Pathway-based analysis of the hidden genetic heterogeneities in cancers.
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 pathway-based approach is promising for unveiling genetic heterogeneities in complex human diseases.
Institute for Medical Systems Biology and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Xiaolei
X
Zhao
Maoming People's Hospital, Maoming 525000, China.
Shouqiang
S
Zhong
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China.
Xiaoyu
X
Zuo
Institute for Medical Systems Biology and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Meihua
M
Lin
Institute for Medical Systems Biology and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Jiheng
J
Qin
Institute for Medical Systems Biology and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China.
Yizhao
Y
Luan
Maoming People's Hospital, Maoming 525000, China.
Naizun
N
Zhang
Maoming People's Hospital, Maoming 525000, China. Electronic address: lye30668@aliyun.com.
Yan
Y
Liang
Institute for Medical Systems Biology and Department of Medical Statistics and Epidemiology, School of Public Health, Guangdong Medical College, Dongguan 523808, China; Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou 510080, China. Electronic address: raoshaoq@gdmc.edu.cn.
Shaoqi
S
Rao
D016000:Cluster Analysis; D020869:Gene Expression Profiling; D018740:Genetic Heterogeneity; D006801:Humans; D016403:Lymphoma, Large B-Cell, Diffuse / Q000235:genetics* / Q000473:pathology; D011379:Prognosis
Cancer; Enrichment analysis; Genetic heterogeneity; Pathway-based approach; Sample partitioning; Survival analysis