Abstract
Introduction
Recent studies provide a convincing support that the presence of cancer cells in the body leads to the alteration of volatile organic compounds (VOCs) emanating from biological samples, particularly of those closely related with tumoral tissues. Thus, a great interest emerged for the study of cancer volatilome and subsequent attempts to confirm VOCs as potential diagnostic biomarkers.
Objectives
The aim of this study was to determine the volatile metabolomic signature of bladder cancer (BC) cell lines and provide an in vitro proof-of-principle that VOCs emanated into the extracellular medium may discriminate BC cells from normal bladder epithelial cells.
Methods
VOCs in the culture media of three BC cell lines (Scaber, J82, 5637) and one normal bladder cell line (SV-HUC-1) were extracted by headspace-solid phase microextraction and analysed by gas chromatography-mass spectrometry (HS-SPME/GC–MS). Two different pH (pH 2 and 7) were used for VOCs extraction to infer the best pH to be used in in vitro metabolomic studies.
Results
Multivariate analysis revealed a panel of volatile metabolites that discriminated cancerous from normal bladder cells, at both pHs, although a higher number of discriminative VOCs was obtained at neutral pH. Most of the altered metabolites were ketones and alkanes, which were generally increased in BC compared to normal cells, and alcohols, which were significantly decreased in BC cells. Among them, three metabolites, namely 2-pentadecanone, dodecanal and γ-dodecalactone (the latter only tentatively identified), stood out as particularly important metabolites and promising volatile biomarkers for BC detection. Furthermore, our results also showed the potential of VOCs in discriminating BC cell lines according to tumour grade and histological subtype.
Conclusions
We demonstrate that a GC–MS metabolomics-based approach for analysis of VOCs is a valuable strategy for identifying new and specific biomarkers that may improve BC diagnosis. Future studies should entail the validation of volatile signature found for BC cell lines in biofluids from BC patients.
Similar content being viewed by others
Abbreviations
- AUC:
-
Area under the curve
- BC:
-
Bladder cancer
- ES:
-
Effect size
- GC:
-
Gas chromatography
- GC-SQ:
-
Gas chromatography-single quadrupole
- HMDB:
-
Human metabolome database
- HS-SPME:
-
Headspace solid-phase microextraction
- MS:
-
Mass spectrometry
- OPLS-DA:
-
Orthogonal partial least squares-discriminant analysis
- PCA:
-
Principal component analysis
- PLS-DA:
-
Partial least squares-discriminant analysis
- QCs:
-
Quality controls
- RI:
-
Retention index
- SCC:
-
Squamous cell carcinoma
- TA:
-
Total area
- TCC:
-
Transitional cell carcinoma
- VOCs:
-
Volatile organic compounds
- VIP:
-
Variable importance in projection
References
Abaffy, T., Duncan, R., Riemer, D. D., Tietje, O., Elgart, G., Milikowski, C., et al. (2010). Differential volatile signatures from skin, naevi and melanoma: A novel approach to detect a pathological process. PLoS ONE, 5(11), e13813. https://doi.org/10.1371/journal.pone.0013813.
Aickin, M., & Gensler, H. (1996). Adjusting for multiple testing when reporting research results: The Bonferroni vs Holm methods. American Journal of Public Health, 86(5), 726–728.
Altomare, D. F., Di Lena, M., Porcelli, F., Trizio, L., Travaglio, E., Tutino, M., et al. (2013). Exhaled volatile organic compounds identify patients with colorectal cancer. British Journal of Surgery, 100(1), 144–150. https://doi.org/10.1002/bjs.8942.
Al-Zoughbi, W., Huang, J., Paramasivan, G. S., Till, H., Pichler, M., Guertl-Lackner, B., et al. (2014). Tumor macroenvironment and metabolism. Seminars in Oncology, 41(2), 281–295. https://doi.org/10.1053/j.seminoncol.2014.02.005.
Bajtarevic, A., Ager, C., Pienz, M., Klieber, M., Schwarz, K., Ligor, M., et al. (2009). Noninvasive detection of lung cancer by analysis of exhaled breath. BMC Cancer, 9, 348. https://doi.org/10.1186/1471-2407-9-348.
Bartolazzi, A., Santonico, M., Pennazza, G., Martinelli, E., Paolesse, R., D’Amico, A., et al. (2010). A sensor array and GC study about VOCs and cancer cells. Sensors and Actuators B: Chemical, 146(2), 483–488. https://doi.org/10.1016/j.snb.2009.11.046.
Berben, L., Sereika, S. M., & Engberg, S. (2012). Effect size estimation: Methods and examples. International Journal of Nursing Studies, 49(8), 1039–1047. https://doi.org/10.1016/j.ijnurstu.2012.01.015.
Burger, M., Catto, J. W., Dalbagni, G., Grossman, H. B., Herr, H., Karakiewicz, P., et al. (2013). Epidemiology and risk factors of urothelial bladder cancer. European Urology, 63(2), 234–241. https://doi.org/10.1016/j.eururo.2012.07.033.
Calenic, B. (2013). Volatile organic compounds expression in different cell types: An in vitro approach. International Journal of Clinical Toxicology, 1, 43–51.
Cauchi, M., Weber, C. M., Bolt, B. J., Spratt, P. B., Bessant, C., Turner, D. C., et al. (2016). Evaluation of gas chromatography mass spectrometry and pattern recognition for the identification of bladder cancer from urine headspace. Analytical Methods, 8(20), 4037–4046. https://doi.org/10.1039/C6AY00400H.
Chan, E. C., Pasikanti, K. K., Hong, Y., Ho, P. C., Mahendran, R., & Raman Nee Mani, L. et al. (2015). Metabonomic profiling of bladder cancer. Journal of Proteome Research, 14(2), 587–602. https://doi.org/10.1021/pr500966h.
Chen, X., Xu, F., Wang, Y., Pan, Y., Lu, D., Wang, P., et al. (2007). A study of the volatile organic compounds exhaled by lung cancer cells in vitro for breath diagnosis. Cancer, 110(4), 835–844. https://doi.org/10.1002/cncr.22844.
Davis, V. W., Bathe, O. F., Schiller, D. E., Slupsky, C. M., & Sawyer, M. B. (2011). Metabolomics and surgical oncology: Potential role for small molecule biomarkers. Journal of Surgical Oncology, 103(5), 451–459. https://doi.org/10.1002/jso.21831.
Di Lena, M., Porcelli, F., & Altomare, D. F. (2016). Volatile organic compounds as new biomarkers for colorectal cancer: A review. Colorectal Disease, 18(7), 654–663. https://doi.org/10.1111/codi.13271.
Erhart, S., Amann, A., Haberlandt, E., Edlinger, G., Schmid, A., Filipiak, W., et al. (2009). 3-Heptanone as a potential new marker for valproic acid therapy. Journal of Breath Research, 3(1), 016004. https://doi.org/10.1088/1752-7155/3/1/016004.
Ferreira, L. M. (2010). Cancer metabolism: The Warburg effect today. Experimental and Molecular Pathology, 89(3), 372–380. https://doi.org/10.1016/j.yexmp.2010.08.006.
Filipiak, W., Filipiak, A., Sponring, A., Schmid, T., Zelger, B., Ager, C., et al. (2014). Comparative analyses of volatile organic compounds (VOCs) from patients, tumors and transformed cell lines for the validation of lung cancer-derived breath markers. Journal of Breath Research, 8(2), 027111. https://doi.org/10.1088/1752-7155/8/2/027111.
Filipiak, W., Sponring, A., Filipiak, A., Ager, C., Schubert, J., Miekisch, W., et al. (2010). TD-GC-MS analysis of volatile metabolites of human lung cancer and normal cells in vitro. Cancer Epidemiology and Prevention Biomarkers, 19(1), 182–195. https://doi.org/10.1158/1055-9965.epi-09-0162.
Fuchs, P., Loeseken, C., Schubert, J. K., & Miekisch, W. (2010). Breath gas aldehydes as biomarkers of lung cancer. International Journal of Cancer, 126(11), 2663–2670. https://doi.org/10.1002/ijc.24970.
Hakim, M., Broza, Y. Y., Barash, O., Peled, N., Phillips, M., Amann, A., et al. (2012). Volatile organic compounds of lung cancer and possible biochemical pathways. Chemical Reviews, 112(11), 5949–5966. https://doi.org/10.1021/cr300174a.
Hakimi, A. A., Reznik, E., Lee, C. H., Creighton, C. J., Brannon, A. R., Luna, A., et al. (2016). An integrated metabolic atlas of clear cell renal cell carcinoma. Cancer Cell, 29(1), 104–116. https://doi.org/10.1016/j.ccell.2015.12.004.
Hanahan, D., & Weinberg, R. A. (2011). Hallmarks of cancer: The next generation. Cell, 144(5), 646–674. https://doi.org/10.1016/j.cell.2011.02.013.
Hu, Y. J., Qiu, Y. H., Chen, E. G., Ying, K. J., Yu, J., & Wang, P. (2010). Determination of volatile organic compounds in lung cancer cell lines and lung cancer tissue. Zhejiang Da Xue Xue Bao Yi Xue Ban, 39(3), 278–284.
Huang, Z., Lin, L., Gao, Y., Chen, Y., Yan, X., Xing, J., et al. (2011). Bladder cancer determination via two urinary metabolites: A biomarker pattern approach. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.M111.007922.
Jobu, K., Sun, C., Yoshioka, S., Yokota, J., Onogawa, M., Kawada, C., et al. (2012). Metabolomics study on the biochemical profiles of odor elements in urine of human with bladder cancer. Biological and Pharmaceutical Bulletin, 35(4), 639–642.
Khasawneh, J., Schulz, M. D., Walch, A., Rozman, J., Hrabe de Angelis, M., Klingenspor, M., et al. (2009). Inflammation and mitochondrial fatty acid beta-oxidation link obesity to early tumor promotion. Proceedings of the National Academy of Sciences USA, 106(9), 3354–3359, https://doi.org/10.1073/pnas.0802864106.
Ku, J. H., Godoy, G., Amiel, G. E., & Lerner, S. P. (2012). Urine survivin as a diagnostic biomarker for bladder cancer: A systematic review. BJU International, 110(5), 630–636. https://doi.org/10.1111/j.1464-410X.2011.10884.x.
Kwak, J., & Preti, G. (2011). Volatile disease biomarkers in breath: A critique. Current Pharmaceutical Biotechnology, 12(7), 1067–1074.
Lauridsen, M., Hansen, S. H., Jaroszewski, J. W., & Cornett, C. (2007). Human urine as test material in 1H NMR-based metabonomics: Recommendations for sample preparation and storage. Analytical Chemistry, 79(3), 1181–1186. https://doi.org/10.1021/ac061354x.
Leon, Z., Garcia-Canaveras, J. C., Donato, M. T., & Lahoz, A. (2013). Mammalian cell metabolomics: Experimental design and sample preparation. Electrophoresis, 34(19), 2762–2775. https://doi.org/10.1002/elps.201200605.
Ligor, M., Ligor, T., Bajtarevic, A., Ager, C., Pienz, M., Klieber, M., et al. (2009). Determination of volatile organic compounds in exhaled breath of patients with lung cancer using solid phase microextraction and gas chromatography mass spectrometry. Clinical Chemistry and Laboratory Medicine, 47(5), 550–560. https://doi.org/10.1515/cclm.2009.133.
Liu, Y. (2006). Fatty acid oxidation is a dominant bioenergetic pathway in prostate cancer. Prostate Cancer and Prostatic Diseases, 9(3), 230–234. https://doi.org/10.1038/sj.pcan.4500879.
McCulloch, M., Jezierski, T., Broffman, M., Hubbard, A., Turner, K., & Janecki, T. (2006). Diagnostic accuracy of canine scent detection in early- and late-stage lung and breast cancers. Integrative Cancer Therapies, 5(1), 30–39. https://doi.org/10.1177/1534735405285096.
Miremami, J., & Kyprianou, N. (2014). The promise of novel molecular markers in bladder cancer. International Journal of Molecular Sciences, 15(12), 23897–23908. https://doi.org/10.3390/ijms151223897.
Mochalski, P., Sponring, A., King, J., Unterkofler, K., Troppmair, J., & Amann, A. (2013). Release and uptake of volatile organic compounds by human hepatocellular carcinoma cells (HepG2) in vitro. Cancer Cell International, 13(1), 72. https://doi.org/10.1186/1475-2867-13-72.
Monteiro, M., Carvalho, M., Henrique, R., Jeronimo, C., Moreira, N., de Lourdes Bastos, M., et al. (2014). Analysis of volatile human urinary metabolome by solid-phase microextraction in combination with gas chromatography-mass spectrometry for biomarker discovery: Application in a pilot study to discriminate patients with renal cell carcinoma. European Journal of Cancer, 50(11), 1993–2002. https://doi.org/10.1016/j.ejca.2014.04.011.
Nunes de Paiva, M. J., Menezes, H. C., & de Lourdes Cardeal, Z. (2014). Sampling and analysis of metabolomes in biological fluids. Analyst, 139(15), 3683–3694. https://doi.org/10.1039/c4an00583j.
Pasikanti, K. K., Esuvaranathan, K., Ho, P. C., Mahendran, R., Kamaraj, R., Wu, Q. H., et al. (2010a). Noninvasive urinary metabonomic diagnosis of human bladder cancer. Journal of Proteome Research, 9(6), 2988–2995. https://doi.org/10.1021/pr901173v.
Pasikanti, K. K., Esuvaranathan, K., Hong, Y., Ho, P. C., Mahendran, R., Raman Nee Mani, L., et al (2013). Urinary metabotyping of bladder cancer using two-dimensional gas chromatography time-of-flight mass spectrometry. Journal of Proteome Research, 12(9), 3865–3873. https://doi.org/10.1021/pr4000448.
Pasikanti, K. K., Norasmara, J., Cai, S., Mahendran, R., Esuvaranathan, K., Ho, P. C., et al. (2010b). Metabolic footprinting of tumorigenic and nontumorigenic uroepithelial cells using two-dimensional gas chromatography time-of-flight mass spectrometry. Analytical and Bioanalytical Chemistry, 398(3), 1285–1293. https://doi.org/10.1007/s00216-010-4055-3.
Peng, G., Hakim, M., Broza, Y. Y., Billan, S., Abdah-Bortnyak, R., Kuten, A., et al. (2010). Detection of lung, breast, colorectal, and prostate cancers from exhaled breath using a single array of nanosensors. British Journal of Cancer, 103(4), 542–551. https://doi.org/10.1038/sj.bjc.6605810.
Phillips, M., Cataneo, R. N., Greenberg, J., Gunawardena, R., Naidu, A., & Rahbari-Oskoui, F. (2000). Effect of age on the breath methylated alkane contour, a display of apparent new markers of oxidative stress. The Journal of Laboratory and Clinical Medicine, 136(3), 243–249. https://doi.org/10.1067/mlc.2000.108943.
Pickel, D., Manucy, G. P., Walker, D. B., Hall, S. B., & Walker, J. C. (2004). Evidence for canine olfactory detection of melanoma. Applied Animal Behaviour Science, 89(1), 107–116. https://doi.org/10.1016/j.applanim.2004.04.008.
Pluskal, T., Castillo, S., Villar-Briones, A., & Oresic, M. (2010). MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinformatics, 11, 395. https://doi.org/10.1186/1471-2105-11-395.
Poli, D., Goldoni, M., Corradi, M., Acampa, O., Carbognani, P., Internullo, E., et al. (2010). Determination of aldehydes in exhaled breath of patients with lung cancer by means of on-fiber-derivatisation SPME-GC/MS. Journal of Chromatography B, 878(27), 2643–2651. https://doi.org/10.1016/j.jchromb.2010.01.022.
Putluri, N., Shojaie, A., Vasu, V. T., Vareed, S. K., Nalluri, S., Putluri, V., et al. (2011). Metabolomic profiling reveals potential markers and bioprocesses altered in bladder cancer progression. Cancer Research, 71(24), 7376–7386. https://doi.org/10.1158/0008-5472.can-11-1154.
Rodrigues, D., Jeronimo, C., Henrique, R., Belo, L., de Lourdes Bastos, M., de Pinho, P. G., et al. (2016a). Biomarkers in bladder cancer: A metabolomic approach using in vitro and ex vivo model systems. International Journal of Cancer, 139(2), 256–268. https://doi.org/10.1002/ijc.30016.
Rodrigues, D., Monteiro, M., Jeronimo, C., Henrique, R., Belo, L., Bastos, M. L., et al. (2016b). Renal cell carcinoma: A critical analysis of metabolomic biomarkers emerging from current model systems. Translational Research. https://doi.org/10.1016/j.trsl.2016.07.018.
Rudnicka, J., Kowalkowski, T., Ligor, T., & Buszewski, B. (2011). Determination of volatile organic compounds as biomarkers of lung cancer by SPME-GC-TOF/MS and chemometrics. Journal of Chromatography B, 879(30), 3360–3366. https://doi.org/10.1016/j.jchromb.2011.09.001.
Schmidt, K., & Podmore, I. (2015). Current challenges in volatile organic compounds analysis as potential biomarkers of cancer. Journal of Biomarkers. https://doi.org/10.1155/2015/981458.
Shirasu, M., & Touhara, K. (2011). The scent of disease: Volatile organic compounds of the human body related to disease and disorder. The Journal of Biochemistry, 150(3), 257–266. https://doi.org/10.1093/jb/mvr090.
Silva, C. L., Passos, M., & Camara, J. S. (2011). Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry. British Journal of Cancer, 105(12), 1894–1904. https://doi.org/10.1038/bjc.2011.437.
Sponring, A., Filipiak, W., Mikoviny, T., Ager, C., Schubert, J., Miekisch, W., et al. (2009). Release of volatile organic compounds from the lung cancer cell line NCI-H2087 in vitro. Anticancer Research, 29(1), 419–426.
Wang, C., Ke, C., Wang, X., Chi, C., Guo, L., Luo, S., et al. (2014). Noninvasive detection of colorectal cancer by analysis of exhaled breath. Analytical and Bioanalytical Chemistry, 406(19), 4757–4763. https://doi.org/10.1007/s00216-014-7865-x.
Willis, C. M., Church, S. M., Guest, C. M., Cook, W. A., McCarthy, N., Bransbury, A., et al. (2004). Olfactory detection of human bladder cancer by dogs: Proof of principle study. BMJ, 329, 712.
Wishart, D. S., Tzur, D., Knox, C., Eisner, R., Guo, A. C., Young, N., et al. (2007). HMDB: The Human Metabolome Database. Nucleic Acids Research, 35(Database issue), D521–D526. https://doi.org/10.1093/nar/gkl923.
Worley, B., & Powers, R. (2013). Multivariate analysis in metabolomics. Current Metabolomics, 1(1), 92–107. https://doi.org/10.2174/2213235x11301010092.
Zhang, Z., & Pawliszyn, J. (1993). Headspace solid-phase microextraction. Analytical Chemistry, 65(14), 1843–1852. https://doi.org/10.1021/ac00062a008.
Zimmermann, D., Hartmann, M., Moyer, M. P., Nolte, J., & Baumbach, J. I. (2007). Determination of volatile products of human colon cell line metabolism by GC/MS analysis. Metabolomics, 3(1), 13–17. https://doi.org/10.1007/s11306-006-0038-y.
Acknowledgements
This work received financial support from the European Union (FEDER funds POCI/01/0145/FEDER/007728) and National Funds (FCT/MEC, Fundação para a Ciência e Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreement PT2020 UID/MULTI/04378/2013. This study is a result of the project NORTE-01-0145-FEDER-000024, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement (DESignBIOtecHealth - New Technologies for three Health Challenges of Modern Societies: Diabetes, Drug Abuse and Kidney Diseases), through the European Regional Development Fund (ERDF). C.J.’s research is funded by a research grant from Research Center of Portuguese Oncology Institute of Porto (FB-GEBC-27) and S.M.-R. is a PhD fellow from Fundação para a Ciência e Tecnología (FCT SFRH/BD/112673/2015). M.C. acknowledges FCT through the project UID/Multi/04546/2013.
Author information
Authors and Affiliations
Contributions
DR was responsible for the execution of the experimental work and data analysis. AMA supported cell culture and data analysis. JP helped with the statistical analysis of the data. SM-R, CJ and RH kindly provided the cell lines used in the study and gave conceptual advice. PGP, MLB and MC designed and supervised the study. DR wrote the manuscript with input from MC. All authors critically commented on and approved the final submitted version of the paper.
Corresponding authors
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interests in relation to the work described.
Research involving human and animals participants
This article does not contain any studies with human participants or animals.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Rodrigues, D., Pinto, J., Araújo, A.M. et al. Volatile metabolomic signature of bladder cancer cell lines based on gas chromatography–mass spectrometry. Metabolomics 14, 62 (2018). https://doi.org/10.1007/s11306-018-1361-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11306-018-1361-9