An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer.
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.
Cui
Juan
J
Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia, Athens, GA 30602, USA.
Chen
Yunbo
Y
Chou
Wen-Chi
WC
Sun
Liankun
L
Chen
Li
L
Suo
Jian
J
Ni
Zhaohui
Z
Zhang
Ming
M
Kong
Xiaoxia
X
Hoffman
Lisabeth L
LL
Kang
Jinsong
J
Su
Yingying
Y
Olman
Victor
V
Johnson
Darryl
D
Tench
Daniel W
DW
Amster
I Jonathan
IJ
Orlando
Ron
R
Puett
David
D
Li
Fan
F
Xu
Ying
Y
D000328:Adult; D000367:Age Factors; D000368:Aged; D014408:Biomarkers, Tumor / Q000097:blood* / Q000235:genetics / Q000378:metabolism; D019295:Computational Biology; D020869:Gene Expression Profiling; D006801:Humans; D008297:Male; D008875:Middle Aged; D012737:Sex Factors; D013274:Stomach Neoplasms / Q000097:blood / Q000145:classification / Q000235:genetics*
D014408:Biomarkers, Tumor