Exploratory analysis using machine learning to predict for chest wall pain in patients with stage I non-small-cell lung cancer treated with stereotactic body radiation therapy.

Background and purposeChest wall toxicity is observed after stereotactic body radiation therapy (SBRT) for peripherally located lung tumors. We utilize machine learning algorithms to identify toxicity predictors to develop dose-volume constraints.Materials and methodsTwenty-five patient, tumor, and dosimetric features were recorded for 197 consecutive patients with Stage I NSCLC treated with SBRT, 11 of whom (5.6%) developed CTCAEv4 grade ≥2 chest wall pain. Decision tree modeling was used to determine chest wall syndrome (CWS) thresholds for individual features. Significant features were determined using independent multivariate methods. These methods incorporate out-of-bag estimation using Random forests (RF) and bootstrapping (100 iterations) using decision trees.ResultsUnivariate analysis identified rib dose to 1 cc < 4000 cGy (P = 0.01), chest wall dose to 30 cc < 1900 cGy (P = 0.035), rib Dmax < 5100 cGy (P = 0.05) and lung dose to 1000 cc < 70 cGy (P = 0.039) to be statistically significant thresholds for avoiding CWS. Subsequent multivariate analysis confirmed the importance of rib dose to 1 cc, chest wall dose to 30 cc, and rib Dmax. Using learning-curve experiments, the dataset proved to be self-consistent and provides a realistic model for CWS analysis.ConclusionsUsing machine learning algorithms in this first of its kind study, we identify robust features and cutoffs predictive for the rare clinical event of CWS. Additional data in planned subsequent multicenter studies will help increase the accuracy of multivariate analysis

Protein Delivery of an Artificial Transcription Factor Restores Widespread Ube3a Expression in an Angelman Syndrome Mouse Brain.

Angelman syndrome (AS) is a neurological genetic disorder caused by loss of expression of the maternal copy of UBE3A in the brain. Due to brain-specific genetic imprinting at this locus, the paternal UBE3A is silenced by a long antisense transcript. Inhibition of the antisense transcript could lead to unsilencing of paternal UBE3A, thus providing a therapeutic approach for AS. However, widespread delivery of gene regulators to the brain remains challenging. Here, we report an engineered zinc finger-based artificial transcription factor (ATF) that, when injected i.p. or s.c., crossed the blood-brain barrier and increased Ube3a expression in the brain of an adult mouse model of AS. The factor displayed widespread distribution throughout the brain. Immunohistochemistry of both the hippocampus and cerebellum revealed an increase in Ube3a upon treatment. An ATF containing an alternative DNA-binding domain did not activate Ube3a. We believe this to be the first report of an injectable engineered zinc finger protein that can cause widespread activation of an endogenous gene in the brain. These observations have important implications for the study and treatment of AS and other neurological disorders

Empiric Radiotherapy for Lung Cancer Collaborative Group multi-institutional evidence-based guidelines for the use of empiric stereotactic body radiation therapy for non-small cell lung cancer without pathologic confirmation

The standard of care for managing early stage non-small cell lung cancer (NSCLC) is definitive surgical resection. Stereotactic body radiation therapy (SBRT) has become the standard treatment for patient who are medically inoperable, and it is increasingly being considered as an option in operable patients. With the growing use of screening thoracic CT scans for patients with a history of heavy smoking, as well as improved imaging capabilities, the discovery of small lung nodes has become a common dilemma. As a result, clinicians are increasingly faced with managing lung nodules in patients in whom diagnostic biopsy is not safe or feasible. Herein, we describe the scope of the problem, tools available for predicting the probability that a lung nodule is a malignancy, staging procedures, benefits of pathology-proven and empiric SBRT, considerations of safety based on location of the lesion of concern, and overall efficacy of SBRT

Updating Photon-Based Normal Tissue Complication Probability Models for Pneumonitis in Patients With Lung Cancer Treated With Proton Beam Therapy

Purpose: No validated models for predicting the risk of radiation pneumonitis (RP) with proton beam therapy (PBT) currently exist. Our goal was to externally validate and recalibrate multiple established photon-based normal tissue complication probability models for RP in a cohort with locally advanced nonsmall cell lung cancer treated with contemporary doses of chemoradiation using PBT. Methods and Materials: The external validation cohort consisted of 99 consecutive patients with locally advanced nonsmall cell lung cancer treated with chemoradiation using PBT. RP was retrospectively scored at 3 and 6 months posttreatment. We evaluated the performance of the photon Quantitative Analyses of Normal Tissue Effects in the Clinic (QUANTEC) pneumonitis model, the QUANTEC model adjusted for clinical risk factors, and the newer Netherlands updated QUANTEC model. A closed testing procedure was performed to test the need for model updating, either by recalibration-in-the-large (re-estimation of intercept), recalibration (re-estimation of intercept/slope), or model revision (re-estimation of all coefficients). Results: There were 21 events (21%) of ≥grade 2 RP. The closed testing procedure on the PBT data set did not detect major deviations between the models and the data and recommended adjustment of the intercept only for the photon-based Netherlands updated QUANTEC model (intercept update: –1.2). However, an update of the slope and revision of the model coefficients were not recommended by the closed testing procedure, as the deviations were not significant within the power of the data. Conclusions: The similarity between the dose-response relationship for PBT and photons for normal tissue complications has been an assumption until now. We demonstrate that the preexisting, widely used photon based models fit our PBT data well with minor modifications. These now-validated and updated normal tissue complication probability models can aid in individualizing selection of the most optimal treatment technique for a particular patient

Reduced Diversity and High Sponge Abundance on a Sedimented Indo-Pacific Reef System: Implications for Future Changes in Environmental Quality

Although coral reef health across the globe is declining as a result of anthropogenic impacts, relatively little is known of how environmental variability influences reef organisms other than corals and fish. Sponges are an important component of coral reef fauna that perform many important functional roles and changes in their abundance and diversity as a result of environmental change has the potential to affect overall reef ecosystem functioning. In this study, we examined patterns of sponge biodiversity and abundance across a range of environments to assess the potential key drivers of differences in benthic community structure. We found that sponge assemblages were significantly different across the study sites, but were dominated by one species Lamellodysidea herbacea (42% of all sponges patches recorded) and that the differential rate of sediment deposition was the most important variable driving differences in abundance patterns. Lamellodysidea herbacea abundance was positively associated with sedimentation rates, while total sponge abundance excluding Lamellodysidea herbacea was negatively associated with rates of sedimentation. Overall variation in sponge assemblage composition was correlated with a number of variables although each variable explained only a small amount of the overall variation. Although sponge abundance remained similar across environments, diversity was negatively affected by sedimentation, with the most sedimented sites being dominated by a single sponge species. Our study shows how some sponge species are able to tolerate high levels of sediment and that any transition of coral reefs to more sedimented states may result in a shift to a low diversity sponge dominated system, which is likely to have subsequent effects on ecosystem functioning. © 2014 Powell et al

Proton Beam Therapy for Non-Small Cell Lung Cancer: Current Clinical Evidence and Future Directions

Lung cancer is the leading cancer cause of death in the United States. Radiotherapy is an essential component of the definitive treatment of early-stage and locally-advanced lung cancer, and the palliative treatment of metastatic lung cancer. Proton beam therapy (PBT), through its characteristic Bragg peak, has the potential to decrease the toxicity of radiotherapy, and, subsequently improve the therapeutic ratio. Herein, we provide a primer on the physics of proton beam therapy for lung cancer, present the existing data in early-stage and locally-advanced non-small cell lung cancer (NSCLC), as well as in special situations such as re-irradiation and post-operative radiation therapy. We then present the technical challenges, such as anatomic changes and motion management, and future directions for PBT in lung cancer, including pencil beam scanning

Focusing on the Person in Personalized Medicine: The Future of Patient-Centered Care in Radiation Oncology

Numerous efforts in radiation oncology aim to improve the value of clinical care. To evaluate the success of these efforts, outcome measures must be well defined and incorporate the beliefs of the patients they affect. These outcomes have historically centered on rates of tumor control, overall survival, and adverse events as perceived and reported by providers. However, the future of patient-centered care in radiation oncology is increasingly focusing on the person in the population and the individual in the studies to more closely reflect the ideals of personalized medicine. Formally known as patient-centered outcomes, this metric encompasses parameters of patient satisfaction, engagement, and treatment compliance. Evaluations that investigate the safety and efficacy of treatments are increasingly soliciting participation from patients within a model of shared decision making that improves patients\u27 knowledge, satisfaction, physical and emotional well-being, and trust in providers. Modern clinical trials that embrace this approach may even focus on patient-reported outcomes as the primary end point, as opposed to time-honored physician-reported events. The authors explore the growing role of patient-centered care, the incorporation of shared decision making, and the relevant body of existing and developing literature on this topic in radiation oncology. The authors report recent discoveries from this area of study and describe how they can not only support high-quality, high-value patient care but also enhance recruitment to clinical oncology trials, both of which are challenging to achieve in today\u27s relatively resource-strapped environment