The screening and analysis of protein signatures and signaling associated with chemoresistance based on Protein Pathway Array technology in gastric cancer

  • Authors:
    • Guodong Lian
    • Leping Li
    • Fei Ye
    • Daguang Wang
    • Jinglei Liu
    • Yulong Shi
    • Changqing Jing
    • Jian Suo
    • David Y. Zhang
    • Man Chen
  • View Affiliations

  • Published online on: November 6, 2017     https://doi.org/10.3892/or.2017.6078
  • Pages:307-315
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Abstract

The present study was aimed to identify proteins associated with signaling pathways involved in chemoresistance, and establish a predictive model for chemoresistance in gastric cancer patients after radical surgery. A total of 140 clinically-staged III gastric cancer samples from patients after D2 radical gastrectomy were enrolled in the present study. Protein Pathway Array (PPA) and 286 antibodies were used to assess the protein expression in tumor tissues of patients. The Significance Analysis of Microarray (SAM) software and clustering and discriminant analysis were used to identify differentially expressed proteins between chemosensitive and chemoresistant subsets, and a predictive model for chemoresistance was established using the independent predictive factors. The Ingenuity Pathway Analysis (IPA) software was also used to investigate the relationship between proteins and the signaling transduction network. A total of 23 proteins were differentially expressed between 67 chemosensitive and 73 chemoresitant tumor tissues. Six proteins including PLK1 and DACH1 were independent risk factors for chemoresistance. A predictive model for chemoresistance by these proteins was established, and the accuracy, the sensitivity, and the specificity of this modal was 89.3, 90.3 and 88.2%, respectively. In addition, the present study revealed that differentially expressed proteins were closely related to cellular activity, DNA methylation and DNA damage and repair, and also involved in the ERK/MAPK, Wnt/β-catenin, PI3K/AKT, apoptosis and p53 signaling pathways. In conclusion, the predictive model established by PPA may be an effective detection system for predicting the chemosensitivity of gastric cancer patients after D2 gastrectomy.

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January 2018
Volume 39 Issue 1

Print ISSN: 1021-335X
Online ISSN:1791-2431

2016 Impact Factor: 2.662
Ranked #31/217 Oncology
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APA
Lian, G., Li, L., Ye, F., Wang, D., Liu, J., Shi, Y. ... Chen, M. (2018). The screening and analysis of protein signatures and signaling associated with chemoresistance based on Protein Pathway Array technology in gastric cancer. Oncology Reports, 39, 307-315. https://doi.org/10.3892/or.2017.6078
MLA
Lian, G., Li, L., Ye, F., Wang, D., Liu, J., Shi, Y., Jing, C., Suo, J., Zhang, D. Y., Chen, M."The screening and analysis of protein signatures and signaling associated with chemoresistance based on Protein Pathway Array technology in gastric cancer". Oncology Reports 39.1 (2018): 307-315.
Chicago
Lian, G., Li, L., Ye, F., Wang, D., Liu, J., Shi, Y., Jing, C., Suo, J., Zhang, D. Y., Chen, M."The screening and analysis of protein signatures and signaling associated with chemoresistance based on Protein Pathway Array technology in gastric cancer". Oncology Reports 39, no. 1 (2018): 307-315. https://doi.org/10.3892/or.2017.6078