FT-IR/GC-MS MODELS FOR PREDICTING PROSTATE CANCER

我们已经证明了傅里叶变换红外(FT-IR)光谱， 与先进的统计数据相结合，是区分 在正常组织、癌前组织和癌症组织的DNA之间，从而使 建立癌症概率关系是可能的。此前， 我们表明，可比较的癌症概率关系可能是 使用诱变剂和其他修饰的碱基结构建立的 采用气相色谱-质谱法(GC-MS)。总体目标 拟议工作的一部分是进一步探索这些 前列腺癌病因的理解和预测模型 它发生在肿瘤发生的早期阶段。具体目标是(一) 在一项盲法研究中，验证我们发表的癌症概率模型 基于FT-IR/统计技术的DNA识别 前列腺癌(腺癌)、良性前列腺增生(BPH)和 形态正常的前列腺组织，使用数量增加的 根据年龄进行调整的病例。预计这将确认我们发布的 基于相对较小数字的癌症概率模型 样本；(Ii)从外围设备获得具有代表性的样本， 正常前列腺癌和前列腺癌的中央和移行区 (70%、20%和10%的癌症是由此产生的)和 确定每个区域DNA结构的差异，使用 FT-IR/统计技术；(Iii)用GC-MS测定自由基- 在DNA中诱导碱基修饰(如8-羟基鸟嘌呤) (Ii)具有代表性的样本，并将结果与 通过FT-IR/统计技术获得；(4)确定差异 前列腺癌DNA与原发癌DNA的比较 基于FT-IR/统计和GC-MS模型的转移；以及 (5)应用最新开发的设备来减少 FT-IR光谱分析所需的前列腺DNA大幅减少 并证明它产生的红外光谱是 在统计上无法与目前使用 样本量大得多。在这些研究的结论中，我们预计 极大地提高了对肺炎的病因的理解 为前列腺癌的预测奠定了良好的基础。

We have shown that Fourier-transform-infrared (FT-IR) spectroscopy, coupled with advanced statistics, is a powerful means for discriminating between the DNA of normal, pre-malignant and cancer tissues, thus making it possible to establish cancer probability relationships. Previously, we showed that comparable cancer probability relationships could be established using mutagenic and other modified base structures evinced by gas chromatography-mass spectrometry (GC-MS). The overall objective of the proposed work is to further explore the capability of these models for understanding the etiology of prostate cancer and predicting its occurrence at early stages of oncogenesis. The specific aims are (I) to validate, in a blinded study, our published cancer probability models of DNA based on FT-IR/statistics technology for distinguishing between prostate cancer (adenocarcinoma), benign prostatic hyperplasia (BPH) and morphologically normal prostate tissue, using an increased number of cases adjusted for age. This would be expected to confirm our published cancer probability models that were based on a relatively small number of samples; (II) to obtain representative samples from the peripheral, central and transition zones of normal and cancerous prostate glands (from which 70 percent, 20 percent and 10 percent of cancers arise) and determine differences in the DNA structures from each zone, using the FT-IR/statistics technology; (III) to determine, with GC-MS, radical- induced base modifications in DNA (e.g., 8-hydroxyguanine) using representative samples from (II) and correlate the results with those obtained by FT-IR/statistics technology; (IV) to determine differences between the DNA of primary prostatic adenocarcinoma and primary tumors that have metastasized based on FT-IR/statistics and GC-MS models; and (V) to apply recently developed equipment for reducing the amount of prostate DNA required for FT-IR spectral analysis to substantially less than a 1.0mug and demonstrate that it produces IR spectra that are statistically indistinguishable from spectra presently obtained with much larger sample sizes. At the conclusion of these studies we expect to have significantly increased understanding of the etiology of prostate cancer and established a promising basis for cancer prediction.