Investigation of Prognostic Markers in Soft tisse Sarcoma by Gene Expression and Tissue Profiling
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE8172 | GEO | 2008/03/31
SECONDARY ACCESSION(S): PRJNA101073
REPOSITORIES: GEO
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Project description:Soft tissue sarcoma diagnostics and prognostics are challenging, particularly in highly malignant and pleomorphic subtypes such as undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS). We applied 32K BAC-arrays and gene expression profiling to 18 extremity soft tissue LMS and 31 extremity soft tissue UPS with the aim to identify molecular subtype signatures and genomic prognostic markers. Both the gains/losses and gene expression signatures revealed striking similarities between UPS and LMS, which were indistinguishable using unsupervised hierarchical cluster analysis and significance analysis for microarrays. Gene expression analysis revealed just 9 genes, among them Tropomyosin beta, that were differentially expressed. Loss of 4q31 (encompassing the SMAD1 locus), loss of 18q22 and tumor necrosis were identified as independent predictors of metastasis in multivariate stepwise Cox regression analysis. Combined analysis applying loss of 4q31 and 18q22 and presence of necrosis improved the area under receiver operating characteristic curve for metastasis prediction from 0.64 to 0.86. The extensive genetic similarities between extremity soft tissue UPS and LMS suggest a shared lineage of these STS subtypes and the new and independent genetic prognosticators identified hold promise for refined prognostic determination in high-grade, genetically complex STS.
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Project description:Soft tissue sarcoma diagnostics and prognostics are challenging, particularly in highly malignant and pleomorphic subtypes such as undifferentiated pleomorphic sarcoma (UPS) and leiomyosarcoma (LMS). We applied 32K BAC-arrays and gene expression profiling to 18 extremity soft tissue LMS and 31 extremity soft tissue UPS with the aim to identify molecular subtype signatures and genomic prognostic markers. Both the gains/losses and gene expression signatures revealed striking similarities between UPS and LMS, which were indistinguishable using unsupervised hierarchical cluster analysis and significance analysis for microarrays. Gene expression analysis revealed just 9 genes, among them Tropomyosin beta, that were differentially expressed. Loss of 4q31 (encompassing the SMAD1 locus), loss of 18q22 and tumor necrosis were identified as independent predictors of metastasis in multivariate stepwise Cox regression analysis. Combined analysis applying loss of 4q31 and 18q22 and presence of necrosis improved the area under receiver operating characteristic curve for metastasis prediction from 0.64 to 0.86. The extensive genetic similarities between extremity soft tissue UPS and LMS suggest a shared lineage of these STS subtypes and the new and independent genetic prognosticators identified hold promise for refined prognostic determination in high-grade, genetically complex STS. Genomic DNA was extracted from a total of 49 samples, 31 Undifferentiated pleomorphic Sarcomas and 18 Leiomyosarcomas. The DNA was labeled using Bioprime array CGH labeling kit (Invitrogen). Promega pooled male DNA was used as reference. Labeled DNA was hybridized onto BAC arrays containing ~32 000 BAC clones printed in singlets. BAC arrays were produced at the SWEGENE DNA Microarray Facility at Lund University.
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