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Analysis of multiple sarcoma expression datasets: implications for classification, oncogenic pathway activation and chemotherapy resistance.
Konstantinopoulos, Panagiotis A; Fountzilas, Elena; Goldsmith, Jeffrey D; Bhasin, Manoj; Pillay, Kamana; Francoeur, Nancy; Libermann, Towia A; Gebhardt, Mark C; Spentzos, Dimitrios.
Afiliação
  • Konstantinopoulos PA; Division of Hematology/Oncology, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
PLoS One ; 5(4): e9747, 2010 Apr 01.
Article em En | MEDLINE | ID: mdl-20368975
ABSTRACT

BACKGROUND:

Diagnosis of soft tissue sarcomas (STS) is challenging. Many remain unclassified (not-otherwise-specified, NOS) or grouped in controversial categories such as malignant fibrous histiocytoma (MFH), with unclear therapeutic value. We analyzed several independent microarray datasets, to identify a predictor, use it to classify unclassifiable sarcomas, and assess oncogenic pathway activation and chemotherapy response. METHODOLOGY/PRINCIPAL

FINDINGS:

We analyzed 5 independent datasets (325 tumor arrays). We developed and validated a predictor, which was used to reclassify MFH and NOS sarcomas. The molecular "match" between MFH and their predicted subtypes was assessed using genome-wide hierarchical clustering and Subclass-Mapping. Findings were validated in 15 paraffin samples profiled on the DASL platform. Bayesian models of oncogenic pathway activation and chemotherapy response were applied to individual STS samples. A 170-gene predictor was developed and independently validated (80-85% accuracy in all datasets). Most MFH and NOS tumors were reclassified as leiomyosarcomas, liposarcomas and fibrosarcomas. "Molecular match" between MFH and their predicted STS subtypes was confirmed both within and across datasets. This classification revealed previously unrecognized tissue differentiation lines (adipocyte, fibroblastic, smooth-muscle) and was reproduced in paraffin specimens. Different sarcoma subtypes demonstrated distinct oncogenic pathway activation patterns, and reclassified MFH tumors shared oncogenic pathway activation patterns with their predicted subtypes. These patterns were associated with predicted resistance to chemotherapeutic agents commonly used in sarcomas. CONCLUSIONS/

SIGNIFICANCE:

STS profiling can aid in diagnosis through a predictor tracking distinct tissue differentiation in unclassified tumors, and in therapeutic management via oncogenic pathway activation and chemotherapy response assessment.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sarcoma / Teorema de Bayes / Redes Neurais de Computação / Análise de Sequência com Séries de Oligonucleotídeos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2010 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sarcoma / Teorema de Bayes / Redes Neurais de Computação / Análise de Sequência com Séries de Oligonucleotídeos Tipo de estudo: Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2010 Tipo de documento: Article