To summarize current knowledge regarding mechanisms of radiation-induced normal tissue injury and medical countermeasures available to reduce its severity. Advances in radiation delivery using megavoltage and intensity-modulated radiation therapy have permitted delivery of higher doses of radiation to well-defined tumor target tissues. Injury to critical normal tissues and organs, however, poses substantial risks in the curative treatment of cancers, especially when radiation is administered in combination with chemotherapy. The principal pathogenesis is initiated by depletion of tissue stem cells and progenitor cells and damage to vascular endothelial microvessels. Emerging concepts of radiation-induced normal tissue toxicity suggest that the recovery and repopulation of stromal stem cells remain chronically impaired by long-lived free radicals, reactive oxygen species, and pro-inflammatory cytokines/chemokines resulting in progressive damage after radiation exposure. Better understanding the mechanisms mediating interactions among excessive generation of reactive oxygen species, production of pro-inflammatory cytokines and activated macrophages, and role of bone marrow-derived progenitor and stem cells may provide novel insight on the pathogenesis of radiation-induced injury of tissues. Further understanding the molecular signaling pathways of cytokines and chemokines would reveal novel targets for protecting or mitigating radiation injury of tissues and organs.
Chemokines ; Cytokines ; Drug Therapy ; Free Radicals ; Macrophages ; Microvessels ; Negotiating ; Radiation Injuries ; Reactive Oxygen Species ; Stem Cells

Successful anticancer strategies require a differential response between tumor and normal tissue (i.e., a therapeutic ratio). In fact, improving the effectiveness of a cancer therapeutic is of no clinical value in the absence of a significant increase in the differential response between tumor and normal tissue. Although radiation dose escalation with the use of intensity modulated radiation therapy has permitted the maximum tolerable dose for most locally advanced cancers, improvements in tumor control without damaging normal adjacent tissues are needed. As a means of increasing the therapeutic ratio, several new approaches are under development. Drugs targeting signal transduction pathways in cancer progression and more recently, immunotherapeutics targeting specific immune cell subsets have entered the clinic with promising early results. Radiobiological research is underway to address pressing questions as to the dose per fraction, irradiated tumor volume and time sequence of the drug administration. To exploit these exciting novel strategies, a better understanding is needed of the cellular and molecular pathways responsible for both cancer and normal tissue and organ response, including the role of radiation-induced accelerated senescence. This review will highlight the current understanding of promising biologically targeted therapies to enhance the radiation therapeutic ratio.
Aging ; Radiobiology ; Radioimmunotherapy ; Signal Transduction ; Tumor Burden

Tumor cell proliferation, infiltration, migration, and neovascularization are known causes of treatment resistance in glioblastoma multiforme (GBM). The purpose of this study was to determine the effect of radiation on the growth characteristics of primary human GBM developed in a nude rat. Primary GBM cells grown from explanted GBM tissues were implanted orthotopically in nude rats. Tumor growth was confirmed by magnetic resonance imaging on day 77 (baseline) after implantation. The rats underwent irradiation to a dose of 50 Gy delivered subcuratively on day 84 postimplantation (n = 8), or underwent no radiation (n = 8). Brain tissues were obtained on day 112 (nonirradiated) or day 133 (irradiated). Immunohistochemistry was performed to determine tumor cell proliferation (Ki-67) and to assess the expression of infiltration marker (matrix metalloproteinase-2, MMP-2) and cell migration marker (CD44). Tumor neovascularization was assessed by microvessel density using von-Willebrand factor (vWF) staining. Magnetic resonance imaging showed well-developed, infiltrative tumors in 11 weeks postimplantation. The proportion of Ki-67-positive cells in tumors undergoing radiation was (71 +/- 15)% compared with (25 +/- 12)% in the nonirradiated group (P = 0.02). The number of MMP-2-positive areas and proportion of CD44-positive cells were also high in tumors receiving radiation, indicating great invasion and infiltration. Microvessel density analysis did not show a significant difference between nonirradiated and irradiated tumors. Taken together, we found that subcurative radiation significantly increased proliferation, invasion, and migration of primary GBM. Our study provides insights into possible mechanisms of treatment resistance following radiation therapy for GBM.
Animals ; Brain Neoplasms ; metabolism ; pathology ; radiotherapy ; Cell Line, Tumor ; Cell Movement ; radiation effects ; Cell Proliferation ; radiation effects ; Female ; Glioblastoma ; metabolism ; pathology ; radiotherapy ; Humans ; Hyaluronan Receptors ; metabolism ; Immunohistochemistry ; Ki-67 Antigen ; metabolism ; Magnetic Resonance Imaging ; Matrix Metalloproteinase 2 ; metabolism ; Microvessels ; pathology ; Neoplasm Transplantation ; Neovascularization, Pathologic ; pathology ; Radiation Tolerance ; Radiotherapy, High-Energy ; Rats ; Rats, Nude

Background: Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA. Materials and methods: A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA.Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions. Results: Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size.The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components. Conclusions A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating.Level of evidence: Prospective cohort, level II.

Background: Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA. Materials and methods: A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA.Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions. Results: Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size.The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components. Conclusions A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating.Level of evidence: Prospective cohort, level II.

Background: Chronic skin wounds are a common complication of many diseases such as diabetes. Various traditional methods for assessing skin wound closure are used in animal studies, including wound tracing, calliper measurements and histological analysis. However, these methods have poorly defined wound closure or practical limitations.Digital image analysis of wounds is an increasingly popular, accessible alternative, but it is unclear whether digital assessment is consistent with traditional methods. This study aimed to optimise and compare digital wound closure assessment with traditional methods, using a diabetic mouse model. Diabetes was induced in male C57BL/6J mice by high-fat diet feeding combined with low dose (65 mg/kg of body weight) streptozotocin injections. Mice fed normal chow were included as controls. After 18 weeks, four circular full-thickness dorsal skin wounds of 4 mm diameter were created per mouse. The wounds were photographed and measured by callipers. Wound closure rate (WCR) was digitally assessed by two reporters using two methods: wound outline (WCR-O) and re-epithelialisation (WCR-E).Wounded skin tissues were collected at 10-days post-wounding and wound width was measured from haematoxylin and eosin-stained skin tissue. Results: Between reporters, WCR-O was more consistent than WCR-E, and WCR-O correlated with calliper measurements. Histological analysis supported digital assessments, especially WCR-E, when wounds were histologically closed. Conclusions WCR-O could replace calliper measurements to measure skin wound closure, but WCR-E assessment requires further refinement. Small animal studies of skin wound healing can greatly benefit from standardised definitions of wound closure and more consistent digital assessment protocols.

Laparoscopic anterior lumbar interbody fusion (L-ALIF), which employs laparoscopic cameras to facilitate a less invasive approach, originally gained traction during the 1990s but has subsequently fallen out of favor. As the envelope for endoscopic approaches continues to be pushed, a recurrence of interest in laparoscopic and/or endoscopic anterior approaches seems possible. Therefore, evaluating the current evidence base in regard to this approach is of much clinical relevance. To this end, a systematic literature search was performed according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines using the following keywords: “(laparoscopic OR endoscopic) AND (anterior AND lumbar).” Out of the 441 articles retrieved, 22 were selected for quantitative analysis. The primary outcome of interest was the radiographic fusion rate. The secondary outcome was the incidence of perioperative complications. Meta-analysis was performed using RStudio’s “metafor” package. Of the 1,079 included patients (mean age, 41.8±2.9 years), 481 were males (44.6%). The most common indication for L-ALIF surgery was degenerative disk disease (reported by 18 studies, 81.8%). The mean follow-up duration was 18.8±11.2 months (range, 6–43 months). The pooled fusion rate was 78.9% (95% confidence interval [CI], 68.9–90.4). Complications occurred in 19.2% (95% CI, 13.4–27.4) of L-ALIF cases. Additionally, 7.2% (95% CI, 4.6–11.4) of patients required conversion from L-ALIF to open surgery. Although L-ALIF does not appear to be supported by studies available in the literature, it is important to consider the context from which these results have been obtained. Even if these results are taken at face value, the failure of endoscopy to have a role in the ALIF approach does not mean that it should not be incorporated in posterior approaches.

There is evidence that a substantial part of genetic predisposition to prostate cancer (PCa) may be due to lower penetrance genes which are found by genome-wide association studies. We have recently conducted such a study and seven new regions of the genome linked to PCa risk have been identified. Three of these loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK2/3. The MSMB and KLK2/3 genes may be useful for PCa screening, and the LMTK2 gene might provide a potential therapeutic target. Together with results from other groups, there are now 23 germline genetic variants which have been reported. These results have the potential to be developed into a genetic test. However, we consider that marketing of tests to the public is premature, as PCa risk can not be evaluated fully at this stage and the appropriate screening protocols need to be developed. Follow-up validation studies, as well as studies to explore the psychological implications of genetic profile testing, will be vital prior to roll out into healthcare.
Genetic Predisposition to Disease ; genetics ; Genetic Testing ; Humans ; Kallikreins ; genetics ; Male ; Membrane Proteins ; genetics ; Prostatic Neoplasms ; diagnosis ; genetics ; Prostatic Secretory Proteins ; genetics ; Protein-Serine-Threonine Kinases ; genetics ; Risk Factors