Ontology highlight
ABSTRACT:
PROVIDER: PRJNA594320 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Intratumor mutational heterogeneity has been documented in primary non-small cell lung cancer. Here, we elucidate mechanisms of tumor evolution and heterogeneity in metastatic thoracic tumors (lung adenocarcinoma and thymic carcinoma) using whole-exome and transcriptome sequencing, SNP array for copy number alterations (CNA) and mass spectrometry-based quantitative proteomics of metastases obtained by rapid autopsy. APOBEC-mutagenesis, promoted by increased expression of APOBEC3 region transcripts and associated with a high-risk germline APOBEC3 variant, strongly correlated with mutational tumor heterogeneity. TP53 mutation status was associated with APOBEC hypermutator status. Interferon pathways were enriched in tumors with high APOBEC mutagenesis and IFN- induced expression of APOBEC3B in lung adenocarcinoma cells in culture suggesting a role for the immune microenvironment in the generation of mutational heterogeneity. CNA occurring late in tumor evolution correlated with downstream transcriptomic and proteomic heterogeneity, although global proteomic heterogeneity was significantly greater than transcriptomic and CNA heterogeneity. These results illustrate key mechanisms underlying multi-dimensional heterogeneity in metastatic thoracic tumors.
2019-05-07 | PXD012845 | Pride
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:High-grade gliomas are aggressive primary brain cancers with poor response to standard regimens, driven by immense heterogeneity. In isocitrate dehydrogenase (IDH) wild-type high-grade glioma (glioblastoma, GBM), increased intra-tumoral heterogeneity is associated with more aggressive disease. Recently, spatial technologies have emerged to dissect this complex heterogeneity within the tumor ecosystem by preserving cellular organization in situ. Here, we construct a high- resolution molecular landscape of GBM and IDH-mutant high-grade glioma patient samples to investigate the cellular subtypes and spatial communities that compose high-grade glioma using digital spatial profiling and spatial molecular imaging. This uncovered striking diversity of the tumor and immune microenvironment, that is embodied by the heterogeneity of the inferred copy- number alterations in the tumor. Reconstructing the tumor architecture revealed brain-intrinsic niches, composed of tumor cells reflecting brain cell types and microglia; and brain-extrinsic niches, populated by mesenchymal tumor cells and monocytes. We further reveal that cellular communication in these niches is underpinned by specific ligand-receptor pairs. This primary study reveals high levels of intra-tumoral heterogeneity in high-grade gliomas, associated with a diverse immune landscape within spatially localized regions.
2023-12-13 | GSE232469 | GEO
Project description:EMT process resulted into tumor heterogeneity in lung adenocarcinoma.
2023-06-30 | GSE235782 | GEO
Project description:Genetic Analysis to interrogate tumor heterogeneity in lung adenocarcinoma
| PRJNA326708 | ENA
Project description:Genetic Analysis to interrogate tumor heterogeneity in lung adenocarcinoma
| PRJNA326709 | ENA
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:Glioblastoma (GBM), the most common malignant tumor originating in the brain remains incurable with few treatment advances despite decades of investigation. Treatment failure is often attributed to intratumoral heterogeneity, which fosters tumor evolution and selection of resistant clones. However, intratumoral heterogeneity and tumor evolution remain poorly understood in GBM as studies are typically based on single tissue biopsies and lack spatial context. Here, we have utilized pre-operative MRI scans and intra-operative 3-D surgical neuronavigation for 10 primary IDH-WT GBM patients to acquire 103 tissue samples that represent maximal tumor diversity and are mapped by 3-D spatial coordinates. We combine insights from deconvolution of GBM transcriptomes and chromatin landscapes with single-cell analysis to assess intratumoral heterogeneity of each program at the cellular level and to distinguish neuronal, glial, and immune programs aberrantly active in tumor cells from their counterparts in normal cells. Collectively, these data provide unprecedented insight into GBM intratumoral heterogeneity and evolution from single-cell to whole-tumor 3D spatial resolution, redefining current understanding and providing a rich resource of targets for therapeutic investigation.
2024-01-18 | GSE226726 | GEO
Project description:Intra-tumor heterogeneity (ITH) has been studied at the morphologic, genomic, and transcriptomic level, but not proteomic level. Recent advances in mass spectrometric (MS) proteome quantification techniques, exemplified by SWATH-MS, a massively parallel targeting method, now also support precise quantitative proteomic comparisons across multiple samples, thus identifying molecular and implied functional differences. Here we used SWATH-MS to analyze the proteome profiles of a set of fresh-frozen prostate tissue samples derived from radical prostatectomy specimens. A high confidence set of 1,906 proteins were consistently quantified across 60 biopsy-level tissue samples from three prostatectomy patients, each consisting of 1.0 mm punch biopsies from histologically malignant (acinar and ductal adenocarcinoma) and matching benign prostatic hyperplasia tissues. The quantitative protein profiles allowed independent quantification of the degree of intra-tumor heterogeneity for each protein in benign and malignant tissues. We found that while majority of the proteins showed comparably low intra-tumor variability, 122 proteins were highly variable in malignant and/or matching benign tissues. We observed that proteins that varied between patients or tissue types also tended to be highly variable within prostate tissues, suggesting that these variability patterns will be a critical selection criterion in future protein biomarker studies. The data also permitted investigation of the heterogeneity of multiple biochemical pathways. The high variability of several of the pathways, including Glypican-1 network, alpha-linolenic acid metabolism and celecoxib pathway, explained contradictory results regarding them in the literature. In conclusion, we demonstrated a methodology for investigating proteomic intra-tumor heterogeneity from biopsy-level tissue samples, and quantified the degree of intra-tumor heterogeneity of 1,906 proteins in prostate tumors. The method and data presented here have advanced our understanding of tumor biology and offered critical insights for future biomarker development.
2018-08-13 | PXD003497 | Pride
Project description:Understanding cellular processes underlying early lung adenocarcinoma (LUAD) development is needed to devise intervention strategies. Here, we performed single-cell RNA sequencing (scRNA-seq) of mouse lungs from Gprc5a-/- mice during lung tumor development. We coupled scRNA-seq analysis with spatial transcriptomics of tumor-bearing lungs.
2024-02-16 | GSE222901 | GEO