The events of 9/11 sparked a revitalization of civil defense in the U.S. for emergency planning and preparedness for future radiological or nuclear event scenarios and specifically for mass casualty medical management of radiation exposure and injury. Research in medical countermeasure development in the form of novel pharmaceuticals to treat radiation injury and new radiation biodosimetry diagnostics, primarily focused on development of research models of uniform total-body irradiation (TBI). With the success of those models, it was recognized that most radiation exposures in the field will involve non-uniform heterogeneous irradiations and many partial-body or organ-specific irradiation models have been utilized. This review examines partial-body models of irradiations developed in the last decade for heterogeneous radiation exposures and organ-specific radiation exposure patterns. These research models have been used to further our understanding of radiation injury, novel medical countermeasures and biodosimetry diagnostics in development for future radiological and nuclear event scenarios.

Purpose/Objective(s) Glioblastoma (GBM) is characterized by poor survival outcomes and high rates of recurrence due to rapid proliferation and treatment resistance. The CXCL family of chemokines has been implicated in multiple aspects of GBM biology, including angiogenesis and tumor progression. There is a pressing need to identify clinically relevant, easily measurable biomarkers to further the understanding of treatment response. CXCL levels in GBM patients before and after chemoirradiation therapy (CRT) were analyzed for alteration in serum and relationship to clinical and radiation therapy (RT) data. Materials/Methods Serum samples from 109 patients with pathologically proven GBM (diagnosed 2005-2023) were collected before and after the completion of CRT and analyzed using the Somalogic 7k proteomic panel. 21 members of the CXCL family were identified, 14 of which were unique. CXCL levels were linked to clinical and RT data. Statistical analyses (Wilcoxon test, Spearman r correlation, Kaplan Meier) were performed to explore alterations following treatment and associations with clinical features, overall survival (OS), and progression free survival (PFS). Results Eight unique CXCLs were found to be significantly altered with CRT: CXCL2 (P = 0.0002), CXCL3 (P<0.0001), CXCL5 (P<0.0001), CXCL6 (P = 0.023), CXCL10 (P<0.0001), CXCL11 (P<0.0001), CXCL13 (P = 0.014), and CXCL16 (P<0.0001). CXCL2, 3, 5, 6, and 11 decreased while CXCL10, 13, and 16 increased in response to CRT. Statistically significant interactions were noted between chemokines and between clinical variables. CXCL1, 2, 3, 5, and 6 were strongly directly correlated with each other (P<0.05) and were weakly inversely correlated with age (CXCL1, 2, 3). CXCL16 alteration following CRT was inversely correlated with the alteration of CXCL1, 2, 3, 6, and 13 while being directly correlated with the alteration of CXCL8 and 10 (P<0.05). OS and PFS were strongly associated with age, MGMT status, and GTVT1 (P<0.05). CXCL16 was associated with MGMT status with MGMT methylated patients exhibiting more significant increases in serum CXCL16 (P = 0.026) pre vs. post CRT. Elevated CXCL16 was associated with improved OS (P = 0.031) (median OS 27 months increased levels vs. 18 months for lower or decreased levels) but was not associated with PFS. Pre CRT CXCL5 had the strongest direct correlation with GTVT1 (P = 0.005) and GTVT2 (P = 0.008) while pre–CRT CXCL13 was directly correlated with GTVT2 only (P = 0.006); however, neither was associated with OS or PFS. Conclusion Several members of the CXCL family are measurable in serum and significantly altered in response to CRT in GBM patients. The directionality of these changes and further analysis with clinical and RT data could enhance the understanding of molecular signaling pathways relevant to the GBM response to CRT. Association of CXCL16 with MGMT status may indicate potential for these molecules to be employed as biomarkers in GBM.

There is a need for point-of-care diagnostics for future mass casualty events involving radiation exposure. The development of radiation exposure and dose prediction algorithms for biodosimetry is needed for screening of large populations during these scenarios, and exploration of the potential effects which sex, age, genetic heterogeneity, and physiological comorbidities may have on the utility of biodosimetry diagnostics is needed. In the current study, proteomic profiling was used to examine sex-specific differences in age-matched C57BL6 mice on the blood proteome after radiation exposure, and the usefulness of development and application of biodosimetry algorithms using both male and female samples. Male and female mice between 9-11 weeks of age received a dose of total-body irradiation (TBI) of either 2, 4 or 8 Gy and plasma was collected at days 1, 3 and 7 postirradiation. Plasma was then screened using the SomaScan v4.1 assay for similar to 7,000 protein analytes. A subset panel of protein biomarkers demonstrated significant (FDR < 0.05 and vertical bar logFC vertical bar > 0.2) changes in expression after radiation exposure. All proteins were used for feature selection to build predictive models of radiation exposure using different sample and sex-specific cohorts. Both binary (prediction of any radiation exposure) and multidose (prediction of specific radiation dose) model series were developed using either female and male samples combined or only female or only male samples. The binary series (models 1, 2 and 3) and multidose series (models 4, 5 and 6) included female/male combined, female only and male only respectively. Detectable values were obtained for all similar to 7,000 proteins included in the SomaScan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies in the binary model series was similar to 100% at the model training level, and when tested with fresh samples, 97.9% for model 1 (female and male) and 100% for model 2 (female only) and model 3 (male only). When sex-specific models 2 and 3 were tested with the opposite sex, the overall predictive accuracy rate dropped to 62.5% for model 2 and remained 100% for model 3. The overall predictive accuracy rate in the multidose model series was 100% for all models at the model training level and, when tested with fresh samples, 83.3%, 75% and 83.3% for Multidose models 4-6, respectively. When sex-specific model 5 (female only) and model 6 (male only) were tested with the opposite sex, the overall predictive accuracy rate dropped to 52.1% and 68.8%, respectively. These models represent novel predictive panels of radiation-responsive proteomic biomarkers and illustrate the utility and necessity of considering sex-specific differences in development of radiation biodosimetry prediction algorithms. As sex-specific differences were observed in this study, and as use of point-of-care radiation diagnostics in future mass casualty settings will necessarily include persons of both sexes, consideration of sex-specific variation is essential to ensure these diagnostic tools have practical utility in the field. (c) 2024 by Radiation Research Society

In future mass casualty medical management scenarios involving radiation injury, medical diagnostics to both identify those who have been exposed and the level of exposure will be needed. As almost all exposures in the field are heterogeneous, determination of degree of exposure and which vital organs have been exposed will be essential for effective medical management. In the current study we sought to characterize novel proteomic biomarkers of radiation exposure and develop exposure and dose prediction algorithms for a variety of exposure paradigms to include uniform total-body exposures, and organ-specific partial-body exposures to only the brain, only the gut and only the lung. C57BL6 female mice received a single total-body irradiation (TBI) of 2, 4 or 8 Gy, 2 and 8 Gy for lung or gut exposures, and 2, 8 or 16 Gy for exposure to only the brain. Plasma was then screened using the SomaScan v4.1 assay for ∼7,000 protein analytes. A subset panel of protein biomarkers demonstrating significant (FDR<0.05 and |logFC|>0.2) changes in expression after radiation exposure was characterized. All proteins were used for feature selection to build 7 different predictive models of radiation exposure using different sample cohort combinations. These models were structured according to practical field considerations to differentiate level of exposure, in addition to identification of organ-specific exposures. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. The overall predictive accuracy for all models was 100% at the model training level. When tested with reserved samples Model 1 which compared an “exposure” group inclusive of all TBI and organ-specific partial-body exposures in the study vs. control, and Model 2 which differentiated between control, TBI and partials (all organ-specific partial-body exposures) the resulting prediction accuracy was 92.3% and 95.4%, respectively. For identification of organ-specific exposures vs. control, Model 3 (only brain), Model 4 (only gut) and Model 5 (only lung) were developed with predictive accuracies of 78.3%, 88.9% and 94.4%, respectively. Finally, for Models 6 and 7, which differentiated between TBI and separate organ-specific partial-body cohorts, the testing predictive accuracy was 83.1% and 92.3%, respectively. These models represent novel predictive panels of radiation responsive proteomic biomarkers and illustrate the feasibility of development of biodosimetry algorithms with utility for simultaneous classification of total-body, partial-body and organ-specific radiation exposures.

The discovery of X rays in the late 19th century heralded the beginning of a new age in medicine, and the advent of channeling the power of radiation to diagnose and treat human disease. Radiation has been leveraged in medicine in a multitude of ways and is a critical element of cancer care including screening, diagnosis, surveillance, and interventional treatments. Modern radiotherapy techniques include a multitude of methodologies utilizing both externally and internally delivered radiation from a variety of approaches. This review provides a comprehensive overview of contemporary radiotherapy methodologies, the field of radiopharmaceuticals and theranostics, effects of low dose radiation and highlights the phenomena of fear of exposure to radiation and its impact in modern medicine.

There is a need to identify new biomarkers of radiation exposure for not only systemic total-body irradiation (TBI) but also to characterize partial-body irradiation and organ specific radiation injury. In the current study, we sought to develop novel biodosimetry models of radiation exposure using TBI and organ specific partial-body irradiation to only the brain, lung or gut using a multivariate proteomics approach. Subset panels of significantly altered proteins were selected to build predictive models of radiation exposure in a variety of sample cohort configurations relevant to practical field application of biodosimetry diagnostics during future radiological or nuclear event scenarios. Female C57BL/6 mice, 8–15 weeks old, received a single total-body or partial-body dose of 2 or 8 Gy TBI or 2 or 8 Gy to only the lung or gut, or 2, 8 or 16 Gy to only the brain using a Pantak X-ray source. Plasma was collected by cardiac puncture at days 1, 3 and 7 postirradiation for total-body exposures and only the lung and brain exposures, and at days 3, 7 and 14 postirradiation for gut exposures. Plasma was then screened using the aptamer-based SOMAscan proteomic assay technology, for changes in expression of 1,310 protein analytes. A subset panel of protein biomarkers which demonstrated significant changes (P < 0.01) in expression after irradiation were used to build predictive models of radiation exposure using different sample cohorts. Model 1 compared controls vs. all pooled irradiated samples, which included TBI and all organ specific partial irradiation. Model 2 compared controls vs. TBI vs. partial irradiation (with all organ specific partial exposure pooled within the partial-irradiated group), and model 3 compared controls vs. each individual organ specific partial-body exposure separately (brain, gut and lung). Detectable values were obtained for all 1,310 proteins included in the SOMAscan assay for all samples. Each model algorithm built using a unique sample cohort was validated with a training set of samples and tested with a separate new sample series. Overall predictive accuracies of 89%, 78% and 55% resulted for models 1–3, respectively, representing novel predictive panels of radiation responsive proteomic biomarkers. Though relatively high overall predictive accuracies were achieved for models 1 and 2, all three models showed limited accuracy at differentiating between the controls and partial-irradiated body samples. In our study we were able to identify novel panels of radiation responsive proteins useful for predicting radiation exposure and to create predictive models of partial-body exposure including organ specific radiation exposures. This proof-of-concept study also illustrates the inherent physiological limitations of distinguishing between small-body exposures and the unirradiated using proteomic biomarkers of radiation exposure. As use of biodosimetry diagnostics in future mass casualty settings will be complicated by the heterogeneity of partial-body exposure received in the field, further work remains in adapting these diagnostic tools for practical use.

e15147 Background: Prostate cancer is the second most common cause of cancer related death for men in the United States. Osteopontin (OPN) is an extracellular structural protein that is over-expressed in various cancers and is associated with tumor angiogenesis and metastasis. We investigated whether normalized OPN levels can be used as a noninvasive biomarker for localized and metastatic prostate cancer. Methods: Urine samples were collected from healthy men (n=19) as well as men with localized cancer prior to receiving radiation therapy (n=65) and men with metastatic prostate cancer (n=36). Samples were assayed in duplicate via an Enzyme Linked Immunosorbent Assay specific to Osteopontin-1 (R&D Systems). Osteopontin values were corrected for urinary creatinine levels obtained using Bayer DCA 2000+ Analyzer (Bayer Healthcare). Results: The mean normalized OPN levels for healthy men (mean: 532.4 ng/mg, range: 51.0 – 1559.0), men with localized cancer (mean: 613.6 ng/mg, range: 2.3 – 2716.0) and men with metastatic cancer (mean: 1024.0 ng/mg, range: 123.6 – 3304.0) were significantly different from each other (p=0.016, Kruskal-Wallis nonparametric ANOVA test). Furthermore, the urinary OPN levels were significantly different between healthy and metastatic groups (p=0.006), as well as between the localized and metastatic groups (p=0.0086). The area under the ROC curve distinguishing between healthy and metastatic groups was 0.70 (p=0.01392, 95% confidence interval of 0.56 to 0.85) and between localized and metastatic groups was 0.65 (p=0.01389, 95% confidence interval of 0.53 to 0.77). Conclusions: Urinary osteopontin levels can be used to identify patients with prostate cancer and differentiate between patients with localized and metastatic disease.

e15144 Background: Hepatocyte growth factor or scatter factor has been linked to the proliferation, motility, and metastatic invasion of cancer cells. Pro-HGF, an inactive precursor, is cleaved into a biologically active heterodimeric form called activated HGF (AHGF). We evaluated the potential of AHGF as a diagnostic and prognostic urinary biomarker candidate for prostate cancer.METHODSUrinary levels of AHGF were determined via enzyme linked immunosorbent assay (Immuno-Biological Laboratories Co., Ltd, Japan) in duplicate. Samples were compared between men with localized (n=65) and metastatic (n=36) cancer and a healthy control group of men (n=19). AHGF concentrations were normalized with creatinine (Bayer DCA 2000+ Analyzer).RESULTSThe difference of urinary AHGF levels between the control group (mean: 111.3 pg/mg, range: 27.0-250.0) and the prostate cancer groups (mean: 230.1 pg/mg, range: 20.9-1010.0) was statistically significant (p<0.0001). Furthermore, urinary AHGF concentrations were significantly different between the control and the localized group (mean: 235.2 pg/mg, range: 24.6-668.0) (p<0.0001) and between the control and the metastatic group (mean: 220.8 pg/mg, range: 20.9-1010.0) (p=0.0039). The area under the receiver operating characteristic curve associated with the diagnostic accuracy of HGF between control and prostate cancer groups was 0.75 (p=0.0006, 0.64 to 0.85 confidence interval). There was no significant difference between the localized and metastatic groups.CONCLUSIONSUrinary levels of activated HGF have the potential as a novel noninvasive diagnostic marker for prostate cancer.

There is a need to identify minimally invasive biomarkers that can be used to accurately and quickly determine radiation exposure. Radiation biodosimeters have applications in clinical medicine and for population screening following a nuclear or radiological event. In this study, we evaluated the efficacy of fms-like tyrosine kinase ligand (Flt3-L) as a biomarker for radiation exposure in plasma from whole body irradiated mice. Ten week old female C57BL6 mice received a single whole body irradiation dose of 1-8 Gy from a Pantak X-ray source at a dose rate of 2.28 Gy/min. Plasma was collected by cardiac puncture at 6, 24, 48 and 72hr post-IR as well as 1-3 weeks post-irradiation. Flt3-L levels were determined via a commercially available ELISA assay (R&D Systems). Data was pooled to generate a linear regression model and cluster dendrogram correlating plasma Flt3-L levels with radiation dose. At doses of 1, 4 and 8 Gy, Flt-3L levels were greater than control and the level of Flt3-L increased proportionally to the irradiation dose. At 24hr post-IR 1Gy averaged 376 pg/ml Flt3-L, 4Gy 947 pg/ml and 8Gy 1350 pg/ml Flt3-L. At 48hr post-IR, the averaged Flt3-L levels were 1Gy 730 pg/ml, 4Gy 1608 pg/ml and 8Gy 2100 pg/ml. Flt3-L at 72hr post-IR was 1Gy 632 pg/ml, 4Gy 1579 pg/ml and 8Gy 2065 pg/ml. Differences in Flt3-L levels were statistically significant at each dose and at all time points. The problem arises from overlap between Flt3-L averages from different dose groups at different time points where an outlier from one group might fall into the wrong dose category if dose calculation is based solely on Flt3-L levels without a known time point of irradiation. To reduce this error we looked at Flt3-L level trends over different time points post-IR. Samples were taken serially from the same mouse at 24hr and 72 hr. The Flt3-L trend over two sequential time points further validated the dose received. If Flt3-L levels remained constant the exposure was 1Gy or less, but if Flt3-L increased from 24hr to 72hr we could assume the mouse received a dose equal to or greater than 4Gy. This method reduced the false dose rate when determining radiation exposure when time of irradiation was unknown. Flt3-L levels at 24, 48 and 72 hrs were used to generate a mathematical model for determination of unknown radiation dose. In a blind study, the working model differentiated mice groups into dose received cohorts of 1, 4 or 8 Gy based on plasma Flt3-L levels irrespective of time of irradiation. Plasma Flt3-L levels at 24, 48 and 72 hrs consistently predicted radiation dose received in mice. Plasma Flt3-L has potential application as a radiation biodosimeter in mammalian systems.

Vascular endothelial growth factor (VEGF) is an angiogenic protein proposed to be an important biomarker for the prediction of tumour growth and disease progression. Recent studies suggest that VEGF measurements in biospecimens, including urine, may have predictive value across a range of cancers. However, the reproducibility and reliability of urinary VEGF measurements have not been determined. We collected urine samples from patients receiving radiation treatment for glioblastoma multiforme (GBM) and examined the effects of five variables on measured VEGF levels using an ELISA assay. To quantify the factors affecting the precision of the assay, two variables were examined: the variation between ELISA kits with different lot numbers and the variation between different technicians. Three variables were tested for their effects on measured VEGF concentration: the time the specimen spent at room temperature prior to assay, the addition of protease inhibitors prior to specimen storage and the alteration of urinary pH. This study found that VEGF levels were consistent across three different ELISA kit lot numbers. However, significant variation was observed between results obtained by different technicians. VEGF concentrations were dependent on time at room temperature before measurement, with higher values observed 3-7 hrs after removal from the freezer. No significant difference was observed in VEGF levels with the addition of protease inhibitors, and alteration of urinary pH did not significantly affect VEGF measurements. In conclusion, this determination of the conditions necessary to reliably measure urinary VEGF levels will be useful for future studies related to protein biomarkers and disease progression.

To report the early toxicity data from our Phase II trial of concurrent Valproic Acid (VPA), Temozolomide (TMZ) and radiotherapy (RT). The VPA is a histone deacetylase inhibitor that enhances the radiosensitivity of glioma cells in vitro and in vivo. We initiated a Phase II clinical trial of VPA, started one week prior to RT, concurrent with TMZ (75 mg/m2) and external beam RT to 60 Gy followed by adjuvant TMZ (150 mg/m2) for at least 6 cycles in patients with glioblastoma multiforme. The initial 2 patients received 50 mg/kg/BID of VPA. However, this dose was reduced to 25 mg/kg/BID after unexpected toxicities occurred. Random valproate levels and lymphocyte acetylation were assessed periodically during treatment to evaluate any correlation between these measures with efficacy or toxicity. A total of 9 patients have been enrolled with 7.5 months of median follow-up. The average patient age was 54 years old, 4/9 were RTOG RPA class 5, and 7/9 had sub-total resections. Average random VPA levels were 162 μg/mL and 110 μg/mL in the higher and lower dose groups, respectively. Lymphocyte histone acetylation status confirmed VPA was biologically active at both dose levels. Neurologic toxicities were the most common event during combined treatment with ataxia occurring in 4/9 patients. All neurological symptoms associated with VPA resolved within 48-72 hours after stopping VPA therapy. At the initial higher dose level, both patients experienced Grade 3 toxicities and 7/8 of these occurred during combined treatment. They included 5 neurologic events, 1 episode of thrombocytopenia, and 1 episode of fatigue. Of the 7 patients receiving the lowered dose of VA, only 2 experienced Grade 3 toxicities. One event, elevated lipase, occurred during combined treatment and the other, lymphopenia, occurred afterward. Grade 3 hematologic toxicity for both dose groups during and after combined treatment was seen in 1/9 and 1/9 patients, respectively. The VPA at 25 mg/kg/BID in combination with TMZ and RT can be given safely without significantly increased hematologic or neurologic toxicities compared with the RT and TMZ arm from the EORTC/NCIC study.

In this study, we sought to explore the merit of proteomic profiling strategies in patients with cancer before and during radiotherapy in an effort to discover clinical biomarkers of radiation exposure. Patients with a diagnosis of cancer provided informed consent for enrollment on a study permitting the collection of serum immediately before and during a course of radiation therapy. High-resolution surface-enhanced laser desorption and ionization-time of flight (SELDI-TOF) mass spectrometry (MS) was used to generate high-throughput proteomic profiles of unfractionated serum samples using an immobilized metal ion-affinity chromatography nickel-affinity chip surface. Resultant proteomic profiles were analyzed for unique biomarker signatures using supervised classification techniques. MS-based protein identification was then done on pooled sera in an effort to begin to identify specific protein fragments that are altered with radiation exposure. Sixty-eight patients with a wide range of diagnoses and radiation treatment plans provided serum samples both before and during ionizing radiation exposure. Computer-based analyses of the SELDI protein spectra could distinguish unexposed from radiation-exposed patient samples with 91% to 100% sensitivity and 97% to 100% specificity using various classifier models. The method also showed an ability to distinguish high from low dose-volume levels of exposure with a sensitivity of 83% to 100% and specificity of 91% to 100%. Using direct identity techniques of albumin-bound peptides, known to underpin the SELDI-TOF fingerprints, 23 protein fragments/peptides were uniquely detected in the radiation exposure group, including an interleukin-6 precursor protein. The composition of proteins in serum seems to change with ionizing radiation exposure. Proteomic analysis for the discovery of clinical biomarkers of radiation exposure warrants further study.

Defining the molecules that regulate tumor cell survival is an essential prerequisite for the development of targeted approaches to cancer treatment. Whereas many studies aimed at identifying such targets use human tumor cells grown in vitro or as s.c. xenografts, it is unclear whether such experimental models replicate the phenotype of the in situ tumor cell. To begin addressing this issue, we have used microarray analysis to define the gene expression profile of two human glioma cell lines (U251 and U87) when grown in vitro and in vivo as s.c. or as intracerebral (i.c.) xenografts. For each cell line, the gene expression profile generated from tissue culture was significantly different from that generated from the s.c. tumor, which was significantly different from those grown i.c. The disparity between the i.c gene expression profiles and those generated from s.c. xenografts suggests that whereas an in vivo growth environment modulates gene expression, orthotopic growth conditions induce a different set of modifications. In this study the U251 and U87 gene expression profiles generated under the three growth conditions were also compared. As expected, the profiles of the two glioma cell lines were significantly different when grown as monolayer cultures. However, the glioma cell lines had similar gene expression profiles when grown i.c. These results suggest that tumor cell gene expression, and thus phenotype, as defined in vitro is affected not only by in vivo growth but also by orthotopic growth, which may have implications regarding the identification of relevant targets for cancer therapy.

The effect of radiation on gene expression has been most frequently studied using tissue culture models. To determine the influence of experimental growth condition on radiation-induced changes in gene expression, microarray analysis was done on two human glioma cell lines (U87 and U251) grown in tissue culture and as s.c. or i.c. xenografts. Compared with tissue culture, the number of genes, whose expression was affected by radiation in both cell lines, was increased in the s.c. xenografts and further increased in the orthotopic tumors. Furthermore, in each growth condition, radiation modulated the expression of a different set of genes. In addition, whereas there were few commonly affected genes after irradiation of U87 and U251 in tissue culture, there were 729 common changes after orthotopic irradiation. These results indicate that the influence of the orthotopic environment on radiation-induced modulation of gene expression in glioma cells was both quantitative and qualitative. Moreover, they suggest that investigations of the functional consequence of radiation-induced gene expression will require accounting for experimental growth conditions.

Endostatin is a potent inhibitor of angiogenesis currently in phase I clinical trials. Imaging technologies that use near-infrared fluorescent probes are well suited to the laboratory setting. The goal of this study was to determine whether endostatin labeled with a near-infrared probe (Cy5.5) could be detected in an animal and whether it would selectively localize to a tumor. Endostatin was conjugated to Cy5.5 monofunctional dye and injected into mice bearing Lewis lung carcinoma tumors (350 mm2). Mice were imaged at various time points while under sedation using a lightproof box affixed to a fluorescent microscope mounted with a filter in the near-infrared bandwidth consistent with Cy5.5 fluorescence. After i.p. injection, endostatin-Cy5.5 was absorbed producing a near-infrared fluorescent image within the tumors at 18 h reaching a maximum at 42 h after injection. No signal was emitted from mice injected with unlabeled endostatin or Cy5.5 dye alone or those that received no injection. Further results show that a dose response exists with injection of endostatin-Cy5.5. Mimicking the clinical route of administration, an i.v. injection had a peak signal emission at 3 h but also persisted to 72 h. Finally, to determine the intratumoral binding site for endostatin, we performed immunofluorescence on tumor specimens and demonstrated that endostatin binds to tumor vasculature and colocalizes with platelet/endothelial cell adhesion molecule 1 expression. This study demonstrates that endostatin covalently bound to Cy5.5 will migrate from a distant i.p. injection site to a tumor. These data indicate that endostatin-Cy5.5 is appropriate for selectively imaging tumors in uninjured experimental animals.

Valproic acid (VA) is a well-tolerated drug used to treat seizure disorders and has recently been shown to inhibit histone deacetylase (HDAC). Because HDAC modulates chromatin structure and gene expression, parameters considered to influence radioresponse, we investigated the effects of VA on the radiosensitivity of human brain tumor cells grown in vitro and in vivo. The human brain tumor cell lines SF539 and U251 were used in our study. Histone hyperacetylation served as an indicator of HDAC inhibition. The effects of VA on tumor cell radiosensitivity in vitro were assessed using a clonogenic survival assay and gammaH2AX expression was determined as a measure of radiation-induced DNA double strand breaks. The effect of VA on the in vivo radioresponse of brain tumor cells was evaluated according to tumor growth delay analysis carried out on U251 xenografts. Irradiation at the time of maximum VA-induced histone hyperacetylation resulted in significant increases in the radiosensitivity of both SF539 and U251 cells. The radiosensitization was accompanied by a prolonged expression of gammaH2AX. VA administration to mice resulted in a clearly detectable level of histone hyperacetylation in U251 xenografts. Irradiation of U251 tumors in mice treated with VA resulted in an increase in radiation-induced tumor growth delay. Valproic acid enhanced the radiosensitivity of both SF539 and U251 cell lines in vitro and U251 xenografts in vivo, which correlated with the induction of histone hyperacetylation. Moreover, the VA-mediated increase in radiation-induced cell killing seemed to involve the inhibition of DNA DSB repair.

Microarray technology allows the rapid and simultaneous screening of gene expression at the level of mRNA. We sought to evaluate the effectiveness of microarray technology in screening for radiation-inducible molecular targets. Relative mRNA levels of receptors and cell surface antigens were determined with microarray screening of control and irradiated (5 Gy 6h) orthotopic LnCaP (prostate) tumors. RNA microarray results were confirmed with RT-PCR. Protein expression of selected antigens was performed on LnCaP tumor lysates 24h following radiation. Additional confirmation studies were performed on irradiated U251 cells (glioma) in vitro and sc tumors by immunoblotting. Increased gene expression of 12 cell adhesion and cell surface antigen molecules in LnCaP tumors following radiation was identified with RNA microarray, while 5 cell surface antigens were found to have decreased expression following radiation. RT-PCR confirmed increased gene expression in 5 of 7 upregulated antigens and decreased gene expression in 1 of 1 antigen. Western blotting of orthotopic LnCaP tumors revealed elevated protein expression of one antigen, glial-derived neurotropic factor receptor α-1 (GFRα-1), 24 hours after irradiation and decreased protein expression of T-cell receptor-γ (TCR-γ). Increased GFRα-1 expression 24 hours after irradiation was also confirmed by Western blotting in the U251 glioma cell line in vitro and in subcutaneous xenografts. GFRα-1protein expression was unaltered in kidney, liver, and spleen following irradiation. Microarray may be an effective tool for screening tumors for molecular targets following radiation in vitro and in vivo

PURPOSE:Endostatin is a 20-kD C-terminal fragment of collagen XVIII and is a potent inhibitor of angiogenesis. Imaging technologies that use near-infrared (NIR) fluorescent probes are well suited to the laboratory setting. The goal of this study was to determine whether endostatin labeled with a NIR probe (Cy5.5) could be detected in an animal after intraperitoneal injection and whether it would selectively localize in a tumor. METHODS:Endostatin was conjugated to Cy5.5 monofunctional dye and purified from free dye by gel filtration. LLC, a murine tumor, was implanted in C57BL/6 mice. The tumors were allowed to grow to 350 mm(2), at which point the mice were injected with 100 microg/100 microL endostatin-Cy5.5 and imaged at various points under sedation. Imaging was performed using a lightproof box affixed to a fluorescent microscope mounted with a filter in the NIR bandwidth (absorbance maximum 675 nm and emission maximum 694 nm). Images were captured by a CCD and desktop computer and stored as 16-bit Tiff files. The mice were also serially imaged for uptake into the tumor and washout from the tumor. RESULTS:After intraperitoneal injection, endostatin-Cy5.5 was quickly absorbed, producing a NIR fluorescent image of the tumors at 24 h that persisted through 7 days. However, the signal peaked at 42 h after injection. Control animals included mice containing green fluorescent protein (GFP) under the control of an actin promotor, which expresses GFP in every cell; tumor-free mice injected with endostatin-Cy5.5; mice with tumors that were not injected with endostatin-Cy5.5; and mice with tumors injected with dye alone. In the four sets of control animals, no NIR photon emissions were detected at 24 hours or 5 days. Only the GFP mouse was detected using the GFP filter. Unlike previous analogous studies with 4-N-(S-glutathionylacetyl)amino) phenylarsenoxide (GSAO)-Cy5.5 in which the tumor image faded with time, the endostatin-Cy5.5 NIR signal was emitted from the tumor up to 7 days after injection, the last time point examined. CONCLUSION:The results of this study demonstrated that endostatin covalently bound to Cy5.5 will migrate from a distant intraperitoneal injection site to a tumor. These data indicate that endostatin-Cy5.5 is appropriate for selectively imaging tumors in experimental animals. Furthermore, data suggest that the anti-angiogenic effect of endostatin occurs through a local mechanism of action, within the tumor or tumor vasculature, rather than through a systemic mechanism.