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

Nucleic Acids Research, Mar 2011

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.

A PDF file should load here. If you do not see its contents the file may be temporarily unavailable at the journal website or you do not have a PDF plug-in installed and enabled in your browser.

Alternatively, you can download the file locally and open with any standalone PDF reader:

https://nar.oxfordjournals.org/content/39/4/1197.full.pdf

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

Juan Cui 2 Yunbo Chen 1 Wen-Chi Chou 2 Liankun Sun 1 Li Chen 1 Jian Suo 1 Zhaohui Ni 1 Ming Zhang 1 Xiaoxia Kong 1 Lisabeth L. Hoffman 0 Jinsong Kang 1 Yingying Su 1 Victor Olman 2 Darryl Johnson 5 Daniel W. Tench 4 I. Jonathan Amster 0 Ron Orlando 5 David Puett 2 Fan Li 1 Ying Xu 2 3 0 Department of Chemistry, University of Georgia 1 Jilin University-University of Georgia Joint Research Center for Systems Biology, College of Medicine, Jilin University , Changchun, Jilin 130021, China 2 Department of Biochemistry and Molecular Biology and Institute of Bioinformatics, University of Georgia , Athens, GA 30602, USA 3 College of Computer Science and Technology, Jilin University , Changchun, Jilin 130021, China 4 Department of Pathology, Athens Regional Medical Center , Athens, GA 30606, USA 5 Department of Biochemistry and Molecular Biology and the Complex Carbohydrate Research Center , Athens, GA 30602 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. - Gastric cancer represents the second leading cause of cancer death worldwide, next only to lung cancer (1). In 2002, 934 000 new cases were reported worldwide. In the USA, 21 500 new cases of gastric cancer were diagnosed in 2008, with 10 800 deaths from the disease (2). The current 5-year survival rate of individuals diagnosed with gastric cancer is 24% (1), reflecting the reality that most cases are already in an advanced stage when diagnosed. As with other cancers, the challenge in early detection lies in the reality that the early symptoms tend to be relatively non-specific, and detection requires that invasive physical procedures, such as gastrointestinal endoscopy, be carried out on a regular basis, which may not be practical for general screening. The most ideal solution for early detection is to find reliable markers that can detect the cancer through simple blood tests. Recent comparative transcriptomic studies have identified a number of gene markers of different types for gastric cancer, such as diagnostic markers [NF2 (3), NEK6 and INHBA (4)], prognostic markers [CDH17 (5), PDCD6 (6)], and gastric-cancer-associated genes [TSPAN1, Ki67 and CD34 (7)]. While exhibiting some predictive power, these gene markers were found highly inconsistent as identified by different studies (Supplementary Table S1), and none of them has reached the clinical trial stage. A few serum markers such as a-fetoprotein antigen (AFP), carcinoembryonic antigen (CEA), and CA19-9, identified through large-scale blood screening (8), have been used for gastric cancer detection. The detection sensitivities of these markers are, however, rather low, no more than 25% at the 90% specificity level (8), and hence they have not been widely used clinically for diagnostic purposes. Using immunoassay and proteomic techniques, a few new serum markers were recently proposed. including MUC1 and MUC5AC (8), pepsinogen C and pepsin A activation peptide (9), and Reprimo (10), although their true diagnostic power for gastric cancer, especially at an early stage, is yet to be thoroughly evaluated. More rigorous studies are in order on these proposed markers. The lack of reliable serum markers for gastric cancer reflects the challenging nature of the problem, but also suggests the possibility that all the information derivable using the powerful omic techniques, in conjunction with computational approaches, may not have been fully utilized. For example, there have been only a few published large-scale studies attempting to link the information derivable from gene-expression profiles of cancer tissues to proteomic biomarker identification in patients sera. The general issue with (...truncated)


This is a preview of a remote PDF: https://nar.oxfordjournals.org/content/39/4/1197.full.pdf

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. An integrated transcriptomic and computational analysis for biomarker identification in gastric cancer, Nucleic Acids Research, 2011, pp. 1197-1207, 39/4, DOI: 10.1093/nar/gkq960