Ontology highlight
ABSTRACT:
PROVIDER: PRJEB10956 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Intra-tumor Genetic Heterogeneity in Rectal Canger
| PRJNA296805 | ENA
Project description:Colorectal cancer arises in part from the cumulative effects of multiple gene lesions. Recent studies in selected cancer types have revealed significant intra-tumor genetic heterogeneity and highlighted its potential role in disease progression and resistance to therapy. We hypothesized the existence of significant intra-tumor genetic heterogeneity in rectal cancers involving variations in localized somatic mutations and copy number abnormalities. Two or three spatially disparate areas from each of six rectal tumors were dissected and subjected to next-generation whole exome DNA sequencing, Oncoscan SNP arrays, and targeted confirmatory sequencing and analysis. The resulting data were integrated to define subclones using SciClone. Mutant-allele tumor heterogeneity (MATH) scores, mutant allele frequency correlation, and mutation percent concordance were calculated, and Copy number analysis including measurement of correlation between samples was performed.
2015-09-24 | GSE73365 | GEO
Project description:Unique sub-clones within rectal tumors may harbor mutations which contribute to inter-patient variation in response to neoadjuvant chemoradiotherapy (nCRT). Analysis of the influence of nCRT on the extent and nature of intra-tumoral genetic heterogeneity in rectal cancer may provide insights into mechanisms of resistance. Ten locally advanced rectal cancer patients underwent pre-treatment biopsies. At the time of surgery, tissue from the treated tumor was obtained and analyzed. Pre- and post-treatment specimens were subjected to whole exome and confirmatory deep sequencing for somatic mutations. Copy number variation was assessed using OncoScan SNP arrays. In total, data from 32 pre/post-treatment samples are provided. The provided data include the pre/post tumor samples and the Affymetrix OncoScan SNP arrays.
2019-09-05 | GSE136872 | GEO
Project description:Colorectal cancer arises in part from the cumulative effects of multiple gene lesions. Recent studies in selected cancer types have revealed significant intra-tumor genetic heterogeneity and highlighted its potential role in disease progression and resistance to therapy. We hypothesized the existence of significant intra-tumor genetic heterogeneity in rectal cancers involving variations in localized somatic mutations and copy number abnormalities. Two or three spatially disparate areas from each of six rectal tumors were dissected and subjected to next-generation whole exome DNA sequencing, Oncoscan SNP arrays, and targeted confirmatory sequencing and analysis. The resulting data were integrated to define subclones using SciClone. Mutant-allele tumor heterogeneity (MATH) scores, mutant allele frequency correlation, and mutation percent concordance were calculated, and Copy number analysis including measurement of correlation between samples was performed. Affymetrix OncoScan V3 arrays were run on all tumor samples. The OncoScan array platform consists of a set of 217k probes designed specifically for profiling tumors. The overall resolution of the assay for detecting copy number change generates data at 50-100kb resolution across a set of 891 cancer genes, and 300-400kb across the rest of the genome. Raw array florescence intensity data generated on the Affymetrix scanners in the form of CEL files were loaded into the OncoScan Console software v.1.1.0 (Affymetrix, Santa Clara, California). Quality control statistics as well as integrated OSCHP files were generated by OncoScan Console. The standard Affymetrix reference control file for OncoScan data was used for processing the arrays.
2015-09-24 | E-GEOD-73365 | biostudies-arrayexpress
Project description:Almost half of all patients diagnosed with colorectal cancer develop liver metastases. The potential role of intra-individual metastatic heterogeneity remains poorly characterized. By high-resolution DNA copy number analyses and a novel approach based on pair-wise genetic distance, we examined the genetic heterogeneity among multiple liver metastatic deposits obtained from 45 patients subject to curative liver resection. We found large variation in intra-individual metastatic heterogeneity. A high level of heterogeneity was associated with poor patient survival. Patients with metachronous metastases who received chemotherapy had significantly more heterogeneity than chemonaïve patients.
2016-07-11 | GSE63490 | GEO
Project description:Here we characterize an association between disease progression and DNA methylation in Diffuse Large B cell Lymphoma (DLBCL). By profiling genome-wide DNA methylation at single base-pair resolution in thirteen DLBCL diagnosis-relapse sample pairs, we show DLBCL patients exhibit heterogeneous evolution of tumor methylomes during relapse. We identify differentially methylated regulatory elements and determine a relapse–associated methylation signature converging on key pathways such as transforming growth factor beta (TGF-beta) receptor activity. We also observe decreased intra-tumor methylation heterogeneity from diagnosis to relapsed tumor samples. Relapse-free patients display lower intra-tumor methylation heterogeneity at diagnosis compared to relapsed patients in an independent validation cohort. Furthermore, intra-tumor methylation heterogeneity is predictive of time to relapse. Therefore, we propose that epigenomic heterogeneity may support or drive the relapse phenotype and can be used to predict DLBCL relapse. Using ERRBS, we profiled genome-wide DNA methylation patterns of non-relapse DLBCL tumor samples at diagnosis, relaspe DLBCL patient samples at diagnosis and relaspe.
2015-04-14 | E-GEOD-66329 | biostudies-arrayexpress
Project description:The inter-patient variability of tumor proteomes has been investigated on a large scale but many tumors display also intra-tumoral heterogeneity (ITH) regarding morphological and genetic features. To what extent the local proteome of tumors intrinsically differs remains largely unknown. Here, we used hepatocellular carcinoma (HCC) as a model system, to quantify both inter- and intra-tumor heterogeneity across human patient specimens with spatial resolution. We first defined proteomic features that robustly distinguish neoplastic from the directly adjacent non-neoplastic tissue by integrating proteomic data from human patient samples and genetically defined mouse models with available gene expression data. We then demonstrated the existence of intra-tumoral variations in protein abundance that re-occur across different patient samples, and affect clinically relevant proteins, even in the absence of obvious morphological differences or genetic alterations. Our work demonstrates the suitability and the benefits of using mass spectrometry based proteomics to analyze diagnostic tumor specimens with spatial resolution
2018-01-24 | PXD007052 | Pride
Project description:Intra-tumor genetic heterogeneity in breast cancers with heterogeneous HER2 gene amplification
| PRJNA281183 | ENA
Project description:Many current cellular models aimed to elucidate cancer biology do not recapitulate pathobiology including tumor heterogeneity, an inherent feature of cancer that underlies treatment resistance. Here we introduce a new cancer modeling paradigm using genetically engineered human pluripotent stem cells (hiPSCs) that capture authentic cancer pathobiology. Orthotopic engraftment of the neural progenitor cells derived from hiPSCs introduced with tumor-associated genetic driver mutations revealed by The Cancer Genome Atlas project for glioblastoma (GBM) results in formation of brain tumors. As observed in GBM patient samples, these models harbor inter-tumor heterogeneity resembling different GBM molecular subtypes, and intra-tumor heterogeneity. Further, re-engraftment of these tumor cells generate tumors with features characteristic of patient samples and present mutation-dependent patterns of tumor evolution. Thus, these cancer avatar models provide a platform for a comprehensive longitudinal assessment of human tumor development as governed by molecular subtype mutations.
2019-12-10 | GSE133509 | GEO
Project description:Many current cellular models aimed to elucidate cancer biology do not recapitulate pathobiology including tumor heterogeneity, an inherent feature of cancer that underlies treatment resistance. Here we introduce a new cancer modeling paradigm using genetically engineered human pluripotent stem cells (hiPSCs) that capture authentic cancer pathobiology. Orthotopic engraftment of the neural progenitor cells derived from hiPSCs introduced with tumor-associated genetic driver mutations revealed by The Cancer Genome Atlas project for glioblastoma (GBM) results in formation of brain tumors. As observed in GBM patient samples, these models harbor inter-tumor heterogeneity resembling different GBM molecular subtypes, and intra-tumor heterogeneity. Further, re-engraftment of these tumor cells generate tumors with features characteristic of patient samples and present mutation-dependent patterns of tumor evolution. Thus, these cancer avatar models provide a platform for a comprehensive longitudinal assessment of human tumor development as governed by molecular subtype mutations.
2019-12-10 | GSE133479 | GEO