Skip to main content
SpringerLink
Log in

Evaluation of Serum Paired MicroRNA Ratios for Differential Diagnosis of Non-Small Cell Lung Cancer and Benign Pulmonary Diseases

  • Original Research Article
  • Published:
Molecular Diagnosis & Therapy Aims and scope Submit manuscript

Abstract

Background and Objective

To clarify whether there are different expressions between lung cancer and benign pulmonary diseases, we studied seven microRNAs (miRNAs) in serum from patients with non-small cell lung cancer (NSCLC), benign pulmonary nodules and four pulmonary inflammation diseases.

Methods

We detected the expression of miRNAs using quantitative reverse transcriptase–polymerase chain reaction (qRT–PCR).

Results

We found that five miRNA ratios—miR-15b-5p/miR-146b-3p, miR-20a-5p/miR-146b-3p, miR-19a-3p/miR-146b-3p, miR-92a-3p/miR-146b-3p, and miR-16-5p/miR-146b-3p—show higher expression in the NSCLC group than the benign pulmonary nodule group, and 13 ratios of miRNAs were significantly upregulated in the NSCLC group compared with the pulmonary inflammation diseases group. Receiver operating characteristic (ROC) curve analysis was performed. For NSCLC and benign pulmonary nodules, the sensitivity and specificity were 0.70 and 0.90, respectively. For NSCLC and pulmonary inflammation diseases, the sensitivity and specificity were 0.81 and 0.71, respectively.

Conclusion

The ratios of miRNAs can be used as potential non-invasive biomarkers for diagnosis of early-stage NSCLC and benign pulmonary diseases.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Crino L, Weder W, van Meerbeeck J, Felip E. Early stage and locally advanced (non-metastatic) non-small-cell lung cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2010;21(Suppl 5):v103–15. https://doi.org/10.1093/annonc/mdq207.

    Article  PubMed  Google Scholar 

  2. Howlader N, Noone AM, Krapcho M, Neyman N, Aminou R, Waldron W, et al. SEER Cancer Statistics Review, 1975-2009 (Vintage 2009 Populations) [based on November 2011 SEER data submission, posted to the SEER website April 2012]. Bethesda: National Cancer Institute; 2012. https://seer.cancer.gov/csr/1975_2009_pops09/. Accessed 1 May 2017.

  3. Chen X, Ba Y, Ma L, Cai X, Yin Y, Wang K, et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell Res. 2008;18(10):997–1006. https://doi.org/10.1038/cr.2008.282.

    Article  PubMed  CAS  Google Scholar 

  4. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA. 2008;105(30):10513–8. https://doi.org/10.1073/pnas.0804549105.

    Article  PubMed  Google Scholar 

  5. Turchinovich A, Weiz L, Langheinz A, Burwinkel B. Characterization of extracellular circulating microRNA. Nucleic Acids Res. 2011;39(16):7223–33. https://doi.org/10.1093/nar/gkr254.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Wozniak MB, Scelo G, Muller DC, Mukeria A, Zaridze D, Brennan P. Circulating MicroRNAs as non-invasive biomarkers for early detection of non-small-cell lung cancer. PLoS One. 2015;10(5):e0125026. https://doi.org/10.1371/journal.pone.0125026.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Boeri M, Verri C, Conte D, Roz L, Modena P, Facchinetti F, et al. MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer. Proc Natl Acad Sci USA. 2011;108(9):3713–8. https://doi.org/10.1073/pnas.1100048108.

    Article  PubMed  Google Scholar 

  8. Sozzi G, Boeri M, Rossi M, Verri C, Suatoni P, Bravi F, et al. Clinical utility of a plasma-based miRNA signature classifier within computed tomography lung cancer screening: a correlative MILD trial study. J Clin Oncol. 2014;32(8):768–73. https://doi.org/10.1200/jco.2013.50.4357.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fan L, Qi H, Teng J, Su B, Chen H, Wang C, et al. Identification of serum miRNAs by nano-quantum dots microarray as diagnostic biomarkers for early detection of non-small cell lung cancer. Tumour Biol. 2016;37(6):7777–84. https://doi.org/10.1007/s13277-015-4608-3.

    Article  PubMed  CAS  Google Scholar 

  10. Le CH, Ko YC, Cheng LS, Lin YC, Lin HJ, Huang MS, et al. The heterogeneity in risk factors of lung cancer and the difference of histologic distribution between genders in Taiwan. Cancer Causes Control. 2001;12(4):289–300.

    Article  PubMed  CAS  Google Scholar 

  11. Rosenberger A, Bickeboller H, McCormack V, Brenner DR, Duell EJ, Tjonneland A, et al. Asthma and lung cancer risk: a systematic investigation by the International Lung Cancer Consortium. Carcinogenesis. 2012;33(3):587–97. https://doi.org/10.1093/carcin/bgr307.

    Article  PubMed  CAS  Google Scholar 

  12. Khoury S, Tran N. Circulating microRNAs: potential biomarkers for common malignancies. Biomark Med. 2015;9(2):131–51. https://doi.org/10.2217/bmm.14.102.

    Article  PubMed  CAS  Google Scholar 

  13. Ost D, Fein AM, Feinsilver SH. Clinical practice. The solitary pulmonary nodule. N Engl J Med. 2003;348(25):2535–42. https://doi.org/10.1056/NEJMcp012290.

    Article  PubMed  Google Scholar 

  14. Kahn N, Kuner R, Eberhardt R, Meister M, Muley T, Winteroll S, et al. Gene expression analysis of endobronchial epithelial lining fluid in the evaluation of indeterminate pulmonary nodules. J Thorac Cardiovasc Surg. 2009;138(2):474–9. https://doi.org/10.1016/j.jtcvs.2009.04.024.

    Article  PubMed  CAS  Google Scholar 

  15. Li CR, Li YZ, Li YM, Zheng YS. Dynamic and contrast enhanced CT imaging of lung carcinoma, pulmonary tuberculoma, and inflammatory pseudotumor. Eur Rev Med Pharmacol Sci. 2017;21(7):1588–92.

    PubMed  Google Scholar 

  16. Basu S, Saboury B, Werner T, Alavi A. Clinical utility of FDG-PET and PET/CT in non-malignant thoracic disorders. Mol Imaging Biol. 2011;13(6):1051–60. https://doi.org/10.1007/s11307-010-0459-x.

    Article  PubMed  Google Scholar 

  17. Miyashita N, Akaike H, Teranishi H, Nakano T, Ouchi K, Okimoto N. Chest computed tomography for the diagnosis of Mycoplasma pneumoniae infection. Respirology. 2014;19(1):144–5. https://doi.org/10.1111/resp.12218.

    Article  PubMed  Google Scholar 

  18. Yeom SK, Kim HJ, Byun JH, Kim AY, Lee MG, Ha HK. Abdominal aspergillosis: CT findings. Eur J Radiol. 2011;77(3):478–82. https://doi.org/10.1016/j.ejrad.2009.08.016.

    Article  PubMed  Google Scholar 

  19. Kuper H, Adami HO, Trichopoulos D. Infections as a major preventable cause of human cancer. J Intern Med. 2000;248(3):171–83.

    Article  PubMed  CAS  Google Scholar 

  20. Wahidi MM, Herth FJ, Ernst A. State of the art: interventional pulmonology. Chest. 2007;131(1):261–74. https://doi.org/10.1378/chest.06-0975.

    Article  PubMed  Google Scholar 

  21. Aberle DR, Adams AM, Berg CD, Black WC, Clapp JD, Fagerstrom RM, et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med. 2011;365(5):395–409. https://doi.org/10.1056/NEJMoa1102873.

    Article  PubMed  Google Scholar 

  22. Welch HG, Woloshin S, Schwartz LM, Gordis L, Gotzsche PC, Harris R, et al. Overstating the evidence for lung cancer screening: the International Early Lung Cancer Action Program (I-ELCAP) study. Arch Intern Med. 2007;167(21):2289–95. https://doi.org/10.1001/archinte.167.21.2289.

    Article  PubMed  Google Scholar 

  23. Reich JM. A critical appraisal of overdiagnosis: estimates of its magnitude and implications for lung cancer screening. Thorax. 2008;63(4):377–83. https://doi.org/10.1136/thx.2007.079673.

    Article  PubMed  CAS  Google Scholar 

  24. Beigelman-Aubry C, Hill C, Grenier PA. Management of an incidentally discovered pulmonary nodule. Eur Radiol. 2007;17(2):449–66. https://doi.org/10.1007/s00330-006-0399-7.

    Article  PubMed  Google Scholar 

  25. Belinsky SA. Gene-promoter hypermethylation as a biomarker in lung cancer. Nat Rev Cancer. 2004;4(9):707–17. https://doi.org/10.1038/nrc1432.

    Article  PubMed  CAS  Google Scholar 

  26. Van Pottelberge GR, Mestdagh P, Bracke KR, Thas O, van Durme YM, Joos GF, et al. MicroRNA expression in induced sputum of smokers and patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2011;183(7):898–906. https://doi.org/10.1164/rccm.201002-0304OC.

    Article  PubMed  Google Scholar 

  27. Lewis A, Riddoch-Contreras J, Natanek SA, Donaldson A, Man WD, Moxham J, et al. Downregulation of the serum response factor/miR-1 axis in the quadriceps of patients with COPD. Thorax. 2012;67(1):26–34. https://doi.org/10.1136/thoraxjnl-2011-200309.

    Article  PubMed  Google Scholar 

  28. Sato T, Liu X, Nelson A, Nakanishi M, Kanaji N, Wang X, et al. Reduced miR-146a increases prostaglandin E(2)in chronic obstructive pulmonary disease fibroblasts. Am J Respir Crit Care Med. 2010;182(8):1020–9. https://doi.org/10.1164/rccm.201001-0055OC.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Ezzie ME, Crawford M, Cho JH, Orellana R, Zhang S, Gelinas R, et al. Gene expression networks in COPD: microRNA and mRNA regulation. Thorax. 2012;67(2):122–31. https://doi.org/10.1136/thoraxjnl-2011-200089.

    Article  PubMed  Google Scholar 

  30. Wang K, Yuan Y, Cho JH, McClarty S, Baxter D, Galas DJ. Comparing the MicroRNA spectrum between serum and plasma. PLoS One. 2012;7(7):e41561. https://doi.org/10.1371/journal.pone.0041561.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  31. Zampetaki A, Mayr M. Analytical challenges and technical limitations in assessing circulating miRNAs. Thromb Haemost. 2012;108(4):592–8. https://doi.org/10.1160/TH12-02-0097.

    Article  PubMed  CAS  Google Scholar 

  32. Kim DJ, Linnstaedt S, Palma J, Park JC, Ntrivalas E, Kwak-Kim JY, et al. Plasma components affect accuracy of circulating cancer-related microRNA quantitation. J Mol Diagn. 2012;14(1):71–80. https://doi.org/10.1016/j.jmoldx.2011.09.002.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. Cheng HH, Yi HS, Kim Y, Kroh EM, Chien JW, Eaton KD, et al. Plasma processing conditions substantially influence circulating microRNA biomarker levels. PLoS One. 2013;8(6):e64795. https://doi.org/10.1371/journal.pone.0064795.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  34. Molina-Pinelo S, Suarez R, Pastor MD, Nogal A, Marquez-Martin E, Martin-Juan J, et al. Association between the miRNA signatures in plasma and bronchoalveolar fluid in respiratory pathologies. Dis Markers. 2012;32(4):221–30. https://doi.org/10.3233/DMA-2011-0882.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

Download references

Author information

Author notes

  1. Lihong Fan and Jie Sha contributed equally to this work.

Authors and Affiliations

  1. Department of Respiration Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China

    Lihong Fan, Changhui Wang, Qing Xia & Hao Chen

  2. Department of Respiration Medicine, Shanghai Tenth People’s Hospital, Nanjing Medical University, Nanjing, China

    Jie Sha

  3. School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, China

    Junliang Teng

  4. Department of Nuclear Medicine, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China

    Dan Li

  5. Central Laboratory, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Road, Shanghai, 200433, China

    Bo Su

  6. Department of Oncology, Shanghai Pulmonary Hospital, Tongji University School of Medicine, 507 Zhengmin Road, Shanghai, 200433, China

    Huiwei Qi

Authors
  1. Lihong Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jie Sha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junliang Teng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Dan Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Changhui Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Qing Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hao Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bo Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Huiwei Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Bo Su or Huiwei Qi.

Ethics declarations

Conflict of interest

All authors (LF, JS, JT, DL, CW, QX, HC, BS and HQ) declare that they have no conflicts of interest.

Funding

This study was funded by the Fundamental Research Funds for the Central Universities (no. 20153590) and the Chinese National Natural Science Foundation (nos. 81703847, 81473469).

Ethical Standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fan, L., Sha, J., Teng, J. et al. Evaluation of Serum Paired MicroRNA Ratios for Differential Diagnosis of Non-Small Cell Lung Cancer and Benign Pulmonary Diseases. Mol Diagn Ther 22, 493–502 (2018). https://doi.org/10.1007/s40291-018-0341-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40291-018-0341-0

Search

Navigation