Genetic prodrug activation therapy (GPAT) in two rat prostate models generates an immune bystander effect and can be monitored by magnetic resonance techniques.

Treatment of hormone refractory prostate cancer requires new treatment strategies. Genetic prodrug activation therapy (GPAT) may provide a new therapeutic avenue. In this study the antitumour efficacy of the gene encoding herpes simplex virus thymidine kinase (HSVtk) activating the prodrug ganciclovir (GCV) was compared in two models of ectopic (subcutaneous) rat prostate cancer. Both models, which differ in their characteristics, were previously shown to be weakly immunogenic but susceptible to immunotherapy. Tumour cell lines were stably transfected with HSVtk and were rendered highly sensitive to GCV. Little or no bystander killing effect was observed by tk-transfected cells on wild-type cells in vitro. However, a significant in vivo bystander effect was observed suggesting an immune-mediated response. Indeed, such an immune response was capable of slowing the growth of distant wild-type tumours and increased overall animal survival. A T helper 1 immune response was generated as a result of GCV activation and cell kill, demonstrated by the secretion of IFNgamma by cultured splenocytes in response to tumour cells. BrDU staining of tk-transfected cells treated with GCV in vitro suggested apoptotic cell death, but Annexin V staining was less marked for one of the cell lines. Serial in vivo monitoring by non-invasive magnetic resonance spectroscopy (MRS) of the tk-transfected MATLyLu tumours demonstrated a decreased ATP/Pi ratio (a measure of cell energy status) during growth and an increase in the ATP/Pi ratio during regression initiated by treatment with GCV. Further, significant differences were found in the phosphomonester (PME) to total phosphate (SigmaP) ratios in treated compared with untreated tumours, a result rarely seen in animal models, but commonly observed in patients. This study showed that a Th1-biased immune response generated by killing prostate tumour cells with tk/GCV can kill distant as well as local wild-type tumour cells. These findings suggest that GPAT may have a potential application in patients with both confined and metastatic prostate cancer and MRS may provide a method of monitoring response to treatment.

Pattern recognition analysis of 1H NMR spectra from perchloric acid extracts of human brain tumor biopsies.

Pattern recognition techniques (factor analysis and neural networks) were used to investigate and classify human brain tumors based on the 1H NMR spectra of chemically extracted biopsies (n = 118). After removing information from lactate (because of variable ischemia times), unsupervised learning suggested that the spectra separated naturally into two groups: meningiomas and other tumors. Principal component analysis reduced the dimensionality of the data. A back-propagation neural network using the first 30 principal components gave 85% correct classification of meningiomas and nonmeningiomas. Simplification by vector rotation gave vectors that could be assigned to various metabolites, making it possible to use or to reject their information for neural network classification. Using scores calculated from the four rotated vectors due to creatine and glutamine gave the best classification into meningiomas and nonmeningiomas (89% correct). Classification of gliomas (n = 47) gave 62% correct within one grade. Only inositol showed a significant correlation with glioma grade.

Lipid metabolite peaks in pattern recognition analysis of tumour in vivo MR spectra.

The ability to classify spectra of tumours according to their stage and type will be essential if magnetic resonance spectroscopy (MRS) is to be used as an aid in the diagnosis of cancer. MRS data are normally classified on the basis of selected peak measurements but these may be difficult to extract automatically. We present two alternative methods of feature extraction which we used to discriminate between spectra from tumours and normal tissues. Discrimination could be achieved either using features from the whole spectrum, or from a selected region containing the peaks from the phospholipid precursors in the phosphomonoester region.