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.
