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

Overview of attention for article published in Journal of Translational Medicine, May 2008
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Title
Identification of heterogeneity among soft tissue sarcomas by gene expression profiles from different tumors
Published in
Journal of Translational Medicine, May 2008
DOI 10.1186/1479-5876-6-23
Pubmed ID
Authors

Keith M Skubitz, Stefan Pambuccian, J Carlos Manivel, Amy PN Skubitz

Abstract

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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 8 21%
Student > Doctoral Student 3 8%
Student > Bachelor 3 8%
Other 3 8%
Other 6 16%
Unknown 6 16%
Readers by discipline Count As %
Medicine and Dentistry 13 34%
Agricultural and Biological Sciences 7 18%
Biochemistry, Genetics and Molecular Biology 4 11%
Nursing and Health Professions 1 3%
Computer Science 1 3%
Other 3 8%
Unknown 9 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 December 2014.
All research outputs
#18,386,678
of 22,774,233 outputs
Outputs from Journal of Translational Medicine
#2,942
of 3,984 outputs
Outputs of similar age
#72,542
of 78,716 outputs
Outputs of similar age from Journal of Translational Medicine
#8
of 8 outputs
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