- Open Access
Analysis of ovarian tumor pathology by Fourier Transform Infrared Spectroscopy
© Mehrotra et al; licensee BioMed Central Ltd. 2010
- Received: 16 September 2010
- Accepted: 21 December 2010
- Published: 21 December 2010
Ovarian cancer is the second most common cancer among women and the leading cause of death among gynecologic malignancies. In recent years, infrared (IR) spectroscopy has gained attention as a simple and inexpensive method for the biomedical study of several diseases. In the present study infrared spectra of normal and malignant ovarian tissues were recorded in the 650 cm-1 to 4000 cm-1 region.
Post surgical tissue samples were taken from the normal and tumor sections of the tissue. Fourier Transform Infrared (FTIR) data on twelve cases of ovarian cancer with different grades of malignancy from patients of different age groups were analyzed.
Significant spectral differences between the normal and the ovarian cancerous tissues were observed. In particular changes in frequency and intensity in the spectral region of protein, nucleic acid and lipid vibrational modes were observed. It was evident that the sample-to-sample or patient-to-patient variations were small and the spectral differences between normal and diseased tissues were reproducible.
The measured spectroscopic features, which are the spectroscopic fingerprints of the tissues, provided the important differentiating information about the malignant and normal tissues. The findings of this study demonstrate the possible use of infrared spectroscopy in differentiating normal and malignant ovarian tissues.
- Ovarian Cancer
- Ovarian Tissue
- Infrared Spectroscopy
- Malignant Tissue
- Ehrlich Ascites Carcinoma
Ovarian cancer is one of the leading causes of cancer-related deaths among women worldwide. In India, the Indian Council of Medical Research reports the incidence rate of ovarian cancer as 4.2 per 100,000 women . A woman has a lifetime risk of ovarian cancer of around 1.5%, which makes it the second most common gynecologic malignancy . Ovarian cancer usually occurs in women over the age of 50 years, but it can also affect younger women. Two types of ovarian cancers are found based on the cell types. Epithelial ovarian cancer, which starts in the surface layer covering the ovary and constitutes 80 to 90% of all tumours of the ovary. Germ line ovarian tumors which are derived from the germ cells of the ovary and occur much less frequently. The survival rate of ovarian cancer patient depends upon the stage at which the cancer is diagnosed. But ovarian cancer is hard to detect early, as early stage is generally asymptomatic. More than 75% of ovarian cancers are diagnosed with late stage disease. Patients would have a significantly-improved survival if their cancer could be detected while still limited to the ovary .
There is a widespread interest in developing screening methods for early ovarian cancer detection because of the high mortality associated with late stage disease. Presently, the test available for screening ovarian cancer patients focus on two areas. One is the assessment of certain biomarkers in the blood. The second area is of producing detailed images of ovaries through various imaging techniques. The most commonly used blood serum biomarker is Cancer Antigen 125 (CA-125) . Specificity is not achieved by this test as other types of cancer can raise the CA-125 levels such as breast, endometrium, gastrointestinal tract, and lung cancer. CA-125 testing is also not effective in women who are pre-menopausal because the CA-125 level fluctuates during the menstrual cycle .
On the imaging area of study several imaging techniques have been employed such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI) and Ultrasound Imaging. Studies have shown that ultrasound gives a poor accuracy in detecting early stage disease . A much more accurate ultrasound imaging screening test is the Trans Vaginal Ultrasonography (TVS) which gives impressive results, however it is inefficient in distinguishing between benign and malignant masses. The only way to diagnose ovarian cancer with certainty is an exploratory operation. But it is not possible in cases when the woman is in poor health or the disease is advanced.
Current screening techniques are challenged due to cost-ineffectiveness, variable false-positive results, and the asymptomatic nature of the early stages of ovarian cancer. Thus, it is required to develop an accurate, quick, convenient, and inexpensive method for detecting early cancer of ovaries at molecular level. Spectroscopy is increasingly used now days to characterize physical and chemical changes occurring in tissues and cells. It offers possibilities for new diagnostic and therapeutic approaches . Spectroscopic techniques such as fluorescence and nuclear magnetic resonance (NMR) have been employed to distinguish cancerous and non-cancerous states of a tissue . Fluorescence spectroscopy can provide biochemical information about the state of a tissue, but suffers from broad band fluorescence features . There are only a small number of endogenous fluorophores in cancerous tissue to provide fluorescent signals and hence give rise to undesirable broad spectral features . Tissue analysis by NMR spectroscopy requires highly sophisticated instrumentation and still suffers with unresolved peaks due to constrained molecular motions .
With the advances in vibrational spectroscopic techniques, its application in medical biology is increasing day by day [12, 13]. Fourier transform infrared spectroscopy (FTIR) is a relatively simple, rapid and nondestructive technique that is adaptable for solids, liquids, and gases with a minimal sample preparation and can be used for both qualitative identification and the quantitative analysis of various components in a complex mixture [14, 15]. Analysis of characteristic group frequencies in a spectrum allows qualitative estimates of chemical composition in these materials. Biomolecular features like conformational state, side chain length and inter/intra chain bondings can be measured easily using infrared spectroscopy. Recently, the application of infrared spectroscopy in biomedical sciences has increased a lot and various new clinical applications have been reported in the literature these applications include analysis of bone , skin , lung , breast , prostate  and cervical tissues . Furthermore, this technique has been used in anticancer drug investigations [20–22], cancer grading (14), and studies on nucleic acid from tumor cells . Fourier transform infrared spectroscopy has been extensively employed in the field of cancer research to address the problems of tumor biology [24–30]. The results of our previous research have shown its advantage in discrimination of breast cancer tissue from normal breast tissue . In the present work, we examine the cancerous and normal tissues of ovaries to obtain information about ovarian cancer at molecular level with FTIR technique.
Tissue samples of 12 cases of ovarian cancer were obtained from Dharamshila Hospital, Delhi. Informed consent from patients have been taken prior to surgery. Post surgical cancer tissue and normal tissue (2-3 cm away from the tumor) samples were collected. All the samples were of stage II and III. For each case two samples were cut, one was put on the glass slide and was used for histological review. The other part of the tissue was frozen (-28°C) to obtain cryostat sections (2-4 μm) which were taken on zinc selenide (ZnSe) crystal plates. The tissue sections were placed on the ZnSe plates without any fixative and were used for spectral analysis.
Varian 660 IR spectrometer equipped with DTGS detector and KBr beam splitter was used to record the spectra. FTIR spectra were collected in the transmission mode. The spectra were scanned in the mid-IR range from 650 to 4000 cm-1 with a resolution of 4 cm-1. Two hundred and fifty six scans were collected for each spectrum and the spectra were ratioed against the background spectrum. The spectra were normalized after the baseline correction. Second order derivative of all the spectra were calculated using savitzky-Golay 2nd order polynomial with 11 data points.
The results of the present study have shown that remarkable difference exist between the IR spectra of normal and malignant tissue in terms of absorption frequencies and intensities of prominent absorption bands of cellular biomolecules. The differences observed in the spectra of normal and malignant tissue reflect changes in the content of nucleic acid and lipids. Protein absorption bands indicate the presence of new proteins as well as changes in their conformation and composition. Spectral absorption patterns observed for major biomolecules; nucleic acid, proteins and lipids can be viewed as IR spectral signatures which can be used for distinguishing malignant ovarian tissue from the normal tissue. Based on this, we can compare the infrared spectrum of malignant tissue with its corresponding normal tissue, and establish a new way to diagnose malignant tumors. Prospectively, in conjunction with other markers this technique could be useful in diagnosis of ovarian cancer.
Authors are thankful to Department of Science and Technology, New Delhi, India for providing the financial support (Grant No. DST/TSG/PT/2006/50).
- Nandkumar A (Ed): Biennial Report (1990–96) of National Cancer Registry Programme, Indian Council of Medical Research: New Delhi. National Printing Press: Bangalore; 2001:62–63.Google Scholar
- American Cancer society[http://www.cancer.org]
- Hoskins WJ: Prospective on ovarian cancer: Why prevent? J Cell Biochem Suppl 1995, 23: 189–199. 10.1002/jcb.240590926View ArticlePubMedGoogle Scholar
- Fritsche HA, Bast RC: CA 125 in Ovarian Cancer: Advances and Controversy. Clin Chem 1998, 44: 1379–1380.PubMedGoogle Scholar
- Togashi K: Ovarian cancer: the clinical role of US, CT and MRI. Eur Radiol 2003, 13: 87–104. 10.1007/s00330-003-1964-yView ArticleGoogle Scholar
- O'Rourke J, Mahon SM: A Comprehensive Look at the Early Detection of Ovarian Cancer. Clin J Oncol Nurs 2002, 7: 41–47.View ArticleGoogle Scholar
- Alfano R, Tata D, Cordero J, Tomashefshy P, Longo F, Alfano M: Laser induced fluorescence spectroscopy from native cancerous and normal tissues. IEEE J Quantum Electron 1984, 20: 1507–1511. 10.1109/JQE.1984.1072322View ArticleGoogle Scholar
- Servick-Muraca E, Richards-Kortum R: Quantitative optical spectroscopy for tissue diagnosis. Annu Rev Phys Chem 1996, 47: 556–606.Google Scholar
- Liu Q, Chen K, Martin M, Wintenberg A, Lenarduzzi R, Panjehpour M, Overholt BF, Vo-Dinh T: Development of a synchronous fluorescence imaging system and data analysis methods. Opt Express 2007, 15(20):12583–12594. 10.1364/OE.15.012583View ArticlePubMedGoogle Scholar
- Haka AS, Shafer-Peltier KE, Fitzmaurice M, Crowe J, Dasari RR, Feld MS: Diagnosing breast cancer by using Raman spectroscopy. PNAS 2005, 102(35):12371–12376. 10.1073/pnas.0501390102PubMed CentralView ArticlePubMedGoogle Scholar
- Whitehead TL, Kieber-Emmons T: Applying in vitro NMR spectroscopy and 1 H NMR metabonomics to breast cancer characterization and detection. Prog Nucl Magn Reson Spectrosc 2005, 47: 165–174. 10.1016/j.pnmrs.2005.09.001View ArticleGoogle Scholar
- Paluszkiewicz C, Kwiatek WM: Analysis of human cancer prostate tissues using FTIR microspectroscopy and SRIXE technique. J Mol Struct 2001, 565–566: 329–334. 10.1016/S0022-2860(01)00527-0View ArticleGoogle Scholar
- Weng SF, Ling XF, Song YY, Xu YZ, Zhang X, Yang L, Sun W, Zhou X, Wu J: FTIR fiber optics and FT-Raman spectroscopic studies for the diagnosis of cancer. Am Clin Lab 2000, 19: 20.PubMedGoogle Scholar
- Andrus PG, Strickland RD: Cancer grading by Fourier transform infrared spectroscopy. Biospectroscopy 1998, 4: 37–46. 10.1002/(SICI)1520-6343(1998)4:1<37::AID-BSPY4>3.0.CO;2-PView ArticlePubMedGoogle Scholar
- Wood BR, Quinn MQ, Tait B, Romeo M, Mantsch HH: A FTIR spectroscopic study to identify potential confounding variables and cell types in screening for cervical malignancies. Biospectroscopy 1998, 4: 75–91. 10.1002/(SICI)1520-6343(1998)4:2<75::AID-BSPY1>3.0.CO;2-RView ArticlePubMedGoogle Scholar
- Rehman I, Smith R, Hench LL, Bonfield W: Structural evaluation of human and sheep bone and comparison with synthetic hydroxyapatite by FT-Raman spectroscopy. J Biomed Mater Res 1995, 29: 1287–1294. 10.1002/jbm.820291016View ArticlePubMedGoogle Scholar
- Wong PTT, Goldstein SM, Grekin RC, Godwin TA, Pivik C, Rigas B: Distinct infrared spectroscopic patterns of human basal cell carcinoma of the skin. Cancer Res 1993, 53: 762–765.PubMedGoogle Scholar
- Das RM, Ahmed MK, Mantsch HH, Scott JE: FT-IR spectroscopy of methylmercury- exposed mouse lung. Mol Cell Biochem 1995, 145: 75–79. 10.1007/BF00925716View ArticlePubMedGoogle Scholar
- Redd DC, Feng ZC, Yue KT, Gansler TS: Raman Spectroscopic Characterization of Human Breast Tissues: Implications for Breast Cancer Diagnosis. Appl Spectrosc 1993, 47: 787–791. 10.1366/0003702934067072View ArticleGoogle Scholar
- Binoy J, Abraham JP, Joe IH, Jayakumar VS, Pettit GR, Nielsen OF: NIR-FT Raman and FT-IR spectral studies and ab initio calculations of the anti-cancer drug combretastatin-A4. J Raman Spectros 2004, 35: 939–946. 10.1002/jrs.1236View ArticleGoogle Scholar
- Jangir DK, Tyagi G, Mehrotra R, Kundu S: Carboplatin interaction with callf-thymus DNA: A FTIR spectroscopic approach. J Mol struct 2010, 969: 126–129. 10.1016/j.molstruc.2010.01.052View ArticleGoogle Scholar
- Tyagi G, Jangir DK, Singh P, Mehrotra R: DNA interaction studies of an anti-cancer plant alkaloid vincristine using Fourier transform infrared spectroscopy. DNA Cell Biol 2010, 29(11):693–699. 10.1089/dna.2010.1035View ArticlePubMedGoogle Scholar
- Dovbeshko GI, Chegel VI, Gridina NY, Repnytska OP, Shirshov YM, Tryndiak VP, Todor IM, Solyanik GI: Surface enhanced IR absorption of nucleic acids from tumor cells: FTIR reflectance study. Biopolymers 2002, 67(6):470–86. 10.1002/bip.10165View ArticlePubMedGoogle Scholar
- Yamada T, Miyoshi N, Ogawa T, Akao K, Fukuda M, Ogasawara T, Kitagawa Y, Sano K: Observation of molecular changes of a necrotic tissue from a murine carcinoma by Fourier-transform infrared microspectroscopy. Clin Cancer Res 2002, 8: 2010–2014.PubMedGoogle Scholar
- Argov S, Ramesh J, Salman A, Sinelnikov I, Goldstein J, Guterman H, Mordechai S: Diagnostic potential of Fourier-transform infrared microspectroscopy and advanced computational methods in colon cancer patients. J Biomed Opt 2002, 7: 248–254. 10.1117/1.1463051View ArticlePubMedGoogle Scholar
- Yano K, Ohoshima S, Gotou Y, Kumaido K, Moriguchi T, Katayama H: Direct measurement of human lung cancerous and noncancerous tissues by fourier transform infrared microscopy: can an infrared microscope be used as a clinical tool? Anal Biochem 2000, 25: 287–218.Google Scholar
- Romeo MJ, Wood BR, Quinn MA, McNaughton D: Removal of blood components from cervical smears: Implications for cancer diagnosis using FTIR spectroscopy. Biopolymers 2003, 72: 69–76. 10.1002/bip.10284View ArticlePubMedGoogle Scholar
- Wong PT, Senterman MK, Jackli P, Wong RK, Salib S, Campbell CE, Feigel R, Faught W, Fung Kee Fung M: Detailed account of confounding factors in interpretation of FTIR spectra of exfoliated cervical cells. Biopolymers 2002, 67: 376–386. 10.1002/bip.10166View ArticlePubMedGoogle Scholar
- Ramesh J, Kapelushnik J, Mordehai J, Moser A, Huleihel M, Erukhimovitch V, Levi C, Mordechai S: Novel methodology for the follow-up of acute lymphoblastic leukemia using FTIR microspectroscopy. J Biochem Biophys Methods 2002, 51: 251–261. 10.1016/S0165-022X(02)00004-0View ArticlePubMedGoogle Scholar
- Wang JS, Shi JS, Xu YZ, Duan XY, Zhang L, Wang J: FT-IR spectroscopic analysis of normal and cancerous tissues of esophagus. World J Gastroenterol 2003, 9: 1897–1899.PubMedGoogle Scholar
- Mehrotra R, Gupta A, Kaushik A, Prakash N, Kandpal Hem: Infrared spectroscopic analysis of tumor pathology. Indian J Exp Biol 2007, 45: 71–76.PubMedGoogle Scholar
- Rehman S, Movasaghi Z, Darr JA, Rehman IU: Fourier Transform Infrared Spectroscopic Analysis of Breast Cancer Tissues; Identifying Differences between Normal Breast, Invasive Ductal Carcinoma, and Ductal Carcinoma In Situ of the Breast. Appl Spectrosc Rev 2010, 45: 355–368. 10.1080/05704928.2010.483674View ArticleGoogle Scholar
- Banyay M, Sarkar M, Graslund A: A library of IR bands of nucleic acids in solution. Biophys Chem 2003, 104: 477–488. 10.1016/S0301-4622(03)00035-8View ArticlePubMedGoogle Scholar
- Wong PTT, Papavassiliou ED, Rigas B: Phosphodiester Stretching Bands in the Infrared Spectra of Human Tissues and Cultured Cells. Appl Spectrosc 1991, 45(9):1563–1567. 10.1366/0003702914335580View ArticleGoogle Scholar
- Sheeler P, Bianchi DE: Cell Biology. John Wiley and Sons, New York; 1980.Google Scholar
- Anastassopoulou J, Arapantoni P, Boukaki E, Konstadoudakis S, Theophanides S, Valavanis C, Conti C, Ferraris P, Giorgini G, Sabbatini S, Tosi G: Micro-FT-IR Spectroscopic Studies Of Breast Tissues. In Brilliant Light in Life and Material Sciences. Volume 13. Edited by: Tsakanov V, Wiedemann H. Springer Netherlands; 2007:273–278. full_textView ArticleGoogle Scholar
- Krafft C, Sobottka SB, Schackert G, Salzera R: Analysis of human brain tissue, brain tumors and tumor cells by infrared spectroscopic mapping. Analyst 2004, 129: 921–925. 10.1039/b408934kView ArticlePubMedGoogle Scholar
- Liu C, Zhang Y, Yan X, Zhang X, Li C, Yang W, Shi D: Infrared absorption of human breast tissues in vitro. J Lumin 2006, 119–120: 132–136. 10.1016/j.jlumin.2005.12.050View ArticleGoogle Scholar
- Dukor RK: Applications in Life, Pharmaceutical and Natural Sciences. In Handbook of Vibrational Spectroscopy. Volume 5. Edited by: Chalmers JM, Griffiths PR. John Wiley & Sons, New York; 2002:3335–3361.Google Scholar
- Mantsch HH, Choo-Smith L, Shaw RA: Vibrational spectroscopy and medicine: an alliance in the making. Vib Spectrosc 2002, 30: 31–41. 10.1016/S0924-2031(02)00036-XView ArticleGoogle Scholar
- Sahu RK, Mordechai S: Fourier transform infrared spectroscopy in cancer detection. Future Oncol 2005, 1(5):635–647. 10.2217/147966188.8.131.525View ArticlePubMedGoogle Scholar
- Yu LR, Zhou M, Conrads TP, Veenstra TD: Diagnostic proteomics: Serum proteomic patterns for the detection of early stage cancers. Dis Markers 2004, 19: 209–218.PubMed CentralView ArticleGoogle Scholar
- Cazares LH, Adam BL, Ward MD, Nasim S, Schellhammer PF, Semmes J, George L: Normal, Benign, Preneoplastic, and Malignant Prostate Cells Have Distinct Protein Expression Profiles Resolved by Surface Enhanced Laser Desorption/Ionization Mass Spectrometry. Clin Cancer Res 2002, 8: 2541–2552.PubMedGoogle Scholar
- Rajkapoor B, Jayakar B, Murugesh N: Antitumor activity of Indigofera aspalathoides on Ehrlich ascites carcinoma in mice. Indian J Pharmacol 2004, 36: 38–40.Google Scholar
- Wong PTT, Lacelle S, Yazdi HM: Normal and malignant human colonic tissues investigated by pressure tuning FT-IR spectroscopy. Appl Spectrosc 1993, 47: 1830–1836. 10.1366/0003702934065885View ArticleGoogle Scholar
- Nomura DK, Long JZ, Nissen S, Hoover HS, Shu-Wing Ng, Cravatt BF: Monoacylglycerol lipase regulates a fatty acid network that promotes cancer pathogenesis. Cell 2010, 140: 49–61. 10.1016/j.cell.2009.11.027PubMed CentralView ArticlePubMedGoogle Scholar
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