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Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors

The heterogeneity that soft tissue sarcomas (STS) exhibit in their clinical behavior, even within histological subtypes, complicates patient care. Histological appearance is determined by gene expression. Morphologic features are generally good predictors of biologic behavior, however, metastatic pr...

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Autores principales: Skubitz, Keith M, Pambuccian, Stefan, Manivel, J Carlos, Skubitz, Amy PN
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2412854/
https://www.ncbi.nlm.nih.gov/pubmed/18460215
http://dx.doi.org/10.1186/1479-5876-6-23
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author Skubitz, Keith M
Pambuccian, Stefan
Manivel, J Carlos
Skubitz, Amy PN
author_facet Skubitz, Keith M
Pambuccian, Stefan
Manivel, J Carlos
Skubitz, Amy PN
author_sort Skubitz, Keith M
collection PubMed
description The heterogeneity that soft tissue sarcomas (STS) exhibit in their clinical behavior, even within histological subtypes, complicates patient care. Histological appearance is determined by gene expression. Morphologic features are generally good predictors of biologic behavior, however, metastatic propensity, tumor growth, and response to chemotherapy may be determined by gene expression patterns that do not correlate well with morphology. One approach to identify heterogeneity is to search for genetic markers that correlate with differences in tumor behavior. Alternatively, subsets may be identified based on gene expression patterns alone, independent of knowledge of clinical outcome. We have reported gene expression patterns that distinguish two subgroups of clear cell renal carcinoma (ccRCC), and other gene expression patterns that distinguish heterogeneity of serous ovarian carcinoma (OVCA) and aggressive fibromatosis (AF). In this study, gene expression in 53 samples of STS and AF [including 16 malignant fibrous histiocytoma (MFH), 9 leiomyosarcoma, 12 liposarcoma, 4 synovial sarcoma, and 12 samples of AF] was determined at Gene Logic Inc. (Gaithersburg, MD) using Affymetrix GeneChip(® )U_133 arrays containing approximately 40,000 genes/ESTs. Gene expression analysis was performed with the Gene Logic Genesis Enterprise System(® )Software and Expressionist software. Hierarchical clustering of the STS using our three previously reported gene sets, each generated subgroups within the STS that for some subtypes correlated with histology, and also suggested the existence of subsets of MFH. All three gene sets also recognized the same two subsets of the fibromatosis samples that we had found in our earlier study of AF. These results suggest that these subgroups may have biological significance, and that these gene sets may be useful for sub-classification of STS. In addition, several genes that are targets of some anti-tumor drugs were found to be differentially expressed in particular subsets of STS.
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spelling pubmed-24128542008-06-05 Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors Skubitz, Keith M Pambuccian, Stefan Manivel, J Carlos Skubitz, Amy PN J Transl Med Research The heterogeneity that soft tissue sarcomas (STS) exhibit in their clinical behavior, even within histological subtypes, complicates patient care. Histological appearance is determined by gene expression. Morphologic features are generally good predictors of biologic behavior, however, metastatic propensity, tumor growth, and response to chemotherapy may be determined by gene expression patterns that do not correlate well with morphology. One approach to identify heterogeneity is to search for genetic markers that correlate with differences in tumor behavior. Alternatively, subsets may be identified based on gene expression patterns alone, independent of knowledge of clinical outcome. We have reported gene expression patterns that distinguish two subgroups of clear cell renal carcinoma (ccRCC), and other gene expression patterns that distinguish heterogeneity of serous ovarian carcinoma (OVCA) and aggressive fibromatosis (AF). In this study, gene expression in 53 samples of STS and AF [including 16 malignant fibrous histiocytoma (MFH), 9 leiomyosarcoma, 12 liposarcoma, 4 synovial sarcoma, and 12 samples of AF] was determined at Gene Logic Inc. (Gaithersburg, MD) using Affymetrix GeneChip(® )U_133 arrays containing approximately 40,000 genes/ESTs. Gene expression analysis was performed with the Gene Logic Genesis Enterprise System(® )Software and Expressionist software. Hierarchical clustering of the STS using our three previously reported gene sets, each generated subgroups within the STS that for some subtypes correlated with histology, and also suggested the existence of subsets of MFH. All three gene sets also recognized the same two subsets of the fibromatosis samples that we had found in our earlier study of AF. These results suggest that these subgroups may have biological significance, and that these gene sets may be useful for sub-classification of STS. In addition, several genes that are targets of some anti-tumor drugs were found to be differentially expressed in particular subsets of STS. BioMed Central 2008-05-06 /pmc/articles/PMC2412854/ /pubmed/18460215 http://dx.doi.org/10.1186/1479-5876-6-23 Text en Copyright © 2008 Skubitz et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Skubitz, Keith M
Pambuccian, Stefan
Manivel, J Carlos
Skubitz, Amy PN
Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
title Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
title_full Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
title_fullStr Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
title_full_unstemmed Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
title_short Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
title_sort identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2412854/
https://www.ncbi.nlm.nih.gov/pubmed/18460215
http://dx.doi.org/10.1186/1479-5876-6-23
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