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Identification of prognosis-related proteins in advanced gastric cancer by mass spectrometry-based comparative proteomics

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Abstract

Purpose

The objective of this study was to identify differentially expressed proteins of advanced gastric cancer from patients with different prognosis using NanoLC–MS/MS (LTQ) (nanoflow liquid chromatography system interfaced with a linear ion trap LTQ mass spectrometer).

Methods

Eight gastric cancer patients with relatively early TNM stage and survival time >34 months were identified as good survival (group G), while the other eight with late stage and survival time <15 months as poor survival (group P). The total protein of the tissue samples from each group was extracted and pooled together respectively. The resulting two protein mixtures were trypsin-digested and analyzed using NanoLC–MS/MS (LTQ). Database searches were done against NCBI non-redundant database and SWISS-PROT database and the identified proteins were classified through an online Web Gene Ontology Annotation Plot tool. Immunohistochemistry was used to verify candidate prognosis-related proteins.

Results

There were 284 and 213 proteins identified for group G and group P respectively. And 117 proteins were detected exclusively in group G and 46 proteins exclusively in group P. These protein markers function in calcium ion signaling pathway, cellular metabolism, cytoskeleton formation, stress reaction, etc. Among those, the down-regulated expression of S100P was verified to claim a poor clinical outcome of gastric cancer patients (P = 0.0375).

Conclusion

The MS-based proteomics approach is efficient in identifying differentially expressed proteins in relation to prognosis of advanced gastric cancer patients. These differentially expressed proteins could be potential prognosis-related cancer markers and deserve further validation and functional study.

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Abbreviations

NanoLC–MS/MS (LTQ):

Nanoflow liquid chromatography interfaced with a linear ion trap spectrometer

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 30571807) and the Foundation of Beijing Municipal Committee of Science & Technology, China (No. D0905001040631). We are grateful to Ph.D Yang Shuang, Beijing Genomics Institute, China, for WEGO plot making.

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Authors and Affiliations

  1. Department of Surgery, Beijing Cancer Hospital, Beijing Institute for Cancer Research, Peking University School of Oncology, 100036, Beijing, China

    Shu-Qin Jia, Lian-Hai Zhang, Xi-Yao Zhong, Tao Shi & Jia-Fu Ji

  2. Department of General Surgery, Qilu Hospital, Shandong University, 250012, Jinan, Shandong, China

    Zhao-Jian Niu

  3. Tissue Bank, Beijing Cancer Hospital, Beijing Institute for Cancer Research, Peking University School of Oncology, 100036, Beijing, China

    Hong Du, Gui-Guo Zhang & Ying Hu

  4. Clinical Medicine Research Center, Inner Mongolia Medical College, 010050, Hohhot, China

    Shu-Qin Jia & Xiu-Lan Su

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  1. Shu-Qin Jia
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  2. Zhao-Jian Niu
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  3. Lian-Hai Zhang
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  4. Xi-Yao Zhong
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  5. Tao Shi
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  7. Gui-Guo Zhang
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  9. Xiu-Lan Su
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Corresponding author

Correspondence to Jia-Fu Ji.

Additional information

S.-Q. Jia and Z.-J. Niu contributed equally to this study.

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Jia, SQ., Niu, ZJ., Zhang, LH. et al. Identification of prognosis-related proteins in advanced gastric cancer by mass spectrometry-based comparative proteomics. J Cancer Res Clin Oncol 135, 403–411 (2009). https://doi.org/10.1007/s00432-008-0474-3

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  • DOI: https://doi.org/10.1007/s00432-008-0474-3

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