Human leiomyosarcoma samples, molecular classification
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE76216 | GEO | 2016/12/31
SECONDARY ACCESSION(S): PRJNA306668
REPOSITORIES: GEO
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2015-05-21 | GSE65362 | GEO
Project description:Ependymal tumors across age groups have been classified solely by histopathology. It is, however, commonly accepted that this classification has limited clinical utility based on its poor reliability. We aimed at establishing a reliable and reproducible molecular classification using DNA methylation fingerprints of the tumors. Studying a cohort of 500 tumors allowed for the delineation of nine robust molecular subgroups, three in each anatomic compartment of the central nervous system (CNS). Two of the supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification by far and thus might serve as a basis for the upcoming update of the WHO classification of CNS tumors. DNA methylation patterns in tumors have been shown to represent a very stable molecular memory of the respective cell of origin throughout the disease course, thus making them particularly suitable for tumor classification purposes. Methylation fingerprinting of a large series of ependymal tumors of all grades revealed a highly reliable way of classifying this clinically extremely heterogeneous group of malignancies. In fact, out of nine highly reproducible molecular subgroups identified in the supratentorial, infratentorial and spinal regions, only two harbor the vast majority of clinical high-risk patients (mostly children) for whom novel therapeutic concepts are desperately needed. Since this analysis can be performed from minute amounts of DNA extracted from archived material, it is ideally suited for routine clinical application. We investigated a set of 562 ependymal tumors using the Illumina 450k methylation array.
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Project description:DNA methylation profiling has emerged as a valuable tool for tumor classification, exemplified by the German Cancer Research Center's creation of online classifiers for CNS tumors and sarcomas. Identification of rare molecular events, such as TRIO::TERT fusion in undifferentiated sarcomas, through DNA methylation profiling and transcriptome analysis aims to define distinct molecular subgroups within sarcomas of uncertain diagnosis, potentially improving classification and treatment strategies.In this study, we present 8 cases of sarcomas characterized by TRIO::TERT fusion, establishing it as a distinct molecular subtype of sarcomas. This fusion represents a consistent molecular feature across all analyzed tumors, suggesting its pivotal role in sarcomatogenesis. Identifying TRIO::TERT transcript sarcoma as a new tumor type may enhance diagnostic strategies for improved patient management.
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Project description:Soft-tissue tumours are derived from mesenchymal cells such as fibroblasts, muscle cells, or adipocytes, but for many such tumours the histogenesis is controversial. We aimed to start molecular characterisation of these rare neoplasms and to do a genome-wide search for new diagnostic markers. We analysed gene-expression patterns of 41 soft-tissue tumours with spotted cDNA microarrays. After removal of errors introduced by use of different microarray batches, the expression patterns of 5520 genes that were well defined were used to separate tumours into discrete groups by hierarchical clustering and singular value decomposition. Synovial sarcomas, gastrointestinal stromal tumours, neural tumours, and a subset of the leiomyosarcomas, showed strikingly distinct gene-expression patterns. Other tumour categories--malignant fibrous histiocytoma, liposarcoma, and the remaining leiomyosarcomas--shared molecular profiles that were not predicted by histological features or immunohistochemistry. Strong expression of known genes, such as KIT in gastrointestinal stromal tumours, was noted within gene sets that distinguished the different sarcomas. However, many uncharacterised genes also contributed to the distinction between tumour types. These results suggest a new method for classification of soft-tissue tumours, which could improve on the method based on histological findings. Large numbers of uncharacterised genes contributed to distinctions between the tumours, and some of these could be useful markers for diagnosis, have prognostic significance, or prove possible targets for treatment. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Computed
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Project description:Transcriptomic profiling Background Cholangiocarcinoma accounts for 5-10% of primary hepatic cancers. The etiology is unclear and patients are often diagnosed without risk factors. Resection is the only curative treatment although patients frequently remain undiagnosed until advanced stage of disease. Methods To construct molecular classification of cholangiocarcinoma, we profiled the transcriptomes of 104 freshly-frozen tumors and 59 matched non-cancerous livers obtained from Australia, Europe and the United States. We also performed mutational analysis of KRAS, EGFR and BRAF, and used laser-capture microdissection to obtain independent gene expression profiles for epithelial and stromal compartments in a subset of tumors. The selected target genes were validated by western blotting and immunohistochemistry. Results Transcriptomic profiling classified cholangiocarcinoma into two distinct subclasses defined by survival (P<0.0007) and early recurrence (P<0.001). Applying leave-one-out cross-validation, we optimized the prognostic classifier to 238 genes which were positively enriched in the epithelial tumor compartment. A deregulated HER2 network was associated with the epithelial compartment which also showed a frequent overexpression of Ki67, EGFR, MET and pRPS6 whereas inflammatory cytokines were enriched in tumor stroma specifically in patients with poor prognosis. KRAS mutations were found in 24.6% of patients with poor disease outcome. Conclusion Our study presents new insights into pathogenesis of cholangiocarcinoma and stratification of the patients according to survival and recurrence. Identification of a subgroup of patients among the poor prognostic cohort characterized by KRAS mutations and oncogenic-addiction may provide a novel therapeutic opportunity for this treatment-refractory malignancy. Profiling of individual cholangiocarcinomas and non-cancerous matched surrounding livers using normal bile ducts as reference
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