Patterns prediction of chemotherapy sensitivity in cancer cell lines using FTIR spectrum, neural network and principal components analysis

Iranian Journal of Pharmaceutical Research

Volumn 11, Issue 2, 2012, Pages 401-410

  Zendehdel, Rezvan ^a,c   Masoudi Nejad, Ali ^b   Shirazi, Farshad H ^a,c  

^a SHAHID BEHESHTI UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^b UNIVERSITY OF TEHRAN   (Iran)

^c SHAHID BEHESHTI UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

Artificial neuronal network; Drug resistant; Fourier transform infrared; Linear discriminate analysis; Pattern recognition; Principle component analysis

Indexed keywords

CISPLATIN DERIVATIVE;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER CELL CULTURE; CANCER CHEMOTHERAPY; CANCER CLASSIFICATION; CANCER RESISTANCE; HUMAN; HUMAN CELL; INFRARED SPECTROSCOPY; OVARY CELL CULTURE; PHENOTYPE; PREDICTIVE VALUE; PRINCIPAL COMPONENT ANALYSIS; PROTEIN STRUCTURE;

EID: 84862739929     PISSN: 17350328     EISSN: 17266890     Source Type: Journal    
DOI: None     Document Type: Article

References (31)

1. Notani PN. Global variation in cancer incidence and mortality. Curr. Sci. (2001) 81: 465-474.
2. Rabik CA and Dolan ME. Molecular mechanisms of resistance and toxicity associated with platinating agents. Cancer Treat. Rev. (2007) 33: 9-23.
3. Paston I, Gottesman M. Multiple-drug resistance in human cancer. N. Engl. J. Med. (1987) 316: 1388-1393.
4. Leung EL, Fraser M, Fiscus RR and Tsang BK. Cisplatin alter nitric oxide synthesis levels in human ovarian cancer cells: involvement in p53 regulation and cisplatin resistance. Brit. J. Cancer (2008) 98: 1803-1809.
5. Tummala R, Diegelman P and Fiuza SM. Characterization of Pt, Pd-spermine complexes for their effect on polyamine pathway and cisplatin resistance in A2780 ovarian carcinoma cells. Oncol. Rep. (2010) 24: 15-24.
6. Manoharan R, Wang Y and Feld MS. Histochemical analysis of biological tissues using Raman spectroscopy. Spectrochim. Acta (Part A) Mol. Biomol. Spectrosc. (1996) 52: 215-249.
7. Wagnieres G, Star WM and Wilson B. In-vivo fuorescence spectroscopy and imaging for oncological applications. Photochem. Photobiol. (1998) 68: 603-632.
8. Mantsch HH, Choo-Smith LP and Shaw RA. Vibrational spectroscopy and medicine: an alliance in the making. Vibr. Spectrosc. (2002) 30: 31-41.
9. Ofr K, Kelly S and Yechiel S. Functional and structural characterization of HIV-1 gp41 ectodomain regions in phospholipid membranes suggests that the fusion-active conformation is extended. J. Mol. Biol. (2006) 364: 1103-1117.
10. Krafft C, Sobottka B and Geiger D. Classifcation of malignant gliomas by infrared spectroscopic imaging and linear discriminant analysis. Anal. Bioanal. Chem. (2007) 387: 1669-1677.
11. Steller W, Einenkel J and Lars-Christian H. Delimitation of squamous cell cervical carcinoma using infrared microspectroscopic imaging. Anal. Bioanal. Chem. (2006) 384: 145-154.
12. Johnson HE, Broadhurst D, Kell DB, Theodorou MK, Merry RJ and Griffth GW. High-throughput metabolic fngerprinting of legume silage fermentations via Fourier transform. Infrared Spectroscopy and Chemometrics (2004) 70: 1583-1592.
13. Ellis DI, Broadhurst D, Kell DB, Rowland JJ and Goodacre R. Rapid and quantitative detection of the microbial spoilage of meat by Fourier transform infrared spectroscopy and machine learning. Am. Soc. Microbiol. (2002) 68: 2822-2828.
14. Marchevsky AM, Tsou JA and Laird-Offringa IA. Classifcation of individual lung cancer cell lines based on DNA methylation markers. J. Mol. Diagnos. (2004) 6: 28-35.
15. Marchevsky AM, Patel S, Wiley KJ, Stephenson MA, Gondo M, Brown RW, Yi ES, Benedict WF, Anton RC and Cagle PT. Artifcial neural networks and logistic regression as tools for prediction of survival in patients with stages I and II non-small cell lung cancer. Mod. Pathol. (1998) 11: 618-625.
16. Cenci M, Nagar C and Vecchione A. PAPNET-assisted primary screening of conventional cervical smears. Anticancer Res. (2000) 20: 3887-3889
17. Troni GM, Cipparrone I, Cariaggi MP, Ciatto S, Miccinesi G, Zappa M and Confortini M. Detection of false-negative Pap smears using the PAPNET system. Tumori (2000) 86: 455-457
18. Jahandideh S and Abdolmaleki P. Prediction of melatonin excretion patterns in the rat exposed to ELF magnetic elds based on support vector machine and linear discriminant analysis. Micron (2010) 41: 882-885.
19. Farid EA. Artifcial neural networks for diagnosis and survival prediction in colon cancer. Molecular Cancer (2005) 4: 1-12.
20. Guo-Zheng L, Hua-Long B, Mary QY and Xue-Qiang Z. Selecting subsets of newly extracted features from PCA and PLS in microarray data analysis. BMC Genomics (2008) 9: 1-15.
21. Safaak H. Spectroscopic study for detection and grading of breast carcinoma in-vitro. Austral. J. Basic Appl. Sci. (2009) 3: 2419-2428.
22. Baker MJ, Gazi E, Brown MD, Shanks JH, Gardner P and Clarke NW. FTIR-based spectroscopic analysis in the identifcation of clinically aggressive prostate cancer. Brit. J. Cancer (2008) 99: 1859-1866.
23. Zendehdel R, Masoudi-Nejad A, Mohammadzadeh J, and Shirazi FH. Cisplatin resistant patterns in ovarian cell line using FTIR and principle component analysis. Iranian J. Pharm. Res. (2012), 11: 237-242.
24. Tewari KS and Monk BJ. Gynecologic oncology group trials of chemotherapy for metastatic and recurrent cervical cancer. Curr. Oncol. Rep. (2005) 7: 419-434.
25. Mishra NN, Yang S, Sawa A and Rubio A. Analysis of cell membrane characteristics of in-vitro-selected daptomycin-resistant strains of methicillin-resistant Staphylococcus aureus. Antimicrob. Agents Chemother. (2009) 53: 2312-2318.
26. Kartalou M and Essigmann JM. Mechanisms of resistance to cisplatin. Mutat. Res. (2001) 478: 23-43.
27. Bosch A. Fourier transforms infrared spectroscopy for rapid identifcation of nonfermenting Gram-negative bacteria isolated from sputum samples from cystic fbrosis patients. J. Clin. Microbiol. (2008) 46: 2535-2546.
28. Zanier K, Ruhlmann C, Melin F and Masson M. E6 proteins from diverse papillomaviruses self-associate both in-vitro and in-vivo. J. Mol. Biol. (2010) 396: 90-104.
29. McCann MC, Defernez M and Urbanowicz BR. Neural network analyses of infrared spectra for classifying cell wall architectures. Plant Physiol. (2007) 143: 1314-1326.
30. Rebuffo-Scheer CA, Schmitt J and Scherer S. Differentiation of network analysis of Fourier-transformed. Infrared Spectra Appl. Environ. Microbiol. (2007) 73: 1036-1040.
31. Tangri N, Ansell D and Naimark D. Predicting technique survival in peritoneal dialysis patients: comparing artifcial neural networks and logistic regression. Nephrol. Dial. Transplant. (2008) 23: 2972-2981.