Genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with the development of erectile dysfunction in African-American men after radiotherapy for prostate cancer

Association of Single Nucleotide Polymorphisms (SNPs) of Chemoattractant Receptor23 (ChemR23) Gene with Susceptibility to Allergic Rhinitis

The chemoattractant Receptor23 (ChemR23) plays an essential role in triggering and resolving acute inflammation. This study aimed to evaluate the association between four potentially functional SNPs of the chemR23 gene (rs4373981 G > C, rs73201532 C > T, rs35121177 G > A, and rs4964676 G > A) with susceptibility to Allergic rhinitis (AR). 130 patients with allergic rhinitis and 130 healthy individuals were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) method. Our findings showed that genotypes and alleles frequencies were not significantly different between patient and control groups (p > 0.05). Furthermore, haplotype analysis (rs4373981, rs73201532, and rs4964676, respectively) revealed a protective effect of CTG, GTA, and GTG haplotypes against AR (p = 0.009, p = 0.0001, p = 0.001, respectively), and CCG, GCA, and GCG haplotypes of ChemR23 polymorphisms were associated with increased risk of AR (p = 0.03, p = 0.02, p = 0.0002, respectively). These findings suggested a possible role for ChemR23 in the pathogenesis of AR.

A comprehensive predictive model for radiation-induced brain injury in risk stratification and personalized radiotherapy of nasopharyngeal carcinoma

BACKGROUND AND PURPOSE

Radiation-induced brain injury (RBI) is a severe radiotoxicity for nasopharyngeal carcinoma (NPC) patients, greatly affecting their long-term life quality and survival. We aim to establish a comprehensive predictive model including clinical factors and newly developed genetic variants to improve the precision of RBI risk stratification.

MATERIALS AND METHODS

By performing a large registry-based retrospective study with magnetic resonance imaging follow-up on RBI development, we conducted a genome-wide association study and developed a polygenic risk score (PRS) for RBI in 1189 NPC patients who underwent intensity-modulated radiotherapy. We proposed a tolerance dose scheme for temporal lobe radiation based on the risk predicted by PRS. Additionally, we established a nomogram by combining PRS and clinical factors for RBI risk prediction.

RESULTS

The 38-SNP PRS could effectively identify high-risk individuals of RBI (P = 1.42 × 10-34). Based on genetic risk calculation, the recommended tolerance doses of temporal lobes should be 57.6 Gy for individuals in the top 10 % PRS subgroup and 68.1 Gy for individuals in the bottom 50 % PRS. Notably, individuals with high genetic risk (PRS > P50) and receiving high radiation dose in the temporal lobes (D0.5CC > 65 Gy) had an approximate 50-fold risk over individuals with low PRS and receiving low radiation dose (HR = 50.09, 95 %CI = 24.27-103.35), showing an additive joint effect (Pinteraction < 0.001). By combining PRS with clinical factors including age, tumor stage, and radiation dose of temporal lobes, the predictive accuracy was significantly improved with C-index increased from 0.78 to 0.85 (P = 1.63 × 10-2).

CONCLUSIONS

The PRS, together with clinical factors, could improve RBI risk stratification and implies personalized radiotherapy.

Lipid metabolism and neuromuscular junction as common pathways underlying the genetic basis of erectile dysfunction and obstructive sleep apnea

Erectile dysfunction (ED) incidence is higher in patients with obstructive sleep apnea (OSA). Studies have suggested that ED and OSA may activate similar pathways; however, few have investigated the links between their underlying genotypic profiles. Therefore, we conducted an in-silico analysis to test whether ED and OSA share genetic variants of risk and to identify any molecular, cellular and biological interactions between them. Two gene lists were manually curated through a literature review based on a PUBMED search, which resulted in one gene list associated with ED (total of 205 genes) and the other with OSA (total of 2622 genes). Between those gene sets, 35 were common for both lists (Fisher exact test, p-value = 0.027). The Protein-protein interaction (PPI) analysis using the intersect list as input showed that 3 of them had direct interactions (LPL, DGKB and PLCB1). In addition, the biological function of the genes contained in the intersect list suggested that pathways related to lipid metabolism and the neuromuscular junction were commonly found in the genetic basis of ED and OSA. From the shared genes between both conditions, the biological pathways highlighted in this study may serve as preliminary findings for future functional investigations on OSA and ED association.

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.

The Normal, the Radiosensitive, and the Ataxic in the Era of Precision Radiotherapy: A Narrative Review

(1) Background: radiotherapy is a cornerstone of cancer treatment. When delivering a tumoricidal dose, the risk of severe late toxicities is usually kept below 5% using dose-volume constraints. However, individual radiation sensitivity (iRS) is responsible (with other technical factors) for unexpected toxicities after exposure to a dose that induces no toxicity in the general population. Diagnosing iRS before radiotherapy could avoid unnecessary toxicities in patients with a grossly normal phenotype. Thus, we reviewed iRS diagnostic data and their impact on decision-making processes and the RT workflow; (2) Methods: following a description of radiation toxicities, we conducted a critical review of the current state of the knowledge on individual determinants of cellular/tissue radiation; (3) Results: tremendous advances in technology now allow minimally-invasive genomic, epigenetic and functional testing and a better understanding of iRS. Ongoing large translational studies implement various tests and enriched NTCP models designed to improve the prediction of toxicities. iRS testing could better support informed radiotherapy decisions for individuals with a normal phenotype who experience unusual toxicities. Ethics of medical decisions with an accurate prediction of personalized radiotherapy's risk/benefits and its health economics impact are at stake; (4) Conclusions: iRS testing represents a critical unmet need to design personalized radiotherapy protocols relying on extended NTCP models integrating iRS.

Identification of Novel Regulators of Radiosensitivity Using High-Throughput Genetic Screening

The biological impact of ionizing radiation (IR) on humans depends not only on the physical properties and absorbed dose of radiation but also on the unique susceptibility of the exposed individual. A critical target of IR is DNA, and the DNA damage response is a safeguard mechanism for maintaining genomic integrity in response to the induced cellular stress. Unrepaired DNA lesions lead to various mutations, contributing to adverse health effects. Cellular sensitivity to IR is highly correlated with the ability of cells to repair DNA lesions, in particular coding sequences of genes that affect that process and of others that contribute to preserving genomic integrity. However, accurate profiling of the molecular events underlying individual sensitivity requires techniques with sensitive readouts. Here we summarize recent studies that have used whole-genome analysis and identified genes that impact individual radiosensitivity. Whereas microarray and RNA-seq provide a snapshot of the transcriptome, RNA interference (RNAi) and CRISPR-Cas9 techniques are powerful tools that enable modulation of gene expression and characterizing the function of specific genes involved in radiosensitivity or radioresistance. Notably, CRISPR-Cas9 has altered the landscape of genome-editing technology with its increased readiness, precision, and sensitivity. Identifying critical regulators of cellular radiosensitivity would help tailor regimens that enhance the efficacy of therapeutic treatments and fast-track prediction of clinical outcomes. It would also contribute to occupational protection based on average individual sensitivity, as well as the formulation of countermeasures to the harmful effects of radiation.

Gene alterations as predictors of radiation-induced toxicity in head and neck squamous cell carcinoma

Background

Optimizing the therapeutic ratio for radiation therapy (RT) in head and neck squamous cell carcinoma (HNSCC) is uniquely challenging owing to high rates of early and late toxicity involving nearby organs at risk. These toxicities have a profound impact on treatment compliance and quality of life. Emerging evidence suggests that RT dose alone cannot fully account for the variable severity of RT-related adverse events (rtAEs) observed in HNSCC patients. Next-generation sequencing has become an increasingly valuable tool with widespread use in the oncology field and is being robustly explored for predicting rtAEs beyond dosimetric data.

Methods

Patients who had Foundation Medicine sequencing data and received RT for primary or locally recurrent HNSCC were selected for this study. Early and late toxicity data were collected and reported based on Common Terminology Criteria for Adverse Events version 5.0. Dosimetric parameters were collected for pertinent structures.

Results

A total of HNSCC 37 patients were analyzed in this study. Genetic alterations in BRCA2, ERBB3, NOTCH1 and CCND1 were all associated with higher mean grade of toxicity with BRCA2 alteration implicated in all toxicity parameters evaluated including mucositis, early dysphagia, xerostomia and to a lesser extent, late dysphagia. Interestingly, patients who exhibited alterations in both BRCA2 and ERBB3 experienced a twofold or greater increase in early dysphagia, early xerostomia and late dysphagia compared to ERBB3 alteration alone. Furthermore, several gene alterations were associated with improved toxicity outcomes. Within an RT supersensitive patient subset, alterations were found in TNFAIP3, HNF1A, SPTA1 and CASP8. All of these alterations were not found in the RT insensitive patient subset. We found 17 gene alterations in the RT insensitive patient subset that were not found in the RT supersensitive patient subset.

Conclusion

Despite consistent RT dosimetric parameters, patients with HNSCC experience heterogeneous patterns of rtAEs. Identifying factors associated with toxicity outcomes offers a new avenue for personalized precision RT therapy and prophylactic management. Here, next-generation sequencing in a population of HNSCC patients correlates several genetic alterations with severity of rtAEs. Further analysis is urgently needed to identify genetic patterns associated with rtAEs in order to reduce harmful outcomes in this challenging population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02876-5.

Liquid biopsy in NSCLC: a new challenge in radiation therapy

Lung cancer is the most common cancer and the leading cause of cancer mortality worldwide. To date, tissue biopsy has been the gold standard for the diagnosis and the identification of specific molecular mutations, to guide choice of therapy. However, this procedure has several limitations. Liquid biopsy could represent a solution to the intrinsic limits of traditional biopsy. It can detect cancer markers such as circulating tumor DNA or RNA (ctDNA, ctRNA), and circulating tumor cells, in plasma, serum or other biological fluids. This procedure is minimally invasive, reproducible and can be used repeatedly. The main clinical applications of liquid biopsy in non-small cell lung cancer (NSCLC) patients are the early diagnosis, stratification of the risk of relapse, identification of mutations to guide application of targeted therapy and the evaluation of the minimum residual disease. In this review, the current role of liquid biopsy and associated markers in the management of NSCLC patients was analyzed, with emphasis on ctDNA and CTCs, and radiotherapy.

Low dose ionizing radiation effects on the immune system

Ionizing radiation interacts with the immune system in many ways with a multiplicity that mirrors the complexity of the immune system itself: namely the need to maintain a delicate balance between different compartments, cells and soluble factors that work collectively to protect, maintain, and restore tissue function in the face of severe challenges including radiation damage. The cytotoxic effects of high dose radiation are less relevant after low dose exposure, where subtle quantitative and functional effects predominate that may go unnoticed until late after exposure or after a second challenge reveals or exacerbates the effects. For example, low doses may permanently alter immune fitness and therefore accelerate immune senescence and pave the way for a wide spectrum of possible pathophysiological events, including early-onset of age-related degenerative disorders and cancer. By contrast, the so called low dose radiation therapy displays beneficial, anti-inflammatory and pain relieving properties in chronic inflammatory and degenerative diseases. In this review, epidemiological, clinical and experimental data regarding the effects of low-dose radiation on the homeostasis and functional integrity of immune cells will be discussed, as will be the role of immune-mediated mechanisms in the systemic manifestation of localized exposures such as inflammatory reactions. The central conclusion is that ionizing radiation fundamentally and durably reshapes the immune system. Further, the importance of discovery of immunological pathways for modifying radiation resilience amongst other research directions in this field is implied.

Telomere Length Dynamics and Chromosomal Instability for Predicting Individual Radiosensitivity and Risk via Machine Learning

The ability to predict a cancer patient's response to radiotherapy and risk of developing adverse late health effects would greatly improve personalized treatment regimens and individual outcomes. Telomeres represent a compelling biomarker of individual radiosensitivity and risk, as exposure can result in dysfunctional telomere pathologies that coincidentally overlap with many radiation-induced late effects, ranging from degenerative conditions like fibrosis and cardiovascular disease to proliferative pathologies like cancer. Here, telomere length was longitudinally assessed in a cohort of fifteen prostate cancer patients undergoing Intensity Modulated Radiation Therapy (IMRT) utilizing Telomere Fluorescence in situ Hybridization (Telo-FISH). To evaluate genome instability and enhance predictions for individual patient risk of secondary malignancy, chromosome aberrations were assessed utilizing directional Genomic Hybridization (dGH) for high-resolution inversion detection. We present the first implementation of individual telomere length data in a machine learning model, XGBoost, trained on pre-radiotherapy (baseline) and in vitro exposed (4 Gy γ-rays) telomere length measurements, to predict post radiotherapy telomeric outcomes, which together with chromosomal instability provide insight into individual radiosensitivity and risk for radiation-induced late effects.

Harnessing genome-wide association studies to minimize adverse radiation-induced side effects

Radiotherapy is used as definitive treatment in approximately two-thirds of all cancers. However, like any treatment, radiation has significant acute and long-term side effects including secondary malignancies. Even when similar radiation parameters are used, 5%–10% of patients will experience adverse radiation side effects. Genomic susceptibility is thought to be responsible for approximately 40% of the clinical variability observed. In the era of precision medicine, the link between genetic susceptibility and radiation-induced side effects is further strengthening. Genome-wide association studies (GWAS) have begun to identify single-nucleotide polymorphisms (SNPs) attributed to overall and tissue-specific toxicity following radiation for treatment of breast cancer, prostate cancer, and other cancers. Here, we review the use of GWAS in identifying polymorphisms that are predictive of acute and long-term radiation-induced side effects with a focus on chest, pelvic, and head-and-neck irradiation. Integration of GWAS with “omic” data, patient characteristics, and clinical correlates into predictive models could decrease radiation-induced side effects while increasing therapeutic efficacy.

[Treatment of radiation-induced late effects: What's new?]

Mechanisms of late radio-induced lesions are the result of multiple and complex phenomena, with many entangled cellular and tissue factors. The biological continuum between acute and late radio-induced effects will be described, with firstly a break in homeostasis that leads to cellular redistributions. New insights into late toxicity will finally be addressed. Individual radiosensitivity is a primary factor for the development of late toxicity, and clinicians urgently need predictive tests to offer truly personalized radiation therapy. An update will be made on the various functional and genetic tests currently being validated. The management of radio-induced side effects remains a frequent issue for radiation oncologists, and an update will be made for certain specific clinical situations. Finally, an innovative management for patients with significant side effects after pelvic radiotherapy will be developed, involved mesenchymal stem cell transplantation, with the presentation of the "PRISME" protocol currently open to patients recruitment.

Genomics models in radiotherapy: From mechanistic to machine learning

Machine learning (ML) provides a broad framework for addressing high-dimensional prediction problems in classification and regression. While ML is often applied for imaging problems in medical physics, there are many efforts to apply these principles to biological data toward questions of radiation biology. Here, we provide a review of radiogenomics modeling frameworks and efforts toward genomically guided radiotherapy. We first discuss medical oncology efforts to develop precision biomarkers. We next discuss similar efforts to create clinical assays for normal tissue or tumor radiosensitivity. We then discuss modeling frameworks for radiosensitivity and the evolution of ML to create predictive models for radiogenomics.

The genetic landscapes of urological cancers and their clinical implications in the era of high-throughput genome analysis

OBJECTIVE

With the advent of high-throughput genome analysis, we are increasingly able to sequence and hence understand the pathogenic processes underlying individual cancers. Recently, consortiums such as The Cancer Genome Atlas (TCGA) have performed large-scale projects to this end, providing significant amounts of information regarding the genetic landscapes of several cancers.

PATIENTS AND METHODS

We performed a narrative review of studies from the TCGA and other major studies. We aimed to summarise data exploring the clinical implications of specific genetic alterations, both prognostically and therapeutically, in four major urological cancers. These were renal cell carcinoma, muscle-invasive bladder cancer/carcinoma, prostate cancer, and testicular germ cell tumours.

RESULTS

With these four urological cancers, great strides have been made in the molecular characterisation of tumours. In particular, recent studies have focussed on identifying molecular subtypes of tumours with characteristic genetic alterations and differing prognoses. Other prognostic alterations have also recently been identified, including those pertaining to epigenetics and microRNAs. In regard to treatment, numerous options are emerging for patients with these cancers such as including immune checkpoint inhibition, epigenetic-based treatments, and agents targeting MAPK, PI3K, and DNA repair pathways. There are a multitude of trials underway investigating the effects of these novel agents, the results of which are eagerly awaited.

CONCLUSIONS

As medicine chases the era of personalised care, it is becoming increasingly important to provide individualised prognoses for patients. Understanding how specific genetic alterations affects prognosis is key for this. It will also be crucial to provide highly targeted treatments against the specific genetics of a patient's tumour. With work performed by the TCGA and other large consortiums, these aims are gradually being achieved. Our review provides a succinct overview of this exciting field that may underpin personalised medicine in urological oncology.

A genome-wide association study identifies FSHR rs2300441 associated with follicle-stimulating hormone levels

Follicle-stimulating hormone (FSH) and luteinizing hormone (LH) play critical roles in female reproduction, while the underlying genetic basis is poorly understood. Genome-wide association studies (GWASs) of FSH and LH levels were conducted in 2590 Chinese females including 1882 polycystic ovary syndrome (PCOS) cases and 708 controls. GWAS for FSH level identified multiple variants at FSHR showing genome-wide significance with the top variant (rs2300441) located in the intron of FSHR. The A allele of rs2300441 led to a reduced level of FSH in the PCOS group (β = -.43, P = 6.70 × 10^-14 ) as well as in the control group (β = -.35, P = 6.52 × 10^-4 ). In the combined sample, this association was enhanced after adjusting for the PCOS status (before: β = -.38, P = 1.77 × 10^-13 ; after: β = -.42, P = 3.33 × 10^-16 ), suggesting the genetic effect is independent of the PCOS status. The rs2300441 explained sevenfold higher proportion of the FSH variance than the total variance explained by the two previously reported FSHR missense variants (rs2300441 R² = 1.40% vs rs6166 R² = 0.17%, rs6165 R² = 0.03%). GWAS for LH did not identify any genome-wide significant associations. In conclusion, we identified genome-wide significant association between variants in FSHR and circulating FSH first, with the top associated variant rs2300441 might be a primary contributor at the population level.

Expression of LHCG receptors in the human penis

The aim of this study is to investigate the expression of the luteinizing hormone/choriogonadotropin (LHCG) receptor in the human penis to see, if the luteinizing hormone (LH) effects are possible in the spongious and cavernous tissue of the penis. The number of men with erection disturbances increases significantly simultaneously with the elevated LH concentrations between 40 and 70 years. It is possible that the elevated LH concentrations may influence locally the erectile mechanisms. The precondition for this is the expression of LHCG receptors in the penis. Penile tissue was obtained from three patients undergoing total or partial penectomy due to a rectal cancer with secondary penile metastasis or squamous cell carcinoma of the penis. Immunohistochemistry was used for the detection of the LHCG receptor. Positive immunoreaction for LHCG receptors was discovered in the endothelial cells of cavernous spaces in the corpus cavernosum and corpus spongiosum penis, also in the endothelial cells of the capillary walls in all patients. Our results show that LHCG receptor is expressed in the spongious and cavernous tissue of the human penis. This finding suggests that LH can affect the spongious and cavernous tissue in human and play a significant role in the development of erectile dysfunction among the aging men.

Developing more sensitive genomic approaches to detect radioresponse in precision radiation oncology: From tissue DNA analysis to circulating tumor DNA

Despite the common application and considerable efforts to achieve precision radiotherapy (RT) in several types of cancer, RT has not yet entered the era of precision medicine; the ability to predict radiosensitivity and treatment responses in tumors and normal tissues is lacking. Therefore, development of genome-based methods for individual prognosis in radiation oncology is urgently required. Traditional DNA sequencing requires tissue samples collected during invasive operations; therefore, repeated tests are nearly impossible. Intra- and inter-tumoral heterogeneity may undermine the predictive power of a single assay from tumor samples. In contrast, analysis of circulating tumor DNA (ctDNA) allows for non-invasive and near real-time sampling of tumors. By investigating the genetic composition of tumors and monitoring dynamic changes during treatment, ctDNA analysis may potentially be clinically valuable in prediction of treatment responses prior to RT, surveillance of responses during RT, and evaluation of residual disease following RT. As a biomarker for RT response, ctDNA profiling may guide personalized treatments. In this review, we will discuss approaches of tissue DNA sequencing and ctDNA detection and summarize their clinical applications in both traditional RT and in combination with immunotherapy.

Elevated Risk of Radiation Therapy-Associated Second Malignant Neoplasms in Young African-American Women Survivors of Stage I-IIIA Breast Cancer

PURPOSE

To estimate the effect of radiation therapy (RT) on nonbreast second malignant neoplasms (SMNs) in young women survivors of stage I-IIIA breast cancer.

METHODS AND MATERIALS

Women aged 20 to 44 years who received a diagnosis of stage I-IIIA breast cancer (1988-2008) were identified in the Surveillance, Epidemiology, and End Results 9 registries. Bootstrapping approach and competing-risk proportional hazards models were used to evaluate the effect of RT on nonbreast SMN risk. The analysis was repeated in racial subgroups. Radiotolerance score analysis of normal airway epithelium was performed using Gene Expression Omnibus (GEO) data sets.

RESULTS

Within records of 30,003 women with primary breast cancer, 20,516 eligible patients were identified, including 2,183 African Americans (AAs) and 16,009 Caucasians. The 25-year cumulative incidences of SMN were 5.2% and 3.6% (RT vs no-RT) for AAs, with 12.8-year and 17.4-year (RT vs no-RT) median follow-up (hazard ratio [HR] = 1.81; 95% bootstrapping confidence interval [BCI], 1.02-2.50; P < .05), respectively, and 6.4% and 5.9% (RT vs no-RT) for Caucasians with 14.3-year and 18.1-year (RT vs no-RT) median follow-up (HR = 1.10; 95% BCI, 0.61-1.40; P > .05), respectively. The largest portion of excess RT-related SMN risk was lung cancer (AA: HR = 2.08, 95% BCI, 1.02-5.39, P < .05; Caucasian: HR = 1.50, 95% BCI, 0.84-5.38, P > .05). Subpopulation Treatment Effect Pattern Plot (STEPP) analysis revealed higher post-RT nonbreast SMN risk in those 20 to 44 years of age, with larger HRs for RT in AAs. Radiotolerance score (RTS) of normal airway epithelium from young AA women was significantly lower than that from young Caucasian women (P = .038).

CONCLUSIONS

With a projected 25-year follow-up, RT is associated with elevated risk of nonbreast SMNs, particularly second lung cancer, in young women survivors of stage I-IIIA breast cancer. Nonbreast SMNs associated with RT are higher in AA women than Caucasian women.

A systematic review of radiation-induced testicular toxicities following radiotherapy for prostate cancer

BACKGROUND

Prostate cancer is the second most common malignancy in men in the world, and radiotherapy is used as a standard treatment modality for this cancer. Although this treatment modality effectively kills prostate cancerous cells, it unavoidably irradiates the organs/tissues that are away from the treatment site. In this regard, radiation-induced testicular toxicities following prostate radiotherapy can affect sexual function, reproduction, and quality of life in cancer survivors. This review summarizes the available data on testicular exposure to radiation during prostate radiotherapy and the consequences on testicular function.

METHODS

To illuminate the radiation-induced testicular toxicities following prostate radiotherapy, a systematic search was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline in PubMed, Web of Science, Scopus, Embase, and clinical trials electronic databases up to September 2018. According to a set of prespecified inclusion and exclusion criteria, 31 eligible articles providing data on testicular function following radiotherapy in patients with prostate cancer were included in the study.

RESULTS

According to the different radiotherapeutic techniques used for prostate cancer treatment, the total tumor dose and scattered testicular dose values were ranging from 36.25 to 78.00 Gy and 0.06 to 6.48 Gy, respectively. Luteinizing hormone and follicle-stimulating hormone levels after prostate radiotherapy were significantly higher in comparison with the pretreatment levels. Around 60% of the studies showed that testosterone levels after prostate radiotherapy were significantly lower than the pretreatment levels. Furthermore, erectile dysfunction (ED), as an adverse side effect resulting from prostate radiotherapy, was reported and this complication is significantly correlated with lower satisfaction with sexual life. Testicular atrophy following prostate radiotherapy has also been observed and its frequency in patients with prior prostate radiotherapy is 2.5 times more than that in the patients without prior radiotherapy.

CONCLUSION

The data revealed that the scattered dose to testicular tissues during prostate radiotherapy can lead to testicular atrophy, variation of the male sex hormones, and quality of sexual life.

[Predictive assays for responses of tumors and normal tissues in radiation oncology]

The impact of curative radiotherapy depends mainly on the total dose delivered homogenously in the target volume. Tumor sensitivity to radiotherapy may be particularly inconstant depending on location, histology, somatic genetic parameters and the capacity of the immune system to infiltrate the tumor. In addition, the dose delivered to the surrounding healthy tissues may reduce the therapeutic ratio of many radiation treatments. In a same population treated in one center with the same technique, it appears that individual radiosensitivity clearly exists, namely in terms of late side effects that are in principle non-reversible. This review details the different radiobiological approaches that have been developed to better predict the tumor response but also the radiation-induced late effects.

Genome-Wide Association Study of Susceptibility Loci for Radiation-Induced Brain Injury

BACKGROUND

Radiation-induced brain injury is a nonnegligible issue in the management of cancer patients treated by partial or whole brain irradiation. In particular, temporal lobe injury (TLI), a deleterious late complication in nasopharyngeal carcinoma, greatly affects the long-term life quality of these patients. Although genome-wide association studies (GWASs) have successfully identified single nucleotide polymorphisms (SNPs) associated with radiation toxicity, genetic variants contributing to the radiation-induced brain injury have not yet been assessed.

METHODS

We recruited and performed follow-up for a prospective observational cohort, Genetic Architecture of Radiotherapy Toxicity and Prognosis, using magnetic resonance imaging for TLI diagnosis. We conducted genome-wide association analysis in 1082 patients and validated the top associations in two independent cohorts of 1119 and 741 patients, respectively. All statistical tests were two-sided.

RESULTS

We identified a promoter variant rs17111237 (A > G, minor allele frequency [MAF] = 0.14) in CEP128 associated with TLI risk (hazard ratio = 1.45, 95% confidence interval = 1.26 to 1.66, Pcombined=3.18 × 10-7) which is in moderate linkage disequilibrium (LD) with rs162171 (MAF = 0.18, R2 = 0.69), the top signal in CEP128 (hazard ratio = 1.46, 95% confidence interval = 1.29-1.66, Pcombined= 6.17 × 10-9). Combining the clinical variables with the top SNP, we divided the patients into different subgroups with varying risk with 5-year TLI-free rates ranging from 33.7% to 95.5%. CEP128, a key component of mother centriole, tightly interacts with multiple radiation-resistant genes and plays an important role in maintaining the functional cilia, which otherwise will lead to a malfunction of the neural network. We found that A > G alteration at rs17111237 impaired the promoter activity of CEP128 and knockdown of CEP128 decreased the clonogenic cell survival of U87 cells under radiation. Noteworthy, 12.7% (27/212) of the GWAS-based associated genes (P < .001) were enriched in the neurogenesis pathway.

CONCLUSIONS

This three-stage study is the first GWAS of radiation-induced brain injury that implicates the genetic susceptibility gene CEP128 involved in TLI development and provides the novel insight into the underlying mechanisms of radiation-induced brain injury.

Radiogenomics in the Era of Advanced Radiotherapy

Most radiogenomics studies investigate how genetic variation can help to explain the differences in early and late radiotherapy toxicity between individuals. The field of radiogenomics in photon beam therapy has grown rapidly in recent years, carving out a unique translational discipline, which has progressed from candidate gene studies to larger scale genome-wide association studies, meta-analyses and now prospective validation studies. Genotyping is increasingly sophisticated and affordable, and whole-genome sequencing may soon become readily available as a diagnostic tool in the clinic. The ultimate aim of radiogenomics research is to tailor treatment to the individual with a test based on a combination of treatment, clinical and genetic factors. This personalisation would allow the greatest tumour control while minimising acute and long-term toxicity. Here we discuss the evolution of the field of radiogenomics with reference to the most recent developments and challenges.

Precision Radiotherapy and Radiation Risk Assessment: How Do We Overcome Radiogenomic Diversity?

Precision medicine is a rapidly developing area that aims to deliver targeted therapies based on individual patient characteristics. However, current radiation treatment is not yet personalized; consequently, there is a critical need for specific patient characteristics of both tumor and normal tissues to be fully incorporated into dose prescription. Furthermore, current risk assessment following environmental, occupational, or accidental exposures to radiation is based on population effects, and does not account for individual diversity underpinning radiosensitivity. The lack of personalized approaches in both radiotherapy and radiation risk assessment resulted in the current situation where a population-based model, effective dose, is being used. In this review article, to stimulate scientific discussion for precision medicine in both radiotherapy and radiation risk assessment, we propose a novel radiological concept and metric - the personalized dose and the personalized risk index - that incorporate individual physiological, lifestyle-related and genomic variations and radiosensitivity, outlining the potential clinical application for precision medicine. We also review on recent progress in both genomics and biobanking research, which is promising for providing novel insights into individual radiosensitivity, and for creating a novel conceptual framework of precision radiotherapy and radiation risk assessment.

Receptor tyrosine kinase recepteur d'origine nantais as predictive marker for aggressive prostate cancer in African Americans

Published evidence shows a correlation between several molecular markers and prostate cancer (PCa) progression including in African Americans (AAs) who are disproportionately affected. Our early detection efforts led to the identification of elevated levels of antiapoptotic protein, c-FLIP and its upstream regulatory factors such as androgen receptor (AR), recepteur d'origine nantais (RON), a receptor tyrosine kinase in human prostate tumors. The primary objective of this study was to explore whether these markers play a role in racial disparities using immunohistochemistry in prostatectomy samples from a cohort of AA, Hispanic Whites (HWs), and non-Hispanic Whites (NHWs). Bivariable and multivariable logistic regression analyses were used to identify a statistical association between molecular markers, possible correlation with risk factors including race, obesity, prostate-specific antigen (PSA) and disease aggressiveness. Further, changes in the levels and expression of these molecular markers were also evaluated using human PCa cell lines. We found significantly elevated levels of RON ( P = 0.0082), AR ( P = 0.0001), c-FLIP ( P = 0.0071) in AAs compared with HWs or NHWs. Furthermore, a higher proportion of HW and NHWs had a high Gleason score (>6) but not PSA as compared to AAs ( P = 0.032). In summary, our findings suggest that PSA was important in predicting aggressive disease for the cohort overall; however, high levels of RON may play a role in predisposing AA men to develop aggressive disease. Future research is needed using large datasets to confirm these findings and to explore whether all or any of these markers could aid in race-specific stratification of patients for treatment.

A phenome-wide association study to discover pleiotropic effects of PCSK9, APOB, and LDLR

We conducted an electronic health record (EHR)-based phenome-wide association study (PheWAS) to discover pleiotropic effects of variants in three lipoprotein metabolism genes PCSK9, APOB, and LDLR. Using high-density genotype data, we tested the associations of variants in the three genes with 1232 EHR-derived binary phecodes in 51,700 European-ancestry (EA) individuals and 585 phecodes in 10,276 African-ancestry (AA) individuals; 457 PCSK9, 730 APOB, and 720 LDLR variants were filtered by imputation quality (r 2 > 0.4), minor allele frequency (>1%), linkage disequilibrium (r 2 < 0.3), and association with LDL-C levels, yielding a set of two PCSK9, three APOB, and five LDLR variants in EA but no variants in AA. Cases and controls were defined for each phecode using the PheWAS package in R. Logistic regression assuming an additive genetic model was used with adjustment for age, sex, and the first two principal components. Significant associations were tested in additional cohorts from Vanderbilt University (n = 29,713), the Marshfield Clinic Personalized Medicine Research Project (n = 9562), and UK Biobank (n = 408,455). We identified one PCSK9, two APOB, and two LDLR variants significantly associated with an examined phecode. Only one of the variants was associated with a non-lipid disease phecode, ("myopia") but this association was not significant in the replication cohorts. In this large-scale PheWAS we did not find LDL-C-related variants in PCSK9, APOB, and LDLR to be associated with non-lipid-related phenotypes including diabetes, neurocognitive disorders, or cataracts.

Role of Germline Genetics in Identifying Survivors at Risk for Adverse Effects of Cancer Treatment

The growing population of cancer survivors often faces adverse effects of treatment, which have a substantial impact on morbidity and mortality. Although certain adverse effects are thought to have a significant heritable component, much work remains to be done to understand the role of germline genetic factors in the development of treatment-related toxicities. In this article, we review current understanding of genetic susceptibility to a range of adverse outcomes among cancer survivors (e.g., fibrosis, urinary and rectal toxicities, ototoxicity, chemotherapy-induced peripheral neuropathy, subsequent malignancies). Most previous research has been narrowly focused, investigating variation in candidate genes and pathways such as drug metabolism, DNA damage and repair, and inflammation. Few of the findings from these earlier candidate gene studies have been replicated in independent populations. Advances in understanding of the genome, improvements in technology, and reduction in laboratory costs have led to recent genome-wide studies, which agnostically interrogate common and/or rare variants across the entire genome. Larger cohorts of patients with homogeneous treatment exposures and systematic ascertainment of well-defined outcomes as well as replication in independent study populations are essential aspects of the study design and are increasingly leading to the discovery of variants associated with each of the adverse outcomes considered in this review. In the long-term, validated germline genetic associations hold tremendous promise for more precisely identifying patients at highest risk for developing adverse treatment effects, with implications for frontline therapy decision-making, personalization of long-term follow-up guidelines, and potential identification of targets for prevention or treatment of the toxicity.

Radiation biology and oncology in the genomic era

Radiobiology research is building the foundation for applying genomics in precision radiation oncology. Advances in high-throughput approaches will underpin increased understanding of radiosensitivity and the development of future predictive assays for clinical application. There is an established contribution of genetics as a risk factor for radiotherapy side effects. An individual's radiosensitivity is an inherited polygenic trait with an architecture that includes rare mutations in a few genes that confer large effects and common variants in many genes with small effects. Current thinking is that some will be tissue specific, and future tests will be tailored to the normal tissues at risk. The relationship between normal and tumor cell radiosensitivity is poorly understood. Data are emerging suggesting interplay between germline genetic variation and epigenetic modification with growing evidence that changes in DNA methylation regulate the radiosensitivity of cancer cells and histone acetyltransferase inhibitors have radiosensitizing effects. Changes in histone methylation can also impair DNA damage response signaling and alter radiosensitivity. An important effort to advance radiobiology in the genomic era was establishment of the Radiogenomics Consortium to enable the creation of the large radiotherapy cohorts required to exploit advances in genomics. To address challenges in harmonizing data from multiple cohorts, the consortium established the REQUITE project to collect standardized data and genotyping for ~5,000 patients. The collection of detailed dosimetric data is important to produce validated multivariable models. Continued efforts will identify new genes that impact on radiosensitivity to generate new knowledge on toxicity pathogenesis and tests to incorporate into the clinical decision-making process.

A Review of Prostate Cancer Genome-Wide Association Studies (GWAS)

Prostate cancer is the most common cancer in men in Europe and the United States. The genetic heritability of prostate cancer is contributed to by both rarely occurring genetic variants with higher penetrance and moderate to commonly occurring variants conferring lower risks. The number of identified variants belonging to the latter category has increased dramatically in the last 10 years with the development of the genome-wide association study (GWAS) and the collaboration of international consortia that have led to the sharing of large-scale genotyping data. Over 40 prostate cancer GWAS have been reported, with approximately 170 common variants now identified. Clinical utility of these variants could include strategies for population-based risk stratification to target prostate cancer screening to men with an increased genetic risk of disease development, while for those who develop prostate cancer, identifying genetic variants could allow treatment to be tailored based on a genetic profile in the early disease setting. Functional studies of identified variants are needed to fully understand underlying mechanisms of disease and identify novel targets for treatment. This review will outline the GWAS carried out in prostate cancer and the common variants identified so far, and how these may be utilized clinically in the screening for and management of prostate cancer. Cancer Epidemiol Biomarkers Prev; 27(8); 845-57. ©2018 AACR.

Precision Oncology and Genomically Guided Radiation Therapy: A Report From the American Society for Radiation Oncology/American Association of Physicists in Medicine/National Cancer Institute Precision Medicine Conference

PURPOSE

To summarize important talking points from a 2016 symposium focusing on real-world challenges to advancing precision medicine in radiation oncology, and to help radiation oncologists navigate the practical challenges of precision, radiation oncology.

METHODS AND MATERIALS

The American Society for Radiation Oncology, American Association of Physicists in Medicine, and National Cancer Institute cosponsored a meeting on precision medicine in radiation oncology. In June 2016 numerous scientists, clinicians, and physicists convened at the National Institutes of Health to discuss challenges and future directions toward personalized radiation therapy. Various breakout sessions were held to discuss particular components and approaches to the implementation of personalized radiation oncology. This article summarizes the genomically guided radiation therapy breakout session.

RESULTS

A summary of existing genomic data enabling personalized radiation therapy, ongoing clinical trials, current challenges, and future directions was collected. The group attempted to provide both a current overview of data that radiation oncologists could use to personalize therapy, along with data that are anticipated in the coming years. It seems apparent from the provided review that a considerable opportunity exists to truly bring genomically guided radiation therapy into clinical reality.

CONCLUSIONS

Genomically guided radiation therapy is a necessity that must be embraced in the coming years. Incorporating these data into treatment recommendations will provide radiation oncologists with a substantial opportunity to improve outcomes for numerous cancer patients. More research focused on this topic is needed to bring genomic signatures into routine standard of care.

Association of a variant in the gene encoding for ERV1/ChemR23 with reduced inflammation in visceral adipose tissue from morbidly obese individuals

Obesity comorbidities are closely associated with chronic low-grade adipose tissue inflammation. A number of SNPs associated with inflammation has been identified, underscoring the impact of genetic determinants on this process. Here, we screened SNPs in genes with pro-inflammatory (IL-1β, IL-6, STAT3 and JAK2), anti-inflammatory (IL-10 and SOCS3) and pro-resolving (ERV1/ChemR23) properties in 101 obese and 99 non-obese individuals. Among the SNPs analyzed, we identified that individuals carrying a C allele in the rs1878022 polymorphism of the ERV1/ChemR23 gene, which encodes for the receptor of the pro-resolving mediator RvE1, had increased ERV1/ChemR23 protein expression and reduced levels of the inflammatory cytokine IL-6 in adipose tissue. Moreover, patients carrying the C allele in homozygosity had lower plasma levels of IL-6, IFN-α2, IL-15, IL-1ra, IL-10, GM-CSF, G-CSF and VEGF and enhanced leukocyte responsiveness to RvE1. C-carriers also exhibited decreased TAG to HDL ratio, a surrogate marker of insulin resistance and a predictor of incident fatty liver. Finally, we confirmed in vivo that the ERV1/ChemR23 receptor regulates systemic and tissue inflammation since mice lacking ERV1/ChemR23 expression showed increased IL-6 levels in adipose tissue and peritoneal macrophages. Together, our study identified an ERV1/ChemR23 variant that protects patients with obesity from excessive inflammatory burden.

Validation of genetic predictors of late radiation-induced morbidity in prostate cancer patients

INTRODUCTION

Normal tissue morbidity sets the dose limit for radiotherapy (RT) in cancer treatment and has importance for quality of life for cancer survivors. A previous study of prostate cancer patients treated with RT generated clinical data for radiation-induced morbidity measured by anorectal physiological methods and validated questionnaires. Other studies have identified genetic predictors associated with late radiation-induced morbidity outcome. We have expanded biobank material aiming to validate single nucleotide polymorphisms (SNPs) and a gene expression classifier with endpoints on patient-reported outcomes and biomechanical properties of the anorectum from our cohort matching originally published endpoints.

MATERIALS AND METHODS

The present cohort of prostate cancer patients was treated with RT curative intent in 1999-2007. Nine SNPs associated with late radiation-induced morbidity were tested in 96 patients (rs2788612, rs1800629, rs264663, rs2682585, rs2268363, rs1801516, rs13035033, rs7120482 and rs17779457). A validated gene expression profile predictive of resistance to radiation-induced skin fibrosis was tested in 42 patients. An RT-induced anorectal dysfunction score (RT-ARD) served as a fibrosis-surrogate and a measure of overall radiation-induced morbidity.

RESULTS

The lowest p-value found in the genotype analyses was for SNP rs2682585 minor allele (A) in the FSHR gene and the RT-ARD score with odds ratios (OR) = 1.76; 95% CI (0.98-3.17) p = .06, which was out of concordance with original data showing a protective effect of the minor allele. The gene expression profile in patients classified as fibrosis-resistant was associated with high RT-ARD scores OR 4.18; 95% CI (1.1-16.6), p = .04 conflicting with the hypothesis that fibrosis-resistant patients would experience lower RT-ARD scores.

CONCLUSIONS

We aimed to validate nine SNPs and a gene expression classifier in a cohort of prostate cancer patients with unique scoring of radiation-induced morbidity. One significant association was found, pointing to the opposite direction of originally published data. We conclude that the material was not able to validate previously published genetic predictors of radiation-induced morbidity.

Radiogenomics: Identification of Genomic Predictors for Radiation Toxicity

The overall goal of radiogenomics is the identification of genomic markers that are predictive for the development of adverse effects resulting from cancer treatment with radiation. The principal rationale for a focus on toxicity in radiogenomics is that for many patients treated with radiation, especially individuals diagnosed with early-stage cancers, the survival rates are high, and therefore a substantial number of people will live for a significant period of time beyond treatment. However, many of these patients could suffer from debilitating complications resulting from radiotherapy. Work in radiogenomics has greatly benefited from creation of the Radiogenomics Consortium (RGC) that includes investigators at multiple institutions located in a variety of countries. The common goal of the RGC membership is to share biospecimens and data so as to achieve large-scale studies with increased statistical power to enable identification of relevant genomic markers. A major aim of research in radiogenomics is the development of a predictive instrument to enable identification of people who are at greatest risk for adverse effects resulting from cancer treatment using radiation. It is anticipated that creation of a predictive assay characterized by a high level of sensitivity and specificity will improve precision radiotherapy and assist patients and their physicians to select the optimal treatment for each individual.

Data-Based Radiation Oncology: Design of Clinical Trials in the Toxicity Biomarkers Era

The ability to stratify patients using a set of biomarkers, which predict that toxicity risk would allow for radiotherapy (RT) modulation and serve as a valuable tool for precision medicine and personalized RT. For patients presenting with tumors with a low risk of recurrence, modifying RT schedules to avoid toxicity would be clinically advantageous. Indeed, for the patient at low risk of developing radiation-associated toxicity, use of a hypofractionated protocol could be proposed leading to treatment time reduction and a cost-utility advantage. Conversely, for patients predicted to be at high risk for toxicity, either a more conformal form or a new technique of RT, or a multidisciplinary approach employing surgery could be included in the trial design to avoid or mitigate RT when the potential toxicity risk may be higher than the risk of disease recurrence. In addition, for patients at high risk of recurrence and low risk of toxicity, dose escalation, such as a greater boost dose, or irradiation field extensions could be considered to improve local control without severe toxicities, providing enhanced clinical benefit. In cases of high risk of toxicity, tumor control should be prioritized. In this review, toxicity biomarkers with sufficient evidence for clinical testing are presented. In addition, clinical trial designs and predictive models are described for different clinical situations.

DNA methylation changes at infertility genes in newborn twins conceived by in vitro fertilisation

BACKGROUND

The association of in vitro fertilisation (IVF) and DNA methylation has been studied predominantly at regulatory regions of imprinted genes and at just thousands of the ~28 million CpG sites in the human genome.

METHODS

We investigated the links between IVF and DNA methylation patterns in whole cord blood cells (n = 98) and cord blood mononuclear cells (n = 82) from newborn twins using genome-wide methylated DNA immunoprecipitation coupled with deep sequencing.

RESULTS

At a false discovery rate (FDR) of 5%, we identified one significant whole blood DNA methylation change linked to conception via IVF, which was located ~3 kb upstream of TNP1, a gene previously linked to male infertility. The 46 most strongly associated signals (FDR of 25%) included a second region in a gene also previously linked to infertility, C9orf3, suggesting that our findings may in part capture the effect of parental subfertility. Using twin modelling, we observed that individual-specific environmental factors appear to be the main overall contributors of methylation variability at the FDR 25% IVF-associated differentially methylated regions, although evidence for methylation heritability was also obtained at several of these regions. We replicated previous findings of differential methylation associated with IVF at the H19/IGF2 region in cord blood mononuclear cells, and we validated the signal at C9orf3 in monozygotic twins. We also explored the impact of intracytoplasmic sperm injection on the FDR 25% signals for potential effects specific to male or female infertility factors.

CONCLUSIONS

To our knowledge, this is the most comprehensive study of DNA methylation profiles at birth and IVF conception to date, and our results show evidence for epigenetic modifications that may in part reflect parental subfertility.

Decision support systems for personalized and participative radiation oncology

A paradigm shift from current population based medicine to personalized and participative medicine is underway. This transition is being supported by the development of clinical decision support systems based on prediction models of treatment outcome. In radiation oncology, these models 'learn' using advanced and innovative information technologies (ideally in a distributed fashion - please watch the animation: http://youtu.be/ZDJFOxpwqEA) from all available/appropriate medical data (clinical, treatment, imaging, biological/genetic, etc.) to achieve the highest possible accuracy with respect to prediction of tumor response and normal tissue toxicity. In this position paper, we deliver an overview of the factors that are associated with outcome in radiation oncology and discuss the methodology behind the development of accurate prediction models, which is a multi-faceted process. Subsequent to initial development/validation and clinical introduction, decision support systems should be constantly re-evaluated (through quality assurance procedures) in different patient datasets in order to refine and re-optimize the models, ensuring the continuous utility of the models. In the reasonably near future, decision support systems will be fully integrated within the clinic, with data and knowledge being shared in a standardized, dynamic, and potentially global manner enabling truly personalized and participative medicine.

Genetic predisposition to prostate cancer

INTRODUCTION

Prostate cancer (PrCa) is the commonest non-cutaneous cancer in men in the UK. Epidemiological evidence as well as twin studies points towards a genetic component contributing to aetiology.

SOURCES OF DATA

Key recently published literature.

AREAS OF AGREEMENT

A family history of PrCa doubles the risk of disease development in first-degree relatives. Linkage and genetic sequencing studies identified rare moderate-high-risk gene loci, which predispose to PrCa development when altered by mutation. Genome-wide association studies have identified common single-nucleotide polypmorphisms (SNPs), which confer a cumulative risk of PrCa development with increasing number of risk alleles. There are emerging data that castrate-resistant disease is associated with mutations in DNA repair genes.

AREAS OF CONTROVERSY

Linkage studies investigating possible high-risk loci leading to PrCa development identified possible loci on several chromosomes, but most have not been consistently replicated by subsequent studies. Germline SNPs related to prostate specific antigen (PSA) levels and to normal tissue radiosensitivity have also been identified though not all have been validated in subsequent studies.

GROWING POINTS

Utilizing germline SNP profiles as well as identifying high-risk genetic variants could target screening to high-risk groups, avoiding the drawbacks of PSA screening.

AREAS TIMELY FOR DEVELOPING RESEARCH

Incorporating genetics into PrCa screening is being investigated currently using both common SNP profiles and higher risk rare variants. Knowledge of germline genetic defects will allow the development of targeted screening programs, preventive strategies and the personalized treatment of PrCa.

Individual patient data meta-analysis shows a significant association between the ATM rs1801516 SNP and toxicity after radiotherapy in 5456 breast and prostate cancer patients

PURPOSE

Several small studies have indicated that the ATM rs1801516 SNP is associated with risk of normal tissue toxicity after radiotherapy. However, the findings have not been consistent. In order to test this SNP in a well-powered study, an individual patient data meta-analysis was carried out by the International Radiogenomics Consortium.

MATERIALS AND METHODS

The analysis included 5456 patients from 17 different cohorts. 2759 patients were given radiotherapy for breast cancer and 2697 for prostate cancer. Eight toxicity scores (overall toxicity, acute toxicity, late toxicity, acute skin toxicity, acute rectal toxicity, telangiectasia, fibrosis and late rectal toxicity) were analyzed. Adjustments were made for treatment and patient related factors with potential impact on the risk of toxicity.

RESULTS

For all endpoints except late rectal toxicity, a significantly increased risk of toxicity was found for carriers of the minor (Asn) allele with odds ratios of approximately 1.5 for acute toxicity and 1.2 for late toxicity. The results were consistent with a co-dominant pattern of inheritance.

CONCLUSION

This study convincingly showed a significant association between the ATM rs1801516 Asn allele and increased risk of radiation-induced normal tissue toxicity.

Radiogenomics: A systems biology approach to understanding genetic risk factors for radiotherapy toxicity?

Adverse reactions in normal tissue after radiotherapy (RT) limit the dose that can be given to tumour cells. Since 80% of individual variation in clinical response is estimated to be caused by patient-related factors, identifying these factors might allow prediction of patients with increased risk of developing severe reactions. While inactivation of cell renewal is considered a major cause of toxicity in early-reacting normal tissues, complex interactions involving multiple cell types, cytokines, and hypoxia seem important for late reactions. Here, we review 'omics' approaches such as screening of genetic polymorphisms or gene expression analysis, and assess the potential of epigenetic factors, posttranslational modification, signal transduction, and metabolism. Furthermore, functional assays have suggested possible associations with clinical risk of adverse reaction. Pathway analysis incorporating different 'omics' approaches may be more efficient in identifying critical pathways than pathway analysis based on single 'omics' data sets. Integrating these pathways with functional assays may be powerful in identifying multiple subgroups of RT patients characterised by different mechanisms. Thus 'omics' and functional approaches may synergise if they are integrated into radiogenomics 'systems biology' to facilitate the goal of individualised radiotherapy.

Meta-analysis of Genome Wide Association Studies Identifies Genetic Markers of Late Toxicity Following Radiotherapy for Prostate Cancer

Nearly 50% of cancer patients undergo radiotherapy. Late radiotherapy toxicity affects quality-of-life in long-term cancer survivors and risk of side-effects in a minority limits doses prescribed to the majority of patients. Development of a test predicting risk of toxicity could benefit many cancer patients. We aimed to meta-analyze individual level data from four genome-wide association studies from prostate cancer radiotherapy cohorts including 1564 men to identify genetic markers of toxicity. Prospectively assessed two-year toxicity endpoints (urinary frequency, decreased urine stream, rectal bleeding, overall toxicity) and single nucleotide polymorphism (SNP) associations were tested using multivariable regression, adjusting for clinical and patient-related risk factors. A fixed-effects meta-analysis identified two SNPs: rs17599026 on 5q31.2 with urinary frequency (odds ratio [OR] 3.12, 95% confidence interval [CI] 2.08-4.69, p-value 4.16×10(-8)) and rs7720298 on 5p15.2 with decreased urine stream (OR 2.71, 95% CI 1.90-3.86, p-value=3.21×10(-8)). These SNPs lie within genes that are expressed in tissues adversely affected by pelvic radiotherapy including bladder, kidney, rectum and small intestine. The results show that heterogeneous radiotherapy cohorts can be combined to identify new moderate-penetrance genetic variants associated with radiotherapy toxicity. The work provides a basis for larger collaborative efforts to identify enough variants for a future test involving polygenic risk profiling.

How Will Big Data Improve Clinical and Basic Research in Radiation Therapy?

Historically, basic scientists and clinical researchers have transduced reality into data so that they might explain or predict the world. Because data are fundamental to their craft, these investigators have been on the front lines of the Big Data deluge in recent years. Radiotherapy data are complex and longitudinal data sets are frequently collected to track both tumor and normal tissue response to therapy. As basic, translational and clinical investigators explore with increasingly greater depth the complexity of underlying disease processes and treatment outcomes, larger sample populations are required for research studies and greater quantities of data are being generated. In addition, well-curated research and trial data are being pooled in public data repositories to support large-scale analyses. Thus, the tremendous quantity of information produced in both basic and clinical research in radiation therapy can now be considered as having entered the realm of Big Data.

Big Data Analytics for Prostate Radiotherapy

Radiation therapy is a first-line treatment option for localized prostate cancer and radiation-induced normal tissue damage are often the main limiting factor for modern radiotherapy regimens. Conversely, under-dosing of target volumes in an attempt to spare adjacent healthy tissues limits the likelihood of achieving local, long-term control. Thus, the ability to generate personalized data-driven risk profiles for radiotherapy outcomes would provide valuable prognostic information to help guide both clinicians and patients alike. Big data applied to radiation oncology promises to deliver better understanding of outcomes by harvesting and integrating heterogeneous data types, including patient-specific clinical parameters, treatment-related dose-volume metrics, and biological risk factors. When taken together, such variables make up the basis for a multi-dimensional space (the "RadoncSpace") in which the presented modeling techniques search in order to identify significant predictors. Herein, we review outcome modeling and big data-mining techniques for both tumor control and radiotherapy-induced normal tissue effects. We apply many of the presented modeling approaches onto a cohort of hypofractionated prostate cancer patients taking into account different data types and a large heterogeneous mix of physical and biological parameters. Cross-validation techniques are also reviewed for the refinement of the proposed framework architecture and checking individual model performance. We conclude by considering advanced modeling techniques that borrow concepts from big data analytics, such as machine learning and artificial intelligence, before discussing the potential future impact of systems radiobiology approaches.

Genetic determinants of polycystic ovary syndrome: progress and future directions

The field of the genetics of polycystic ovary syndrome (PCOS) has relatively recently moved into the era of genome-wide association studies. This has led to the discovery of 16 robust loci for PCOS. Some loci contain genes with clear roles in reproductive (LHCGR, FSHR, and FSHB) and metabolic (INSR and HMGA2) dysfunction in the syndrome. The next challenge facing the field is the identification of causal variants and genes and the role they play in PCOS pathophysiology. The potential for gene discovery to improve diagnosis and treatment of PCOS is promising, though there is much to be done in the field before the current findings can be translated to the clinic.

Germline genetic profiling in prostate cancer: latest developments and potential clinical applications

Familial and twin studies have demonstrated a significant inherited component to prostate cancer predisposition. Genome wide association studies have shown that there are 100 single nucleotide polymorphisms which have been associated with the development of prostate cancer. This review aims to discuss the scientific methods used to identify these susceptibility loci. It will also examine the current clinical utility of these loci, which include the development of risk models as well as predicting treatment efficacy and toxicity. In order to refine the clinical utility of the susceptibility loci, international consortia have been developed to combine statistical power as well as skills and knowledge to further develop models that could be used to predict risk and treatment outcomes.

ERCC2 polymorphisms and radiation-induced adverse effects on normal tissue: systematic review with meta-analysis and trial sequential analysis

Background

The relationship between ERCC2 polymorphisms and the risk of radiotoxicity remains inconclusive. The aim of our study is to systematically evaluate the association between ERCC2 polymorphisms and the risk of radiotoxicity.

Methods

Publications were identified through a search of the PubMed and Web of Science databases up to August 15, 2015. The pooled odds ratios (ORs) with corresponding 95 % confidence intervals (CIs) were calculated to evaluate the association between ERCC2 polymorphisms and radiotoxicity. Trial sequential analysis (TSA) and power calculation were performed to evaluate the type 1 and type 2 errors.

Results

Eleven studies involving 2584 patients were ultimately included in this meta-analysis. Conventional meta-analysis identified a significant association between ERCC2 rs13181 polymorphism and radiotoxicity (OR = 0.71, 95 % CI: 0.55-0.93, P = 0.01), but this association failed to get the confirmation of TSA.

Conclusions

The minor allele of rs13181 polymorphism may confer a protect effect against radiotoxicity. To confirm this correlation at the level of OR = 0.71, an overall information size of approximate 2800 patients were needed.

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-015-0558-6) contains supplementary material, which is available to authorized users.