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Comparative Study
. 2010 Oct 27;5(10):e13696.
doi: 10.1371/journal.pone.0013696.

A comparative analysis of gene-expression data of multiple cancer types

Kun Xu  1 , Juan Cui, Victor Olman, Qing Yang, David Puett, Ying Xu
Affiliations
Comparative Study

A comparative analysis of gene-expression data of multiple cancer types

Kun Xu et al. PLoS One. .

Abstract

A comparative study of public gene-expression data of seven types of cancers (breast, colon, kidney, lung, pancreatic, prostate and stomach cancers) was conducted with the aim of deriving marker genes, along with associated pathways, that are either common to multiple types of cancers or specific to individual cancers. The analysis results indicate that (a) each of the seven cancer types can be distinguished from its corresponding control tissue based on the expression patterns of a small number of genes, e.g., 2, 3 or 4; (b) the expression patterns of some genes can distinguish multiple cancer types from their corresponding control tissues, potentially serving as general markers for all or some groups of cancers; (c) the proteins encoded by some of these genes are predicted to be blood secretory, thus providing potential cancer markers in blood; (d) the numbers of differentially expressed genes across different cancer types in comparison with their control tissues correlate well with the five-year survival rates associated with the individual cancers; and (e) some metabolic and signaling pathways are abnormally activated or deactivated across all cancer types, while other pathways are more specific to certain cancers or groups of cancers. The novel findings of this study offer considerable insight into these seven cancer types and have the potential to provide exciting new directions for diagnostic and therapeutic development.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Figure 1
Figure 1. Classification accuracies by the top 100 k-gene markers, k = 1, 2, 3, 4, on the training and the test sets of breast cancer.
For each panel, the x-axis is the list of 100 k-gene markers ordered by their classification performance on the training datasets, and the y-axis represents the classification accuracy. (A) classification accuracies by the top 100 k-gene combinations between breast cancer and reference samples in the training set, and (B) and (C) on the two test sets; (D) classification accuracies by top 100 k-gene combinations between early breast cancer and corresponding reference samples in the training set and (E) on the test set.
Figure 2
Figure 2. Correlation between 5-year survival rate and the number of differentially genes in each cancer type.
See this image and copyright information in PMC

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