Fourier transform infrared imaging analysis in discrimination studies of prostate cell lines and prostate cancer tissue J. D. Pallua1, C. Pezzei1, G. Schaefer2, C. Seifarth2, L. Bittner1, V. Huck-Pezzei1, S. A. Schönbichler1 H. Klocker2, G. Bartsch2, G. K. Bonn1 and C. W. Huck1 1 Institute of Analytical Chemistry and Radiochemistry, Leopold-Franzens University, Innrain 52a, 6020 Innsbruck, Austria 2 Department of Urology, Medical University of Innsbruck, Anichstraße 35, 6020 Innsbruck, Austria INTRODUCTION Prostate cancer (PCa) has become one of the most common malignancies worldwide 1,2. Clinical and pathological diagnose of PCa is very complex and demands a range of bioanalytical techniques for its investigation. The lack of reliable tools to swiftly diagnose has led to a considerable amount of interest in the evolution of new techniques such as FTIR imaging3-6. This newly emerging biospectroscopic technique has been applied in imaging mode to the study of whole single cells at subcellular spatial resolution and enables one to study the state of chemical bonding or to map the relative concentration of the lipid, protein, carbohydrate and phosphorylated molecular domains, across the cell7-9. In order to gain more insight into FTIR prostate pathology, a detailed investigation into the spectral cytology of various cell types was deemed necessary so that the origin of major spectral types observed in prostate cancer cells and the spectral characteristics of abnormality could be understood. Therefore FTIR microscopic imaging was applied to the analysis of prostate tissue and different prostate cancer cell lines to incorporate multivariate methods of analysis. Figure 2. (A)Spectra of different prostate cell cultures, (B)Pretreated spectra, (C)PCA, (D) Scores plot of first and second principal component. Each colored data point represents one cell line (c =cancer cell line ; n = non-cancer cell line). METHODS Spectroscopic imaging data of cell culture monolayer (tumor cells:22Rv1, Du145, DuCaP, LNCaP, PC3, RT4V and VCaP; prostate cell lines: EP156T, HF219, PF128 and PM151T) and prostate tissue were acquired in transmission mode using a commercially available infrared spectrometer Spectrum One FT-IR spectrometer (Perkin-Elmer, England) coupled to an infrared microscope Spectrum Spotlight 400 (Perkin-Elmer). Spectral data were recorded using a mirror speed of 1 cm s-1, a spectral resolution of 4 cm-1, and a pixel resolution of 6.25µm. RESULTS The analysis of the resulting data sets by spectra analysis, principal component analysis (PCA) and cluster analysis images are illustrated in Figure 1, Figure 2 and Figure 3 by using Spectrum IMAGE software (PerkinElmer), The Unscrambler 9.6 (Camo, Oslo, Norway) and CytoSpec software package (http://www.cytospec.com), which enables spectral processing and cluster analysis. Figure 2. (A) H&E-stained tissue section of human prostate cancer (Gleason score 5) with marked regions (1 = stroma, 2 = cancer, 3 = lumen) scanned by MIRAX MIDI scanner (Zeiss,Germany) at high resolution (B) FTIR imaging result shown in false color representation. Colors reflect intensities of the selected absorption at 1080-1060 cm-1, which is commonly attributed to nucleic acids and cholesterols (C)FTIR imaging result shown in false color representation. Colors reflect intensities of the selected absorption at 1591-1483  cm-1, which is commonly attributed to proteins (D)FTIR imaging result shown in false color representation. Colors reflect intensities of the selected absorption at 2920-2850 cm-1, which is commonly attributed to lipids and carbohydrates (E)Scores plot of first and second principal component. Each colored data point represents one region of interest (ROI). The data sets were chosen from cancer- (red) and stroma tissue region (green), which are co-registered with the scanned H&E. This co-registration allows a parallel assessment of the histopathological features. (F)Hierarchial Cluster Analysis spectroscopic image of a human prostate cancer section with 5 clusters CONCLUSION Figure 1 . (A)Tissue section of human prostate cancer cell line (LNCaP) scanned at high resolution (400µm x 400µm) (B)FTIR imaging result shown in false color representation. Colors reflect intensities of the selected absorption at 1080-1060 cm-1, which is commonly attributed to nucleic acids and cholesterols (C)FTIR imaging result shown in false color representation. Colors reflect intensities of the selected absorption at 1591-1483  cm-1, which is commonly attributed to proteins (D)FTIR imaging result shown in false color representation. Colors reflect intensities of the selected absorption at 2920-2850 cm-1, which is commonly attributed to lipids and carbohydrates FTIR imaging of tissue sections allows the differentiation of different prostate cell lines (IR histopathology) and illustrates a possible option for a tool to detect prostate cancer in tissue samples to assist histopathological routine analysis. REFERENCES 1. Nelen, V. Epidemiology of prostate cancer. Recent Results Cancer Res 175, 1-8 (2007). 2. Pardal, R., Clarke, M.F. & Morrison, S.J. Applying the principles of stem-cell biology to cancer. Nat Rev Cancer 3, 895-902 (2003). 3. Petter, C.H., et al. Development and application of Fourier-transform infrared chemical imaging of tumour in human tissue. Curr Med Chem 16, 318-326 (2009). 4. Bhargava, R. Towards a practical Fourier transform infrared chemical imaging protocol for cancer histopathology. Anal Bioanal Chem 389, 1155-1169 (2007). 5. Low, G., et al. Role of imaging in clinical islet transplantation. Radiographics 30, 353-366. 6. Bird, B., et al. Infrared micro-spectral imaging: distinction of tissue types in axillary lymph node histology. BMC Clin Pathol 8, 8 (2008). 7. Dumas, P., Jamin, N., Teillaud, J.L., Miller, L.M. & Beccard, B. Imaging capabilities of synchrotron infrared microspectroscopy. Faraday Discuss 126, 289-302; discussion 303-211 (2004). 8. Jamin, N., et al. Chemical imaging of nucleic acids, proteins and lipids of a single living cell. Application of synchrotron infrared microspectrometry in cell biology. Cell Mol Biol (Noisy-le-grand) 44, 9-13 (1998). 9. Lasch, P., Pacifico, A. & Diem, M. Spatially resolved IR microspectroscopy of single cells. Biopolymers 67, 335-338 (2002).