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

我们已经表明，傅里叶变换红外（FT-IR）光谱， 再加上先进的统计数据，是一个强大的手段， 正常组织、癌前病变组织和癌组织的DNA之间的相互作用， 可以建立癌症概率关系。 在此之前， 我们发现，可比较的癌症概率关系可能是 使用诱变和其他修饰的基础结构建立， 通过气相色谱-质谱法（GC-MS）。 总体目标 建议的工作是进一步探索这些能力， 了解前列腺癌病因和预测的模型 其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， 基于FT-IR/统计学技术的DNA鉴别 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，使用增加数量的 按年龄调整的病例。 预计这将证实我们公布的 癌症概率模型是基于相对较少的 （二）从外周获得代表性样本， 正常和癌变前列腺的中央和过渡区 (from 70%，20%和10%的癌症发生）， 确定每个区域的DNA结构差异，使用 FT-IR/统计学技术;（III）GC-MS测定自由基- 诱导DNA中的碱基修饰（例如，8-羟基鸟嘌呤）， 来自（II）的代表性样品，并将结果与那些 通过FT-IR/统计技术获得;（IV）确定差异 原发性前列腺癌与原发性肿瘤DNA之间的关系 根据FT-IR/统计学和GC-MS模型，已经转移;以及 (V)应用最新开发的设备， FT-IR光谱分析所需的前列腺DNA大大减少 并证明它产生的红外光谱是 统计上与目前获得的光谱无法区分， 更大的样本量。 在这些研究结束时，我们预计 对疾病的病因学有了更深入的了解 前列腺癌，为癌症预测建立了有希望的基础。

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.