Elsevier

Lung Cancer

Volume 74, Issue 1, October 2011, Pages 41-47
Lung Cancer

Specific peripheral miRNA profiles for distinguishing lung cancer from COPD

https://doi.org/10.1016/j.lungcan.2011.02.003Get rights and content

Abstract

Recently we reported differential miRNA signatures in blood cells of lung cancer patients and healthy controls. With the present study we wanted to investigate if miRNA blood signatures are also suited to differentiate lung cancer patients from COPD patients. We compared the expression of 863 human miRNAs in blood cells of lung cancer patients, COPD patients, and healthy controls. The miRNA pattern from patients with lung cancer and COPD were more similar to each other than to the healthy controls. However, we were able to discriminate lung cancer patients and COPD patients with 90.4% accuracy, 89.2% specificity, and 91.7% sensitivity. In total, 140 miRNAs were significant for the comparison COPD and controls, 61 miRNAs were significant for the comparison lung cancer and controls, and 14 miRNAs were significant for the comparison lung cancer and COPD. Screening target databases yielded over 400 putative targets for those 14 miRNAs. The predicted mRNA targets of three of the 14 miRNAs were significantly up-regulated in PBMCs of lung cancer patients compared to patients with non-malignant lung diseases. In conclusion, we showed that blood miRNA signatures are suitable to distinguish lung cancer from COPD.

Introduction

Worldwide more than one million people die each year from lung cancer making it the leading cause of cancer related deaths [1]. The five-year survival rate is among the lowest of all cancers. A major challenge is the prevailing lack of specific biomarkers for detection and monitoring of lung cancer. While single markers show a rather low sensitivity and specificity for the identification of lung cancer and other cancers, complex marker signatures often reach a significantly higher degree of accuracy. Most recently, microRNA (miRNA) expression profiles have been proposed as potential biomarkers for cancer diagnosis and treatment monitoring [2]. MicroRNAs are small (17–24 nt) non-coding RNA transcripts, involved in physiological and pathophysiological processes including cancer development through the regulation of gene expression [3], [4].

Based on the differential expression of miRNAs in tumors, miRNA expression signatures allow classification of many cancers, including lung cancer [5]. First attempts were made to differentiate specific subtypes of lung cancer such as primary lung cancer from metastatic lung tumors by miRNA signatures [6]. While the overwhelming majority of published miRNA signatures has been established on tumor cells, recent studies have identified specific miRNA signatures in sera and peripheral blood cells from cancer patients [7], [8], [9], [10], [11]. The remarkable stability of miRNAs makes miRNA signatures in body fluids especially intriguing for future minimally invasive diagnostics [10], [12]. Recently, we identified a microRNA expression signature in blood cells that allows for differentiation between lung cancer patients and healthy individuals [13]. To further evaluate the utility of blood based miRNA signatures for diagnostic purposes, it is important to compare cancer not only to healthy controls but also to other non-cancer diseases of the same organ. Here, we analyzed Chronic Obstructive Pulmonary Disease (COPD), a common pulmonary affliction encompassing chronic obstructive bronchitis and lung emphysema [14]. COPD is a global burden affecting 10–15% of adults older than 40 years [15]. COPD is not only a common co-morbidity but also precedes lung cancer in 50–90% of cases [16]. We compared the expression of 863 miRNAs in blood cells of lung cancer patients, patients suffering from COPD, and healthy individuals to further our knowledge of miRNA signatures in blood cells of lung cancer and COPD patients. In detail, we address the following questions: How similar are miRNA signatures among the aforementioned three groups? Can lung cancer be distinguished from COPD by blood based miRNA signatures? Which miRNAs contribute most to a separation of lung cancer from COPD? What are the predicted target genes of miRNAs differentially expressed in blood cells of patients with lung cancer and COPD. Overall, the study shows that blood miRNA signatures are suitable to distinguish lung cancer from COPD. Furthermore, we identified significant deregulated miRNAs and analyzed their putative target genes by database screening.

Section snippets

Materials and methods

See Online Data Supplement for additional methologic details.

Results

Using the Geniom Real Time Analyzer Platform, we analyzed the expression of the 863 human miRNAs annotated in miRBase version 12.0. In total, we screened the miRNA expression in blood cells from 71 different individuals, including 28 lung cancer patients, 24 COPD patients, and 19 healthy controls. The group of lung cancer patients included both patients without COPD (n = 15) and with COPD (n = 13).

Intensity values of all analyzed miRNAs and samples were subjected to quantile normalization prior to

Discussion

Here, we compared miRNA expression profiles of peripheral blood cells in patients with lung cancer, patients with COPD, and healthy individuals. As expected, the miRNA signatures of lung cancer patients and COPD patients were more similar to each other than to the signature of healthy controls as revealed by principle components analysis. However, the miRNA signatures of blood cells were still so different between lung cancer patients and COPD patients as to permit separation between these

Conclusion

In conclusion, we showed for the first time that lung cancer patients are distinguishable from COPD patients by their peripheral miRNA expression profile with high accuracy. Therefore, our proof-of-principle study strengthens the hypothesis that blood based miRNA signatures might be potential cancer biomarker. In combination with imaging techniques blood based miRNA signatures might contribute to an earlier lung cancer detection and thus improve the survival rates. Prospective studies will

Conflict of interest

Andreas Keller and Anne Borries are employees of febit biomed GmbH.

Acknowledgements

We acknowledge the technical assistance of Hannah Schroers and Pamela Haeberle. We thank Dr. Jack Leonard for carefully proof-reading and correcting the manuscript.

Funding: This work was supported by funding of the German Ministry of Research Education (BMBF) under contract 01EX0806, the Hedwig-Stalter foundation, Deutsche Forschungsgemeinschaft (DFG, LE2783/1-1), and HOMFOR 2010.

References (38)

  • S. Vorwerk et al.

    Microfluidic-based enzymatic on-chip labeling of miRNAs

    Nat Biotechnol

    (2008)
  • Y. Benjamini et al.

    Controlling the false discovery rate in behavior genetics research

    Behav Brain Res

    (2001)
  • D.M. Parkin et al.

    Global cancer statistics, 2002

    CA Cancer J Clin

    (2005)
  • W. Roa et al.

    Identification of a new microRNA expression profile as a potential cancer screening tool

    Clin Invest Med

    (2010)
  • S. Sassen et al.

    MicroRNA: implications for cancer

    Virchows Arch

    (2008)
  • A. Esquela-Kerscher et al.

    Oncomirs—microRNAs with a role in cancer

    Nat Rev Cancer

    (2006)
  • J. Lu et al.

    MicroRNA expression profiles classify human cancers

    Nature

    (2005)
  • I. Barshack et al.

    MicroRNA expression differentiates between primary lung tumors and metastases to the lung

    Pathol Res Pract

    (2010)
  • K. Wang et al.

    Circulating microRNAs, potential biomarkers for drug-induced liver injury

    Proc Natl Acad Sci USA

    (2009)
  • J. Wang et al.

    MicroRNAs in plasma of pancreatic ductal adenocarcinoma patients as novel blood-based biomarkers of disease

    Cancer Prev Res (Phila Pa)

    (2009)
  • M.A. Cortez et al.

    MicroRNA identification in plasma and serum: a new tool to diagnose and monitor diseases

    Expert Opin Biol Ther

    (2009)
  • S. Gilad et al.

    Serum microRNAs are promising novel biomarkers

    PLoS One

    (2008)
  • L.J. Chin et al.

    A truth serum for cancer—microRNAs have major potential as cancer biomarkers

    Cell Res

    (2008)
  • X. Chen et al.

    Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases

    Cell Res

    (2008)
  • A. Keller et al.

    miRNAs in lung cancer—studying complex fingerprints in patient's blood cells by microarray experiments

    BMC Cancer

    (2009)
  • C.M. Tammemagi et al.

    Impact of comorbidity on lung cancer survival

    Int J Cancer

    (2003)
  • Y.R. van Gestel et al.

    COPD and cancer mortality: the influence of statins

    Thorax

    (2009)
  • R.P. Young et al.

    COPD prevalence is increased in lung cancer, independent of age, sex and smoking history

    Eur Respir J

    (2009)
  • A. Keller et al.

    Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls

    PLoS One

    (2009)
  • Cited by (91)

    • Circulating MicroRNAs as Biomarkers and Diagnosis Tool for Diseases

      2023, MicroRNA in Regenerative Medicine, Second Edition
    • Genome-wide MicroRNA Expression Profiles in COPD: Early Predictors for Cancer Development

      2018, Genomics, Proteomics and Bioinformatics
      Citation Excerpt :

      Some miRNAs are not linked to one single cancer type, but may be dysregulated in multiple cancer types or even in diseases in general, such as miR-144 [23]. A substantial fraction of miRNA lung biomarker studies rely on case–control set-ups where diseased patients are compared with a control cohort of unaffected individuals or with patients suffering from diseases with similar symptoms [24]. Being aware of both the promises and challenges of miRNAs for a future diagnostic applications in general [25] and for lung cancer specifically [26], we asked whether blood-based miRNA signatures of COPD patients who develop cancer within a given time window, are different from COPD patients who do not develop cancer.

    • Bootstrapping integrative hypothesis test for identifying biomarkers that differentiates lung cancer and chronic obstructive pulmonary disease

      2017, Neurocomputing
      Citation Excerpt :

      Some discarded miRNAs with relatively smaller mean IHT ranks but big standard deviation were also shown in Table 2. Fourteen of the top-15 miRNAs listed in Table 2 were also included in Table 3 that consists of the significant miRNAs for the differentiation between lung cancer and COPD found in [12]. In other words, the findings of [12] are confirmed here independently by a very different method, which may enhance attentions to these findings.

    View all citing articles on Scopus
    1

    Both authors equally contributed to this work.

    View full text