Skip to main content
Log in

Data-independent acquisition (DIA) mass spectrometry reveals related proteins involved in the occurrence of early intestinal-type gastric cancer

  • Original Paper
  • Published:
Medical Oncology Aims and scope Submit manuscript

Abstract

Identifying proteins associated with the onset of early intestinal-type gastric cancer (EIGC) can yield valuable insights into the pathogenesis of this specific subtype of gastric cancer. Data-independent acquisition mass spectroscopy (DIA-MS) was utilized to identify the differential protein between 10 cases of EIGC and atrophic gastritis with intestinal metaplasia (NGC). The expressions of IPO4, TBL1XR1, p62/SQSTM1, PKP3, and CRTAP were verified by immunohistochemistry (IHC) in 20 EIGC samples, 17 gastric low-grade intraepithelial neoplasia (LGIN) samples, and 21 healthy controls. The prognostic values of the five genes were validated in the transcriptome data by survival analysis. A total of 4,028 proteins were identified using DIA-MS and a total of 177 differential proteins were screened with log2(fold change) > 1.5. Among them, 113 proteins were significantly up-regulated, and 64 proteins were significantly down-regulated in EIGC tissues. IHC results showed that proteins IPO4, TBL1XR1, p62/SQSTM1, PKP3, and CRTAP were highly expressed in the cytoplasm of EIGC and LGIN, which was consistent with the results of DIA-MS. Among them, p62/SQSTM1 may undergo nuclear-cytoplasmic transfer. The five protein-coding genes were associated with intestinal-type gastric cancer survival and exhibited differential expression across various disease stages. The study successfully identified differentially expressed proteins between EIGC and NGC, providing potential biomarkers and valuable insights into the mechanism underlying intestinal-type gastric cancer.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Data availability

The datasets analyzed in the study are available in public repositories at NCBI GEO (https://www.ncbi.nlm.nih.gov/geo/).

References

  1. Ajani JA, Bentrem DJ, Besh S, D’Amico TA, Das P, Denlinger C, et al. Gastric cancer, version 2.2013: featured updates to the NCCN Guidelines. J Natl Compr Canc Netw. 2013;11:531–46. https://doi.org/10.6004/jnccn.2013.0070.

    Article  CAS  PubMed  Google Scholar 

  2. Aquino PF, Fischer JS, Neves-Ferreira AG, Perales J, Domont GB, Araujo GD, et al. Are gastric cancer resection margin proteomic profiles more similar to those from controls or tumors? J Proteome Res. 2012;11:5836–42. https://doi.org/10.1021/pr300612x.

    Article  CAS  PubMed  Google Scholar 

  3. Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM, et al. Gene ontology: tool for the unification of biology The Gene Ontology Consortium. Nat Gene. 2000;25:25–9. https://doi.org/10.1038/75556.

    Article  CAS  Google Scholar 

  4. Balluff B, Rauser S, Meding S, Elsner M, Schone C, Feuchtinger A, et al. MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer. Am J Pathol. 2011;179:2720–9. https://doi.org/10.1016/j.ajpath.2011.08.032.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Chandrashekar DS, Karthikeyan SK, Korla PK, Patel H, Shovon AR, Athar M, et al. UALCAN: An update to the integrated cancer data analysis platform. Neoplasia. 2022;25:18–27. https://doi.org/10.1016/j.neo.2022.01.001.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Correa P. Gastric cancer: overview. Gastroenterol Clin North Am. 2013;42:211–7. https://doi.org/10.1016/j.gtc.2013.01.002.

    Article  PubMed Central  Google Scholar 

  7. Demirag GG, Sullu Y, Gurgenyatagi D, Okumus NO, Yucel I. Expression of plakophilins (PKP1, PKP2, and PKP3) in gastric cancers. Diagn Pathol. 2011;6:1. https://doi.org/10.1186/1746-1596-6-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Dixon MF, Genta RM, Yardley JH, Correa P. Classification and grading of gastritis. The updated Sydney System. International Workshop on the Histopathology of Gastritis, Houston 1994. Am J Surg Pathol. 1996;20:1161–81. https://doi.org/10.1097/00000478-199610000-00001.

    Article  CAS  PubMed  Google Scholar 

  9. Domon B, Aebersold R. Mass spectrometry and protein analysis. Science. 2006;312:212–7. https://doi.org/10.1126/science.1124619.

    Article  CAS  PubMed  Google Scholar 

  10. Ferlay J, Soerjomataram I, Dikshit R, Eser S, Mathers C, Rebelo M, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer. 2015;136:E359-386. https://doi.org/10.1002/ijc.29210.

    Article  CAS  PubMed  Google Scholar 

  11. Fujiyoshi MRA, Inoue H, Fujiyoshi Y, Nishikawa Y, Toshimori A, Shimamura Y, et al. Endoscopic classifications of early gastric cancer: a literature review. Cancers. 2021. https://doi.org/10.3390/cancers14010100.

    Article  PubMed Central  Google Scholar 

  12. Gravina GL, Senapedis W, McCauley D, Baloglu E, Shacham S, Festuccia C. Nucleo-cytoplasmic transport as a therapeutic target of cancer. J Hematol Oncol. 2014;7:85. https://doi.org/10.1186/s13045-014-0085-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Ivanova OM, Anufrieva KS, Kazakova AN, Malyants IK, Shnaider PV, Lukina MM, et al. Non-canonical functions of spliceosome components in cancer progression. Cell Death Dis. 2023;14:77. https://doi.org/10.1038/s41419-022-05470-9.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Japanese Gastric Cancer A. (2011) Japanese classification of gastric carcinoma: 3rd English edition. Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association 14:101–112. doi: https://doi.org/10.1007/s10120-011-0041-5

  15. Kaise M, Kato M, Urashima M, Arai Y, Kaneyama H, Kanzazawa Y, et al. Magnifying endoscopy combined with narrow-band imaging for differential diagnosis of superficial depressed gastric lesions. Endoscopy. 2009;41:310–5. https://doi.org/10.1055/s-0028-1119639.

    Article  CAS  PubMed  Google Scholar 

  16. Kim HK, Reyzer ML, Choi IJ, Kim CG, Kim HS, Oshima A, et al. Gastric cancer-specific protein profile identified using endoscopic biopsy samples via MALDI mass spectrometry. J Proteome Res. 2010;9:4123–30. https://doi.org/10.1021/pr100302b.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Kim JS, Bae GE, Kim KH, Lee SI, Chung C, Lee D, et al. Prognostic significance of LC3B and p62/SQSTM1 expression in gastric adenocarcinoma. Anticancer Res. 2019;39:6711–22. https://doi.org/10.21873/anticanres.13886.

    Article  CAS  PubMed  Google Scholar 

  18. Kitata RB, Yang JC, Chen YJ. Advances in data-independent acquisition mass spectrometry towards comprehensive digital proteome landscape. Mass Spectrometry Rev. 2022. https://doi.org/10.1002/mas.21781.

    Article  Google Scholar 

  19. Komatsu M, Kageyama S, Ichimura Y. p62/SQSTM1/A170: physiology and pathology. Pharmacol Res. 2012;66:457–62. https://doi.org/10.1016/j.phrs.2012.07.004.

    Article  CAS  Google Scholar 

  20. Kuramitsu Y, Baron B, Yoshino S, Zhang X, Tanaka T, Yashiro M, et al. Proteomic differential display analysis shows up-regulation of 14-3-3 sigma protein in human scirrhous-type gastric carcinoma cells. Anticancer Res. 2010;30:4459–65.

    CAS  PubMed  Google Scholar 

  21. Lauren P. The two histological main types of gastric carcinoma: diffuse and so-called intestinal-type carcinoma. an attempt at a histo-clinical classification. Acta Pathol Microbiol Scand. 1965;64:31–49. https://doi.org/10.1111/apm.1965.64.1.31.

    Article  CAS  PubMed  Google Scholar 

  22. Liu W, Yang Q, Liu B, Zhu Z. Serum proteomics for gastric cancer. Clin Chim Acta. 2014;431:179–84. https://doi.org/10.1016/j.cca.2014.02.001.

    Article  CAS  PubMed  Google Scholar 

  23. Lordick F, Carneiro F, Cascinu S, Fleitas T, Haustermans K, Piessen G, et al. Gastric cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol. 2022;33:1005–20. https://doi.org/10.1016/j.annonc.2022.07.004.

    Article  CAS  PubMed  Google Scholar 

  24. Lu J, Bang H, Kim SM, Cho SJ, Ashktorab H, Smoot DT, et al. Lymphatic metastasis-related TBL1XR1 enhances stemness and metastasis in gastric cancer stem-like cells by activating ERK1/2-SOX2 signaling. Oncogene. 2021;40:922–36. https://doi.org/10.1038/s41388-020-01571-x.

    Article  CAS  PubMed  Google Scholar 

  25. Ludwig C, Gillet L, Rosenberger G, Amon S, Collins BC, Aebersold R. Data-independent acquisition-based SWATH-MS for quantitative proteomics: a tutorial. Mol Syst Biol. 2018;14: e8126. https://doi.org/10.15252/msb.20178126.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Mao D, Xu R, Chen H, Chen X, Li D, Song S, et al. Cross-talk of focal adhesion-related gene defines prognosis and the immune microenvironment in gastric cancer. Front Cell Develop Biol. 2021;9: 716461. https://doi.org/10.3389/fcell.2021.716461.

    Article  Google Scholar 

  27. Park S, Karalis JD, Hong C, Clemenceau JR, Porembka MR, Kim IH, et al. ACTA2 expression predicts survival and is associated with response to immune checkpoint inhibitors in gastric cancer. Clin Cancer Res. 2023;29:1077–85. https://doi.org/10.1158/1078-0432.CCR-22-1897.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Perdigao-Henriques R, Petrocca F, Altschuler G, Thomas MP, Le MT, Tan SM, et al. miR-200 promotes the mesenchymal to epithelial transition by suppressing multiple members of the Zeb2 and Snail1 transcriptional repressor complexes. Oncogene. 2016;35:158–72. https://doi.org/10.1038/onc.2015.69.

    Article  CAS  PubMed  Google Scholar 

  29. Raftopoulos SC, Kumarasinghe P, de Boer B, Iacobelli J, Kontorinis N, Fermoyle S, et al. Gastric intraepithelial neoplasia in a Western population. Eur J Gastroenterol Hepatol. 2012;24:48–54. https://doi.org/10.1097/MEG.0b013e32834dc1bb.

    Article  PubMed  Google Scholar 

  30. Raju D, Hussey S, Ang M, Terebiznik MR, Sibony M, Galindo-Mata E, et al. Vacuolating cytotoxin and variants in Atg16L1 that disrupt autophagy promote Helicobacter pylori infection in humans. Gastroenterology. 2012;142:1160–71. https://doi.org/10.1053/j.gastro.2012.01.043.

    Article  CAS  PubMed  Google Scholar 

  31. Schlemper RJ, Kato Y, Stolte M. Review of histological classifications of gastrointestinal epithelial neoplasia: differences in diagnosis of early carcinomas between Japanese and Western pathologists. J Gastroenterol. 2001;36:445–56. https://doi.org/10.1007/s005350170067.

    Article  CAS  PubMed  Google Scholar 

  32. Sekine S, Yoshida H, Jansen M, Kushima R. The Japanese viewpoint on the histopathology of early gastric cancer. Adv Exp Med Biol. 2016;908:331–46. https://doi.org/10.1007/978-3-319-41388-4_16.

    Article  PubMed  Google Scholar 

  33. Shen Q, Wang YE, Palazzo AF. Crosstalk between nucleocytoplasmic trafficking and the innate immune response to viral infection. J Biol Chem. 2021;297: 100856. https://doi.org/10.1016/j.jbc.2021.100856.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Szasz AM, Lanczky A, Nagy A, Forster S, Hark K, Green JE, et al. Cross-validation of survival associated biomarkers in gastric cancer using transcriptomic data of 1,065 patients. Oncotarget. 2016;7:49322–33. https://doi.org/10.18632/oncotarget.10337.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Tang B, Li N, Gu J, Zhuang Y, Li Q, Wang HG, et al. Compromised autophagy by MIR30B benefits the intracellular survival of Helicobacter pylori. Autophagy. 2012;8:1045–57. https://doi.org/10.4161/auto.20159.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wagner AD, Syn NL, Moehler M, Grothe W, Yong WP, Tai BC, et al. Chemotherapy for advanced gastric cancer. Cochrane Database Syst Rev. 2017. https://doi.org/10.1002/14651858.CD004064.pub4.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Wang S, Han H, Hu Y, Yang W, Lv Y, Wang L, et al. MicroRNA-130a-3p suppresses cell migration and invasion by inhibition of TBL1XR1-mediated EMT in human gastric carcinoma. Mol Carcinog. 2018;57:383–92. https://doi.org/10.1002/mc.22762.

    Article  CAS  PubMed  Google Scholar 

  38. Xu X, Zhang X, Xing H, Liu Z, Jia J, Jin C, et al. Importin-4 functions as a driving force in human primary gastric cancer. J Cell Biochem. 2019;120:12638–46. https://doi.org/10.1002/jcb.28530.

    Article  CAS  PubMed  Google Scholar 

  39. Zhou X, Yao K, Zhang L, Zhang Y, Han Y, Liu HL, et al. Identification of differentiation-related proteins in gastric adenocarcinoma tissues by proteomics. Technol Cancer Res Treat. 2016;15:697–706. https://doi.org/10.1177/1533034615595792.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful for the technical support from Shanghai Applied Protein Technology Co. Ltd. This study was funded by the Zhejiang Provincial Natural Science Foundation of China (Nos. LGF19H030006 and LQ20H030001), Ningbo Science and Technology Project (No. 2019C50100), and Ningbo Clinical Medicine Research Center Project (No. 2019A21003).

Funding

This article was funded by Zhejiang Provincial Natural Science Foundation of China, LGF19H030006, Hua Ye, LQ20H030001, Hua Ye, Ningbo Science and Technology Project, 2019C50100, Hua Ye,Ningbo Clinical Medicine Research Center Project, 2019A21003, Hong Li.

Author information

Authors and Affiliations

Authors

Contributions

Hua Ye and Hong Li: conceived and designed the experiments. Liangshun Zhang and Feng Xu: collected samples, performed the proteome analysis, and analysed the data. Hongna Lu and Xianwen Dong: data analysis and plotting figures. Zhiqiang Gao and Qiaosu Zhao: performed the WGCNA and transcriptome data analysis. Ting Weng: survival analysis. Hong Li: drafting the manuscript. Hua Ye: project administration and revised the manuscript. All the authors participated in the manuscript revision.

Corresponding authors

Correspondence to Hong Li or Hua Ye.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Ethical approval

The experimental protocol was approved by the Ethics Committee of Ningbo Medical Center Lihuili Hospital (KY2019PJ055). Informed consent was obtained from all participating patients or their family members.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (XLSX 125 KB)

Supplementary file2 (DOCX 89 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, L., Xu, F., Lu, H. et al. Data-independent acquisition (DIA) mass spectrometry reveals related proteins involved in the occurrence of early intestinal-type gastric cancer. Med Oncol 41, 23 (2024). https://doi.org/10.1007/s12032-023-02241-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12032-023-02241-0

Keywords

Navigation