Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2014 Feb;12(1):31-8.
doi: 10.1016/j.gpb.2013.12.001. Epub 2014 Jan 22.

Pathway-based analysis of the hidden genetic heterogeneities in cancers

Xiaolei Zhao  1 , Shouqiang Zhong  2 , Xiaoyu Zuo  3 , Meihua Lin  1 , Jiheng Qin  1 , Yizhao Luan  1 , Naizun Zhang  2 , Yan Liang  4 , Shaoqi Rao  5
Affiliations

Pathway-based analysis of the hidden genetic heterogeneities in cancers

Xiaolei Zhao et al. Genomics Proteomics Bioinformatics. 2014 Feb.

Abstract

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.

Keywords: Cancer; Enrichment analysis; Genetic heterogeneity; Pathway-based approach; Sample partitioning; Survival analysis.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Decision tree based on three signature pathways for five cancer types The internal nodes of the tree are the signature pathways. The leaf nodes represent the classification for five types of cancer (renal cancer, central nervous system cancer, melanoma, colon cancer and leukemia). Included in the leaf nodes are the total number of samples over the number of the incorrectly predicted samples for the specific type of cancer indicated.
Figure 2
Figure 2
Clinically distinct DLBCL subtypes defined by gene expression profiling of two signature pathways Kaplan–Meier plot of the overall survival of the three molecular subtypes of DLBCL, partitioned using the expression profiles of the genes contained in two signature pathways, hsa04640 and hsa04060.
Figure 3
Figure 3
A detailed procedure chart for pathway-based analysis of genetic heterogeneities
See this image and copyright information in PMC

References

    1. Xu J.Z., Guo Z., Zhang M., Li X., Li Y.J., Rao S.Q. Peeling off the hidden genetic heterogeneities of cancers based on disease-relevant functional modules. Mol Med. 2006;12:25–33. - PMC - PubMed
    1. Alizadeh A.A., Eisen M.B., Davis R.E., Ma C., Lossos I.S., Rosenwald A. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503–511. - PubMed
    1. Getz G., Levine E., Domany E. Coupled two-way clustering analysis of gene microarray data. Proc Natl Acad Sci U S A. 2000;97:12079–12084. - PMC - PubMed
    1. Zhang W., Li L., Li X., Jiang W., Huo J., Wang Y. Unravelling the hidden heterogeneities of diffuse large B-cell lymphoma based on coupled two-way clustering. BMC Genomics. 2007;8:332. - PMC - PubMed
    1. Bullinger L., Dohner K., Bair E., Frohling S., Schlenk R.F., Tibshirani R. Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med. 2004;350:1605–1616. - PubMed

Publication types