverage, differing annotations, and different filter protocols. CNAs showed overall agreement in 76% for the genomic sequence with high wet-lab variability. Complex biomarkers correlated strongly between institutions (HRD: 0.79-1, TMB: 0.97-0.99) and all institutions agreed on microsatellite instability. This study will contribute to the development of quality control frameworks for comprehensive genomic profiling and sheds light onto parameters that require stringent standardization.

  Study EGAS00001007363