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Molecular subtypes identified by gene expression profiling in early stage endometrioid endometrial adenocarcinoma 被引量:4

Molecular subtypes identified by gene expression profiling in early stage endometrioid endometrial adenocarcinoma
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摘要 Background Early stage (FIGO stage Ⅰ-Ⅱ) endometrioid endometrial adenocarcinoma (EEA) is very common in clinical practice.However,patients with the early stage EEA show various clinical behaviors due to biological heterogeneity.Hence,we aimed to discover distinct classes of tumors based on gene expression profiling,and analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters.Methods Hierarchical clustering was performed for class discovery in 28 eady stage EEA samples using a special cDNA microarray chip containing 492 genes designed for endometrial cancer.Correlations between clinicopathologic parameters and our classification were analyzed.And the significance analysis of microarrays (SAM) array was used to identify the signature genes according to the tumor grade and myometrial invasion.Results Three tumor subtypes (subtypes Ⅰ,Ⅱ and Ⅲ) were identified by hierarchical clustering,each subtype had different clinicopathological factors,such as tumor grade,myometrial invasion status,and FIGO stage.Moreover,SAM analysis showed 34 up-regulated genes in high grade tumors,and 38 up-regulated genes and 1 down-regulated in deep myometrial invasive tumors.The overlap genes between these two high-risk factors were markedly up-regulated in subtype Ⅰ,but down-regulated in subtype Ⅲ.Conclusion We have identified novel molecular subtypes in early stage EEA.Differential gene signatures characterize each tumor subtype,which could be used for recognizing the tumor risk and providing a basis for further treatment stratification. Background Early stage (FIGO stage Ⅰ-Ⅱ) endometrioid endometrial adenocarcinoma (EEA) is very common in clinical practice.However,patients with the early stage EEA show various clinical behaviors due to biological heterogeneity.Hence,we aimed to discover distinct classes of tumors based on gene expression profiling,and analyze whether the molecular classification correlated with the histopathological stages or other clinical parameters.Methods Hierarchical clustering was performed for class discovery in 28 eady stage EEA samples using a special cDNA microarray chip containing 492 genes designed for endometrial cancer.Correlations between clinicopathologic parameters and our classification were analyzed.And the significance analysis of microarrays (SAM) array was used to identify the signature genes according to the tumor grade and myometrial invasion.Results Three tumor subtypes (subtypes Ⅰ,Ⅱ and Ⅲ) were identified by hierarchical clustering,each subtype had different clinicopathological factors,such as tumor grade,myometrial invasion status,and FIGO stage.Moreover,SAM analysis showed 34 up-regulated genes in high grade tumors,and 38 up-regulated genes and 1 down-regulated in deep myometrial invasive tumors.The overlap genes between these two high-risk factors were markedly up-regulated in subtype Ⅰ,but down-regulated in subtype Ⅲ.Conclusion We have identified novel molecular subtypes in early stage EEA.Differential gene signatures characterize each tumor subtype,which could be used for recognizing the tumor risk and providing a basis for further treatment stratification.
出处 《Chinese Medical Journal》 SCIE CAS CSCD 2013年第19期3680-3684,共5页 中华医学杂志(英文版)
关键词 endometrioid adenocarcinoma molecular classification gene expression profiling risk factor endometrioid adenocarcinoma molecular classification gene expression profiling risk factor
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  • 1Plataniotis G, Castiglione M. Endometrial cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow- up. Ann Oncol 2010; 21 Suppl 5: v41-v45.
  • 2Kitchener HC, Trimble EL. Endometrial cancer state of the science meeting. Int J Gynecol Cancer 2009; 19: 134-140.
  • 3Creasman W. Revised FIGO staging for carcinoma of the endometrium. Int J Gynaecol Obstet 2009; 105: 109.
  • 4Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast turnouts. Nature 2000; 406: 747-752.
  • 5Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 1999; 286: 531-537.
  • 6Yao Y, Chen Y, Wang Y, Li X, Wang J, Shen D, et al. Molecular classification of human endometrial cancer based on gene expression profiles from specialized microarrays. Int J Gynaecol Obstet 2010; 110: 125-129.
  • 7Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, et al. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res 2002; 30: e15.
  • 8Zaino RJ. FIGO staging of endometrial adenocarcinoma: a critical review and proposal. Int J Gynecol Patho12009; 28: 1-9.
  • 9Eisen MB, Spellman PT, Brown PO, Botstein D. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 1998; 95: 14863-14868.
  • 10Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 2001; 98: 10869-10874.

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