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乳腺上皮细胞与癌细胞的激光镊子拉曼光谱研究 被引量:2

Laser tweezers Raman spectrum of normal breast cell line and carcinoma breast cell line
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摘要 目的:研究人正常上皮乳腺细胞株(HBL-100)和乳腺癌细胞株(MCF-7)的单细胞拉曼光谱与分子生物学变化之间的关系,以及癌变发生发展过程中生物组分的变化,以期建立乳腺癌细胞的特征拉曼光谱库。方法:分别测试了正常乳腺细胞株和乳腺癌细胞株的拉曼光谱,结果用PCA主成分分析。结果:乳腺癌细胞和乳腺正常细胞间的平均光谱存在较多的差异;乳腺癌细胞的谱线强度整体变强;乳腺癌细胞的936、1002、1298和1445cm-1的峰高升高,1102cm-1峰移位到1094cm-1,484cm-1峰消失;乳腺癌癌细胞的核酸、蛋白质、脂类等重要生物分子在结构或含量都发生了不同的改变。用PCA主成分对单个细胞的平均拉曼光谱进行分析发现,PCA可以正确区分乳腺正常细胞和癌细胞,PCA区分率为87%(13/15)。结论:激光镊子拉曼光谱是判断正常乳腺细胞和乳腺癌细胞的有效方法,单细胞光镊拉曼光谱技术有可能成为癌症诊断的新途径,具有广阔的前景。 OBJECTIVE:To detect the interaction between Raman spectrum of normal breast cell line(HBL-100)and carcinoma breast cell line(MCF-7),as well as the change of biological tissue composition from normal cell to carcinogenesis.In the end,Characteristic Raman spectra of cancer cells were presented.METHODS:Raman spectrum of normal breast cell line and carcinoma breast cell line were recorded,The result of which was performed by principal component analysis(PCA).RESULTS:Significant differences of average Raman spectrums were founded between the normal cell and the carcinoma one; The spectra line of carcinoma cell became strong at the whole; The strength of 936,1 002,1 298 and 1 445 cm-1 increased; the peak of 1102 cm-1 shifted to 1094 cm-1 ;the peak of 484 cm-1 disappeared; Additionally,the structure and the amount of protein,nucleic acid,lipids and other such molecules had also changed.Average Raman spectrum of monocell was analyzed with the principal component of PCA,the result of which suggested normal cell and carcinoma cell could be differentiated with PCA,The discrimination rate was 87%(13/15).CONCLUSIONS:Judging normal breast cell and carcinoma cell with laser tweezers Raman spectrums is an efficient method.Single cells laser tweezers raman spectra technique can become a new way to diagnose cancer,which has very wide prospect.
出处 《中华肿瘤防治杂志》 CAS 2010年第20期1605-1608,共4页 Chinese Journal of Cancer Prevention and Treatment
基金 国家自然科学基金(30760278)
关键词 拉曼光谱 乳腺肿瘤 主成分分析 激光镊子 Raman spectroscopy breast neoplasms principal component analysis laser tweezers
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