The genomics revolution and radiotherapy

Prediction of the Acute or Late Radiation Toxicity Effects in Radiotherapy Patients Using Ex Vivo Induced Biodosimetric Markers: A Review

A search for effective methods for the assessment of patients' individual response to radiation is one of the important tasks of clinical radiobiology. This review summarizes available data on the use of ex vivo cytogenetic markers, typically used for biodosimetry, for the prediction of individual clinical radiosensitivity (normal tissue toxicity, NTT) in cells of cancer patients undergoing therapeutic irradiation. In approximately 50% of the relevant reports, selected for the analysis in peer-reviewed international journals, the average ex vivo induced yield of these biodosimetric markers was higher in patients with severe reactions than in patients with a lower grade of NTT. Also, a significant correlation was sometimes found between the biodosimetric marker yield and the severity of acute or late NTT reactions at an individual level, but this observation was not unequivocally proven. A similar controversy of published results was found regarding the attempts to apply G2- and γH2AX foci assays for NTT prediction. A correlation between ex vivo cytogenetic biomarker yields and NTT occurred most frequently when chromosome aberrations (not micronuclei) were measured in lymphocytes (not fibroblasts) irradiated to relatively high doses (4-6 Gy, not 2 Gy) in patients with various grades of late (not early) radiotherapy (RT) morbidity. The limitations of existing approaches are discussed, and recommendations on the improvement of the ex vivo cytogenetic testing for NTT prediction are provided. However, the efficiency of these methods still needs to be validated in properly organized clinical trials involving large and verified patient cohorts.

Enhancing the Bystander and Abscopal Effects to Improve Radiotherapy Outcomes

In this paper, we summarize published articles and experiences related to the attempt to improve radiotherapy outcomes and, thus, to personalize the radiation treatment according to the individual characteristics of each patient. The evolution of ideas and the study of successively published data have led us to envisage new biophysical models for the interpretation of tumor and healthy normal tissue response to radiation. In the development of the model, we have shown that when mesenchymal stem cells (MSCs) and radiotherapy are administered simultaneously in experimental radiotherapy on xenotumors implanted in a murine model, the results of the treatment show the existence of a synergic mechanism that is able to enhance the local and systemic actions of the radiation both on the treated tumor and on its possible metastasis. We are convinced that, due to the physical hallmarks that characterize the neoplastic tissues, the physical-chemical tropism of MSCs, and the widespread functions of macromolecules, proteins, and exosomes released from activated MSCs, the combination of radiotherapy plus MSCs used intratumorally has the effect of counteracting the pro-tumorigenic and pro-metastatic signals that contribute to the growth, spread, and resistance of the tumor cells. Therefore, we have concluded that MSCs are appropriate for therapeutic use in a clinical trial for rectal cancer combined with radiotherapy, which we are going to start in the near future.

Identification and analysis of hub genes and networks related to hypoxia preconditioning in mice (No 035215)

Hypoxia preconditioning is an effective strategy of intrinsic cell protection. An acute repetitive hypoxic mice model was developed. High-throughput microarray analysis was performed to explore the integrative alterations of gene expression in repetitive hypoxic mice. Data obtained was analyzed via multiple bioinformatics approaches to identify the hub genes, pathways and biological processes related to hypoxia preconditioning. The current study, for the first time, provides insights into the gene expression profiles in repetitive hypoxic mice. It was found that a total of 1175 genes expressed differentially between the hypoxic mice and normal mice. Overall, 113 significantly up-regulated and 138 significantly down-regulated functions were identified from the differentially expressed genes in repetitive hypoxic brains. Among them, at least fourteen of these genes were very associated with hypoxia preconditioning. The change trends of these genes were validated by reverse-transcription polymerase chain reaction and were found to be consistent with the microarray data. Combined the results of pathway and gene co-expression networks, we defined Plcb1, Cacna2d1, Atp2b4, Grin2a, Grin2b and Glra1 as the main hub genes tightly related with hypoxia preconditioning. The differential functions mainly included the mitogen-activated protein kinase pathway and ion or neurotransmitter transport. The multiple reactions in cell could be initiated by activating MAPK pathway to prevent hypoxia damage. Plcb1 was an important and hub gene and node in the hypoxia preconditioning signal networks. The findings in the hub genes and integrated gene networks provide very useful information for further exploring the molecular mechanisms of hypoxia preconditioning.

Radiogenomics and radiotherapy response modeling

Advances in patient-specific information and biotechnology have contributed to a new era of computational medicine. Radiogenomics has emerged as a new field that investigates the role of genetics in treatment response to radiation therapy. Radiation oncology is currently attempting to embrace these recent advances and add to its rich history by maintaining its prominent role as a quantitative leader in oncologic response modeling. Here, we provide an overview of radiogenomics starting with genotyping, data aggregation, and application of different modeling approaches based on modifying traditional radiobiological methods or application of advanced machine learning techniques. We highlight the current status and potential for this new field to reshape the landscape of outcome modeling in radiotherapy and drive future advances in computational oncology.

The contribution of women to radiobiology: Marie Curie and beyond

Marie Sklodowska-Curie, an extraordinary woman, a Polish scientist who lived and worked in France, led to the development of nuclear energy and the treatment of cancer. She was the laureate of two Nobel Prizes, the first woman in Europe who obtained the degree of Doctor of Science and opened the way for women to enter fields which had been previously reserved for men only. As a result of her determination and her love of freedom, she has become an icon for many female scientists active in radiation sciences. They are successors of Maria Curie and without the results of their work, improvement in radiation oncology will not be possible. Many of them shared some elements of Maria Curie's biography, like high ethical and moral standards, passionate dedication to work, strong family values, and scientific collaboration with their husbands. The significance of Tikvah Alper, Alma Howard, Shirley Hornsey, Juliana Denekamp, Helen Evans, Eleanor Blakely, Elizabeth L. Travis, Fiona Stewart, Andree Dutreix, Catharine West, Peggy Olive, Ingela Turesson, Penny Jeggo, Irena Szumiel, Eleonor Blakely, Sara Rockwell and Carmel Mothersill contribution to radiation oncology is presented. All the above mentioned ladies made significant contribution to the development of radiotherapy (RT) and more efficient cancer treatment. Due to their studies, new schedules of RT and new types of ionizing radiation have been applied, lowering the incidence of normal tissue toxicity. Their achievements herald a future of personalized medicine.

Exploiting biological and physical determinants of radiotherapy toxicity to individualize treatment

The recent advances in radiation delivery can improve tumour control probability (TCP) and reduce treatment-related toxicity. The use of intensity-modulated radiotherapy (IMRT) in particular can reduce normal tissue toxicity, an objective in its own right, and can allow safe dose escalation in selected cases. Ideally, IMRT should be combined with image guidance to verify the position of the target, since patients, target and organs at risk can move day to day. Daily image guidance scans can be used to identify the position of normal tissue structures and potentially to compute the daily delivered dose. Fundamentally, it is still the tolerance of the normal tissues that limits radiotherapy (RT) dose and therefore tumour control. However, the dose-response relationships for both tumour and normal tissues are relatively steep, meaning that small dose differences can translate into clinically relevant improvements. Differences exist between individuals in the severity of toxicity experienced for a given dose of RT. Some of this difference may be the result of differences between the planned dose and the accumulated dose (DA). However, some may be owing to intrinsic differences in radiosensitivity of the normal tissues between individuals. This field has been developing rapidly, with the demonstration of definite associations between genetic polymorphisms and variation in toxicity recently described. It might be possible to identify more resistant patients who would be suitable for dose escalation, as well as more sensitive patients for whom toxicity could be reduced or avoided. Daily differences in delivered dose have been investigated within the VoxTox research programme, using the rectum as an example organ at risk. In patients with prostate cancer receiving curative RT, considerable daily variation in rectal position and dose can be demonstrated, although the median position matches the planning scan well. Overall, in 10 patients, the mean difference between planned and accumulated rectal equivalent uniform doses was -2.7 Gy (5%), and a dose reduction was seen in 7 of the 10 cases. If dose escalation was performed to take rectal dose back to the planned level, this should increase the mean TCP (as biochemical progression-free survival) by 5%. Combining radiogenomics with individual estimates of DA might identify almost half of patients undergoing radical RT who might benefit from either dose escalation, suggesting improved tumour cure or reduced toxicity or both.

A Dosimetric Comparative Analysis of TomoDirect and Three-Dimensional Conformal Radiotherapy in Early Breast Cancer

PURPOSE

The purpose of this study is to compare dosimetric parameters of intensity-modulated mode of TomoDirect and three-dimensional conformal radiotherapy (3D-CRT) in patients with early breast cancer.

METHODS

TomoDirect and 3D-CRT planning were carried out for 26 patients with early breast cancer who had received breast-conserving surgery. A total of 50.4 Gy in 28 fractions were prescribed to the planning target volume. The organs at risk (OAR) such as lung and heart were contoured. Planning target volume (PTV) dose coverage, radiation conformity index (RCI), radical dose homogeneity index (rDHI), and irradiation dose of organs at risk were compared between TomoDirect and 3D-CRT planning.

RESULTS

The mean PTV dose (51.65±0.37 Gy) and V47.8 (100%) in TomoDirect were significantly higher than the mean PTV dose (50.88±0.65 Gy) and V47.8 (89.23%±0.06%) in 3D-CRT (all, p<0.001). The RCI value in TomoDirect was significantly better than that in 3D-CRT (1.00 vs. 1.13, p<0.001). However, the rDHI value in TomoDirect was not significantly better than that in 3D-CRT (0.72 vs. 0.67, p=0.056). The mean lung dose and V10, V20, V30, and V40 values of ipsilateral lung in TomoDirect were significantly lower than those in 3D-CRT (all, p<0.05). There is no significant difference in the V10, V20, V30, and V40 values of heart between TomoDirect and 3D-CRT. And the mean dose for heart in TomoDirect was marginally lower than that in 3D-CRT (1.05 Gy vs. 1.62 Gy, p=0.085). The mean dose for left anterior descending coronary artery in left breast cancer was significantly lower in TomoDirect than in 3D-CRT (7.2 Gy vs. 12.1 Gy, p<0.001).

CONCLUSION

Compared to 3D-CRT, TomoDirect could result in favorable target coverage while reducing the irradiation dose of the ipsilateral lung for patients with early breast cancer.

Radiogenomics helps to achieve personalized therapy by evaluating patient responses to radiation treatment

Radiogenomics is the whole genome application of radiogenetics, which focuses on uncovering the underlying genetic causes of individual variation in sensitivity to radiation. There is a growing consensus that radiosensitivity is a complex, inherited polygenic trait, dependent on the interaction of many genes involved in multiple cell processes. An understanding of the genes involved in processes such as DNA damage response and oxidative stress response, has evolved toward examination of how genetic variants, most often, single nucleotide polymorphisms (SNPs), may influence interindividual radioresponse. Many experimental approaches, such as candidate SNP association studies, genome-wide association studies and massively parallel sequencing are being proposed to address these questions. We present a review focusing on recent advances in association studies of SNPs to radiotherapy response and discuss challenges and opportunities for further studies. We also highlight the clinical perspective of radiogenomics in the future of personalized treatment in radiation oncology.

Among 45 variants in 11 genes, HDM2 promoter polymorphisms emerge as new candidate biomarker associated with radiation toxicity

Due to individual variations in radiosensitivity, biomarkers are needed to tailor radiation treatment to cancer patients. Since single nucleotide polymorphisms (SNPs) are frequent in human, we hypothesized that SNPs in genes that mitigate the radiation response are associated with radiotoxicity, in particular late complications to radiotherapy and could be used as genetic biomarkers for radiation sensitivity. A total of 155 patients with nasopharyngeal cancer were included in the study. Normal tissue fibrosis was scored using RTOG/EORTC grading system. Eleven candidate genes (ATM, XRCC1, XRCC3, XRCC4, XRCC5, PRKDC, LIG4, TP53, HDM2, CDKN1A, TGFB1) were selected for their presumed influence on radiosensitivity. Forty-five SNPs (12 primary and 33 neighboring) were genotyped by direct sequencing of genomic DNA. Patients with severe fibrosis (cases, G3–4, n = 48) were compared to controls (G0–2, n = 107). Results showed statistically significant (P < 0.05) association with radiation complications for six SNPs (ATM G/A rs1801516, HDM2 promoter T/G rs2279744 and T/A rs1196333, XRCC1 G/A rs25487, XRCC5 T/C rs1051677 and TGFB1 C/T rs1800469). We conclude that these six SNPs are candidate genetic biomarkers for radiosensitivity in our patients that have cumulative effects as patients with severe fibrosis harbored significantly higher number of risk alleles than the controls (P < 0.001). Larger cohort, independent replication of these findings and genome-wide association studies are required to confirm these results in order for SNPs to be used as biomarkers to individualize radiotherapy on genetic basis.

A novel high-throughput irradiator for in vitro radiation sensitivity bioassays

This paper describes the development and characterization of a fully automated in vitro cell irradiator using an electronic brachytherapy source to perform radiation sensitivity bioassays. This novel irradiator allows complex variable dose and dose rate schemes to be delivered to multiple wells of 96-well culture plates used in standard biological assays. The Xoft Axxent® eBx™ was chosen as the x-ray source due to its ability to vary tube current up to 300 µA for a 50 kVp spectrum using clinical surface applicators. Translation of the multiwell plate across the fixed radiation field is achieved using a precision motor driven computer controlled positioning system. A series of measurements was performed to characterize dosimetric performance of the system. Measurements have shown that the radiation output measured with an end window ionization chamber is stable between operating currents of 50-300 µA. In addition, radiochromic film was used to characterize the field flatness and symmetry. The average field flatness in the in-plane and cross-plane direction was 2.9 ± 1.0% and 4.0 ± 1.7%, respectively. The average symmetry in the in-plane and cross-plane direction was 1.8 ± 0.9% and 1.6 ± 0.5%, respectively. The optimal focal spot resolution at the cellular plane was determined by measuring sequential irradiations on radiochromic film for three different well spacing schemes. It was determined that the current system can irradiate every other well with negligible impact on the radiation field characteristics. Finally, a performance comparison between this system and a common cabinet irradiator is presented.

Radiation pneumonitis and pulmonary function with lung dose-volume constraints in breast cancer irradiation

Purpose

We studied symptomatic radiation pneumonitis (RP) and changes in pulmonary function tests (PFTs) after loco-regional radiotherapy (LRRT) with V₂₀ lung constraints in breast cancer (BC).

Patients and methods

Sixty-four women underwent PFTs before and 5 months after 3D planned LRRT for BC. The incidentally irradiated ipsilateral lung V₂₀ was minimised to <30%. Patients were monitored for symptoms of RP 1, 4 and 7 months after radiotherapy (RT) and data on covariates were collected prospectively. The outcome was compared with previous treatment series.

Results

Pneumonitis was less frequent with the applied constraint, that is, four mild and one moderate case, than in our previous report (p < 0·001). In multivariate analyses, neither dosimetric data nor covariates appeared to influence mean changes in vital capacity [−0·11L, standard error of the mean (SEM) 0·03] or diffusing capacity of the lung for carbon monoxide (DLCO) (−0·20 mmol/kPa/min, SEM 0·01), except for pre-RT chemotherapy, which diminished the change in DLCO 5 months post-RT.

Conclusions

The used constraint and 3D planning lowered the rate of RP and short-term changes in PFTs compared with our previous treatment series. Pre-RT chemotherapy affects DLCO baseline levels. Rates of side effects should be continuously studied when new target definitions or therapies are introduced in LRRT of BC.

SNPs in genes implicated in radiation response are associated with radiotoxicity and evoke roles as predictive and prognostic biomarkers

BACKGROUND

Biomarkers are needed to individualize cancer radiation treatment. Therefore, we have investigated the association between various risk factors, including single nucleotide polymorphisms (SNPs) in candidate genes and late complications to radiotherapy in our nasopharyngeal cancer patients.

METHODS

A cohort of 155 patients was included. Normal tissue fibrosis was scored using RTOG/EORTC grading system. A total of 45 SNPs in 11 candidate genes (ATM, XRCC1, XRCC3, XRCC4, XRCC5, PRKDC, LIG4, TP53, HDM2, CDKN1A, TGFB1) were genotyped by direct genomic DNA sequencing. Patients with severe fibrosis (cases, G3-4, n = 48) were compared to controls (G0-2, n = 107).

RESULTS

Univariate analysis showed significant association (P < 0.05) with radiation complications for 6 SNPs (ATM G/A rs1801516, HDM2 promoter T/G rs2279744 and T/A rs1196333, XRCC1 G/A rs25487, XRCC5 T/C rs1051677 and TGFB1 C/T rs1800469). In addition, Kaplan-Meier analyses have also highlighted significant association between genotypes and length of patients' follow-up after radiotherapy. Multivariate logistic regression has further sustained these results suggesting predictive and prognostic roles of SNPs.

CONCLUSIONS

Univariate and multivariate analysis suggest that radiation toxicity in radiotherapy patients are associated with certain SNPs, in genes including HDM2 promoter studied for the 1st time. These results support the use of SNPs as genetic predictive markers for clinical radiosensitivity and evoke a prognostic role for length of patients' follow-up after radiotherapy.

Cerebral radiation necrosis: a review of the pathobiology, diagnosis and management considerations

Radiation therapy forms one of the building blocks of the multi-disciplinary management of patients with brain tumors. Improved survival following radiation therapy may come with a cost, including the potential complication of radiation necrosis. Radiation necrosis impacts the quality of life in cancer survivors, and it is essential to detect and effectively treat this entity as early as possible. Significant progress in neuro-radiology and molecular pathology facilitate more straightforward diagnosis and characterization of cerebral radiation necrosis. Several therapeutic interventions, both medical and surgical, may halt the progression of radiation necrosis and diminish or abrogate its clinical manifestations, but there are still no definitive guidelines to follow explicitly that guide treatment of radiation necrosis. We discuss the pathobiology, clinical features, diagnosis, available treatment modalities, and outcomes in the management of patients with intracranial radiation necrosis that follows radiation used to treat brain tumors.

(Radio)biological optimization of external-beam radiotherapy

“Biological optimization” (BIOP) means planning treatments using (radio)biological criteria and models, that is, tumour control probability and normal-tissue complication probability. Four different levels of BIOP are identified: Level I is “isotoxic” individualization of prescription dose D_presc at fixed fraction number. D_presc is varied to keep the NTCP of the organ at risk constant. Significant improvements in local control are expected for non-small-cell lung tumours. Level II involves the determination of an individualized isotoxic combination of D_presc and fractionation scheme. This approach is appropriate for “parallel” OARs (lung, parotids). Examples are given using our BioSuite software. Hypofractionated SABR for early-stage NSCLC is effectively Level-II BIOP. Level-III BIOP uses radiobiological functions as part of the inverse planning of IMRT, for example, maximizing TCP whilst not exceeding a given NTCP. This results in non-uniform target doses. The NTCP model parameters (reflecting tissue “architecture”) drive the optimizer to emphasize different regions of the DVH, for example, penalising high doses for quasi-serial OARs such as rectum. Level-IV BIOP adds functional imaging information, for example, hypoxia or clonogen location, to Level III; examples are given of our prostate “dose painting” protocol, BioProp. The limitations of and uncertainties inherent in the radiobiological models are emphasized.

Genomic medicine: what are the challenges for the National Health Service?

'Personalized medicine' is inextricably linked with current advances in genomics. Although initial claims about the power of genomic tests have been modified, they have the potential to inform a personalized approach to healthcare. Within the health service, genomic testing is being applied in specific situations to inform therapy; however, more robust studies are needed to identify those tests that can make significant improvements to management and prevention of disease. Despite efforts to educate health professionals, genetic literacy remains unsatisfactory and more efforts are needed to embed genetics in pre- and post-registration professional education, and therefore, maximize benefit for patients. Primary care and public health professionals may be contexts in which genomics can be utilized for both personalized healthcare and promotion of community health.

Lymphoblastoid cell lines in pharmacogenomic discovery and clinical translation

The ability to predict how an individual patient will respond to a particular treatment is the ambitious goal of personalized medicine. The genetic make up of an individual has been shown to play a role in drug response. For pharmacogenomic studies, human lymphoblastoid cell lines (LCLs) comprise a useful model system for identifying genetic variants associated with pharmacologic phenotypes. The availability of extensive genotype data for many panels of LCLs derived from individuals of diverse ancestry allows for the study of genetic variants contributing to interethnic and interindividual variation in susceptibility to drugs. Many genome-wide association studies for drug-induced phenotypes have been performed in LCLs, often incorporating gene-expression data. LCLs are also being used in follow-up studies to clinical findings to determine how an associated variant functions to affect phenotype. This review describes the most recent pharmacogenomic findings made in LCLs, including the translation of some findings to clinical cohorts.

Standardized Total Average Toxicity score: a scale- and grade-independent measure of late radiotherapy toxicity to facilitate pooling of data from different studies

PURPOSE

The search for clinical and biologic biomarkers associated with late radiotherapy toxicity is hindered by the use of multiple and different endpoints from a variety of scoring systems, hampering comparisons across studies and pooling of data. We propose a novel metric, the Standardized Total Average Toxicity (STAT) score, to try to overcome these difficulties.

METHODS AND MATERIALS

STAT scores were derived for 1010 patients from the Cambridge breast intensity-modulated radiotherapy trial and 493 women from the University Hospitals of Leicester. The sensitivity of the STAT score to detect differences between patient groups, stratified by factors known to influence late toxicity, was compared with that of individual endpoints. Analysis of residuals was used to quantify the effect of these covariates.

RESULTS

In the Cambridge cohort, STAT scores detected differences (p < 0.00005) between patients attributable to breast volume, surgical specimen weight, dosimetry, acute toxicity, radiation boost to tumor bed, postoperative infection, and smoking (p < 0.0002), with no loss of sensitivity over individual toxicity endpoints. Diabetes (p = 0.017), poor postoperative surgical cosmesis (p = 0.0036), use of chemotherapy (p = 0.0054), and increasing age (p = 0.041) were also associated with increased STAT score. When the Cambridge and Leicester datasets were combined, STAT was associated with smoking status (p < 0.00005), diabetes (p = 0.041), chemotherapy (p = 0.0008), and radiotherapy boost (p = 0.0001). STAT was independent of the toxicity scale used and was able to deal with missing data. There were correlations between residuals of the STAT score obtained using different toxicity scales (r > 0.86, p < 0.00005 for both datasets).

CONCLUSIONS

The STAT score may be used to facilitate the analysis of overall late radiation toxicity, from multiple trials or centers, in studies of possible genetic and nongenetic determinants of radiotherapy toxicity.

SNPs in DNA repair or oxidative stress genes and late subcutaneous fibrosis in patients following single shot partial breast irradiation

Background

The aim of this study was to evaluate the potential association between single nucleotide polymorphisms related response to radiotherapy injury, such as genes related to DNA repair or enzymes involved in anti-oxidative activities. The paper aims to identify marker genes able to predict an increased risk of late toxicity studying our group of patients who underwent a Single Shot 3D-CRT PBI (SSPBI) after BCS (breast conserving surgery).

Methods

A total of 57 breast cancer patients who underwent SSPBI were genotyped for SNPs (single nucleotide polymorphisms) in XRCC1, XRCC3, GST and RAD51 by Pyrosequencing technology. Univariate analysis (ORs and 95% CI) was performed to correlate SNPs with the risk of developing ≥ G2 fibrosis or fat necrosis.

Results

A higher significant risk of developing ≥ G2 fibrosis or fat necrosis in patients with: polymorphic variant GSTP1 (Ile105Val) (OR = 2.9; 95%CI, 0.88-10.14, p = 0.047).

Conclusions

The presence of some SNPs involved in DNA repair or response to oxidative stress seem to be able to predict late toxicity.

Trial Registration

ClinicalTrials.gov: NCT01316328

Biochemical markers predicting response to radiation- and radiochemo-therapy in cancer patients

In last years there is increasing interest in radiogenomics and the characterization of DNA array molecular profiles that can predict tumor and no tumor tissues radioresponse. Ongoing studies carried out worldwide in the banking of tumor and no tumor samples give evidence that perspective markers for response prediction in individual patient to intended radiation therapy can be some apoptotic indexes, spectrum a number of specific proteins, and DNA-based microarray molecular profiling analysis as well determination of single nucleotide polymorphisms in genome of the patients. So far there are only a few robust reports of molecular markers predicting tumor and no tumor tissues response to radiation. The results of new studies, which in future should be validated in larger definitive trials, are likely to see in nearest years. It is needed to determine technologies of methods and to define more precisely areas of its applications.

A review of the logistic role of L-carnitine in the management of radiation toxicity and radiotherapy side effects

Radiation therapy is a key modality in the treatment of different cancer types. Fatigue is the most common side effect of radiotherapy, while others include nausea, hair loss, skin irritation, anemia, infertility, cardiovascular disease, cognitive impairment and even the development of second cancers. Studies in experimental animals have shown protective effects of carnitine against exposure of various organs to ionizing radiation, whereas carnitine deficiency is known to enhance radiation-induced toxicity. This report summarizes the recent literature on the adverse effects of radiotherapy and the impact of radiation on carnitine homeostasis. Although some studies have demonstrated the prophylactic benefits of carnitine against the toxic effects of chemotherapy, the role of carnitine in the prognosis and management of cancer patients receiving radiotherapy is not clear and needs to be explored.

Identification of hub genes related to the recovery phase of irradiation injury by microarray and integrated gene network analysis

BACKGROUND

Irradiation commonly causes long-term bone marrow injury charactertized by defective HSC self-renewal and a decrease in HSC reserve. However, the effect of high-dose IR on global gene expression during bone marrow recovery remains unknown.

METHODOLOGY

Microarray analysis was used to identify differentially expressed genes that are likely to be critical for bone marrow recovery. Multiple bioinformatics analyses were conducted to identify key hub genes, pathways and biological processes.

PRINCIPAL FINDINGS

1) We identified 1302 differentially expressed genes in murine bone marrow at 3, 7, 11 and 21 days after irradiation. Eleven of these genes are known to be HSC self-renewal associated genes, including Adipoq, Ccl3, Ccnd1, Ccnd2, Cdkn1a, Cxcl12, Junb, Pten, Tal1, Thy1 and Tnf; 2) These 1302 differentially expressed genes function in multiple biological processes of immunity, including hematopoiesis and response to stimuli, and cellular processes including cell proliferation, differentiation, adhesion and signaling; 3) Dynamic Gene Network analysis identified a subgroup of 25 core genes that participate in immune response, regulation of transcription and nucleosome assembly; 4) A comparison of our data with known irradiation-related genes extracted from literature showed 42 genes that matched the results of our microarray analysis, thus demonstrated consistency between studies; 5) Protein-protein interaction network and pathway analyses indicated several essential protein-protein interactions and signaling pathways, including focal adhesion and several immune-related signaling pathways.

CONCLUSIONS

Comparisons to other gene array datasets indicate that global gene expression profiles of irradiation damaged bone marrow show significant differences between injury and recovery phases. Our data suggest that immune response (including hematopoiesis) can be considered as a critical biological process in bone marrow recovery. Several critical hub genes that are key members of significant pathways or gene networks were identified by our comprehensive analysis.

Genetics and genomics of radiotherapy toxicity: towards prediction

Radiotherapy is involved in many curative treatments of cancer; millions of survivors live with the consequences of treatment, and toxicity in a minority limits the radiation doses that can be safely prescribed to the majority. Radiogenomics is the whole genome application of radiogenetics, which studies the influence of genetic variation on radiation response. Work in the area focuses on uncovering the underlying genetic causes of individual variation in sensitivity to radiation, which is important for effective, safe treatment. In this review, we highlight recent advances in radiotherapy and discuss results from four genome-wide studies of radiotoxicity.

Molecular biology: the key to personalised treatment in radiation oncology?

We know considerably more about what makes cells and tissues resistant or sensitive to radiation than we did 20 years ago. Novel techniques in molecular biology have made a major contribution to our understanding at the level of signalling pathways. Before the "New Biology" era, radioresponsiveness was defined in terms of physiological parameters designated as the five Rs. These are: repair, repopulation, reassortment, reoxygenation and radiosensitivity. Of these, only the role of hypoxia proved to be a robust predictive and prognostic marker, but radiotherapy regimens were nonetheless modified in terms of dose per fraction, fraction size and overall time, in ways that persist in clinical practice today. The first molecular techniques were applied to radiobiology about two decades ago and soon revealed the existence of genes/proteins that respond to and influence the cellular outcome of irradiation. The subsequent development of screening techniques using microarray technology has since revealed that a very large number of genes fall into this category. We can now obtain an adequately robust molecular signature, predicting for a radioresponsive phenotype using gene expression and proteomic approaches. In parallel with these developments, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) can now detect specific biological molecules such as haemoglobin and glucose, so revealing a 3D map of tumour blood flow and metabolism. The key to personalised radiotherapy will be to extend this capability to the proteins of the molecular signature that determine radiosensitivity.

DNA repair targeting and radiotherapy: a focus on the therapeutic ratio

Radiotherapy (RT) results in the production of a variety of ionizing radiation-induced lesion in DNA. Specific pathways of DNA repair are required to repair the variety of lesions, which include DNA single-strand breaks (SSBs), DNA double-strand breaks (DSBs), DNA base alterations, and DNA-DNA or DNA-protein cross-links. Nonrepaired DNA damage can lead to normal and tumor cell death via apoptosis, mitotic catastrophe, autophagy, or terminal growth arrest senescence. Targeting the sensing and repair of DNA damage is an exciting concept. This must be combined with precision RT to limit the volume of irradiated normal tissue, including the use of image-guided radiotherapy (IGRT) and brachytherapy. The therapeutic ratio of combined targeting of DNA combined with RT could also be preserved using biological approaches and includes the following: (1) the documentation of relative defects in DNA damage sensing and repair in malignant cells; (2) the preferential use of certain DNA repair pathways (eg, base excision repair or homologous recombination) in malignant tissues compare with normal tissues; (3) the targeting of repair defects in chronically hypoxic cells; and (4) optimal scheduling of a DNA repair inhibitor in the neoadjuvant, concurrent, or adjuvant combined treatment settings. In this review, we discuss the general rationale and the optimal timing and duration of DNA repair inhibition during fractionated RT with the emphasis on preserving the therapeutic ratio of cancer treatment.

Pharmacogenetic analysis in neoadjuvant chemoradiation for rectal cancer: high incidence of somatic mutations and their relation with response

Aims: The identification of predictive markers of response to chemoradiotherapy treatment remains a promising approach for patient management in order to obtain the best response with minor side effects. Initially, we investigated whether the analysis of several markers previously studied and others not yet evaluated could predict response to 5-fluorouracil- and capecitabine-based neoadjuvant treatment in locally advanced rectal cancer. Methods & materials: We studied germline and tumoral samples of 65 stage II/III rectal patients. A panel of pharmacogenetic markers was genotyped in paired peripheral blood samples and rectal cancer tumors. Results: Our results seem to confirm the previously described association of thymidylate synthase and the prediction of chemoradiotherapy response in rectal cancer. However, it failed to confirm the clinical utility proposed for XRCC1, ERCC1, ERCC2, MTHFR and EGFR polymorphisms in blood/germline samples. Subsequently, with the aim of improving prediction of individual response and assessing the role of studied polymorphisms in response to treatment, we determined if changes in tumor response to these markers could predict clinical outcome. We found a high degree of changes between germline and tumor samples, mainly somatic mutations without microsatellite instability, and a minor frequency of loss-of-heterozygosity events. In tumoral samples, XRCC1 appeared to be significantly associated (p = 0.006) with downstaging of the tumor (odds ratio: 7.93; 95% CI: 1.03–60.83), but the increasing of TYMS low-expression alleles contradict the previous results observed in germline samples. Conclusion: The detection of somatic mutations in rectal cancer tumors led us to re-evaluate the utility of the tests performed in blood samples for these polymorphisms in rectal cancer. Furthermore, studies aimed at assessing the influence of pharmacogenetic markers in treatment response performed in blood samples should take into account the particular pattern of hypermutability present in each tumor type. We hypothesize that different patterns of hypermutability present in each tumor type would be related to the different results in association studies related to response to the treatment.

Sequence variant discovery in DNA repair genes from radiosensitive and radiotolerant prostate brachytherapy patients

PURPOSE

The presence of intrinsic radiosensitivity within prostate cancer patients may be an important factor contributing to development of radiation toxicity. We investigated whether variants in genes responsible for detecting and repairing DNA damage independently contribute to toxicity following prostate brachytherapy.

EXPERIMENTAL DESIGN

Genomic DNA was extracted from blood samples of 41 prostate brachytherapy patients, 21 with high and 20 with low late toxicity scores. For each patient, 242 PCR amplicons were generated containing 173 exons of eight candidate genes: ATM, BRCA1, ERCC2, H2AFX, LIG4, MDC1, MRE11A, and RAD50. These amplicons were sequenced and all sequence variants were subjected to statistical analysis to identify those associated with late radiation toxicity.

RESULTS

Across 41 patients, 239 sites differed from the human genome reference sequence; 170 of these corresponded to known polymorphisms. Sixty variants, 14 of them novel, affected protein coding regions and 43 of these were missense mutations. In our patient population, the high toxicity group was enriched for individuals with at least one LIG4 coding variant (P = 0.028). One synonymous variant in MDC1, rs28986317, was associated with increased radiosensitivity (P = 0.048). A missense variant in ATM, rs1800057, associated with increased prostate cancer risk, was found exclusively in two high toxicity patients but did not reach statistical significance for association with radiosensitivity (P = 0.488).

CONCLUSIONS

Our data revealed new germ-line sequence variants, indicating that existing sequence databases do not fully represent the full extent of sequence variation. Variants in three DNA repair genes were linked to increased radiosensitivity but require validation in larger populations.

Bioinformatics methods for learning radiation-induced lung inflammation from heterogeneous retrospective and prospective data

Radiotherapy outcomes are determined by complex interactions between physical and biological factors, reflecting both treatment conditions and underlying genetics. Recent advances in radiotherapy and biotechnology provide new opportunities and challenges for predicting radiation-induced toxicities, particularly radiation pneumonitis (RP), in lung cancer patients. In this work, we utilize datamining methods based on machine learning to build a predictive model of lung injury by retrospective analysis of treatment planning archives. In addition, biomarkers for this model are extracted from a prospective clinical trial that collects blood serum samples at multiple time points. We utilize a 3-way proteomics methodology to screen for differentially expressed proteins that are related to RP. Our preliminary results demonstrate that kernel methods can capture nonlinear dose-volume interactions, but fail to address missing biological factors. Our proteomics strategy yielded promising protein candidates, but their role in RP as well as their interactions with dose-volume metrics remain to be determined.

Basic principles and technologies for deciphering the genetic map of cancer

The progress achieved in the field of genomics in recent years is leading medicine to adopt a personalized model in which the knowledge of individual DNA alterations will allow a targeted approach to cancer. Using pancreatic cancer as a model, we discuss herein the fundamentals that need to be considered for the high throughput and global identification of mutations. These include patient-related issues, sample collection, DNA isolation, gene selection, primer design, and sequencing techniques. We also describe the possible applications of the discovery of DNA changes to the approach of this disease and cite preliminary efforts where the knowledge has been translated into the clinical or preclinical setting.

Normal tissue reactions to radiotherapy: towards tailoring treatment dose by genotype

A key challenge in radiotherapy is to maximize radiation doses to cancer cells while minimizing damage to surrounding healthy tissue. As severe toxicity in a minority of patients limits the doses that can be safely given to the majority, there is interest in developing a test to measure an individual's radiosensitivity before treatment. Variation in sensitivity to radiation is an inherited genetic trait and recent progress in genotyping raises the possibility of genome-wide studies to characterize genetic profiles that predict patient response to radiotherapy.

Molecular markers of radiation-related normal tissue toxicity

Over the past five decades, those interested in markers of radiation effect have focused primarily on tumor response. More recently, however, the view has broadened to include irradiated normal tissues-markers that predict unusual risk of side-effects, prognosticate during the prodromal and therapeutic phases, diagnose a particular toxicity as radiation-related, and, in the case of bioterror, allow for tissue-specific biodosimetry. Currently, there are few clinically useful radiation-related biomarkers. Notably, levels of some hormones such as thyroid-stimulating hormone (TSH) have been used successfully as markers of dysfunction, indicative of the need for replacement therapy, and for prevention of cancers. The most promising macromolecular markers are cytokines: TGFbeta, IL-1, IL-6, and TNFalpha being lead molecules in this class as both markers and targets for therapy. Genomics and proteomics are still in nascent stages and are actively being studied and developed.

Genetic markers for prediction of normal tissue toxicity after radiotherapy

During the last decade, a number of studies have supported the hypothesis that there is an important genetic component to the observed interpatient variability in normal tissue toxicity after radiotherapy. This review summarizes the candidate gene association studies published so far on the risk of radiation-induced morbidity and highlights some recent successful whole-genome association studies showing feasibility in other research areas. Future genetic association studies are discussed in relation to methodological problems such as the characterization of clinical and biological phenotypes, genetic haplotypes, and handling of confounding factors. Finally, candidate gene studies elucidating the genetic component of radiation-induced morbidity and the functional consequences of single nucleotide polymorphisms by studying intermediate phenotypes will be discussed.