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Article

Systems biology analysis of the lung cancer‑related secretome

  • Authors:
    • Lin Feng
    • Yikun Yang
    • Min Li
    • Jie Song
    • Yanning Gao
    • Shujun Cheng
    • Ting Xiao
  • View Affiliations / Copyright

    Affiliations: State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China, Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China, State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Carcinogenesis and Cancer Prevention, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, P.R. China
  • Pages: 1103-1118
    |
    Published online on: June 20, 2018
       https://doi.org/10.3892/or.2018.6509
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Abstract

Tumorigenesis is closely and highly associated with developmental biology. The present study aimed to discover and identify marker proteins strongly associated with the occurrence and development of non‑small cell lung cancer (NSCLC) in humans and to provide new ideas for investigating lung cancer markers by combining biological analyses of embryonic development. We established primary cultures for samples of tumor and control tissues from 9 patients with NSCLC and collected conditioned medium (CM). Subsequently, we used liquid chromatography and linear ion trap (LTQ) mass spectrometry to isolate and identify proteins in CM samples. Data mining of free proteins was conducted using the analogous analysis strategy in systems biology to obtain important lung cancer‑associated proteins (plasma markers). Proteins with significant plasma enrichment in lung cancer patients were detected via enzyme‑linked immunosorbent assay (ELISA). We identified 987 high‑confidence proteins and established a primary database of free proteins associated with lung cancer. Furthermore, 511 high‑confidence proteins were present in CM from primary tissue cultures from at least 2 of the 9 examined cases of lung cancer. Analysis using Gene Set Enrichment Analysis (GSEA) software revealed significant enrichment for 197 proteins from the CM of lung cancer samples in maternal‑placental interface expression profiles for a mid‑term placenta with strong invasiveness relative to RNA expression profiles for a human full‑term placenta after delivery. ELISA results demonstrated that hypoxanthine phosphoribosyltransferase 1 (HPRT1) was associated with worse rates of disease‑free survival (DFS) and overall survival (OS). The biological behaviors of embryonic implantation are similar to those of tumor invasion and metastasis, and the information obtained regarding developmental biology could facilitate the interpretation of tumor invasion and metastasis. Therefore, similar biological behaviors combined with analyses at different molecular levels from the perspective of systems biology will provide new ideas for tumor research.
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Copy and paste a formatted citation
Spandidos Publications style
Feng L, Yang Y, Li M, Song J, Gao Y, Cheng S and Xiao T: Systems biology analysis of the lung cancer‑related secretome. Oncol Rep 40: 1103-1118, 2018.
APA
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., & Xiao, T. (2018). Systems biology analysis of the lung cancer‑related secretome. Oncology Reports, 40, 1103-1118. https://doi.org/10.3892/or.2018.6509
MLA
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., Xiao, T."Systems biology analysis of the lung cancer‑related secretome". Oncology Reports 40.2 (2018): 1103-1118.
Chicago
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., Xiao, T."Systems biology analysis of the lung cancer‑related secretome". Oncology Reports 40, no. 2 (2018): 1103-1118. https://doi.org/10.3892/or.2018.6509
Copy and paste a formatted citation
x
Spandidos Publications style
Feng L, Yang Y, Li M, Song J, Gao Y, Cheng S and Xiao T: Systems biology analysis of the lung cancer‑related secretome. Oncol Rep 40: 1103-1118, 2018.
APA
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., & Xiao, T. (2018). Systems biology analysis of the lung cancer‑related secretome. Oncology Reports, 40, 1103-1118. https://doi.org/10.3892/or.2018.6509
MLA
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., Xiao, T."Systems biology analysis of the lung cancer‑related secretome". Oncology Reports 40.2 (2018): 1103-1118.
Chicago
Feng, L., Yang, Y., Li, M., Song, J., Gao, Y., Cheng, S., Xiao, T."Systems biology analysis of the lung cancer‑related secretome". Oncology Reports 40, no. 2 (2018): 1103-1118. https://doi.org/10.3892/or.2018.6509
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