Many cancers apparently showing similar phenotypes are actually distinct at the molecular level,leading to very different responses to the same treatment.It has been recently demonstrated that pathway-based approaches...Many cancers apparently showing similar phenotypes are actually distinct at the molecular level,leading to very different responses to the same treatment.It has been recently demonstrated that pathway-based approaches are robust and reliable for genetic analysis of cancers.Nevertheless,it remains unclear whether such function-based approaches are useful in deciphering molecular heterogeneities in cancers.Therefore,we aimed to test this possibility in the present study.First,we used a NCI60 dataset to validate the ability of pathways to correctly partition samples.Next,we applied the proposed method to identify the hidden subtypes in diffuse large B-cell lymphoma （DLBCL）.Finally,the clinical significance of the identified subtypes was verified using survival analysis.For the NCI60 dataset,we achieved highly accurate partitions that best fit the clinical cancer phenotypes.Subsequently,for a DLBCL dataset,we identified three hidden subtypes that showed very different 10-year overall survival rates （90％,46％ and 20％） and were highly significantly （P =0.008） correlated with the clinical survival rate.This study demonstrated that the pathwaybased approach is promising for unveiling genetic heterogeneities in complex human diseases.展开更多
基金supported in part by the National Natural Science Foundation of China(Grant Nos.31071166 and 81373085)Natural Science Foundation of Guangdong Province,China(Grant No.8251008901000007)+2 种基金Science and Technology Planning Project of Guangdong Province(Grant No.2009A030301004)Science and Technology Project of Dongguan(Grant No.2011108101015)the funds from Guangdong Medical College(Grant Nos.XG1001,JB1214,XZ1105,STIF201122,M2011024 and M2011010)
文摘Many cancers apparently showing similar phenotypes are actually distinct at the molecular level,leading to very different responses to the same treatment.It has been recently demonstrated that pathway-based approaches are robust and reliable for genetic analysis of cancers.Nevertheless,it remains unclear whether such function-based approaches are useful in deciphering molecular heterogeneities in cancers.Therefore,we aimed to test this possibility in the present study.First,we used a NCI60 dataset to validate the ability of pathways to correctly partition samples.Next,we applied the proposed method to identify the hidden subtypes in diffuse large B-cell lymphoma （DLBCL）.Finally,the clinical significance of the identified subtypes was verified using survival analysis.For the NCI60 dataset,we achieved highly accurate partitions that best fit the clinical cancer phenotypes.Subsequently,for a DLBCL dataset,we identified three hidden subtypes that showed very different 10-year overall survival rates （90％,46％ and 20％） and were highly significantly （P =0.008） correlated with the clinical survival rate.This study demonstrated that the pathwaybased approach is promising for unveiling genetic heterogeneities in complex human diseases.
