open access
Discrimination of papillary thyroid cancer from non-cancerous thyroid tissue based on lipid profiling by mass spectrometry imaging
open access
Abstract
Introduction: The distinction of papillary thyroid carcinomas from benign thyroid lesions has important implication for clinical management. Classification based on histopathological features can be supported by molecular biomarkers, including lipidomic signatures, identified with the use of high-throughput mass spectrometry techniques. Formalin fixation is a standard procedure for stabilization and preservation of tissue samples, therefore this type of samples constitute highly valuable source of clinical material for retrospective molecular studies. In this study we used mass spectrometry imaging to detect lipids discriminating papillary cancer from not cancerous thyroid directly in formalin-fixed tissue sections.
Material and methods: For this purpose imaging and profiling of lipids present in non-malignant and cancerous thyroid tissue specimens were conducted. High resolution MALDI-Q-Ion Mobility-TOF-MS technique was used for lipidomic analysis of formalin fixed thyroid tissue samples. Lipids were identified by the comparison of the exact molecular masses and fragmentation pathways of the protonated molecule ions, recorded during the MS/MS experiments, with LIPID MAPS database.
Results: Several phosphatidylcholines (32:0, 32:1, 34:1 and 36:3), sphingomyelins (34:1 and 36:1) and phosphatidic acids (36:2 and 36:3) were detected and their abundances were significantly higher in cancerous tissue compared to non-cancerous tissue. The same lipid species were detected in formalin-fixed as in fresh-frozen tissue, but [M + Na]+ ions were the most abundant in formalin fixed whereas [M + K]+ ions were predominant in fresh tissue.
Conclusions: Our results prove the viability of MALDI-MSI for analysis of lipid distribution directly in formalin-fixed tissue, and the potential for their use in the classification of thyroid diseases.
Abstract
Introduction: The distinction of papillary thyroid carcinomas from benign thyroid lesions has important implication for clinical management. Classification based on histopathological features can be supported by molecular biomarkers, including lipidomic signatures, identified with the use of high-throughput mass spectrometry techniques. Formalin fixation is a standard procedure for stabilization and preservation of tissue samples, therefore this type of samples constitute highly valuable source of clinical material for retrospective molecular studies. In this study we used mass spectrometry imaging to detect lipids discriminating papillary cancer from not cancerous thyroid directly in formalin-fixed tissue sections.
Material and methods: For this purpose imaging and profiling of lipids present in non-malignant and cancerous thyroid tissue specimens were conducted. High resolution MALDI-Q-Ion Mobility-TOF-MS technique was used for lipidomic analysis of formalin fixed thyroid tissue samples. Lipids were identified by the comparison of the exact molecular masses and fragmentation pathways of the protonated molecule ions, recorded during the MS/MS experiments, with LIPID MAPS database.
Results: Several phosphatidylcholines (32:0, 32:1, 34:1 and 36:3), sphingomyelins (34:1 and 36:1) and phosphatidic acids (36:2 and 36:3) were detected and their abundances were significantly higher in cancerous tissue compared to non-cancerous tissue. The same lipid species were detected in formalin-fixed as in fresh-frozen tissue, but [M + Na]+ ions were the most abundant in formalin fixed whereas [M + K]+ ions were predominant in fresh tissue.
Conclusions: Our results prove the viability of MALDI-MSI for analysis of lipid distribution directly in formalin-fixed tissue, and the potential for their use in the classification of thyroid diseases.
Keywords
mass spectrometry imaging, papillary thyroid carcinoma, clinical lipidomics, formalin-fixed tissue specimens
Supp./Additional Files (4)
About this articleTitle
Discrimination of papillary thyroid cancer from non-cancerous thyroid tissue based on lipid profiling by mass spectrometry imaging
Journal
Issue
Article type
Original paper
Pages
2-8
Published online
2017-12-20
Page views
3662
Article views/downloads
2168
DOI
Pubmed
Bibliographic record
Endokrynol Pol 2018;69(1):2-8.
Keywords
mass spectrometry imaging
papillary thyroid carcinoma
clinical lipidomics
formalin-fixed tissue specimens
Authors
Anna Wojakowska
Laura M. Cole
Mykola Chekan
Katarzyna Bednarczyk
Magdalena Maksymiak
Małgorzata Oczko-Wojciechowska
Barbara Jarząb
Malcolm R. Clench
Joanna Polańska
Monika Pietrowska
Piotr Widlak
References (24)- Cibas ES, Ali SZ. The Bethesda system for reporting thyroid cytopathology. Thyroid. 2009; 19: 1159–1165.
- DeLellis RA, Lloyd RV, Heitz PU. Pathology and Genetics of Tumours of Endocrine Organs. WHO Classification of Tumours. IARC Press, Lyon 2004: Lyon.
- Lloyd RV, Buehler D, Khanafshar E. Papillary thyroid carcinoma variants. Head Neck Pathol. 2011; 5(1): 51–56.
- Kakudo K, Kameyama K, Miyauchi A, et al. Introducing the reporting system for thyroid fine-needle aspiration cytology according to the new guidelines of the Japan Thyroid Association. Endocr J. 2014; 61(6): 539–552.
- Faquin WC. The thyroid gland: recurring problems in histologic and cytologic evaluation. Arch Pathol Lab Med. 2008; 132(4): 622–632.
- Sakorafas GH. Thyroid nodules; interpretation and importance of fine-needle aspiration (FNA) for the clinician - practical considerations. Surg Oncol. 2010; 19(4): e130–e139.
- Jelonek K, Pietrowska M, Ros M, et al. Radiation-induced changes in serum lipidome of head and neck cancer patients. Int J Mol Sci. 2014; 15(4): 6609–6624.
- Fernandis AZ, Wenk MR. Membrane lipids as signaling molecules. Curr Opin Lipidol. 2007; 18(2): 121–128.
- Coussens LM, Werb Z. Inflammation and cancer. Nature. 2002; 420(6917): 860–867.
- Gschwind A, Prenzel N, Ullrich A. Lysophosphatidic acid-induced squamous cell carcinoma cell proliferation and motility involves epidermal growth factor receptor signal transactivation. Cancer Res. 2002; 62(21): 6329–6336.
- Dória ML, Cotrim Z, Macedo B, et al. Lipidomic approach to identify patterns in phospholipid profiles and define class differences in mammary epithelial and breast cancer cells. Breast Cancer Res Treat. 2012; 133(2): 635–648.
- Fernandis AZ, Wenk MR. Lipid-based biomarkers for cancer. J Chromatogr B Analyt Technol Biomed Life Sci. 2009; 877(26): 2830–2835.
- Caprioli RM, Farmer TB, Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal Chem. 1997; 69(23): 4751–4760.
- Schwamborn K, Caprioli RM. Molecular imaging by mass spectrometry--looking beyond classical histology. Nat Rev Cancer. 2010; 10(9): 639–646.
- Seeley EH, Caprioli RM. MALDI imaging mass spectrometry of human tissue: method challenges and clinical perspectives. Trends Biotechnol. 2011; 29(3): 136–143.
- Clench MR. Advances in mass spectrometry imaging. Proteomics. 2016; 16(11-12): 1605–1606.
- Ishikawa S, Tateya I, Hayasaka T, et al. Increased expression of phosphatidylcholine (16:0/18:1) and (16:0/18:2) in thyroid papillary cancer. PLoS One. 2012; 7(11): e48873.
- Ryu J. Lipid MALDI MS Profiling Accurately Distinguishes Papillary Thyroid Carcinoma from Normal Tissue. Journal of Proteomics & Bioinformatics. 2013; 06(04).
- Guo S, Qiu L, Wang Y, et al. Tissue imaging and serum lipidomic profiling for screening potential biomarkers of thyroid tumors by matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance mass spectrometry. Anal Bioanal Chem. 2014; 406(18): 4357–4370.
- Guo S, Wang Y, Zhou D, et al. Significantly increased monounsaturated lipids relative to polyunsaturated lipids in six types of cancer microenvironment are observed by mass spectrometry imaging. Sci Rep. 2014; 4: 5959.
- Fox CH, Johnson FB, Whiting J, et al. Formaldehyde fixation. J Histochem Cytochem. 1985; 33(8): 845–853.
- Hackett MJ, McQuillan JA, El-Assaad F, et al. Chemical alterations to murine brain tissue induced by formalin fixation: implications for biospectroscopic imaging and mapping studies of disease pathogenesis. Analyst. 2011; 136(14): 2941–2952.
- Pietrowska M, Gawin M, Polańska J, et al. Tissue fixed with formalin and processed without paraffin embedding is suitable for imaging of both peptides and lipids by MALDI-IMS. Proteomics. 2016; 16(11-12): 1670–1677.
- Initializing EM algorithm for univariate Gaussian, multi-component, heteroscedastic mixture models by dynamic programming partitions. arXiv:1506.07450v2 [stat.AP] 2015.
