Malins D C, Polissar N L, Gunselman S J
Molecular Epidemiology Program, Pacific Northwest Research Foundation, Seattle, WA 98122, USA.
Proc Natl Acad Sci U S A. 1997 Jan 7;94(1):259-64. doi: 10.1073/pnas.94.1.259.
In our previous studies of DNA, wavenumber-absorbance relationships of infrared spectra analyzed by principal components analysis (PCA) were expressed as points in space. Each point represented a highly discriminating measure of structural modifications that altered vibrational and rotational motion, thus changing the spatial orientation of the points. PCA/Fourier transform-infrared technology has now provided a virtually perfect separation of clusters of points representing DNA from normal prostate tissue, BPH, and adenocarcinoma. The findings suggest that the progression of normal prostate tissue to BPH and to prostate cancer involves structural alterations in DNA that are distinctly different. The hydroxyl radical is likely a major contributor to these structural alterations, which is consistent with previous studies of breast cancer. Models based on logistic regression of infrared spectral data were used to calculate the probability of a tissue being BPH or adenocarcinoma. The models had a sensitivity and specificity of 100% for classifying normal vs. cancer and normal vs. BPH, and close to 100% for BPH vs. cancer. Thus, the PCA/Fourier transform-infrared technology was shown to be a powerful means for discriminating between normal prostate tissue, BPH and prostate cancer and has considerable promise for risk prediction and clinical application.
在我们之前对DNA的研究中，通过主成分分析（PCA）分析的红外光谱的波数-吸光度关系以空间中的点来表示。每个点代表了对结构修饰的高度鉴别性测量，这些修饰改变了振动和旋转运动，从而改变了点的空间取向。PCA/傅里叶变换红外技术现在已经实现了代表DNA的点簇与正常前列腺组织、良性前列腺增生（BPH）和腺癌之间几乎完美的分离。这些发现表明，正常前列腺组织向BPH和前列腺癌的进展涉及DNA中明显不同的结构改变。羟基自由基可能是这些结构改变的主要促成因素，这与先前对乳腺癌的研究一致。基于红外光谱数据的逻辑回归模型用于计算组织为BPH或腺癌的概率。这些模型对正常与癌症以及正常与BPH分类的敏感性和特异性均为100%，对BPH与癌症分类的敏感性和特异性接近100%。因此，PCA/傅里叶变换红外技术被证明是区分正常前列腺组织、BPH和前列腺癌的有力手段，并且在风险预测和临床应用方面具有很大的前景。
