An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer

Juan Cui, Yunbo Chen, Wen Chi Chou, Liankun Sun, Li Chen, Jian Suo, Zhaohui Ni, Ming Zhang, Xiaoxia Kong, Lisabeth L. Hoffman, Jinsong Kang, Yingying Su, Victor Olman, Darryl Johnson, Daniel W. Tench, I. Jonathan Amster, Ron Orlando, David Puett, Fan Li, Ying Xu

Research output: Contribution to journalArticle

116 Scopus citations

Abstract

This report describes an integrated study on identification of potential markers for gastric cancer in patients' cancer tissues and sera based on: (i) genome-scale transcriptomic analyses of 80 paired gastric cancer/reference tissues and (ii) computational prediction of blood-secretory proteins supported by experimental validation. Our findings show that: (i) 715 and 150 genes exhibit significantly differential expressions in all cancers and early-stage cancers versus reference tissues, respectively; and a substantial percentage of the alteration is found to be influenced by age and/or by gender; (ii) 21 co-expressed gene clusters have been identified, some of which are specific to certain subtypes or stages of the cancer; (iii) the top-ranked gene signatures give better than 94 classification accuracy between cancer and the reference tissues, some of which are gender-specific; and (iv) 136 of the differentially expressed genes were predicted to have their proteins secreted into blood, 81 of which were detected experimentally in the sera of 13 validation samples and 29 found to have differential abundances in the sera of cancer patients versus controls. Overall, the novel information obtained in this study has led to identification of promising diagnostic markers for gastric cancer and can benefit further analyses of the key (early) abnormalities during its development. The Author(s) 2010. Published by Oxford University Press.2010This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2. 5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Original languageEnglish (US)
Pages (from-to)1197-1207
Number of pages11
JournalNucleic acids research
Volume39
Issue number4
DOIs
StatePublished - Mar 1 2011

    Fingerprint

ASJC Scopus subject areas

  • Genetics

Cite this

Cui, J., Chen, Y., Chou, W. C., Sun, L., Chen, L., Suo, J., Ni, Z., Zhang, M., Kong, X., Hoffman, L. L., Kang, J., Su, Y., Olman, V., Johnson, D., Tench, D. W., Amster, I. J., Orlando, R., Puett, D., Li, F., & Xu, Y. (2011). An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer. Nucleic acids research, 39(4), 1197-1207. https://doi.org/10.1093/nar/gkq960