Association between single nucleotide polymorphisms of the transforming growth factor β1 gene and the risk of severe radiation esophagitis in patients with lung cancer

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.

Using inflammatory indexes and clinical parameters to predict radiation esophagitis in patients with small-cell lung cancer undergoing chemoradiotherapy

OBJECTIVE

Radiation esophagitis (RE) is a common adverse effect in small cell lung cancer (SCLC) patients undergoing thoracic radiotherapy. We aim to develop a novel nomogram to predict the acute severe RE (grade≥2) receiving chemoradiation in SCLC patients.

MATERIALS AND METHODS

the risk factors were analyzed by logistic regression, and a nomogram was constructed based on multivariate analysis results. The clinical value of the model was evaluated using the area under the receiver operating curve (ROC) curve (AUC), calibration curves, and decision curve analysis (DCA). The correlations of inflammation indexes were assessed using Spearman correlation analysis.

RESULTS

Eighty-four of 187 patients (44.9%) developed grade ≥2 RE. Univariate analysis indicated that concurrent chemoradiotherapy (CCRT, p < 0.001), chemotherapy cycle (p = 0.097), system inflammation response index (SIRI, p = 0.048), prognostic-nutrition index (PNI, p = 0.073), platelets-lymphocyte radio (PLR, p = 0.026), platelets-albumin ratio (PAR, p = 0.029) were potential predictors of RE. In multivariate analysis, CCRT [p < 0.001; OR, 3.380; 95% CI, 1.767-6.465], SIRI (p = 0.047; OR, 0.436; 95% CI, 0.192-0.989), and PAR (p = 0.036; OR, 2.907; 95% CI, 1.071-7.891) were independent predictors of grade ≥2 RE. The AUC of nomogram was 0.702 (95% CI, 0.626-0.778), which was greater than each independent predictor (CCRT: 0.645; SIRI: 0.558; PAR: 0.559). Calibration curves showed high coherence between the predicted and actual observation RE, and DCA displayed satisfactory clinical utility.

CONCLUSION

In this study, CCRT, SIRI, and PAR were independent predictors for RE (grade ≥2) in patients with SCLC receiving chemoradiotherapy. We developed and validated a predictive model through these factors. The developed nomogram with superior prediction ability can be used as a quantitative model to predict RE.

Improving Patients' Life Quality after Radiotherapy Treatment by Predicting Late Toxicities

Personalized treatment and precision medicine have become the new standard of care in oncology and radiotherapy. Because treatment outcomes have considerably improved over the last few years, permanent side-effects are becoming an increasingly significant issue for cancer survivors. Five to ten percent of patients will develop severe late toxicity after radiotherapy. Identifying these patients before treatment start would allow for treatment adaptation to minimize definitive side effects that could impair their long-term quality of life. Over the last decades, several tests and biomarkers have been developed to identify these patients. However, out of these, only the Radiation-Induced Lymphocyte Apoptosis (RILA) assay has been prospectively validated in multi-center cohorts. This test, based on a simple blood draught, has been shown to be correlated with late radiation-induced toxicity in breast, prostate, cervical and head and neck cancer. It could therefore greatly improve decision making in precision radiation oncology. This literature review summarizes the development and bases of this assay, as well as its clinical results and compares its results to the other available assays.

Predicting Severe Radiation Esophagitis in Patients With Locally Advanced Esophageal Squamous Cell Carcinoma Receiving Definitive Chemoradiotherapy: Construction and Validation of a Model Based in the Clinical and Dosimetric Parameters as Well as Inflammatory Indexes

Objective

Radiation esophagitis (RE) is common in patients treated with radiotherapy (RT) for locally advanced esophageal squamous cell carcinoma (ESCC). We aim to construct a nomogram predicting the severe RE (grade ≥2) in patients with ESCC receiving definitive chemoradiotherapy (dCRT).

Materials and Methods

Logistic regression was performed to evaluate the risk factors in predicting RE. Nomogram was built based on the multivariate analysis result. The model was validated using the area under the receiver operating curve (ROC) curve (AUC), calibration curves, and decision curve analyses (DCA). Spearman correlation analysis was used to evaluate the correlation between inflammation indexes.

Results

A total of 547 patients with stage II–IVA ESCC treated with dCRT from the retrospective study were included. Two hundred and thirty-two of 547 patients (42.4%) developed grade ≥2 RE. Univariate analysis indicated that gender (p = 0.090), RT dose (p < 0.001), targeted therapy (p = 0.047), tumor thickness (p = 0.013), lymphocyte-monocyte ratio (LMR, p = 0.016), neutrophil-lymphocyte ratio (NLR, p < 0.001), and platelet-lymphocyte ratio (PLR, p < 0.001) were the significant factors for a higher incidence of RE. In multivariate analysis, RT dose [p < 0.001; odds ratio (OR), 4.680; 95% confidence interval (CI), 2.841–6.709], NLR (p < 0.001; OR, 0.384; 95% CI, 0.239–0.619), and PLR (p < 0.001; OR, 3.539; 95% CI: 2.226–5.626) were independently associated grade ≥2 RE and were involved in the nomogram. ROC curves showed the AUC of the nomogram was 0.714 (95% CI, 0.670–0.757), which was greater than each factor alone (RT dose: 0.615; NLR: 0.596; PLR: 0.590). Calibration curves showed good consistency between the actual observation and the predicted RE. DCA showed satisfactory positive net benefits of the nomogram among most threshold probabilities.

Conclusions

The study demonstrated that RT dose, NLR, and PLR were independent risk factors for grade ≥2 RE in patients with locally advanced ESCC receiving dCRT. A predictive model including all these factors was built and performed better than it based on each separately. Further validation in large patient populations is still warranted.

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.

Validation of Polymorphisms Associated with the Risk of Radiation-Induced Oesophagitis in an Independent Cohort of Non-Small-Cell Lung Cancer Patients

Simple Summary

Genetic variants identified in association with radiation therapy side effects in non-small-cell lung cancer patients require an independent validation. Therefore, the aim of our study was to replicate, in an independent cohort, the analyses of previously published studies associating single-nucleotide polymorphisms with radiation-induced oesophagitis. Following the original models, 2 of the 18 variants associated with radiation-induced oesophagitis in non-small-cell lung cancer patients were confirmed. Furthermore, we meta-analysed our cohort together with those of the reference studies. Twelve variants located in genes of inflammation and DNA double-strand break repair pathways remained associated with oesophagitis. These variants could be included in models for clinical prediction of radiation-induced oesophagitis to evaluate their performance.

Abstract

Several studies have identified single-nucleotide polymorphisms (SNPs) associated with adverse effects in non-small-cell lung cancer (NSCLC) patients treated with radiation therapy. Here, using an independent cohort, we aimed to validate the reported associations. We selected 23 SNPs in 17 genes previously associated with radiation-induced oesophagitis for validation in a cohort of 178 Spanish NSCLC patients. Of them, 18 SNPs were finally analysed, following the methods described in the original published studies. Two SNPs replicated their association with radiation-induced oesophagitis (rs7165790 located in the BLM gene: odds ratio (OR) = 0.16, 95% CI = 0.04–0.65, p-value = 0.010; rs4772468 at FGF14: OR = 4.36, 95% CI = 1.15–16.46, p-value = 0.029). The SNP rs2868371 at HSPB1 was also validated but displayed an opposite effect to the formerly described (OR = 3.72; 95% CI = 1.49–9.25; p-value = 0.004). Additionally, we tested a meta-analytic approach including our results and the previous datasets reported in the referenced publications. Twelve SNPs (including the two previously validated) retained their statistically significant association with radiation-induced oesophagitis. This study strengthens the role of inflammation and DNA double-strand break repair pathways in the risk prediction of developing radiation-induced oesophagitis in NSCLC patients. The validated variants are good candidates to be evaluated in risk prediction models for patient stratification based on their radiation susceptibility.

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.

Association Between Polymorphisms in DNA Damage Repair Genes and Radiation Therapy-Induced Early Adverse Skin Reactions in a Breast Cancer Population: A Polygenic Risk Score Approach

PURPOSE

Genetic variations in DNA damage repair (DDR) genes may influence radiation therapy (RT)-induced acute normal tissue toxicity in patients with breast cancer. Identifying an individual or multiple single-nucleotide polymorphisms (SNPs) associated with RT-induced early adverse skin reactions (EASR) is critical for precision medicine in radiation oncology.

METHODS AND MATERIALS

At the completion of RT, EASR was assessed using the Oncology Nursing Society scale (0-6) in 416 patients with breast cancer, and Oncology Nursing Society score ≥4 was considered RT-induced EASR. PLINK set-based tests and subsequent individual SNP association analyses were conducted to identify genes and SNPs associated with EASR among the 53 DDR genes and 1968 SNPs. A weighted polygenic risk score (PRS) model was constructed to ascertain the association between the joint effect of risk alleles and EASR.

RESULTS

The study population consisted of 264 Hispanic whites, 86 blacks or African Americans, 55 non-Hispanic whites, and 11 others. A total of 115 patients (27.6%) developed EASR. Five genes (ATM, CHEK1, ERCC2, RAD51C, and TGFB1) were significantly associated with RT-induced EASR. Nine SNPs within these 5 genes were further identified: ATM rs61915066, CHEK1 rs11220184, RAD51C rs302877, rs405684, TBFB1 rs4803455, rs2241714, and ERCC2 rs60152947, rs10404465, rs1799786. In a multivariable-adjusted PRS model, patients in a higher quartile of PRS were more likely to develop EASR compared with patients in the lowest quartile (OR_{q2 vs.q1} = 1.94, 95% CI, 0.86-4.39; OR_{q3 vs.q1} = 3.46, 95% CI, 1.57-7.63; OR_{q4 vs.q1} = 8.64, 95% CI, 3.92-19.02; and P_trend < .0001).

CONCLUSIONS

We newly identified the associations between 9 SNPs in ATM, CHEK1, RAD51C, TGFB1, and ERCC2 and RT-induced EASR. PRS modeling showed its potential in identifying populations at risk. Multiple SNPs in DDR genes may jointly contribute to interindividual variation in RT-induced EASR. Validation in an independent external cohort is required to determine the clinical significance of these predictive biomarkers.

Phase II Trial of Epigallocatechin-3-Gallate in Acute Radiation-Induced Esophagitis for Esophagus Cancer

Acute radiation-induced esophagitis (ARIE) is among the most serious form of toxicities associated with definitive radiotherapy or chemoradiotherapy used for treatment of patients with esophageal cancer. Our preliminary phase I and II trials of lung cancer patients who received radiotherapy indicated epigallocatechin-3-gallate (EGCG) as a promising therapeutic option against ARIE. Therefore, we conducted a prospective phase II study to validate the efficacy and safety of EGCG in the treatment of ARIE. The patients who received chemoradiotherapy or definitive radiotherapy for treatment of esophageal cancer in the Shandong Cancer Hospital and Institute in China were enrolled for the present study. EGCG (440 μM) was administered with first onset of ARIE and then at weeks after final radiotherapy. The patients were monitored every week for dysphagia, Radiation Therapy Oncology Group (RTOG) score, and esophagitis-related pain. Moreover, tumor response and the effect on survival following the treatment were also evaluated. Comparison of the RTOG score in the first, second, third, fourth, fifth, and even sixth week after EGCG prescription and the first and second week after radiotherapy with baseline indicates a significant reduction. The tumor response rate was 86.3%. The overall survival rate in 1, 2, and 3 years was found to be 74.5%, 58%, and 40.5%. Oral administration of EGCG solution seems to be feasible for treating ARIE in patients with esophageal cancer who receive radiation therapy. EGCG might be an ARIE-reliever without compromising the efficacy of radiation therapy. A randomized study with a control group is needed for further evaluation.

Esophageal Stricture Following Radiation, Concurrent Immunochemotherapy, Treated With Hyperbaric Oxygen and Dilation

Low-dose palliative radiation may offer symptomatic relief in patients with spinal metastases from primary renal cell cancer and is unlikely to result in radiation injury. Patients with advanced malignancy requiring palliative radiation are often also receiving chemotherapy. Synergistic adverse effects resulting from combined palliative radiation and novel antiprogrammed cell death-1 (anti-PD 1) and/or multityrosine kinase inhibitors are rare.

We report about a 60-year-old woman with metastatic clear-cell renal cancer, status post-left nephrectomy, with debilitating mid-back pain from metastatic tumor burden and foraminal nerve compression. Her chemotherapeutic regimen was repeatedly altered because of progression of disease until she was maintained on the anti-PD 1 checkpoint inhibitor, nivolumab. She received palliative radiation to her thoracic spine over a 2-week period, and nivolumab was then switched to cabozantinib midway through a course of palliative radiation. The patient rapidly developed severe esophagitis, progressing to esophageal stricture, and required placement of a percutaneous endoscopic gastrostomy tube. She was successfully treated with serial esophageal dilation and hyperbaric oxygen treatments to diminish inflammation and improve tissue vascularity. Concurrent use of anti-PD 1 and/or multityrosine kinase drugs may accelerate development of radiation injury regardless of radiation dosage. Radiation-induced esophageal stricture was managed successfully in this patient with serial esophageal dilation and adjuvant hyperbaric oxygen.

Genomics of radiation sensitivity in squamous cell carcinomas

Radiotherapy is an important modality in the management of squamous cell cancers with 50% of patients receiving radiotherapy at some point. Despite technological advances, the risk of severe toxicity in a proportion of radiosensitive patients limits radiation doses that can be safely prescribed affecting the potential for cure. While comorbidities, lifestyle and treatment factors can influence interindividual variations, genetic factors are thought to play a major role, accounting for approximately 80% of the variance observed. Over the last decade, substantial progress has been made in the field of radiogenomics, with compelling associations for SNPs identified in genes involved in DNA-damage response, cell-cycle control, apoptosis, antioxidant defenses and cytokine production. Future research efforts should be collaborative, focused on validating and broadening their clinical applicability. Numerous obstacles exist to the clinical application of this knowledge, which need to be overcome before personalized radiation therapy becomes a routine component of oncologic care.

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 model combining age, equivalent uniform dose and IL-8 may predict radiation esophagitis in patients with non-small cell lung cancer

BACKGROUND AND PURPOSE

To study whether cytokine markers may improve predictive accuracy of radiation esophagitis (RE) in non-small cell lung cancer (NSCLC) patients.

MATERIALS AND METHODS

A total of 129 patients with stage I-III NSCLC treated with radiotherapy (RT) from prospective studies were included. Thirty inflammatory cytokines were measured in platelet-poor plasma samples. Logistic regression was performed to evaluate the risk factors of RE. Stepwise Akaike information criterion (AIC) and likelihood ratio test were used to assess model predictions.

RESULTS

Forty-nine of 129 patients (38.0%) developed grade ≥2 RE. Univariate analysis showed that age, stage, concurrent chemotherapy, and eight dosimetric parameters were significantly associated with grade ≥2 RE (p < 0.05). IL-4, IL-5, IL-8, IL-13, IL-15, IL-1α, TGFα and eotaxin were also associated with grade ≥2 RE (p < 0.1). Age, esophagus generalized equivalent uniform dose (EUD), and baseline IL-8 were independently associated grade ≥2 RE. The combination of these three factors had significantly higher predictive power than any single factor alone. Addition of IL-8 to toxicity model significantly improves RE predictive accuracy (p = 0.019).

CONCLUSIONS

Combining baseline level of IL-8, age and esophagus EUD may predict RE more accurately. Refinement of this model with larger sample sizes and validation from multicenter database are warranted.

Immunogenetics of prostate cancer: a still unexplored field of study

The immune system is a double-edged sword with regard to the prostate cancer (PCa) battle. Immunogenetics, the study of the potential role of immune-related polymorphisms, is taking its first steps in the treatment of this malignancy. This review summarizes the most recent papers addressing the potential of immunogenetics in PCa, reporting immune-related polymorphisms associated with tumor aggressiveness, treatment toxicity and patients' prognosis. With some peculiarities, RNASEL, IL-6, IL-10, IL-1β and MMP7 have arisen as the most significant biomarkers in PCa treatment and management, having a potential clinical role. Validation prospective clinical studies are required to translate immunogenetics into precision treatment of PCa.

Prediction of Radiation Esophagitis in Non-Small Cell Lung Cancer Using Clinical Factors, Dosimetric Parameters, and Pretreatment Cytokine Levels

Radiation esophagitis (RE) is a common adverse event associated with radiotherapy for non-small cell lung cancer (NSCLC). While plasma cytokine levels have been correlated with other forms of radiation-induced toxicity, their association with RE has been less well studied. We analyzed data from 126 patients treated on 4 prospective clinical trials. Logistic regression models based on combinations of dosimetric factors [maximum dose to 2 cubic cm (D2cc) and generalized equivalent uniform dose (gEUD)], clinical variables, and pretreatment plasma levels of 30 cytokines were developed. Cross-validated estimates of area under the receiver operating characteristic curve (AUC) and log likelihood were used to assess prediction accuracy. Dose-only models predicted grade 3 RE with AUC values of 0.750 (D2cc) and 0.727 (gEUD). Combining clinical factors with D2cc increased the AUC to 0.779. Incorporating pretreatment cytokine measurements, modeled as direct associations with RE and as potential interactions with the dose-esophagitis association, produced AUC values of 0.758 and 0.773, respectively. D2cc and gEUD correlated with grade 3 RE with odds ratios (ORs) of 1.094/Gy and 1.096/Gy, respectively. Female gender was associated with a higher risk of RE, with ORs of 1.09 and 1.112 in the D2cc and gEUD models, respectively. Older age was associated with decreased risk of RE, with ORs of 0.992/year and 0.991/year in the D2cc and gEUD models, respectively. Combining clinical with dosimetric factors but not pretreatment cytokine levels yielded improved prediction of grade 3 RE compared to prediction by dose alone. Such multifactorial modeling may prove useful in directing radiation treatment planning.

Blood-based biomarkers for precision medicine in lung cancer: precision radiation therapy

Both tumors and patients are complex and models that determine survival and toxicity of radiotherapy or any other treatment ideally must take into account this variability as well as its dynamic state. The genetic features of the tumor and the host, and increasingly also the epi-genetic and proteomic characteristics, are being unraveled. Multiple techniques, including histological examination, blood sampling, measurement of circulating tumor cells (CTCs), and functional and molecular imaging, can be used for this purpose. However, the effects of radiation on the tumor and on organs at risk (OARs) are also influenced by the applied dose and volume of irradiated tissues. Combining all these biological, clinical, imaging, and dosimetric parameters in a validated prognostic or predictive model poses a major challenge. Here we aimed to provide an objective review of the potential of blood markers to guide high precision radiation therapy. A combined biological-mathematical approach opens new doors beyond prognostication of patients, as it allows truly precise oncological treatment. Indeed, the core for individualized and precision medicine is not only selection of patients, but even more the optimization of the therapeutic window on an individual basis. A holistic model will allow for determination of an individual dose-response relationship for each organ at risk for each tumor in each individual patient for the complete oncological treatment package. This includes, but is not limited to, radiotherapy alone. Individualized dose-response curves will allow for consideration of different doses of radiation and combinations with other drugs to plan for both optimal toxicity and complete response. Insights into the interactions between a multitude of parameters will lead to the discovery of new pathways and networks that will fuel new biological research on target discovery.

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.

Genetic variants in the inflammation pathway as predictors of recurrence and progression in non-muscle invasive bladder cancer treated with Bacillus Calmette-Guérin

Inflammation plays a critical role in the etiology of several cancers and may affect their clinical outcome. Our objective was to assess the association of genetic variants within the inflammation pathway with recurrence and progression among non-muscle invasive bladder cancer (NMIBC) patients with or without Bacillus Calmette–Guérin (BCG) treatment. We genotyped 372 single nucleotide polymorphisms (SNPs) in 27 selected genes within the inflammation pathway in 349 patients diagnosed with NMIBC, followed by internal validation in 322 additional patients. We used Cox proportional hazards regression analyses to identify SNPs as predictors for recurrence and progression. In the discovery phase, we identified 20 variants that were significantly associated with recurrence outcomes and 15 SNPs significantly associated with progression in patients treated with BCG but not in the transurethral resection (TUR)-only group. In BCG treated patients, rs7089861 was the only SNP significantly associated with risk of progression in both the discovery phase (Hazard Ratio [HR]=3.15, 95% Confidence Interval [CI]: 1.38-7.22, P<0.01) and validation phase (HR=3.84, 95% CI: 1.64-9.0, P=0.002; meta-analysis HR=3.47, 95% CI: 1.92-6.28, P<0.001). Two variants, rs1800686 and rs2071081, had probable association with HRs of the same trend in the discovery and validation groups (meta-analysis P=0.002). These findings supported the notion that genetic variation of inflammation pathway may impact clinical outcome of NMIBC patients treated with BCG immunotherapy. Further validation of these results in order to improve risk stratification to identify patients most likely to benefit from BCG treatment versus upfront radical cystectomy and future development of potential targeted therapies are warranted.

Radiogenomics and radiotherapy response modeling

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

A Novel Methodology using CT Imaging Biomarkers to Quantify Radiation Sensitivity in the Esophagus with Application to Clinical Trials

Personalized cancer therapy seeks to tailor treatment to an individual patient's biology. Therefore, a means to characterize radiosensitivity is necessary. In this study, we investigated radiosensitivity in the normal esophagus using an imaging biomarker of radiation-response and esophageal toxicity, esophageal expansion, as a method to quantify radiosensitivity in 134 non-small-cell lung cancer patients, by using K-Means clustering to group patients based on esophageal radiosensitivity. Patients within the cluster of higher response and lower dose were labelled as radiosensitive. This information was used as a variable in toxicity prediction modelling (lasso logistic regression). The resultant model performance was quantified and compared to toxicity prediction modelling without utilizing radiosensitivity information. The esophageal expansion-response was highly variable between patients, even for similar radiation doses. K-Means clustering was able to identify three patient subgroups of radiosensitivity: radiosensitive, radio-normal, and radioresistant groups. Inclusion of the radiosensitive variable improved lasso logistic regression models compared to model performance without radiosensitivity information. Esophageal radiosensitivity can be quantified using esophageal expansion and K-Means clustering to improve toxicity prediction modelling. Finally, this methodology may be applied in clinical trials to validate pre-treatment biomarkers of esophageal toxicity.

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.

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.

Single Nucleotide Polymorphisms in CBLB, a Regulator of T-Cell Response, Predict Radiation Pneumonitis and Outcomes After Definitive Radiotherapy for Non-Small-Cell Lung Cancer

BACKGROUND

The immune system has important roles in tumor development and outcomes after cancer treatment. We evaluated whether single-nucleotide polymorphisms (SNPs) in the gene encoding casitas B-lineage lymphoma b protein (Cbl-b), an E3 ubiquitin ligase that maintains immune tolerance by negatively regulating T-cell activation and function, were associated with outcomes after treatment of non-small-cell lung cancer (NSCLC).

PATIENTS AND METHODS

Samples from 393 patients with NSCLC treated with definitive radiotherapy at a single institution between March 1998 and February 2009 were used to genotype 3 potentially functional SNPs in CBLB (rs1042852 C>T, rs2305035 G>A, and rs7649466 C>G). We evaluated associations between these SNPs and local recurrence-free survival, distant metastasis-free survival, overall survival, and risk of radiation pneumonitis (RP).

RESULTS

Having the rs2305035 A variant genotypes (AA or AG) was associated with better local recurrence-free survival (median 15.8 vs. 15.3 months; adjusted hazard ratio [HR], 0.76; 95% confidence interval [CI], 0.60-0.98; P = .033), distant metastasis-free survival (median 15.4 vs. 14.0 months; adjusted HR, 0.74; 95% CI, 0.57-0.96; P = .024) and overall survival (median 23.5 vs. 22.8 months; adjusted HR, 0.72; 95% CI, 0.56-0.93; P = .013) after adjustment in a Cox proportional hazard model. Patients with these genotypes were also at greater risk of developing grade 3 or higher RP than were patients with GG genotypes in an adjusted Cox proportional hazard model.

CONCLUSION

This is the first report that rs2305035 genotypes in CBLB were associated with clinical and RP risk among patients with NSCLC treated with definitive radiotherapy. These findings could assist in generating hypothesis for further mechanistic studies.

Radiation esophagitis

The esophagus is frequently exposed to radiation during treatment of advanced stages of common cancers such as lung, breast, and esophagus. However, symptomatic radiation esophagitis requiring endoscopic and histologic evaluation occurs quite rarely, affecting less than 1% of patients receiving radiation treatment. Symptoms occur acutely, generally within the first 2 months. Patients typically present with nonspecific symptoms such as dysphagia and odynophagia. Endoscopic changes such as erythema and ulceration are also nonspecific and nondiagnostic. Biopsies from affected areas show variable inflammatory changes and radiation-related atypia of endothelial and stromal cells. Such atypia mimics cytomegalovirus cytopathic changes, which are ruled out through absence of immunostaining. Radiation esophagitis is thus clinically unsuspected and endoscopically and histologically quite different from the more common and familiar radiation proctitis for which angioectasia is the predominant finding.

Normal tissue complication models for clinically relevant acute esophagitis (≥ grade 2) in patients treated with dose differentiated accelerated radiotherapy (DART-bid)

Background

One of the primary dose-limiting toxicities during thoracic irradiation is acute esophagitis (AE). The aim of this study is to investigate dosimetric and clinical predictors for AE grade ≥ 2 in patients treated with accelerated radiotherapy for locally advanced non-small cell lung cancer (NSCLC).

Patients and methods

66 NSCLC patients were included in the present analysis: 4 stage II, 44 stage IIIA and 18 stage IIIB. All patients received induction chemotherapy followed by dose differentiated accelerated radiotherapy (DART-bid). Depending on size (mean of three perpendicular diameters) tumors were binned in four dose groups: <2.5 cm 73.8 Gy, 2.5–4.5 cm 79.2 Gy, 4.5–6 cm 84.6 Gy, >6 cm 90 Gy. Patients were treated in 3D target splitting technique. In order to estimate the normal tissue complication probability (NTCP), two Lyman models and the cutoff-logistic regression model were fitted to the data with AE ≥ grade 2 as statistical endpoint. Inter-model comparison was performed with the corrected Akaike information criterion (AIC_c), which calculates the model’s quality of fit (likelihood value) in relation to its complexity (i.e. number of variables in the model) corrected by the number of patients in the dataset. Toxicity was documented prospectively according to RTOG.

Results

The median follow up was 686 days (range 84–2921 days), 23/66 patients (35 %) experienced AE ≥ grade 2. The actuarial local control rates were 72.6 % and 59.4 % at 2 and 3 years, regional control was 91 % at both time points. The Lyman-MED model (D50 = 32.8 Gy, m = 0.48) and the cutoff dose model (D_c = 38 Gy) provide the most efficient fit to the current dataset. On multivariate analysis V38 (volume of the esophagus that receives 38 Gy or above, 95 %-CI 28.2–57.3) was the most significant predictor of AE ≥ grade 2 (HR = 1.05, CI 1.01–1.09, p = 0.007).

Conclusion

Following high-dose accelerated radiotherapy the rate of AE ≥ grade 2 is slightly lower than reported for concomitant radio-chemotherapy with the additional benefit of markedly increased loco-regional tumor control. In the current patient cohort the most significant predictor of AE was found to be V38. A second clinically useful parameter in treatment planning may be MED (mean esophageal dose).

Electronic supplementary material

The online version of this article (doi:10.1186/s13014-015-0429-1) contains supplementary material, which is available to authorized users.

The Prediction of Radiotherapy Toxicity Using Single Nucleotide Polymorphism-Based Models: A Step Toward Prevention

Radiotherapy is a mainstay of cancer treatment, used in either a curative or palliative manner to treat approximately 50% of patients with cancer. Normal tissue toxicity limits the doses used in standard radiation therapy protocols and impedes improvements in radiotherapy efficacy. Damage to surrounding normal tissues can produce reactions ranging from bothersome symptoms that negatively affect quality of life to severe life-threatening complications. Improved ways of predicting, before treatment, the risk for development of normal tissue toxicity may allow for more personalized treatment and reduce the incidence and severity of late effects. There is increasing recognition that the cause of normal tissue toxicity is multifactorial and includes genetic factors in addition to radiation dose and volume of exposure, underlying comorbidities, age, concomitant chemotherapy or hormonal therapy, and use of other medications. An understanding of the specific genetic risk factors for normal tissue response to radiation has the potential to enhance our ability to predict adverse outcomes at the treatment-planning stage. Therefore, the field of radiogenomics has focused upon the identification of genetic variants associated with normal tissue toxicity resulting from radiotherapy. Innovative analytic methods are being applied to the discovery of risk variants and development of integrative predictive models that build on traditional normal tissue complication probability models by incorporating genetic information. Results from initial studies provide promising evidence that genetic-based risk models could play an important role in the implementation of precision medicine for radiation oncology through enhancing the ability to predict normal tissue reactions and thereby improve cancer treatment.

A prospective phase II trial of EGCG in treatment of acute radiation-induced esophagitis for stage III lung cancer

BACKGROUND

Acute radiation-induced esophagitis (ARIE) is one of main toxicities complicated by thoracic radiotherapy, influencing patients' quality of life and radiotherapy proceeding seriously. It is difficult to be cured rapidly so far. Our phase I trial preliminarily showed that EGCG may be a promising strategy in the treatment of ARIE.

MATERIALS AND METHODS

We prospectively enrolled patients with stage III lung cancer from the Shandong Tumor Hospital & Institute in China from January 2013 to September 2014. All patients received concurrent or sequential chemo-radiotherapy, or radiotherapy only. EGCG was administrated once ARIE appeared. EGCG was given with the concentration of 440μmol/L during radiotherapy and additionally two weeks after radiotherapy. RTOG score, dysphagia and pain related to esophagitis were recorded every week.

RESULTS

Thirty-seven patients with stage IIIA and IIIB lung cancer were enrolled in this trial. In comparison to the original, the RTOG score in the 1st, 2nd, 3rd, 4th, 5th week after EGCG prescription and the 1st, 2nd week after radiotherapy decreased significantly (P=0.002, 0.000, 0.000, 0.001, 0.102, 0.000, 0.000, respectively). The pain score of each week was significantly lower than the baseline (P=0.000, 0.000, 0.000, 0.000, 0.006, 0.000, 0.000, respectively).

CONCLUSION

This trial confirmed that the oral administration of EGCG is an effective and safe method to deal with ARIE. A phase III randomized controlled trial is expected to further corroborate the consequence of EGCG in ARIE treatment.

Predictive SNPs for radiation-induced damage in lung cancer patients with radiotherapy: a potential strategy to individualize treatment

In the treatment of lung cancer, radiotherapy has become one of the most important therapies, despite its sometimes unpredictable side effects. As such, identifying lung cancer patients who are at high risk of developing severe radiation-induced damage (mainly radiation pneumonitis and radiation-induced esophageal toxicity) and applying effect intervention or monitoring techniques are important. Although human diversity to a certain amount is explained by clinical and dosimetric factors, the presence of specific genetic determinants also influences the occurrence of radiation-induced damage. Here we summarize the data on mechanisms of radiation pneumonitis and radiation-induced esophageal toxicity supporting the involvement of variances of genes in the evolution of radiation-induced damage. Furthermore, the available evidence from current clinical studies of genetic polymorphisms for the prediction of radiation pneumonitis and radiation-induced esophageal toxicity is discussed. Eventually, this may help to truly individualize radiotherapy, using a personal genetic profile of the most relevant genes for each lung cancer patient.

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

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

Radiogenomics: the search for genetic predictors of radiotherapy response

'Radiogenomics' is the study of genetic variation associated with response to radiotherapy. Radiogenomics aims to uncover the genes and biologic pathways responsible for radiotherapy toxicity that could be targeted with radioprotective agents and; identify genetic markers that can be used in risk prediction models in the clinic. The long-term goal of the field is to develop single nucleotide polymorphism-based risk models that can be used to stratify patients to more precisely tailored radiotherapy protocols. The field has evolved over the last two decades in parallel with advances in genomics, moving from narrowly focused candidate gene studies to large, collaborative genome-wide association studies. Several confirmed genetic variants have been identified and the field is making progress toward clinical translation.

Serum inflammatory miRNAs predict radiation esophagitis in patients receiving definitive radiochemotherapy for non-small cell lung cancer

BACKGROUND AND PURPOSE

MicroRNAs (miRNAs) are small, highly conserved non-coding RNAs that regulate many biological processes. We sought to investigate whether three serum miRNAs related to immunity or inflammation were associated with esophagitis induced by chemoradiation therapy (CRT) for non-small cell lung cancer (NSCLC).

MATERIAL AND METHODS

We measured serum miR-155, miR-221 and miR-21, before and during week 1-2 of CRT for 101 NSCLC patients by real-time PCR. Associations between miRNA and severe radiation-induced esophageal toxicity (RIET) were analyzed by logistic regression.

RESULTS

We found that patients with stage IIIB-IV disease, higher mean esophagus dose or esophageal V50 had higher rates of severe RIET. Furthermore, high levels of miR-155 and miR-221 at week 1-2 of CRT were also risk factors for severe RIET (miR-155: OR=1.53, 95% CI: 1.04-2.25, P=0.03; miR-221: OR=2.07, 95% CI: 1.17-3.64, P=0.012). In addition, the fold change of miR-221 was also predictive of severe RIET (OR=1.18, 95% CI: 1.02-1.37, P=0.026). However, pretreatment miRNAs was not predictive of severe RIET.

CONCLUSIONS

High serum miR-155 and miR-221 during the first 2 weeks of CRT were associated with the development of severe RIET, suggesting that these miRNAs may be useful as an early surrogate for this form of toxicity.

Infrequent chemoradiation-induced acute esophagitis in the Asian population: A meta-analysis of published clinical trials for unresectable stage III non-small cell lung cancer

Severe (grade 3 or higher) esophagitis is one of the major toxicities for chemoradiation in the treatment of stage III non-small cell lung cancer (NSCLC). The difference among ethnic groups has never been investigated in detail. Prospective trials with concurrent platinum-containing chemoradiation in unresectable disease were investigated, and a total of 116 treatment arms with 7520 patients were identified. Univariate analysis demonstrated that treatment arms conducted in Asia had significantly lower incidence of severe esophagitis (170/2534, 6.7%, odds ratio 0.289) than in other nations (1025/4986, 20.6%). In the multivariable model, Asian/non-Asian ethnicity, multi-/single-agent, and split are jointly significant predictors after adjusting for all possible factors. This study suggests that severe esophagitis occurs less frequently in the Asian population compared to the non-Asian population.

Inflammation-related genetic variants predict toxicity following definitive radiotherapy for lung cancer

Definitive radiotherapy improves locoregional control and survival in inoperable non-small cell lung cancer (NSCLC) patients. However, radiation-induced toxicities (pneumonitis/esophagitis) are common dose-limiting inflammatory conditions. We therefore conducted a pathway-based analysis to identify inflammation-related SNPs associated with radiation-induced pneumonitis or esophagitis. 11,930 SNPs were genotyped in 201 stage I-III NSCLC patients treated with definitive radiotherapy. Validation was performed in an additional 220 NSCLC cases. After validation, 19 SNPs remained significant. A polygenic risk score (PRS) was generated to summarize the effect from validated SNPs. Significant improvements in discriminative ability were observed by adding the PRS into the clinical/epidemiological variable-based model. We then used 277 lymphoblastoid cell-lines to assess radiation sensitivity and eQTL relationships of the identified SNPs. Three genes (PRKCE,DDX58 and TNFSF7) were associated with radiation sensitivity. We concluded that inflammation-related genetic variants could contribute to the development of radiation-induced toxicities. These loci could assist in predicting those unfavorable events.

Polymorphisms in radio-responsive genes and its association with acute toxicity among head and neck cancer patients

Cellular and molecular approaches are being explored to find a biomarker which can predict the development of radiation induced acute toxicity prior to radiation therapy. SNPs in radiation responsive genes may be considered as an approach to develop tools for finding the inherited basis of clinical radiosensitivity. The current study attempts to screen single nucleotide polymorphisms/deletions in DNA damage response, DNA repair, profibrotic cytokine as well as antioxidant response genes and its predictive potential with the normal tissue adverse reactions from 183 head and neck cancer patients undergoing platinum based chemoradiotherapy or radiotherapy alone. We analysed 22 polymorphisms in 17 genes having functional relevance to radiation response. Radiation therapy induced oral mucositis and skin erythema was considered as end point for clinical radiosensitivity. Direct correlation of heterozygous and mutant alleles with acute reactions as well as haplotype correlation revealed NBN variants to be of predictive significance in analysing oral mucositis prior to radiotherapy. In addition, genetic linkage disequilibrium existed in XRCC1 polymorphisms for >grade 2 oral mucositis and skin reaction indicating the complex inheritance pattern. The current study indicates an association for polymorphism in NBN with normal tissue radiosensitivity and further warrants the replication of such studies in a large set of samples.

Acute phase response before treatment predicts radiation esophagitis in non-small cell lung cancer

BACKGROUND AND PURPOSE

Radiation esophagitis (RE) represents an inflammatory reaction to radiation therapy (RT). We hypothesized that aspects of the physiologic acute phase response (APR) predicts RE.

MATERIAL AND METHODS

We retrospectively analyzed 285 patients with non-small cell lung cancer (NSCLC) treated with definitive radiation. The primary analysis was the association of pretreatment lab values reflective of the APR with symptomatic (grade ⩾ 2) RE. Univariate and multivariate odds ratios (ORs) were calculated to test associations of clinical and pretreatment lab values with RE. Optimal cutpoints and multivariable risk stratification groupings were determined via recursive partitioning analysis.

RESULTS

Pretreatment platelet counts were higher and hemoglobin levels lower in patients who developed RE (P<0.05). Based on these two pre-treatment risk factors, an APR score was defined as 0 (no risk factors), 1 (either risk factor), or 2 (both risk factors). APR score was significantly associated with RE in both univariate (OR = 2.3 for each point, 95% confidence interval [CI] 1.5-3.4, P = 0.001) and multivariate (OR = 2.1, 95% CI 1.3-3.4, P = 0.002) analyses.

CONCLUSIONS

The APR score may represent a novel metric to predict RE. However, pending validation in an independent dataset, caution is advised when interpreting these results given their retrospective and thus exploratory nature.

A phase I study of concurrent chemotherapy and thoracic radiotherapy with oral epigallocatechin-3-gallate protection in patients with locally advanced stage III non-small-cell lung cancer

BACKGROUND AND PURPOSE

Patients with unresectable stage III non-small-cell lung cancer receiving concurrent chemoradiotherapy often develop esophagitis that may lead to unplanned treatment interruptions, which may severely reduce rates of locoregional tumor control and survival. No effectivetreatment that would reduce the incidence and severity of this complication has been identified up to now. Although acceleration of normal tissue protection using epigallocatechin-3-gallate (EGCG) has been reported, its actual clinical practicability remains obscure.

METHODS AND MATERIALS

This is a phase I study of EGCG in combination with standard chemoradiation in surgically unresectable stage III non-small-cell lung cancer. Chemotherapy (cisplatin and etoposide) was given concurrently with radiation. EGCG solution was swallowed three times a day after the occurrence of grade 2 esophagitis at six concentration levels and dose escalation followed a standard phase I design. Esophageal toxicity and patient-reported pain was recorded weekly.

RESULTS

Twenty-four patients with AJCC stage IIIA (six) and IIIB (eighteen) completed the course of therapy. Twelve had squamous histology, ten adenocarcinoma, and two not specified. Patients were treated in six cohorts at six dose levels of EGCG. RT was not interrupted with a median dose of 64 Gy. There were no dose-limiting toxicities reported in all EGCG dosing tiers. Dramatic regression of esophagitis to grade 0/1 was observed in 22 of 24 patients, whereas grade 2 esophagitis persisted in 2 of 24 patients at the end of radiotherapy. The pain score was also reduced from a mean of 4.58 (N=24), 1.29 (N=24), 1.42 (N=24), 0.96 (N=23) to 1.13 (N=16) every week in turn.

CONCLUSION

We conclude that the oral administration of EGCG is feasible, safe and effective. The phase II recommended concentration is 440 μmol/L.

Transcriptome analysis and SNP identification in SCC of horn in (Bos indicus) Indian cattle

Single Nucleotide Polymorphisms (SNPs) have become the marker of choice for genome wide association studies. In order to provide the best genome coverage for the analysis of disease, production and performance traits, a large number of relatively evenly distributed SNPs are needed. The main objective of present work was to identify large numbers of gene-associated SNPs using high-throughput sequencing in squamous cell carcinoma of horn. RNA-seq analysis was conducted on 2 tissues viz. Horn Cancer (HC) and Horn Normal (HN) in Kankrej breed of cattle. A total of 909,362 reads with average read length of 405 bp for HC and 583,491 reads with average read length of 411 bp for HN were obtained. We found 9532 and 7065 SNPs as well as 1771 and 1172 Indels in HC and HN, respectively, from which, 7889 SNPs and 1736 Indels were uniquely present in HC, 5886 SNPs and 1146 Indels were uniquely present in HN and reported first time in Bos indicus, whereas the rest are already reported in Bos taurus dbSNP database. The gene-associated SNPs and Indels were high in upregulated genes of HC as compared to HN. Analysis of differentially expressed genes was identified, these genes are involved in regulation of cell proliferation, apoptosis, gene transcription, cell survival and metabolism through various metabolic pathways. The result of transcriptome expression profiling was validated using Real Time quantitative PCR in nine randomly selected genes. We identified numbers aberrant signaling pathways responsible for carcinogenesis in HC which are also commonly altered in squamous cell carcinoma (SCC) of lung in human being. We conclude that a large number of altered genes and dysfunction of multiple pathways are involved in the development of Horn Cancer. The present findings contribute to theoretical information for further screening of genes and identification of markers for early diagnosis of HC as well as SNPs identified in this report provide a much needed resource for genetic studies in B. indicus and shall contribute to the development of a high density SNP array. Validation and testing of these SNPs using SNP arrays will form the material basis for gene associated SNPs in HC.