Comparison of global gene expression of gastric cardia and noncardia cancers from a high-risk population in china

Abstract

Objective: To profile RNA expression in gastric cancer by anatomic subsites as an initial step in identifying molecular subtypes and providing targets for early detection and therapy.

Methods: We performed transcriptome analysis using the Affymetrix GeneChip U133A in gastric cardia adenocarcinomas (n = 62) and gastric noncardia adenocarcinomas (n = 72) and their matched normal tissues from patients in Shanxi Province, and validated selected dysregulated genes with additional RNA studies. Expression of dysregulated genes was also related to survival of cases.

Results: Principal Component Analysis showed that samples clustered by tumor vs. normal, anatomic location, and histopathologic features. Paired t-tests of tumor/normal tissues identified 511 genes whose expression was dysregulated (P<4.7E-07 and at least two-fold difference in magnitude) in cardia or noncardia gastric cancers, including nearly one-half (n = 239, 47%) dysregulated in both cardia and noncardia, one-fourth dysregulated in cardia only (n = 128, 25%), and about one-fourth in noncardia only (n = 144, 28%). Additional RNA studies confirmed profiling results. Expression was associated with case survival for 20 genes in cardia and 36 genes in noncardia gastric cancers.

Conclusions: The dysregulated genes identified here represent a comprehensive starting point for future efforts to understand etiologic heterogeneity, develop diagnostic biomarkers for early detection, and test molecularly-targeted therapies for gastric cancer.

Figure 1. Principle component analyses of RNA expression for gastric cardia, gastric noncardia, and esophageal cancers.

PCA revealed two major clusters of samples separating gastric cancer (CC [GCA] in red, N = 62; BC [GNCA] in blue, N = 72) from EC [ESCC] (green, N = 53) in the PC1 axis. PC2 further divided clusters into tumor (t) and normal (n) samples. (Note regarding comparability of expression results: Cases of ESCC, GCA, and GNCA were enrolled concurrently from a single hospital using a common protocol; samples were collected, processed, stored, and transported in an identical manner; and laboratory analyses were performed during the same time period, in the same lab, by the same technical staff, using the same platform, and the same technical approach.).

Figure 2. PCA analysis of GCA patients (124 chips from 62 patients).

Red “t “ represents tumor and green “n” represents matched normal tissue.

Figure 3. PCA analysis of GNCA patients (144 chips from 72 patients).

Red “t “ represents tumor and green “n” represents matched normal tissue.

Figure 4. Diagram showing the number of significantly dysregulated genes (GCA only, GNCA only, and common to both GCA and GNCA).

Figure 5. Survival curve for MMP9 in GCA by Kaplan-Meier analyses.

Dotted red lines indicate high (above the median) expression and broken blue lines indicate low (below the median) expression.

Figure 6. Survival curve for ESRRG in GNCA by Kaplan-Meier analyses.

Dotted red lines indicate high (above the median) expression and broken blue lines indicate low (below the median) expression.