Molecular markers predicting radiotherapy response: report and recommendations from an International Atomic Energy Agency technical meeting

Research Trends and Evolution in Radiogenomics (2005-2023): Bibliometric Analysis

BACKGROUND

Radiogenomics is an emerging technology that integrates genomics and medical image-based radiomics, which is considered a promising approach toward achieving precision medicine.

OBJECTIVE

The aim of this study was to quantitatively analyze the research status, dynamic trends, and evolutionary trajectory in the radiogenomics field using bibliometric methods.

METHODS

The relevant literature published up to 2023 was retrieved from the Web of Science Core Collection. Excel was used to analyze the annual publication trend. VOSviewer was used for constructing the keywords co-occurrence network and the collaboration networks among countries and institutions. CiteSpace was used for citation keywords burst analysis and visualizing the references timeline.

RESULTS

A total of 3237 papers were included and exported in plain-text format. The annual number of publications showed an increasing annual trend. China and the United States have published the most papers in this field, with the highest number of citations in the United States and the highest average number per item in the Netherlands. Keywords burst analysis revealed that several keywords, including "big data," "magnetic resonance spectroscopy," "renal cell carcinoma," "stage," and "temozolomide," experienced a citation burst in recent years. The timeline views demonstrated that the references can be categorized into 8 clusters: lower-grade glioma, lung cancer histology, lung adenocarcinoma, breast cancer, radiation-induced lung injury, epidermal growth factor receptor mutation, late radiotherapy toxicity, and artificial intelligence.

CONCLUSIONS

The field of radiogenomics is attracting increasing attention from researchers worldwide, with the United States and the Netherlands being the most influential countries. Exploration of artificial intelligence methods based on big data to predict the response of tumors to various treatment methods represents a hot spot research topic in this field at present.

Radiogenomics in lung cancer: Where are we?

Huge technological and biomedical advances have improved the survival and quality of life of lung cancer patients treated with radiotherapy. However, during treatment planning, a probability that the patient will experience adverse effects is assumed. Radiotoxicity is a complex entity that is largely dose-dependent but also has important intrinsic factors. One of the most studied is the genetic variants that may be associated with susceptibility to the development of adverse effects of radiotherapy. This review aims to present the current status of radiogenomics in lung cancer, integrating results obtained in association studies of SNPs (single nucleotide polymorphisms) related to radiotherapy toxicities. We conclude that despite numerous publications in this field, methodologies and endpoints vary greatly, making comparisons between studies difficult. Analyzing SNPs from the candidate gene approach, together with the study in cohorts limited by the sample size, has complicated the possibility of having validated results. All this delays the incorporation of genetic biomarkers in predictive models for clinical application. Thus, from all analysed SNPs, only 12 have great potential as esophagitis genetic risk factors and deserve further exploration. This review highlights the efforts that have been made to date in the radiogenomic study of radiotoxicity in lung cancer.

Correlation between tumor voxel dose response matrix and tumor biomarker profile in patients with head and neck squamous cell carcinoma

BACKGROUND

We have developed a novel imaging analysis procedure that is highly predictive of local failure after chemoradiation in head and neck cancer. In this study we investigated whether any pretreatment biomarkers correlated with key imaging parameters.

METHODS

Pretreatment biopsy material was available for 28 patients entered into an institutional trial of adaptive radiotherapy in which FDG-PET images were collected weekly during treatment. The biopsies were immunohistochemically stained for CD44, EGFR, GLUT1, ALDH1, Ki-67 and p53 and quantified using image analysis. Expression levels were correlated with previously derived imaging parameters, the pretreatment SUV_max and the dose response matrix (DRM).

RESULTS

The different parameters of the SUV_max and DRM did not correlate with each other. We observed a positive and highly significant (p = 0.0088) correlation between CD44 expression and volume of tumor with a DRM greater than 0.8. We found no correlation between any DRM parameter and GLUT1, p53, Ki-67 and EGFR or ALDH1. GLUT1 expression did correlate with the maximum SUV₀ and the volume of tumor with an SUV₀ greater than 20.

CONCLUSIONS

The pretreatment SUV_max and DRM are independent imaging parameters that combine to predict local recurrence. The significant correlation between CD44 expression, a known cancer stem cell (CSC) marker, and volume of tumor with a DRM greater than 0.8 is consistent with concept that specific foci of cells are responsible for tumor recurrence and that CSCs may be randomly distributed in tumors in specific niches. Dose painting these small areas may lead to improved tumor control.

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.

Diagnostic value of imaging examinations in patients with primary hepatocellular carcinoma

Primary hepatocellular carcinoma (PHC) includes hepatocellular carcinoma, intrahepatic cholangiocarcinoma and other pathological types and is characterized by rapid progression. Most of the clinical diagnoses are made at late stage or when distant metastasis occurs, increasing the difficulty of treatment and resulting in a poor prognosis. Therefore, the early diagnosis of PHC plays an important role in timely treatment and the improvement of prognosis. The gold standard for the diagnosis of primary liver cancer is liver biopsy, but it has limitations as an invasive examination. Presently, imaging has become the first choice for the diagnosis of liver cancer. We here summarize the new methods and techniques of imaging in diagnosis and evaluation of primary liver cancer in recent years, including ultrasonography, computed tomography perfusion imaging, diffusion-weighted imaging technology-voxel incoherent motion, diffusion tensor imaging, iterative decomposition of water and fat with echo asymmetry and least squares estimation-iron quantification, dynamic enhanced magnetic resonance imaging and hepatocyte-specific contrast medium imaging. Imaging diagnosis can not only evaluate the degree of differentiation, blood supply and perfusion, and invasiveness of the lesion, but also predict the prognosis, evaluate liver function, and provide references for clinical diagnosis and treatment.

In vitro prediction of breast cancer therapy toxicity

BACKGROUND

Understanding the basis of clinical radiosensitivity is a key goal of radiation research. In this study, we used the limiting dilution assay (LDA) to analyze in vitro radiosensitivity of cell lines from individuals with breast and other cancers, who had been treated with ionizing radiation, and who either had a non-radiosensitive (RS) radiation response or who were clinically RS.

METHODS

Lymphoblastoid cell lines (LCLs) were created from 29 cancer patients including 19 RS patients, 10 controls who had not developed severe normal tissue reactions, and 1 ataxia telangiectasia RS control cell line. The clinically RS patients had grade 3 or grade 4 reactions; one had a grade 2 reaction. All cells were exposed to graded doses of gamma-radiation in vitro and cell survival assessed via LDA. Cell survival was expressed on non-linear regression analysis-fitted survival curves and also as the surviving fraction at 2 Gray (Gy) (SF₂).

RESULTS

Our LDA analysis yielded two notable positive results. Firstly, it could distinguish control cells from cells from pooled breast cancer cases with severe reactions of all types (acute reactors, consequential late reactors and late reactors). Secondly, two radiosensitivity outliers were detected on the fitted curves, corresponding clinically to grade 3 and 4 late radiation reactions in breast and head and neck cancer cases respectively. The assay showed considerable cell survival heterogeneity.

CONCLUSIONS

The LDA as used here may provide unique clinical utility in detecting potential RS breast cancer patients prior to radiotherapy (RT), a form of personalized medicine. The assay may be especially useful in situations where its results can be temporally available prior to therapy initiation (e.g., those patients not undergoing RT until some months after surgery, typically those having adjuvant chemotherapy prior to RT). Two LCLs from RS outliers could potentially yield insight into the cellular and/or genetic basis of radiosensitivity, for example by undertaking genomic analyses on these cell lines.

Investigation of pulsed IMRT and VMAT for re-irradiation treatments: dosimetric and delivery feasibilities

Many tumor cells demonstrate hyperradiosensitivity at doses below ~50 cGy. Together with the increased normal tissue repair under low dose rate, the pulsed low dose rate radiotherapy (PLDR), which separates a daily fractional dose of 200 cGy into 10 pulses with 3 min interval between pulses (~20 cGy/pulse and effective dose rate 6.7 cGy min−1), potentially reduces late normal tissue toxicity while still providing significant tumor control for re-irradiation treatments. This work investigates the dosimetric and technical feasibilities of intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT)-based PLDR treatments using Varian Linacs. Twenty one cases (12 real re-irradiation cases) including treatment sites of pancreas, prostate, pelvis, lung, head-and-neck, and breast were recruited for this study. The lowest machine operation dose rate (100 MU min−1) was employed in the plan delivery. Ten-field step-and-shoot IMRT and dual-arc VMAT plans were generated using the Eclipse TPS with routine planning strategies. The dual-arc plans were delivered five times to achieve a 200 cGy daily dose (~20 cGy arc−1). The resulting plan quality was evaluated according to the heterogeneity and conformity indexes (HI and CI) of the planning target volume (PTV). The dosimetric feasibility of retaining the hyperradiosensitivity for PLDR was assessed based on the minimum and maximum dose in the target volume from each pulse. The delivery accuracy of VMAT and IMRT at the 100 MU min−1 machine operation dose rate was verified using a 2D diode array and ion chamber measurements. The delivery reproducibility was further investigated by analyzing the Dynalog files of repeated deliveries. A comparable plan quality was achieved by the IMRT (CI 1.10–1.38; HI 1.04–1.10) and the VMAT (CI 1.08–1.26; HI 1.05–1.10) techniques. The minimum/maximum PTV dose per pulse is 7.9 ± 5.1 cGy/33.7 ± 6.9 cGy for the IMRT and 12.3 ± 4.1 cGy/29.2 ± 4.7 cGy for the VMAT. Six out of the 186 IMRT pulses (fields) were found to exceed 50 cGy maximum PTV dose per pulse while the maximum PTV dose per pulse was within 40 cGy for all the VMAT pulses (arcs). However, for VMAT plans, the dosimetric quality of the entire treatment plan was less superior for the breast cases and large irregular targets. The gamma passing rates for both techniques at the 100 MU min−1 dose rate were at least 94.1% (3%/3 mm) and the point dose measurements agreed with the planned values to within 2.2%. The average root mean square error of the leaf position was 0.93 ± 0.83 mm for IMRT and 0.53 ± 0.48 mm for VMAT based on the Dynalog file analysis. The RMS error of the leaf position was nearly identical for the repeated deliveries of the same plans. In general, both techniques are feasible for PLDR treatments. VMAT was more advantageous for PLDR with more uniform target dose per pulse, especially for centrally located tumors. However, for large, irregular and/or peripheral tumors, IMRT could produce more favorable PLDR plans. By taking the biological benefit of PLDR delivery and the dosimetric benefit of IMRT and VMAT, the proposed methods have a great potential for those previously-irradiated recurrent patients.

Global radiation oncology waybill

BACKGROUND/AIM

Radiation oncology covers many different fields of knowledge and skills. Indeed, this medical specialty links physics, biology, research, and formation as well as surgical and clinical procedures and even rehabilitation and aesthetics. The current socio-economic situation and professional competences affect the development and future or this specialty. The aim of this article was to analyze and highlight the underlying pillars and foundations of radiation oncology, indicating the steps implicated in the future developments or competences of each.

METHODS

This study has collected data from the literature and includes highlights from discussions carried out during the XVII Congress of the Spanish Society of Radiation Oncology (SEOR) held in Vigo in June, 2013. Most of the aspects and domains of radiation oncology were analyzed, achieving recommendations for the many skills and knowledge related to physics, biology, research, and formation as well as surgical and clinical procedures and even supportive care and management.

RESULTS

Considering the data from the literature and the discussions of the XVII SEOR Meeting, the "waybill" for the forthcoming years has been described in this article including all the aspects related to the needs of radiation oncology.

CONCLUSIONS

Professional competences affect the development and future of this specialty. All the types of radio-modulation are competences of radiation oncologists. On the other hand, the pillars of Radiation Oncology are based on experience and research in every area of Radiation Oncology.

Direct and bystander radiation effects: a biophysical model and clinical perspectives

In planning treatment for each new patient, radiation oncologists pay attention to the aspects that they control. Thus their attention is usually focused on volume and dose. The dilemma for the physician is how to protract the treatment in a way that maximizes control of the tumor and minimizes normal tissue injury. The initial radiation-induced damage to DNA may be a biological indicator of the quantity of energy transferred to the DNA. However, until now the biophysical models proposed cannot explain either the early or the late adverse effects of radiation, and a more general theory appears to be required. The bystander component of tumor cell death after radiotherapy measured in many experimental works highlights the importance of confirming these observations in a clinical situation.

Delivering adaptive radiotherapy to the bladder during radical treatment

Radical radiotherapy to the bladder for muscle-invasive bladder cancer is a challenging treatment to plan and deliver because of organ mobility and its varying volume. The dynamic target volume can be tracked with imaging during the treatment course, enabling an adaptive response and adjustment of the patient’s individual treatment plan. This article summarises the difficulties encountered when treating the bladder, different approaches to patient imaging and adaptive radiotherapy techniques. Ultimately these technological advances support the delivery of a personalised treatment plan to ensure optimal dose delivery to the tumour and simultaneous sparing of adjacent normal tissue.

Genomic determinants of normal tissue toxicity after radiotherapy for head and neck malignancy: a systematic review

Interindividual variations in radiotoxicity responses exist despite uniform treatment protocols. It is speculated that normal genetic variants, particularly single nucleotide polymorphisms (SNPs) may influence normal head and neck (HN) tissue radiotoxicity. This first-ever systematic review was undertaken to evaluate the association of SNPs with normal HN tissues radiotoxicity. Multiple databases (1950-February 2012) were reviewed using a combination of related keywords and MeSH terms. All published HN radiotoxicity studies with sufficient relevant data for extraction were included. The outcomes evaluated were acute and late radiotoxicity endpoints. Methodological quality assessment based on the STrengthening the REporting of Genetic Association (STREGA) statement was performed. Seven articles from 692 articles searched fulfilled the eligibility criteria. Recruited sample sizes were small (range, 32-140). There were 5/7 case-control studies. All studies used multimodality treatment with heterogeneous radiation parameters. Candidate gene approach was used in all studies. Fourteen SNPs from 9 genes were evaluated from the following pathways: DNA damage response, radiation fibrogenesis and oxidative/xenobiotic metabolism. Acute radiotoxicity events were associated with SNPs of DNA repair genes (OR, 3.01-4.08). SNPs of TGFβ1 were associated with osteoradionecrosis (OR, 4.2) and subcutaneous fibrosis. Genetic association studies in HN radiotoxicity currently provide hypothesis-generating findings that require validation in larger studies. Future studies must incorporate critical methodological issues and technological improvements, including using a genome-wide approach. Headway is possible through case-pooling of existing clinical trial data which could create a larger sample size of well-characterized treatment and endpoints. Also, on-going HN cancer clinical trials should consider extending their toxicity evaluation to include genetic association studies.

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.

Decreasing the adverse effects of cancer therapy: National Cancer Institute guidance for the clinical development of radiation injury mitigators

Recently, many agents have been identified that target molecular pathways that can mitigate radiation toxicity. To date, no drugs have been approved as radiation injury mitigators, which are defined as agents administered after irradiation but before toxicity is manifest. In order to accelerate the application of potential mitigators for cancer patients, a meeting sponsored by the National Cancer Institute (NCI) and National Institute of Allergy and Infectious Diseases (NIAID) was held in January 2010. This article presents an algorithm to guide clinical trials for such agents in patients receiving radiotherapy or radiochemotherapy. It reviews the mechanisms of radiation injury, the clinical problem, the preclinical and clinical development of candidate agents, and the design and conduct of clinical trials. The central role of patient reported outcomes is outlined, as well as key lessons learned from prior clinical trials. Ultimately, the goal is to be able to apply such promising agents to improve the quality of life for patients receiving radiotherapy or chemoradiotherapy for cancer.

Biomarkers and surrogate endpoints for normal-tissue effects of radiation therapy: the importance of dose-volume effects

Biomarkers are of interest for predicting or monitoring normal tissue toxicity of radiation therapy. Advances in molecular radiobiology provide novel leads in the search for normal tissue biomarkers with sufficient sensitivity and specificity to become clinically useful. This article reviews examples of studies of biomarkers as predictive markers, as response markers, or as surrogate endpoints for radiation side effects. Single nucleotide polymorphisms are briefly discussed in the context of candidate gene and genomewide association studies. The importance of adjusting for radiation dose distribution in normal tissue biomarker studies is underlined. Finally, research priorities in this field are identified and discussed.

Association of single nucleotide polymorphisms in ATM, GSTP1, SOD2, TGFB1, XPD and XRCC1 with clinical and cellular radiosensitivity

PURPOSE

To examine the association of polymorphisms in ATM (codon 158), GSTP1 (codon 105), SOD2 (codon 16), TGFB1 (position -509), XPD (codon 751), and XRCC1 (codon 399) with fibrosis and also individual radiosensitivity.

METHODS AND MATERIALS

Retrospective analysis with 69 breast cancer patients treated with breast-conserving radiotherapy; total dose delivered was restricted to vary between 54 and 55Gy. Fibrosis was evaluated according to LENT/SOMA score. DNA was extracted from blood samples; cellular radiosensitivity was measured using the G0 assay and polymorphisms by PCR-RFLP and MALDI-TOF, respectively.

RESULTS

Twenty-five percent of all patients developed fibrosis of grade 2 or 3. This proportion tends to be higher in patients being polymorphic in TGFB1 or XRCC1 when compared to patients with wildtype genotype, whereas for ATM, GSTP1, SOD2 and XPD the polymorphic genotype appears to be associated with a lower risk of fibrosis. However, none of these associations are significant. In contrast, when a risk score is calculated based on all risk alleles, there was significant association with an increased risk of fibrosis (per risk allele odds ratio (ORs)=2.09, 95% confidence interval (CI): 1.32-3.55, p=0.0005). All six polymorphisms were found to have no significant effect on cellular radiosensitivity.

CONCLUSIONS

It is most likely that risk for radiation-induced fibrosis can be assessed by a combination of risk alleles. This finding needs to be replicated in further studies.

Profiling protein markers associated with the sensitivity to concurrent chemoradiotherapy in human cervical carcinoma

Concurrent chemoradiotherapy (CCRT) is recently recommended as the primary and standard treatment modality for cervical cancer. The aim of this study is to investigate the protein biomarkers associated with CCRT sensitivity, so as to better understand the mechanisms underlying CCRT resistance. Fresh tumor tissues from five cases for each group of CCRT-highly sensitive (CCRT-HS) and CCRT-lowly sensitive (CCRT-LS) were analyzed by 2-D electrophoresis coupled with MALDI-TOF-MS, followed by Western blot for four candidate proteins including S100A9, galectin-7, nuclear matrix protein-238 (NMP-238), and heat shock protein-70 (HSP-70). In randomly selected CCRT-HS (n = 60) and CCRT-LS (n = 35) cases, these four differentially expressed proteins were detected by tissue microarray with immunohistochemistry staining to explore the association between these interested proteins and CCRT sensitivity. Nineteen proteins differentially expressed more than four times between two groups were identified. An association was revealed between CCRT sensitivity and increased S100A9 and galectin-7, but decreased NMP-238 and HSP-70 expression (p < 0.001, respectively). Although none of these four protein markers could be used as an independent predictive factor, a recurrence prediction model was generated by combining S100A9, galectin-7, NMP-238, and HSP-70 as a full predictive factor. The proteomic analysis combined with tissue microarray provides us a dramatic tool in predicting CCRT response. The increased expression of S100A9 and galectin-7, but decreased expression of NMP-238 and HSP-70, suggests a significantly increased sensitivity to CCRT in cervical cancer.

Predicting the response of advanced cervical and ovarian tumors to therapy

The management of advanced cervical and ovarian cancers remains a significant challenge as many women fail to respond to recommended therapy, resulting in disease progression and ultimately patient death. Because of tumor heterogeneity, it is rare for all cancers of a particular type to respond to a specific therapy; and, as a result, many patients receive treatment from which they derive little or no benefit, leading to increased morbidity and undue costs. A marker that could rapidly predict or forecast disease outcome would clearly be beneficial in allowing the administration of a tailored regime for each patient while reducing toxicity and cost. Traditional prognostic factors of tumor size, grade, and stage are not ideal for predicting patient outcome, whereas the use of in vitro assays to detect chemosensitivity or resistance has not yet translated into routine clinical practice. Similarly, biomarkers and tumor markers vary in their predictive ability. DNA array technology offers great promise in predicting the response to therapy based on gene expression profiles, and can allow for targeted therapies against specific molecular alterations that cause disease. Imaging techniques, particularly those with the ability to characterize biological tissues and provide functional, structural, and molecular information, have the potential to noninvasively integrate physical and metabolic information. These include F-18-fluorodeoxyglucose positron emission tomography, dynamic contrast-enhanced magnetic resonance imaging, and diffusion weighted magnetic resonance imaging, all techniques that attempt to evaluate and predict therapy response and so influence clinical outcome. This review examines different methods of predicting the response to treatment in advanced cervical and ovarian tumors.

TARGET AUDIENCE

Obstetricians & Gynecologists, Family Physicians.

LEARNING OBJECTIVES

After completion of this article, the reader should be able to describe why prediction of response to therapy for cervical and ovarian cancers is important, describe obstacles to use of in vitro assays to predict outcomes for therapy for ovarian and cervical cancers, and explain potentially new predictive markers.

Genetic variations in DNA repair genes, radiosensitivity to cancer and susceptibility to acute tissue reactions in radiotherapy-treated cancer patients

Ionizing radiation is a well established carcinogen for human cells. At low doses, radiation exposure mainly results in generation of double strand breaks (DSBs). Radiation-related DSBs could be directly linked to the formation of chromosomal rearrangements as has been proven for radiation-induced thyroid tumors. Repair of DSBs presumably involves two main pathways, non-homologous end joining (NHEJ) and homologous recombination (HR). A number of known inherited syndromes, such as ataxia telangiectasia, ataxia-telangiectasia like-disorder, radiosensitive severe combined immunodeficiency, Nijmegen breakage syndrome, and LIG4 deficiency are associated with increased radiosensitivity and/or cancer risk. Many of them are caused by mutations in DNA repair genes. Recent studies also suggest that variations in the DNA repair capacity in the general population may influence cancer susceptibility. In this paper, we summarize the current status of DNA repair proteins as potential targets for radiation-induced cancer risk. We will focus on genetic alterations in genes involved in HR- and NHEJ-mediated repair of DSBs, which could influence predisposition to radiation-related cancer and thereby explain interindividual differences in radiosensitivity or radioresistance in a general population.

Predictive markers for normal tissue reactions: fantasy or reality?

Interpatient heterogeneity in normal tissue reactions varies considerably, yet the genetic determinants and the molecular mechanisms of therapeutic radiation sensitivity remain poorly understood. Predictive assays and markers for normal tissue reactions are still in their infancy, although some progress has been made, particularly, for predicting late toxicity. For instance the T-lymphocyte radiation-induced apoptosis assay was shown to significantly predict differences in late toxicity between individuals and an 18 gene classifier based on radiation-induced expression in subcutaneous fibroblasts has also been identified that differentiated between patients with a high and low risk of radiation-induced fibrosis. However, the technical set-up for gene expression measurements means that this latter assay is unlikely to be introduced soon into a routine clinical setting but has importantly allowed the identification of genes that are involved in the fibrotic process. Serum markers have also been identified that show potential for the prediction of patients who will develop acute and late pulmonary toxicity. Few genetic predictive markers for normal tissue reaction have been identified and validated. Many of the single nucleotide polymorphism association studies have been limited by size and the inclusion of subjects with different kinds of radiation morbidity. International collaboration to assemble well-defined cohorts and technological progress should mean that the identification and validation of such markers using candidate gene approaches and whole genome association studies, which have been successful in other research areas, will make rapid progress.

From cellular to high-throughput predictive assays in radiation oncology: challenges and opportunities

Substantial research efforts into predictive radiation oncology have so far produced very little in terms of clinically applicable assays. This may change with the development of novel high-throughput assays that are of potential interest in a radiation oncology setting. However, it seems that much current research is opportunistic, driven by the available technologies rather than addressing pertinent clinical or biological questions. This review looks at the experience gained from the attempts to develop cellular radiobiology assays. The research process and, in particular, the need for rigorous validation of any promising assay in an independent dataset are stressed. Some common design problems are discussed using examples from radiation oncology. The statistical challenges and some of the key concepts in analyzing dense datasets from high-throughput assays are briefly reviewed. Single nucleotide polymorphisms, immunohistochemical markers, and DNA microarray gene signatures are used as examples of assays that show promise in radiation oncology applications. Some recent studies suggest a differential treatment response between tumor stem cells and other tumor cells. If this is a general pattern, then future predictive assays may have to be performed on stems cells rather than on unselected tumor cells. Advances in radiogenomics or radioproteomics will come from large collaborative research networks, collecting high-quality dosimetric and clinical outcome data and combining state-of-the-art laboratory techniques with appropriate biostatical methods.

Randomized controlled trials in health technology assessment: overkill or overdue?

Evidence-based medicine has become a cornerstone in the development of radiation oncology and the randomized controlled phase III trial remains the gold standard for assessing differential benefits in clinical outcome between therapies. Health technologies aimed at improving treatment quality should primarily be tested using process measures or operational characteristics, the reason being that the sensitivity and specificity of clinical outcome is low for detecting quality improvements. The ongoing discussion of the relative merits of intensity modulated photon versus proton radiotherapy is used to illustrate these concepts. Concerns over clinical and individual equipoise as well as the potential limitations of health economics considerations in this setting are also discussed. Working in a technology and science based medical discipline, radiation oncology researchers need to further develop methodology for critical assessment of health technologies as a complement to randomized controlled trials.

Flow cytometry in radiation research: past, present and future

Flow cytometry is an invaluable technique in research and clinical laboratories. The technique has been applied extensively to many areas of radiation research at both the experimental and clinical level. In the past few years, there has been a significant increase in the capabilities of modern flow cytometers to undertake multicolor analysis in a user-friendly manner. The developments in cytometric technology are being matched by the rapid development of new reagents, new fluorochromes and new platforms such as bead arrays. These developments are facilitating many new applications in both basic and clinical research that have relevance for many fields of biology, including radiation research. This review provides a historical overview of the application of flow cytometry to radiobiology and an update on how technology and reagents have changed and cites examples of new applications relevant to radiation researchers. In addition, some entirely new flow instrumentation is currently under development that has significant potential for applications in radiation research.

Evaluation of Early and Late Toxicities in Chemoradiation Trials

Combined chemoradiotherapy is increasingly becoming a standard of care for the nonoperative management of a variety of solid malignancies. A string of randomized controlled phase III trials have shown statistically significant and clinically relevant improvements in outcome, ostensibly without any apparent increase in late toxicity. However, the reliability and the sensitivity of toxicity reporting in most trials are questionable. Audits and phase IV studies suggest that the chemoradiotherapy success comes at a price in terms of late toxicity. This review presents some of the challenges in recording, analyzing, and reporting toxicity data. Methods for summarizing toxicity are reviewed, and a new investigational metric, the TAME reporting system, is discussed. The need for special vigilance in the era of molecular-targeted agents is emphasized because of the possibility that unexpected serious adverse events with a low incidence may occur. Finally, we discuss how progress in molecular pathology and radiation biology may provide novel opportunities for stratifying patients according to risk of adverse effects, interventional targets for reducing or treating adverse effects, and surrogate markers of normal-tissue injury.

Predicting Risk of Radiation-Induced Lung Injury

Radiation-induced lung injury (RILI) is the most common, dose-limiting complication of thoracic radio- and radiochemotherapy. Unfortunately, predicting which patients will suffer from this complication is extremely difficult. Ideally, individual phenotype- and genotype-based risk profiles should be able to identify patients who are resistant to RILI and who could benefit from dose escalation in chemoradiotherapy. This could result in better local control and overall survival. We review the risk predictors that are currently in clinical use--dosimetric parameters of radiotherapy such as normal tissue complication probability, mean lung dose, V20 and V30--as well as biomarkers that might individualize risk profiles. These biomarkers comprise a variety of proinflammatory and profibrotic cytokines and molecules including transforming growth factor beta1 that are implicated in development and persistence of RILI. Dosimetric parameters of radiotherapy show a low negative predictive value of 60% to 80%. Depending on the studied molecule, negative predictive value of biomarkers is approximately 50%. The predictive power of biomarkers might be increased if they are coupled with radiogenomics, e.g., genotyping analysis of single nucleotide polymorphisms in transforming growth factor beta1, transforming growth factor beta1 pathway genes, and other cytokines. Genetic variability and the complexity of RILI and its underlying molecular mechanisms make identification of biological risk predictors challenging. Further investigations are needed to develop more effective risk predictors of RILI.

Genetic susceptibility to late normal tissue injury

The outcome of all cancer therapies, including radiation, has greatly improved in the last 25 years, resulting in a doubling of the number of long-term cancer survivors. However, a subset of these survivors incurs adverse chronic side effects in unavoidably irradiated normal tissues, persisting long after treatment and compromising the quality of life of these patients. Interpatient variability in normal tissue radiation response is well documented and suggested to be under genetic control. Fibrosis, a clinically significant late effect in many irradiated tissues that results in tissue remodeling and loss of function, is a complex genetic trait making identification of the underlying genes difficult. Current clinical and animal studies are providing information on the genetics and molecular basis of late normal tissue injury in the radiation therapy setting, bringing us closer to our dual goal of individualizing treatment by genetic profiling and improving the quality of life of long-term survivors.

The genomics revolution and radiotherapy

The expansion of our knowledge through the Human Genome Project has been accompanied by the development of new high-throughput techniques, which provide extensive capabilities for the analysis of a large number of genes or the whole genome. These assays can be carried out in various clinical samples at the DNA (genome), RNA (transcriptome) or protein (proteome) level. There is a belief that this genomic revolution, i.e. sequencing of the human genome and developments in high-throughput technology, heralds a future of personalised medicine. For clinical oncology, this progress should increase the possibility of predicting individual patient responses to radiotherapy. This review highlights some of the work involving sparsely ionising radiation and the new technologies.

Preventing or reducing late side effects of radiation therapy: radiobiology meets molecular pathology

Radiation therapy has curative or palliative potential in roughly half of all incident solid tumours, and offers organ and function preservation in most cases. Unfortunately, early and late toxicity limits the deliverable intensity of radiotherapy, and might affect the long-term health-related quality of life of the patient. Recent progress in molecular pathology and normal-tissue radiobiology has improved the mechanistic understanding of late normal-tissue effects and shifted the focus from initial-damage induction to damage recognition and tissue remodelling. This stimulates research into new pharmacological strategies for preventing or reducing the side effects of radiation therapy.

Genetic predictors of adverse radiotherapy effects: the Gene-PARE project

PURPOSE

The development of adverse effects resulting from the radiotherapy of cancer limits the use of this treatment modality. The validation of a test capable of predicting which patients would be most likely to develop adverse responses to radiation treatment, based on the possession of specific genetic variants, would therefore be of value. The purpose of the Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE) project is to help achieve this goal.

METHODS AND MATERIALS

A continuously expanding biorepository has been created consisting of frozen lymphocytes and DNA isolated from patients treated with radiotherapy. In conjunction with this biorepository, a database is maintained with detailed clinical information pertaining to diagnosis, treatment, and outcome. The DNA samples are screened using denaturing high performance liquid chromatography (DHPLC) and the Surveyor nuclease assay for variants in ATM, TGFB1, XRCC1, XRCC3, SOD2, and hHR21. It is anticipated that additional genes that control the biologic response to radiation will be screened in future work.

RESULTS

Evidence has been obtained that possession of variants in genes, the products of which play a role in radiation response, is predictive for the development of adverse effects after radiotherapy.

CONCLUSIONS

It is anticipated that the Gene-PARE project will yield information that will allow radiation oncologists to use genetic data to optimize treatment on an individual basis.

Can risk of radiotherapy-induced normal tissue complications be predicted from genetic profiles?

Over the last decade, increasing efforts have been taken to establish associations between various genetic germline alterations and risk of normal tissue complications after radiotherapy. Though the studies have been relatively small and methodologically heterogeneous, preliminary indications have been provided that single nucleotide polymorphisms in the genes TGFB1 and ATM may modulate risk of particularly late toxicity. In addition, rare ATM alterations may enhance complication susceptibility. Nevertheless, we are still far from having an exhaustive understanding of the genetics that may underlie differences in clinical normal tissue radiosensitivity. Recent technical advances and emerging insights to the structure of inter-individual genetic variation open up unprecedented opportunities to dissect the molecular and genetic basis of normal tissue radiosensitivity. However, to fully exploit these new possibilities well-planed large-scale clinical studies are mandatory. Currently, international initiatives are taken to establish the bio banks and databases needed for this task.

Gene expression profile changes correlating with radioresistance in human cell lines

PURPOSE

To identify gene expression profiles specific to radioresistance of human cells.

METHODS AND MATERIALS

Global gene expression profiles of a total of 15 tumor and normal fibroblast cell lines were analyzed using DNA microarrays and statistical clustering methods. Initially, six of the cell lines were categorized into radioresistant (RG) or nonradioresistant (NRG) groups according to the radiation dose required to reduce their survival to 10% (D10). Genes for which expression was specific to each group at 1 or 3 h after irradiation were identified using statistical procedures including analysis of variance and a two-dimensional hierarchical clustering method. The remaining nine cell lines were subjected to the k-nearest neighbor pattern classification.

RESULTS

The nine test cell lines were successfully classified by their D10 value using 46 and 44 genes for which transcription levels had significantly changed at 1 and 3 h after irradiation, respectively. Of these genes, 25 showed altered expression at both time points in the NRG or RG, but independently were unable to classify the test cell lines.

CONCLUSIONS

Radioresistant cell lines analyzed in this study showed certain radiation-induced changes in gene expression profiles that are different from the profile changes of the more-sensitive cell lines.

Influence of connective tissue diseases on the expression of radiation side effects: a systematic review

BACKGROUND AND PURPOSE

Patient related co-factors may increase the risk of radiation morbidity. Connective tissue diseases (CTD) are among the co-morbidities that are relatively well studied and have been shown to be of potential clinical relevance for radiotherapy. The aim of this systematic review is to quantify the contribution of CTD to the risk of radiation related side effects.

PATIENTS AND METHODS

Relevant publications reporting the outcome of radiotherapy in patients with CTD were retrieved according to a standardized query and evaluated for their methodology and quality of reporting, using defined quality criteria. A quantitative estimate of the relative risk of developing side effects in patients with CTD was derived from the observed proportions of responders in patients with or without CTD. Risk estimates were synthesized across studies.

RESULTS

Eight studies which include data of 9-209 patients who had CTD and were treated with radiotherapy were identified and reviewed. Three of these studies included data suited for further quantitative analysis. The test of the uni-directional hypothesis that patients with CTD had an increased risk of late effects after radiotherapy reached statistical significance, the one-tailed P-value being 0.03. The pooled relative risk was 2.0 with 95% confidence interval (0.99, 4.1).

CONCLUSIONS

CTD is associated with an increased risk of late radiation induced normal tissue reaction. The literature published to date provides some support for this assertion although most of the reports are plagued by methodological weaknesses, thus calling for a large coordinated study.

Update on clinical radiobiology

Radiation therapy is an important local cytotoxic modality for cancer treatment whose aim is to control the disease while minimising damage to normal tissue. The combination of different treatment modalities offers a more effective cure and reduction in normal tissue toxicity. However, the differences in genetic profiles can cause diverse treatment outcomes. Multidisciplinary research, where technologies and knowledge from different areas are integrated, is necessary to design the optimal regimen for individualised cancer treatment. This paper offers an overview of some new cancer treatment strategies; the impact of molecular imaging on radiation oncology; and a computer simulation model to optimise treatment planning based on patient information. It briefly discusses molecular targeted therapy, tumour microenvironment and bioreductive agents, and evidence for making individualised medicine a reality. Using DNA microarrays and proteomic technologies, information on defined molecular targets and genetic profiling for individual patients can be obtained and new algorithms for radiation oncology-related diagnosis, treatment response and prognosis can be developed.