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Shared prognostic markers in undifferentiated pleomorphic sarcoma and leiomyosarcoma of the extremities

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE13775 | GEO | 2009/03/24

SECONDARY ACCESSION(S): PRJNA110785

REPOSITORIES: GEO

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Shared prognostic markers in undifferentiated pleomorphic sarcoma and leiomyosarcoma of the extremities

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.

2010-10-08 | E-GEOD-13775 | biostudies-arrayexpress

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Project description:Background: Undifferentiated pleomorphic sarcoma (UPS), used to be called malignant fibrous histiocytoma (MFH), is a malignant soft tissue tumor of uncertain origin, and is characterized by morphology. UPS often share similar morphological characters with other sarcomas, especially Leiomyosarcoma. Leiomyosarcoma (LMS) is another malignant soft tissue sarcoma with complex genomic abnormalities, origin from smooth muscle. As a result, development of gene signature and/or biomarkers distinguishing UPS and LMS will definitely help the pathologist to precisely diagnose those patients. However, in the past, UPS was reported to be indistinguishable with LMS by genomic profiles. Methods and Results: In this study, 3’ end RNA Sequencing (3SEQ) was used to expression profile 6 UPS and 99 LMS cases. Overall, UPS was undistinguished with LMS by 3SEQ data, however, when we stratified LMS into three subtypes, UPS was shown to share similar expression pattern with Subtype II LMS, but had distinct molecular expression patterns with Subtype I and Subtype III LMS. Additional Immunohistochemistry staining by using LMS Subtype I and Subtype II markers validated that UPSs were positive for Subtype II marker ARL4C, but negative for Subtype I marker LMOD1. Furthermore, CD4 was shown to be significantly more highly expressed in UPS than LMS in both mRNA and protein levels. Conclusion: This study first reported that UPS shared similar gene expression pattern with subtype II LMS and UPS recapitulated the expression profiles of subtype II LMS. In this study, 3’ end RNA Sequencing (3SEQ) was used to expression profile 6 UPS and 99 LMS cases. In order to explore the molecular differences between UPS and LMS, We analyzed the expression data by SAMseq to identify the genes which were significantly differently expressed between UPS and LMS, between UPS and each LMS subtype.

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