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Sun L.,Fuzhou University | Chen Y.,Fuzhou University | Huang Y.-W.,North University of China | Ou L.,Fujian Normal University | And 3 more authors.
Guang Pu Xue Yu Guang Pu Fen Xi/Spectroscopy and Spectral Analysis | Year: 2013

In the present work, two algorithms of support vector classification (SVC) were utilized to analyze and classify Raman spectra of nasopharyngeal cell lines C666-1, CNE2 and nasopharyngeal normal cell line NP69, and achieved great sensitivity and specificity which are all up to 90%. This is coincident with our previous LDA classification model. The final results show that both of these two SVC algorithms can well classify the cell lines, and meanwhile may be helpful to the realization of Raman spectroscopy to be one of diagnostic techniques of nasopharyngeal carcinoma. Source


Ou L.,Fujian Normal University | Chen Y.,Fuzhou University | Su Y.,Laboratory of Radiobiology | Huang Y.,North University of China | And 2 more authors.
Journal of Raman Spectroscopy | Year: 2013

This work aims to explore the application of silver nanoparticle-based surface-enhanced Raman scattering (SERS) for nasopharyngeal carcinoma cell line CNE2's DNA analysis after X-ray radiation. The cells are separated into control group and radiated groups with different dose of 6, 10, 15 and 20 Gy. The results show that after radiation (6, 10, 15 and 20 Gy), the DNA of radiated CNE2 have changed after 72 h of cell incubation. Principal components analysis is employed for significant differences and the DNA extracted after 72 h of incubation show significant divisions from control group. Moreover, a classifier based on support vector machines shows high classification accuracy between DNA extracted after 72 h of incubation and control group. In conclusion, this study first reveals SERS characteristics of CNE2's DNA under different dose of X-ray radiation, and the final results may do favor to make known the mechanism of X-ray radiation interacting with tumor. Copyright © 2013 John Wiley & Sons, Ltd. Source


Chen Y.,Xiamen University | Su Y.,Laboratory of Radiobiology | Ou L.,Fujian Normal University | Zou C.,Laboratory of Radiobiology | Chen Z.,Xiamen University
Vibrational Spectroscopy | Year: 2015

Researchers have demonstrated that Raman spectroscopy can be used for characterization of tumor cells with excellent spatial resolution. However, performance evaluation of different algorithms in classifying multiclass of Raman spectra has not been reported yet. In this work, we present Raman spectra of nasopharyngeal carcinoma and nasopharyngeal normal cell lines. Combined with student's t-test and several multivariate approaches, including decision tree, support vector classification, and linear discriminant analysis, our work shows that the relative content of two histological abnormality sensitive bands at 1449 and 1658 cm-1 in tumor cells is significantly different from that of normal cells (p = 0.0132), and can be a biomarker to classify these cells. This difference is confirmed by importance analyses in the decision tree model. Furthermore, performances of statistical methods are compared with one another to explore the ability in classification. Results show that the decision tree can be more capable for classification between tumorous and normal cell lines with sensitivity and specificity of 99.0% and 96.9%, respectively. Findings of this work further support our previous work and indicate that the decision tree performs more robustly in cell classification. Our work will prove helpful to the early diagnosis of nasopharyngeal carcinoma, and will indicate the decision tree to be the primary algorithm in tumor-cell classification. © 2015 Elsevier B.V. All rights reserved. Source


Gravina G.L.,Laboratory of Radiobiology | Gravina G.L.,University of Rome La Sapienza | Marampon F.,Laboratory of Radiobiology | Mancini A.,University of LAquila | And 8 more authors.
Endocrine-Related Cancer | Year: 2013

Aberrant activation or 'reactivation' of androgen receptor (AR) during androgen ablation therapy shows a potential cause for the development of castration-resistant prostate cancer. This study tested the hypothesis that PXD101, a potent pan histone deacetylase (HDAC) inhibitor, may prevent onset of castration-resistant phenotype and potentiate hormonal therapy. A panel of human prostate cancer cells with graded castration-resistant phenotype and in vivo models were used to verify this hypothesis. In this report, we demonstrated that hormonal manipulation favors the onset of castration-resistant phenotype increasing HDAC expression and activity as well as modulating expression and activity of AR, EGFR, HER2, and Akt. Consistent with these observations, the functional knockdown of HDACs by PXD101 prevented the onset of castration-resistant phenotype with a significant downregulation of AR, EGFR, HER2, and Akt expression/activity. The dysregulation of functional cooperation between HDAC6 with hsp90, on the one hand, and between GSK-3β with CRM1, on the other hand, may explain the biological effects of PXD101. In this regard, the HDAC6 silencing or the functional knockdown of hsp90 by 17AAG resulted in the selective downregulation of AR, EGFR, HER2, and Akt expression/activity, while the decreased phosphorylation of GSK-3β mediated by PXD101 increased the nuclear expression of CRM1, which in turn modified the AR and survivin recycling with increased caspase 3 activity. HDAC inhibitors retain the ability to prevent the onset of castration-resistant phenotype and, therefore, merit clinical. Copyright © 2013 Society for Endocrinology. Source


Williams J.R.,Loma Linda University | Zhang Y.,Laboratory of Radiobiology | Zhou H.,Laboratory of Radiobiology | Gridley D.S.,Loma Linda University | And 4 more authors.
Radiation Oncology | Year: 2010

Background: We have previously shown that in vitro radiosensitivity of human tumor cells segregate non-randomly into a limited number of groups. Each group associates with a specific genotype. However we have also shown that abrogation of a single gene (p21) in a human tumor cell unexpectedly sensitized xenograft tumors comprised of these cells to radiotherapy while not affecting in vitro cellular radiosensitivity. Therefore in vitro assays alone cannot predict tumor response to radiotherapy.In the current work, we measure in vitro radiosensitivity and in vivo response of their xenograft tumors in a series of human tumor lines that represent the range of radiosensitivity observed in human tumor cells. We also measure response of their xenograft tumors to different radiotherapy protocols. We reduce these data into a simple analytical structure that defines the relationship between tumor response and total dose based on two coefficients that are specific to tumor cell genotype, fraction size and total dose.Methods: We assayed in vitro survival patterns in eight tumor cell lines that vary in cellular radiosensitivity and genotype. We also measured response of their xenograft tumors to four radiotherapy protocols: 8 × 2 Gy; 2 × 5Gy, 1 × 7.5 Gy and 1 × 15 Gy. We analyze these data to derive coefficients that describe both in vitro and in vivo responses.Results: Response of xenografts comprised of human tumor cells to different radiotherapy protocols can be reduced to only two coefficients that represent 1) total cells killed as measured in vitro 2) additional response in vivo not predicted by cell killing. These coefficients segregate with specific genotypes including those most frequently observed in human tumors in the clinic. Coefficients that describe in vitro and in vivo mechanisms can predict tumor response to any radiation protocol based on tumor cell genotype, fraction-size and total dose.Conclusions: We establish an analytical structure that predicts tumor response to radiotherapy based on coefficients that represent in vitro and in vivo responses. Both coefficients are dependent on tumor cell genotype and fraction-size. We identify a novel previously unreported mechanism that sensitizes tumors in vivo; this sensitization varies with tumor cell genotype and fraction size. © 2010 Williams et al; licensee BioMed Central Ltd. Source

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