RESUMO
PURPOSE: We have previously characterized a tumor stroma expression signature in a subset of breast tumors that correlates with better clinical outcome. The purpose of this study is to determine whether this stromal signature, termed the "DTF fibroblast" (desmoid-type fibromatosis) signature, is specific to breast cancer or is a common stromal response found in different types of cancer. EXPERIMENTAL DESIGNS: The DTF fibroblast signature was applied to gene expression profiles from five ovarian, five lung, two colon, and three prostate cancer expression microarray datasets. In addition, two different tissue microarrays of 204 ovarian tumors and 140 colon tumors were examined for the expression of previously characterized protein markers of DTF fibroblast signature. The DTF fibroblast stromal response was then correlated with clinicopathologic features. RESULTS: The DTF fibroblast signature is robustly present in ovarian, lung, and colon carcinomas. Both expression microarray data and immunohistochemistry show that the subset of ovarian tumors with strong DTF fibroblast signature expression has statistically significant, worse survival outcomes. No reproducible survival differences were found in either the lung or the colon cancers. The prostate cancers failed to show a DTF fibroblast signature. Multivariant analysis showed that DTF fibroblast signature was significantly more prognostic than the proliferation status in ovarian carcinomas. CONCLUSIONS: Our results suggest that the DTF fibroblast signature is a common tumor stroma signature in different types of cancer, including ovarian, lung, and colon carcinomas. Our findings provide further insight into the DTF fibroblast stromal responses across different types of carcinomas and their potential as prognostic and therapeutic targets.
Assuntos
Neoplasias da Mama/patologia , Neoplasias do Colo/patologia , Fibroblastos/patologia , Perfilação da Expressão Gênica , Neoplasias Ovarianas/patologia , Neoplasias da Próstata/patologia , Células Estromais/patologia , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Neoplasias da Mama/genética , Neoplasias da Mama/mortalidade , Proliferação de Células , Estudos de Coortes , Neoplasias do Colo/genética , Neoplasias do Colo/mortalidade , Feminino , Fibroblastos/metabolismo , Seguimentos , Regulação Neoplásica da Expressão Gênica , Humanos , Técnicas Imunoenzimáticas , Masculino , Gradação de Tumores , Estadiamento de Neoplasias , Análise de Sequência com Séries de Oligonucleotídeos , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/mortalidade , Prognóstico , Neoplasias da Próstata/genética , Neoplasias da Próstata/mortalidade , Células Estromais/metabolismo , Taxa de SobrevidaRESUMO
Existing methods to quantify angiogenesis range from image analysis of photographs to fluorescent microscopy. These methods are often time consuming and costly; they also may not detect capillaries if they are indistinct from the background of the image. We have developed a simple method based on the motion of blood to create an image that reveals the entire angiogenic vasculature. Two image analysis software programs were used separately to demonstrate the method. Using either ImageJ or Environment for Visualizing Images, we analyzed a video clip of regenerated tissue from the partially amputated caudal fin of a zebrafish (Danio rerio). The deviations among the frames in the video stack were calculated to reveal pixels where motion has occurred. The resulting image highlighted all vessels through which blood flowed and allowed for automatic quantification of the newly developed vasculature. Using this method, we quantified the angiogenic action of basic fibroblast growth factor and vascular endothelial growth factor, as well as suppression of angiogenesis by an inhibitor. In a preliminary study, we also found that it could be used to trace the developing vasculature in zebrafish embryos. Thus, motion-based angiogenesis analysis may provide an easy and accurate quantification of angiogenesis.