Purpose-Development of a radiosensitivity predictive assay is a central goal of radiation oncology. We reasoned a gene expression model could be developed to predict intrinsic radiosensitivity and treatment response in patients.Methods and Materials-Radiosensitivity (determined by survival fraction at 2 Gy) was modeled as a function of gene expression, tissue of origin, ras status (mut/wt), and p53 status (mut/wt) in 48 human cancer cell lines. Ten genes were identified and used to build a rank-based linear regression algorithm to predict an intrinsic radiosensitivity index (RSI, high index = radioresistance). This model was applied to three independent cohorts treated with concurrent chemoradiation: head-and-neck cancer (HNC, n = 92); rectal cancer (n = 14); and esophageal cancer (n = 12).Results-Predicted RSI was significantly different in responders (R) vs. nonresponders (NR) in the rectal (RSI R vs. NR 0.32 vs. 0.46, p = 0.03), esophageal (RSI R vs. NR 0.37 vs. 0.50, p = 0.05) and combined rectal/esophageal (RSI R vs. NR 0.34 vs. 0.48, p = 0.001511) cohorts. Using a threshold RSI of 0.46, the model has a sensitivity of 80%, specificity of 82%, and positive predictive value of 86%. Finally, we evaluated the model as a prognostic marker in HNC. There was an improved 2-year locoregional control (LRC) in the predicted radiosensitive group (2-year LRC 86% vs. 61%, p = 0.05).Conclusions-We validate a robust multigene expression model of intrinsic tumor radiosensitivity in three independent cohorts totaling 118 patients. To our knowledge, this is the first time that a systems biology-based radiosensitivity model is validated in multiple independent clinical datasets.

Purpose The discovery of effective biomarkers is a fundamental goal of molecular medicine. Developing a systems-biology understanding of radiosensitivity can enhance our ability of identifying radiation-specific biomarkers. Methods and Materials Radiosensitivity, as represented by the Survival Fraction at 2 Gy (SF2) was modeled in 48 human cancer cell lines. We apply a linear regression algorithm that integrates gene expression with biological variables including: ras status (mut/wt), tissue of origin (TO) and p53 status (mut/wt). Results The biomarker discovery platform is a network representation of the top 500 genes identified by linear regression. This network was reduced to a 10-hub network that includes: c-Jun, HDAC1, RELA (p65 subunit of NFKB), PKC-beta, SUMO-1, c-Abl, STAT1, AR, CDK1 and IRF1. Nine targets associated with radiosensitization drugs link to the network, demonstrating clinical relevance. Furthermore, the model identifies four significant radiosensitivity clusters of terms and genes. Ras was a dominant variable in the analysis along with TO and their interaction with gene expression but not p53. Overrepresented biological pathways differed between clusters but included: DNA repair, cell cycle, apoptosis and metabolism. The c-Jun network hub was validated using a knockdown approach in 8 human cell lines representing lung, colon and breast cancers. Conclusions We developed a novel radiation-biomarker discovery platform using a systems biology modeling approach. We propose this platform will play a central role in the integration of biology into clinical radiation oncology practice.

Studies on the expression and cellular function of sigma receptors in autonomic neurons were conducted in neonatal rat intracardiac and superior cervical (SCG) ganglia. Individual neurons from SCG and intracardiac ganglia were shown to express transcripts encoding the sigma-1 receptor using single-cell RT-PCR techniques. The relationship between sigma receptors and calcium channels was studied in isolated neurons of these ganglia under voltage-clamp mode using the perforated-patch configuration of the whole cell patch-clamp recording technique. Bath application of sigma receptor agonists was shown to rapidly depress peak calcium channel currents in a reversible manner in both SCG and intracardiac ganglion neurons. The inhibition of barium (I(Ba)) currents was dose-dependent, and half-maximal inhibitory concentration (IC50) values for haloperidol, ibogaine, (+)-pentazocine, and 1,3-Di-O-tolylguanidin (DTG) were 6, 31, 61, and 133 microM, respectively. The rank order potency of haloperidol > ibogaine > (+)-pentazocine > DTG is consistent with the effects on calcium channels being mediated by a sigma-2 receptor. Preincubation of neurons with the irreversible sigma receptor antagonist, metaphit, blocked DTG-mediated inhibition of Ca2+ channel currents. Maximum inhibition of calcium channel currents was > or =95%, suggesting that sigma receptors block all calcium channel subtypes found on the cell body of these neurons, which includes N-, L-, P/Q-, and R-type calcium channels. In addition to depressing peak Ca2+ channel current, sigma receptors altered the biophysical properties of these channels. Following sigma receptor activation, Ca2+ channel inactivation rate was accelerated, and the voltage dependence of both steady-state inactivation and activation shifted toward more negative potentials. Experiments on the signal transduction cascade coupling sigma receptors and Ca2+ channels demonstrated that neither cell dialysis nor intracellular application of 100 microM guanosine 5'-O-(2-thiodiphosphate) trilithium salt (GDP-beta-S) abolished the modulation of I(Ba) by sigma receptor agonists. These data suggest that neither a diffusible cytosolic second messenger nor a G protein is involved in this pathway. Activation of sigma receptors on sympathetic and parasympathetic neurons is likely to modulate cell-to-cell signaling in autonomic ganglia and thus the regulation of cardiac function by the peripheral nervous system.

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