Hilmar Warenius

Exit from G2 phase after 2 gy gamma irradiation is faster in radiosensitive human cells with high expression of the RAF1 proto-oncogene

We have previously noted that high endogenous expression of the protein product of the full-length RAF1 proto-oncogene is related to relative intrinsic cellular radiosensitivity in 19 human cells lines in vitro. This appeared to be unrelated to the parameters of cell kinetics. In rodent and human cell lines transfected with dominant oncogenes, including Myc and MYC, Hras and HRAS and SV40, increased radioresistance has been accompanied by increased delay in progress through the G2 phase of the cell cycle after irradiation. We have thus examined the putative relationship between RAF1 expression and postirradiation perturbation of G2 phase in six of the human cell lines for which data have been reported previously. These lines exhibit a wide range of both radiosensitivity and Raf1 protein levels as measured previously by Western blotting. We report here that the cell lines whose cells appear to exit more rapidly from G2 phase are more radiosensitive (r = 0.91, P = 0.01) and express high levels of Raf1 protein (r = -0.93, P = 0.006).

The Influence of Hypoxia on the Relative Sensitivity of Human Tumor Cells to 62.5 MeV (p→Be) Fast Neutrons and 4 MeV Photons

Abstract Warenius, H. M., White, R., Peacock, J. H., Hanson, J., Britten, R. A. and Murray, D. The Influence of Hypoxia on the Relative Sensitivity of Human Tumor Cells to 62.5 MeV (p→Be) Fast Neutrons and 4 MeV Photons. Fast neutrons have been used in the clinical radiation therapy of tumors largely because of experimental evidence that their cytotoxic effects are much less dependent on oxygen levels than those of low-LET photons. The potential therapeutic advantage of fast neutrons based on hypoxia alone can be calculated as the “hypoxic gain factor”, which is the ratio of the OERs for the fast-neutron compared to the photon beams. The hypoxic gain factor that is generally anticipated based on studies with established mammalian cell lines is about 1.6. However, surprisingly few studies have examined the influence of hypoxia on the fast-neutron radiosensitivity of human tumor cells of different histological types. For this reason, we have determined the OERs of five human tumor cell lines exposed to 62.5 MeV (p→Be) cyclotron-generated fast neutrons or 4 MeV photons from a clinical linear accelerator. The OERs for four chemotherapy-naive cell lines, HT29/5, Hep2, HeLa and RT112, were invariably greater for photons than for neutrons, but all of these values were lower than expected on the basis of the previous literature. Despite their low OERs, these cell lines showed hypoxic gain factors that were within the range of 1.31−1.63, indicating that such effects cannot entirely explain the disappointing clinical results obtained with fast neutrons. In contrast, comparison of the surviving fractions at clinically relevant doses (1.6 Gy of neutrons and 2.0 Gy of photons) for these four tumor cell lines suggested that little benefit should result from neutron treatment. Only the cisplatin-resistant OAW42-CP line showed a significant hypoxic gain factor by this method of analysis. We conclude that, at the dose fractions used in clinical radiation therapy, there may not be a radiobiological precedent for higher local control rates after fast-neutron irradiation of hypoxic tumor cells.

Technological challenges of theranostics in oncology

BACKGROUND Although the term theranostics has been coined only fairly recently, attempts to relate the level of biomarkers to therapeutic response in the oncology clinic go back several decades. After a long period in which a limited number of individual theranostic molecular biomarkers gained general clinical acceptance, extremely powerful genomic and proteomic technologies have now emerged. METHODS These technologies, reviewed here, promise a potential revolution in our ability to predict therapeutic response in cancer, and by so doing, guide new anticancer drugs more successfully into clinical oncology practice. A full understanding of the detailed molecular nature of clinical cancer is, however, still evolving. The need for appropriate models of the highly complex disease, against which we are attempting to direct effective therapy more accurately, is also addressed. These should include an understanding of genomic and proteomic heterogeneity, genetic instability and systems biology models of cancer that take into account recent demonstrations of the vastly increased mutational state of the average clinical cancer as compared with the normal cell(s) from which it arose. CONCLUSION The way forward in theranostics is, arguably, less dependent on further improvements in the already powerful genomic and proteomic technologies themselves than on our improved understanding of how we should apply them to the complex reality of the average clinical cancer.