Integrated expression analysis identifies transcription networks in mouse and human gastric neoplasia

Zheng Chen, Mohammed Soutto, Bushra Rahman, Muhammad W. Fazili, Dun Fa Peng, Maria Blanca Piazuelo, Heidi Chen, M. Kay Washington, Yu Shyr, Wael El-Rifai

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide. The Tff1 knockout (KO) mouse model develops gastric lesions that include low-grade dysplasia (LGD), high-grade dysplasia (HGD), and adenocarcinomas. In this study, we used Affymetrix microarrays gene expression platforms for analysis of molecular signatures in the mouse stomach [Tff1-KO (LGD) and Tff1 wild-type (normal)] and human gastric cancer tissues and their adjacent normal tissue samples. Combined integrated bioinformatics analysis of mouse and human datasets indicated that 172 genes were consistently deregulated in both human gastric cancer samples and Tff1-KO LGD lesions (P <.05). Using Ingenuity pathway analysis, these genes mapped to important transcription networks that include MYC, STAT3, β-catenin, RELA, NFATC2, HIF1A, and ETS1 in both human and mouse. Further analysis demonstrated activation of FOXM1 and inhibition of TP53 transcription networks in human gastric cancers but not in Tff1-KO LGD lesions. Using real-time RT-PCR, we validated the deregulated expression of several genes (VCAM1, BGN, CLDN2, COL1A1, COL1A2, COL3A1, EpCAM, IFITM1, MMP9, MMP12, MMP14, PDGFRB, PLAU, and TIMP1) that map to altered transcription networks in both mouse and human gastric neoplasia. Our study demonstrates significant similarities in deregulated transcription networks in human gastric cancer and gastric tumorigenesis in the Tff1-KO mouse model. The data also suggest that activation of MYC, STAT3, RELA, and β-catenin transcription networks could be an early molecular step in gastric carcinogenesis.

Original languageEnglish
Pages (from-to)535-547
Number of pages13
JournalGenes Chromosomes and Cancer
Volume56
Issue number7
DOIs
Publication statusPublished - 2017 Jul

    Fingerprint

All Science Journal Classification (ASJC) codes

  • Genetics
  • Cancer Research

Cite this

Chen, Z., Soutto, M., Rahman, B., Fazili, M. W., Peng, D. F., Blanca Piazuelo, M., Chen, H., Kay Washington, M., Shyr, Y., & El-Rifai, W. (2017). Integrated expression analysis identifies transcription networks in mouse and human gastric neoplasia. Genes Chromosomes and Cancer, 56(7), 535-547. https://doi.org/10.1002/gcc.22456