Skip to main content

Advertisement

Log in

Global analysis of chromosome 1 genes among patients with lung adenocarcinoma, squamous carcinoma, large-cell carcinoma, small-cell carcinoma, or non-cancer

  • Published:
Cancer and Metastasis Reviews Aims and scope Submit manuscript

Abstract

The present study aimed at investigating genetic variations, specific signal pathways, or biological processes of chromosome 1 genes between subtypes and stages of lung cancer and prediction of selected targeting genes for patient survival rate. About 537 patients with lung adenocarcinoma (ADC), 140 with lung squamous carcinoma (SCC), 9 with lung large-cell carcinoma (LCC), 56 with small-cell lung cancer (SCLC), and 590 without caner were integrated from 16 databases and analyzed in the present study. Three (ASPM, CDC20, KIAA1799) or 28 genes significantly up- or down-expressed in four subtypes of lung cancer. The activated cell division and down-regulated immune responses were identified in patients with lung cancer. Keratinocyte development associated genes S100 and SPRR families dominantly up-expressed in SCC and AKT3 and NRAS in SCLC. Subtype-specific genes of ADC, SCC, LCC, or SCLC were also identified. C1orf106, CAPN8, CDC20, COL11A1, CRABP2, and NBPF9 up-expressed at four stages of ADC. Fifty six related with keratinocytes or potassium channels up-expressed in three stages of SCC. CDC20, IL10, ECM1, GABPB2, CRABP2, and COL11A1 significantly predicted the poor overall survival of ADC patients and S100A2 and TIMM17A in SCC patients. Our data indicate that a number of altered chromosome 1 genes have the subtype and stage specificities of lung cancer and can be considered as diagnostic and prognosis biomarkers.

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

Access this article

Price includes VAT (France)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. Jemal, A., Bray, F., Center, M. M., Ferlay, J., Ward, E., & Forman, D. (2011). Global cancer statistics. CA: A Cancer Journal for Clinicians, 61, 69–90.

    Google Scholar 

  2. Hensing, T., Chawla, A., Batra, R., & Salgia, R. (2014). A personalized treatment for lung cancer: molecular pathways, targeted therapies, and genomic characterization. Advances in Experimental Medicine and Biology, 799, 85–117.

    Article  CAS  PubMed  Google Scholar 

  3. Oxnard, G. R., Binder, A., & Janne, P. A. (2013). New targetable oncogenes in non-small-cell lung cancer. Journal of Clinical Oncology, 31, 1097–1104.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  4. Baty, F., Facompre, M., Kaiser, S., et al. (2010). Gene profiling of clinical routine biopsies and prediction of survival in non-small cell lung cancer. American Journal of Respiratory and Critical Care Medicine, 181, 181–188.

    Article  CAS  PubMed  Google Scholar 

  5. Sanchez-Palencia, A., Gomez-Morales, M., Gomez-Capilla, J. A., et al. (2011). Gene expression profiling reveals novel biomarkers in nonsmall cell lung cancer. International Journal of Cancer, 129, 355–364.

    Article  CAS  Google Scholar 

  6. Kuner, R., Muley, T., Meister, M., et al. (2009). Global gene expression analysis reveals specific patterns of cell junctions in non-small cell lung cancer subtypes. Lung Cancer, 63, 32–38.

    Article  PubMed  Google Scholar 

  7. Takeuchi, T., Tomida, S., Yatabe, Y., et al. (2006). Expression profile-defined classification of lung adenocarcinoma shows close relationship with underlying major genetic changes and clinicopathologic behaviors. Journal of Clinical Oncology, 24, 1679–1688.

    Article  CAS  PubMed  Google Scholar 

  8. Lockwood, W. W., Chari, R., Coe, B. P., et al. (2008). DNA amplification is a ubiquitous mechanism of oncogene activation in lung and other cancers. Oncogene, 27, 4615–4624.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Stella, G. M., Luisetti, M., Pozzi, E., & Comoglio, P. M. (2013). Oncogenes in non-small-cell lung cancer: emerging connections and novel therapeutic dynamics. Lancet Respiratory Medecine, 1, 251–261.

    Article  CAS  Google Scholar 

  10. Barrett, T., Troup, D. B., Wilhite, S. E., et al. (2007). NCBI GEO: mining tens of millions of expression profiles—database and tools update. Nucleic Acids Research, 35, D760–D765.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  11. Huang, Z. X., Tian, H. Y., Hu, Z. F., Zhou, Y. B., Zhao, J., & Yao, K. T. (2008). GenCLiP: a software program for clustering gene lists by literature profiling and constructing gene co-occurrence networks related to custom keywords. BMC Bioinformatics, 9, 308.

    Article  PubMed Central  PubMed  Google Scholar 

  12. Kanehisa, M., Goto, S., Kawashima, S., Okuno, Y., & Hattori, M. (2004). The KEGG resource for deciphering the genome. Nucleic Acids Research, 32, D277–D280.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  13. Therneau, T. (2014). A package for survival analysis in S. R package version 2.37-7, http://CRAN.R-project.org/package=survival.

  14. Gyorffy, B., Surowiak, P., Budczies, J., & Lanczky, A. (2013). Online survival analysis software to assess the prognostic value of biomarkers using transcriptomic data in non-small-cell lung cancer. PLoS One, 8, e82241.

    Article  PubMed Central  PubMed  Google Scholar 

  15. Gregory, S. G., Barlow, K. F., McLay, K. E., et al. (2006). The DNA sequence and biological annotation of human chromosome 1. Nature, 441, 315–321.

    Article  CAS  PubMed  Google Scholar 

  16. Nilsson, J., Yekezare, M., Minshull, J., & Pines, J. (2008). The APC/C maintains the spindle assembly checkpoint by targeting Cdc20 for destruction. Nature Cell Biology, 10, 1411–1420.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Kato, T., Daigo, Y., Aragaki, M., Ishikawa, K., Sato, M., & Kaji, M. (2012). Overexpression of CDC20 predicts poor prognosis in primary non-small cell lung cancer patients. Journal of Surgical Oncology, 106, 423–430.

    Article  CAS  PubMed  Google Scholar 

  18. Bond, J., Roberts, E., Mochida, G. H., et al. (2002). ASPM is a major determinant of cerebral cortical size. Nature Genetics, 32, 316–320.

    Article  CAS  PubMed  Google Scholar 

  19. Higgins, J., Midgley, C., Bergh, A. M., et al. (2010). Human ASPM participates in spindle organisation, spindle orientation and cytokinesis. BMC Cell Biology, 11, 85.

    Article  PubMed Central  PubMed  Google Scholar 

  20. Finger, E. C., Turley, R. S., Dong, M., How, T., Fields, T. A., & Blobe, G. C. (2008). TbetaRIII suppresses non-small cell lung cancer invasiveness and tumorigenicity. Carcinogenesis, 29, 528–535.

    Article  CAS  PubMed  Google Scholar 

  21. Wei, S., Wang, H., Lu, C., et al. (2014). The activating transcription factor 3 protein suppresses the oncogenic function of mutant p53 proteins. Journal of Biological Chemistry, 289, 8947–8959.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  22. Samten, B. (2013). CD52 as both a marker and an effector molecule of T cells with regulatory action: identification of novel regulatory T cells. Cellular and molecular immunology, 10, 456–458.

    Article  PubMed Central  PubMed  Google Scholar 

  23. Shen, B., Yu, H., Hao, X., Qu, L., Cai, X., & Li, N. (2013). Impact of antimouse CD52 monoclonal antibody on graft’s gammadelta intraepithelial lymphocytes after orthotopic small bowel transplantation in mice. Transplantation, 95, 663–670.

    Article  CAS  PubMed  Google Scholar 

  24. Shipman, M., Lubick, K., Fouchard, D., et al. (2012). Proteomic and systems biology analysis of monocytes exposed to securinine, a GABA(A) receptor antagonist and immune adjuvant. PLoS One, 7, e41278.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  25. Cha, I. S., Castillo, C. S., Nho, S. W., Hikima, J., Aoki, T., & Jung, T. S. (2011). Innate immune response in the hemolymph of an ascidian, Halocynthia roretzi, showing soft tunic syndrome, using label-free quantitative proteomics. Developmental and Comparative Immunology, 35, 809–816.

    Article  CAS  PubMed  Google Scholar 

  26. Park, I. H., Park, S. J., Cho, J. S., et al. (2012). Increased expression of intelectin-1 in nasal polyps. American Journal of Rhinology & Allergy, 26, 274–277.

    Article  Google Scholar 

  27. Park, J. C., Chae, Y. K., Son, C. H., et al. (2008). Epigenetic silencing of human T (brachyury homologue) gene in non-small-cell lung cancer. Biochemical and Biophysical Research Communications, 365, 221–226.

    Article  CAS  PubMed  Google Scholar 

  28. Chong, I. W., Chang, M. Y., Chang, H. C., et al. (2006). Great potential of a panel of multiple hMTH1, SPD, ITGA11 and COL11A1 markers for diagnosis of patients with non-small cell lung cancer. Oncology Reports, 16, 981–988.

    CAS  PubMed  Google Scholar 

  29. Roche, J., Nasarre, P., Gemmill, R., et al. (2013). Global decrease of histone H3K27 acetylation in ZEB1-induced epithelial to mesenchymal transition in lung cancer cells. Cancers (Basel), 5, 334–356.

    Article  CAS  Google Scholar 

  30. Jo, U., Park, K. H., Whang, Y. M., et al. (2014). EGFR endocytosis is a novel therapeutic target in lung cancer with wild-type EGFR. Oncotarget, 5, 1265–1278.

    PubMed Central  PubMed  Google Scholar 

  31. Sundarraj, S., Kannan, S., Thangam, R., & Gunasekaran, P. (2012). Effects of the inhibition of cytosolic phospholipase A(2)alpha in non-small cell lung cancer cells. Journal of Cancer Research and Clinical Oncology, 138, 827–835.

    Article  CAS  PubMed  Google Scholar 

  32. Salama, I., Malone, P. S., Mihaimeed, F., & Jones, J. L. (2008). A review of the S100 proteins in cancer. European Journal of Surgical Oncology, 34, 357–364.

    Article  CAS  PubMed  Google Scholar 

  33. Naz, S., Bashir, M., Ranganathan, P., Bodapati, P., Santosh, V., & Kondaiah, P. (2014). Protumorigenic actions of S100A2 involve regulation of PI3/Akt signaling and functional interaction with Smad3. Carcinogenesis, 35, 14–23.

    Article  CAS  PubMed  Google Scholar 

  34. Tsuta, K., Tanabe, Y., Yoshida, A., et al. (2011). Utility of 10 immunohistochemical markers including novel markers (desmocollin-3, glypican 3, S100A2, S100A7, and Sox-2) for differential diagnosis of squamous cell carcinoma from adenocarcinoma of the Lung. Journal of Thoracic Oncology, 6, 1190–1199.

    Article  PubMed  Google Scholar 

  35. Vermeij, W. P., & Backendorf, C. (2010). Skin cornification proteins provide global link between ROS detoxification and cell migration during wound healing. PLoS One, 5, e11957.

    Article  PubMed Central  PubMed  Google Scholar 

  36. Woenckhaus, M., Klein-Hitpass, L., Grepmeier, U., et al. (2006). Smoking and cancer-related gene expression in bronchial epithelium and non-small-cell lung cancers. Journal of Pathology, 210, 192–204.

    Article  CAS  PubMed  Google Scholar 

  37. Fujii, S. I., Shimizu, K., Okamoto, Y., et al. (2013). NKT cells as an ideal Anti-tumor immunotherapeutic. Frontiers in Immunology, 4, 409.

    Article  PubMed Central  PubMed  Google Scholar 

  38. Declerck, S., & Vansteenkiste, J. (2014). Immunotherapy for lung cancer: ongoing clinical trials. Future Oncology, 10, 91–105.

    Article  CAS  PubMed  Google Scholar 

  39. Mollbrink, A., Jawad, R., Vlamis-Gardikas, A., et al. (2014). Expression of thioredoxins and glutaredoxins in human hepatocellular carcinoma: correlation to cell proliferation, tumor size and metabolic syndrome. International Journal of Immunopathology and Pharmacology, 27, 169–183.

    CAS  PubMed  Google Scholar 

  40. Su, D. M., Zhang, Q., Wang, X., et al. (2009). Two types of human malignant melanoma cell lines revealed by expression patterns of mitochondrial and survival-apoptosis genes: implications for malignant melanoma therapy. Molecular Cancer Therapeutics, 8, 1292–1304.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  41. Salio, M., Silk, J. D., Jones, E. Y., & Cerundolo, V. (2014). Biology of CD1- and MR1-restricted T cells. Annual Review of Immunology, 32, 323–366.

    Article  CAS  PubMed  Google Scholar 

  42. Umemura, S., Mimaki, S., Makinoshima, H., et al. (2014). Therapeutic priority of the PI3K/AKT/mTOR pathway in small cell lung cancers as revealed by a comprehensive genomic analysis. Journal of Thoracic Oncology, 9, 1324–1331.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  43. Zitzmann, K., Vlotides, G., Brand, S., et al. (2012). Perifosine-mediated Akt inhibition in neuroendocrine tumor cells: role of specific Akt isoforms. Endocrine-Related Cancer, 19, 423–434.

    Article  CAS  PubMed  Google Scholar 

  44. Ohashi, K., Sequist, L. V., Arcila, M. E., et al. (2013). Characteristics of lung cancers harboring NRAS mutations. Clinical Cancer Research, 19, 2584–2591.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  45. Kim, B. H., Shenoy, A. R., Kumar, P., Das, R., Tiwari, S., & MacMicking, J. D. (2011). A family of IFN-gamma-inducible 65-kD GTPases protects against bacterial infection. Science, 332, 717–721.

    Article  CAS  PubMed  Google Scholar 

  46. Aoyama, D., Hashimoto, N., Sakamoto, K., et al. (2013). Involvement of TGFbeta-induced phosphorylation of the PTEN C-terminus on TGFbeta-induced acquisition of malignant phenotypes in lung cancer cells. PLoS One, 8, e81133.

    Article  PubMed Central  PubMed  Google Scholar 

  47. Hill, K. S., Erdogan, E., Khoor, A., et al. (2013). Protein kinase Calpha suppresses Kras-mediated lung tumor formation through activation of a p38 MAPK-TGFbeta signaling axis. Oncogene. doi:10.1038/onc.2013.147.

    Google Scholar 

Download references

Acknowledgments

The work was supported by Zhongshan Distinguished Professor Grant (XDW), The National Nature Science Foundation of China (91230204, 81270099, 81320108001, 81270131, 81300010), The Shanghai Committee of Science and Technology (12JC1402200, 12431900207, 11410708600, 14431905100), Zhejiang Provincial Natural Science Foundation (Z2080988), Zhejiang Provincial Science Technology Department Foundation (2010C14011), and Ministry of Education, Academic Special Science and Research Foundation for PhD Education (20130071110043).

Conflict of interest

The authors declare that they have no competing interests.

Authors’ contributions

YZ contributed the study design and performance, collection of information, analysis, mining, and interpretation of data and writing of the manuscript; JW and LMB contributed the data analyses; HYW contributed the prognosis prediction analyses; XDW contributed the study design and data mining, and preparation of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Xiangdong Wang.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Table 1

(XLSX 71 kb)

Supplementary Table 2

(XLSX 10 kb)

Supplementary Table 3

(XLSX 113 kb)

Supplementary Table 4

(XLSX 73 kb)

Supplementary Table 5

(XLSX 89 kb)

Supplementary Table 6

(XLSX 14 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Wang, H., Wang, J. et al. Global analysis of chromosome 1 genes among patients with lung adenocarcinoma, squamous carcinoma, large-cell carcinoma, small-cell carcinoma, or non-cancer. Cancer Metastasis Rev 34, 249–264 (2015). https://doi.org/10.1007/s10555-015-9558-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10555-015-9558-0

Keywords

Navigation