Capivasertib in combination with enzalutamide for metastatic castration resistant prostate cancer after docetaxel and abiraterone: Results from the randomized phase II RE-AKT trial.

BACKGROUND: PTEN loss and aberrations in PI3K/AKT signaling kinases associate with poorer response to abiraterone acetate (AA) in metastatic castration-resistant prostate cancer (mCRPC). In this study, we assessed antitumor activity of the AKT inhibitor capivasertib combined with enzalutamide in mCRPC with prior progression on AA and docetaxel. METHODS: This double-blind, placebo-controlled, randomized phase 2 trial, recruited men ≥ 18 years with progressing mCRPC and performance status 0-2 from 15 UK centers. Randomized participants (1:1) received enzalutamide (160 mg orally, once daily) with capivasertib (400 mg)/ placebo orally, twice daily on an intermittent (4 days on, 3 days off) schedule. Primary endpoint was composite response rate (RR): RECIST 1.1 objective response, ≥ 50 % PSA decrease from baseline, or circulating tumor cell count conversion (from ≥ 5 at baseline to < 5 cells/7.5 mL). Subgroup analyses by PTENIHC status were pre-planned. RESULTS: Overall, 100 participants were randomized (50:50); 95 were evaluable for primary endpoint (47:48); median follow-up was 43 months. RR were 9/47 (19.1 %) enzalutamide/capivasertib and 9/48 (18.8 %) enzalutamide/placebo (absolute difference 0.4 % 90 %CI -12.8 to 13.6, p = 0.58), with similar results in the PTENIHC loss subgroup. Irrespective of treatment, OS was significantly worse for PTENIHC loss (10.1 months [95 %CI: 4.6-13.9] vs 14.8 months [95 %CI: 10.8-18]; p = 0.02). Most common treatment-emergent grade ≥ 3 adverse events for the combination were diarrhea (13 % vs 2 %) and fatigue (10 % vs 6 %). CONCLUSIONS: Combined capivasertib/enzalutamide was well tolerated but didn't significantly improve outcomes from abiraterone pre-treated mCRPC.

Machine-learning with region-level radiomic and dosimetric features for predicting radiotherapy-induced rectal toxicities in prostate cancer patients.

BACKGROUND AND PURPOSE: This study aims to build machine learning models to predict radiation-induced rectal toxicities for three clinical endpoints and explore whether the inclusion of radiomic features calculated on radiotherapy planning computerised tomography (CT) scans combined with dosimetric features can enhance the prediction performance. MATERIALS AND METHODS: 183 patients recruited to the VoxTox study (UK-CRN-ID-13716) were included. Toxicity scores were prospectively collected after 2 years with grade ≥ 1 proctitis, haemorrhage (CTCAEv4.03); and gastrointestinal (GI) toxicity (RTOG) recorded as the endpoints of interest. The rectal wall on each slice was divided into 4 regions according to the centroid, and all slices were divided into 4 sections to calculate region-level radiomic and dosimetric features. The patients were split into a training set (75%, N = 137) and a test set (25%, N = 46). Highly correlated features were removed using four feature selection methods. Individual radiomic or dosimetric or combined (radiomic + dosimetric) features were subsequently classified using three machine learning classifiers to explore their association with these radiation-induced rectal toxicities. RESULTS: The test set area under the curve (AUC) values were 0.549, 0.741 and 0.669 for proctitis, haemorrhage and GI toxicity prediction using radiomic combined with dosimetric features. The AUC value reached 0.747 for the ensembled radiomic-dosimetric model for haemorrhage. CONCLUSIONS: Our preliminary results show that region-level pre-treatment planning CT radiomic features have the potential to predict radiation-induced rectal toxicities for prostate cancer. Moreover, when combined with region-level dosimetric features and using ensemble learning, the model prediction performance slightly improved.

Sub-regional analysis of the parotid glands: model development for predicting late xerostomia with radiomics features in head and neck cancer patients.

BACKGROUND: The irradiation of sub-regions of the parotid has been linked to xerostomia development in patients with head and neck cancer (HNC). In this study, we compared the xerostomia classification performance of radiomics features calculated on clinically relevant and de novo sub-regions of the parotid glands of HNC patients. MATERIAL AND METHODS: All patients (N = 117) were treated with TomoTherapy in 30-35 fractions of 2-2.167 Gy per fraction with daily mega-voltage-CT (MVCT) acquisition for image-guidance purposes. Radiomics features (N = 123) were extracted from daily MVCTs for the whole parotid gland and nine sub-regions. The changes in feature values after each complete week of treatment were considered as predictors of xerostomia (CTCAEv4.03, grade ≥ 2) at 6 and 12 months. Combinations of predictors were generated following the removal of statistically redundant information and stepwise selection. The classification performance of the logistic regression models was evaluated on train and test sets of patients using the Area Under the Curve (AUC) associated with the different sub-regions at each week of treatment and benchmarked with the performance of models solely using dose and toxicity at baseline. RESULTS: In this study, radiomics-based models predicted xerostomia better than standard clinical predictors. Models combining dose to the parotid and xerostomia scores at baseline yielded an AUCtest of 0.63 and 0.61 for xerostomia prediction at 6 and 12 months after radiotherapy while models based on radiomics features extracted from the whole parotid yielded a maximum AUCtest of 0.67 and 0.75, respectively. Overall, across sub-regions, maximum AUCtest was 0.76 and 0.80 for xerostomia prediction at 6 and 12 months. Within the first two weeks of treatment, the cranial part of the parotid systematically yielded the highest AUCtest. CONCLUSION: Our results indicate that variations of radiomics features calculated on sub-regions of the parotid glands can lead to earlier and improved prediction of xerostomia in HNC patients.

Assessing the generalisability of radiomics features previously identified as predictive of radiation-induced sticky saliva and xerostomia.

Background and purpose: While core to the scientific approach, reproducibility of experimental results is challenging in radiomics studies. A recent publication identified radiomics features that are predictive of late irradiation-induced toxicity in head and neck cancer (HNC) patients. In this study, we assessed the generalisability of these findings. Materials and Methods: The procedure described in the publication in question was applied to a cohort of 109 HNC patients treated with 50-70 Gy in 20-35 fractions using helical radiotherapy although there were inherent differences between the two patient populations and methodologies. On each slice of the planning CT with delineated parotid and submandibular glands, the imaging features that were previously identified as predictive of moderate-to-severe xerostomia and sticky saliva 12 months post radiotherapy (Xer12m and SS12m) were calculated. Specifically, Short Run Emphasis (SRE) and maximum CT intensity (maxHU) were evaluated for improvement in prediction of Xer12m and SS12m respectively, compared to models solely using baseline toxicity and mean dose to the salivary glands. Results: None of the associations previously identified as statistically significant and involving radiomics features in univariate or multivariate models could be reproduced on our cohort. Conclusion: The discrepancies observed between the results of the two studies delineate limits to the generalisability of the previously reported findings. This may be explained by the differences in the approaches, in particular the imaging characteristics and subsequent methodological implementation. This highlights the importance of external validation, high quality reporting guidelines and standardisation protocols to ensure generalisability, replication and ultimately clinical implementation.

Predicting radiotherapy-induced xerostomia in head and neck cancer patients using day-to-day kinetics of radiomics features.

Background and purpose: The images acquired during radiotherapy for image-guidance purposes could be used to monitor patient-specific response to irradiation and improve treatment personalisation. We investigated whether the kinetics of radiomics features from daily mega-voltage CT image-guidance scans (MVCT) improve prediction of moderate-to-severe xerostomia compared to dose/volume parameters in radiotherapy of head-and-neck cancer (HNC). Materials and Methods: All included HNC patients (N = 117) received 30 or more fractions of radiotherapy with daily MVCTs. Radiomics features were calculated on the contra-lateral parotid glands of daily MVCTs. Their variations over time after each complete week of treatment were used to predict moderate-to-severe xerostomia (CTCAEv4.03 grade ≥ 2) at 6, 12 and 24 months post-radiotherapy. After dimensionality reduction, backward/forward selection was used to generate combinations of predictors.Three types of logistic regression model were generated for each follow-up time: 1) a pre-treatment reference model using dose/volume parameters, 2) a combination of dose/volume and radiomics-based predictors, and 3) radiomics-based predictors. The models were internally validated by cross-validation and bootstrapping and their performance evaluated using Area Under the Curve (AUC) on separate training and testing sets. Results: Moderate-to-severe xerostomia was reported by 46 %, 33 % and 26 % of the patients at 6, 12 and 24 months respectively. The selected models using radiomics-based features extracted at or before mid-treatment outperformed the dose-based models with an AUCtrain/AUCtest of 0.70/0.69, 0.76/0.74, 0.86/0.86 at 6, 12 and 24 months, respectively. Conclusion: Our results suggest that radiomics features calculated on MVCTs from the first half of the radiotherapy course improve prediction of moderate-to-severe xerostomia in HNC patients compared to a dose-based pre-treatment model.

Docetaxel for Nonmetastatic Prostate Cancer: Long-Term Survival Outcomes in the STAMPEDE Randomized Controlled Trial.

BACKGROUND: STAMPEDE previously reported adding upfront docetaxel improved overall survival for prostate cancer patients starting long-term androgen deprivation therapy. We report long-term results for non-metastatic patients using, as primary outcome, metastatic progression-free survival (mPFS), an externally demonstrated surrogate for overall survival. METHODS: Standard of care (SOC) was androgen deprivation therapy with or without radical prostate radiotherapy. A total of 460 SOC and 230 SOC plus docetaxel were randomly assigned 2:1. Standard survival methods and intention to treat were used. Treatment effect estimates were summarized from adjusted Cox regression models, switching to restricted mean survival time if non-proportional hazards. mPFS (new metastases, skeletal-related events, or prostate cancer death) had 70% power (α = 0.05) for a hazard ratio (HR) of 0.70. Secondary outcome measures included overall survival, failure-free survival (FFS), and progression-free survival (PFS: mPFS, locoregional progression). RESULTS: Median follow-up was 6.5 years with 142 mPFS events on SOC (3 year and 54% increases over previous report). There was no good evidence of an advantage to SOC plus docetaxel on mPFS (HR = 0.89, 95% confidence interval [CI] = 0.66 to 1.19; P = .43); with 5-year mPFS 82% (95% CI = 78% to 87%) SOC plus docetaxel vs 77% (95% CI = 73% to 81%) SOC. Secondary outcomes showed evidence SOC plus docetaxel improved FFS (HR = 0.70, 95% CI = 0.55 to 0.88; P = .002) and PFS (nonproportional P = .03, restricted mean survival time difference = 5.8 months, 95% CI = 0.5 to 11.2; P = .03) but no good evidence of overall survival benefit (125 SOC deaths; HR = 0.88, 95% CI = 0.64 to 1.21; P = .44). There was no evidence SOC plus docetaxel increased late toxicity: post 1 year, 29% SOC and 30% SOC plus docetaxel grade 3-5 toxicity. CONCLUSIONS: There is robust evidence that SOC plus docetaxel improved FFS and PFS (previously shown to increase quality-adjusted life-years), without excess late toxicity, which did not translate into benefit for longer-term outcomes. This may influence patient management in individual cases.

Peppermint protocol: first results for gas chromatography-ion mobility spectrometry.

ThePeppermint Initiativeseeks to inform the standardisation of breath analysis methods. FivePeppermint Experimentswith gas chromatography-ion mobility spectrometry (GC-IMS), operating in the positive mode with a tritium3H 5.68 keV, 370 MBq ionisation source, were undertaken to provide benchmarkPeppermint Washoutdata for this technique, to support its use in breath-testing, analysis, and research. Headspace analysis of a peppermint-oil capsule by GC-IMS with on-column injection (0.5 cm3) identified 12 IMS responsive compounds, of which the four most abundant were: eucalyptol;ß-pinene;α-pinene; and limonene. Elevated concentrations of these four compounds were identified in exhaled-breath following ingestion of a peppermint-oil capsule. An unidentified compound attributed as a volatile catabolite of peppermint-oil was also observed. The most intense exhaled peppermint-oil component was eucalyptol, which was selected as a peppermint marker for benchmarking GC-IMS. Twenty-five washout experiments monitored levels of exhaled eucalyptol, by GC-IMS with on-column injection (0.5 cm3), att= 0 min, and then att+ 60,t+ 90,t+ 165,t+ 285 andt+ 360 min from ingestion of a peppermint capsule resulting in 148 peppermint breath analyses. Additionally, thePeppermint Washoutdata was used to evaluate clinical deployments with a further five washout tests run in clinical settings generating an additional 35 breath samples. Regression analysis yielded an average extrapolated time taken for exhaled eucalyptol levels to return to baseline values to be 429 ± 62 min (±95% confidence-interval). The benchmark value was assigned to the lower 95% confidence-interval, 367 min. Further evaluation of the data indicated that the maximum number of volatile organic compounds discernible from a 0.5 cm3breath sample was 69, while the use of an in-line biofilter appeared to reduce this to 34.

Fast and automated biomarker detection in breath samples with machine learning.

Volatile organic compounds (VOCs) in human breath can reveal a large spectrum of health conditions and can be used for fast, accurate and non-invasive diagnostics. Gas chromatography-mass spectrometry (GC-MS) is used to measure VOCs, but its application is limited by expert-driven data analysis that is time-consuming, subjective and may introduce errors. We propose a machine learning-based system to perform GC-MS data analysis that exploits deep learning pattern recognition ability to learn and automatically detect VOCs directly from raw data, thus bypassing expert-led processing. We evaluate this new approach on clinical samples and with four types of convolutional neural networks (CNNs): VGG16, VGG-like, densely connected and residual CNNs. The proposed machine learning methods showed to outperform the expert-led analysis by detecting a significantly higher number of VOCs in just a fraction of time while maintaining high specificity. These results suggest that the proposed novel approach can help the large-scale deployment of breath-based diagnosis by reducing time and cost, and increasing accuracy and consistency.

The Political Economy of Circular Economies: Lessons from Future Repair Scenario Deliberations in Sweden.

The dominant technocratic and neoliberal imaginary of a circular economy dependent on corporate leadership, market mechanisms, and changed consumer behaviour is here explored using the findings of deliberative stakeholder workshops examining diverse scenarios for the promotion of repair as part of a circular economy. Stakeholder responses to four scenarios-digital circularity, planned circularity, circular modernism, and bottom-up sufficiency-are described with reference to the ideologies, interests, and institutions involved. We distinguish two levels of discourse in the stakeholder discussions. The main narrative in which individualist and consumerist ideologies dominate, even within ideals of sustainability, reflects a conjunction of corporate, labour, and public interests in the market liberal social democratic state, with proposed interventions focused on the institutions of markets and education. A subaltern narrative present in the margins of the discussions challenges the consumerist and productivist presumptions of the market liberal political economy and hints at more transformative change. These conflicting responses not only cast light on the ways in which the political economy of contemporary Sweden (within the European Union) constrains and conditions current expectations and imaginaries of circularity, but also suggest ways in which the future political economy of circular economies might be contested and evolve. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43615-021-00128-8.

50 years of radiotherapy research: Evolution, trends and lessons for the future.

Rapid and relentless technological advances in an ever-more globalized world have shaped the field of radiation oncology in which we practise today. These developments have drastically modified the habitus1 of health professionals and researchers at an individual and organisational level. In this article we present an analysis of trends in radiation oncology research over the last half a century. To do so, the data from >350,000 scientific publications pertaining to a yearly search of the PubMed database with the keywords cancer radiotherapy was analysed. This analysis revealed that, over the years, radiotherapy research output has declined relative to alternative cancer therapies, representing 64% in 1970 it decreased to 31% in 2019. Also, the pace of research has significantly accelerated with, in the last 15 years, a doubling in the number of articles published by the 10% most productive researchers. Researchers are also facing stronger competition today with a proportion of first authors that will never get to publish as a last author increasing steadily from 58% in 1970 to 84% in 2000. Additionally, radiotherapy research output is extremely unequally distributed in the world, with Africa and South America contributing to ∼3% of radiotherapy articles in 2019 while representing 23% of the world's population. This disparity, reflecting economic situations and radiotherapy capabilities, has a knock-on effect for the provision of routine clinical treatment. Since research activity is inherent to delivery of high quality clinical care, this contributes to the global inequity of radiotherapy services. Learning from these trends is crucial for the future not only of radiation oncology research but also for effective and equitable cancer care.

Tissue- and Liquid-Based Biomarkers in Prostate Cancer Precision Medicine.

Worldwide, prostate cancer (PC) is the second-most-frequently diagnosed male cancer and the fifth-most-common cause of all cancer-related deaths. Suspicion of PC in a patient is largely based upon clinical signs and the use of prostate-specific antigen (PSA) levels. Although PSA levels have been criticised for a lack of specificity, leading to PC over-diagnosis, it is still the most commonly used biomarker in PC management. Unfortunately, PC is extremely heterogeneous, and it can be difficult to stratify patients whose tumours are unlikely to progress from those that are aggressive and require treatment intensification. Although PC-specific biomarker research has previously focused on disease diagnosis, there is an unmet clinical need for novel prognostic, predictive and treatment response biomarkers that can be used to provide a precision medicine approach to PC management. In particular, the identification of biomarkers at the time of screening/diagnosis that can provide an indication of disease aggressiveness is perhaps the greatest current unmet clinical need in PC management. Largely through advances in genomic and proteomic techniques, exciting pre-clinical and clinical research is continuing to identify potential tissue, blood and urine-based PC-specific biomarkers that may in the future supplement or replace current standard practices. In this review, we describe how PC-specific biomarker research is progressing, including the evolution of PSA-based tests and those novel assays that have gained clinical approval. We also describe alternative diagnostic biomarkers to PSA, in addition to biomarkers that can predict PC aggressiveness and biomarkers that can predict response to certain therapies. We believe that novel biomarker research has the potential to make significant improvements to the clinical management of this disease in the near future.

Breath markers for therapeutic radiation.

Radiation dose is important in radiotherapy. Too little, and the treatment is not effective, too much causes radiation toxicity. A biochemical measurement of the effect of radiotherapy would be useful in personalisation of this treatment. This study evaluated changes in exhaled breath volatile organic compounds (VOC) associated with radiotherapy with thermal desorption gas chromatography mass-spectrometry followed by data processing and multivariate statistical analysis. Further the feasibility of adopting gas chromatography ion mobility spectrometry for radiotherapy point-of-care breath was assessed. A total of 62 participants provided 240 end-tidal 1 dm3 breath samples before radiotherapy and at 1, 3, and 6 h post-exposure, that were analysed by thermal-desorption/gas-chromatography/quadrupole mass-spectrometry. Data were registered by retention-index and mass-spectra before multivariate statistical analyses identified candidate markers. A panel of sulfur containing compounds (thio-VOC) were observed to increase in concentration over the 6 h following irradiation. 3-methylthiophene (80 ng.m-3 to 790 ng.m-3) had the lowest abundance while 2-thiophenecarbaldehyde(380 ng.m-3 to 3.85 µg.m-3) the highest; note, exhaled 2-thiophenecarbaldehyde has not been observed previously. The putative tumour metabolite 2,4-dimethyl-1-heptene concentration reduced by an average of 73% over the same time. Statistical scoring based on the signal intensities thio-VOC and 3-methylthiophene appears to reflect individuals' responses to radiation exposure from radiotherapy. The thio-VOC are hypothesised to derive from glutathione and Maillard-based reactions and these are of interest as they are associated with radio-sensitivity. Further studies with continuous monitoring are needed to define the development of the breath biochemistry response to irradiation and to determine the optimum time to monitor breath for radiotherapy markers. Consequently, a single 0.5 cm3 breath-sample gas chromatography-ion mobility approach was evaluated. The calibrated limit of detection for 3-methylthiophene was 10 µg.m-3 with a lower limit of the detector's response estimated to be 210 fg.s-1; the potential for a point-of-care radiation exposure study exists.

Protocol for tumour-focused dose-escalated adaptive radiotherapy for the radical treatment of bladder cancer in a multicentre phase II randomised controlled trial (RAIDER): radiotherapy planning and delivery guidance.

INTRODUCTION: Daily radiotherapy delivered with radiosensitisation offers patients with muscle invasive bladder cancer (MIBC) comparable outcomes to cystectomy with functional organ preservation. Most recurrences following radiotherapy occur within the bladder. Increasing the delivered radiotherapy dose to the tumour may further improve local control. Developments in image-guided radiotherapy have allowed bladder tumour-focused 'plan of the day' radiotherapy delivery. We aim to test within a randomised multicentre phase II trial whether this technique will enable dose escalation with acceptable rates of toxicity. METHODS AND ANALYSIS: Patients with T2-T4aN0M0 unifocal MIBC will be randomised (1:1:2) between standard/control whole bladder single plan radiotherapy, standard dose adaptive tumour-focused radiotherapy or dose-escalated adaptive tumour-focused radiotherapy (DART). Adaptive tumour-focused radiotherapy will use a library of three plans (small, medium and large) for treatment. A cone beam CT taken prior to each treatment will be used to visualise the anatomy and inform selection of the most appropriate plan for treatment.Two radiotherapy fractionation schedules (32f and 20f) are permitted. A minimum of 120 participants will be randomised in each fractionation cohort (to ensure 57 evaluable DART patients per cohort).A comprehensive radiotherapy quality assurance programme including pretrial and on-trial components is instituted to ensure standardisation of radiotherapy planning and delivery.The trial has a two-stage non-comparative design. The primary end point of stage I is the proportion of patients meeting predefined normal tissue constraints in the DART group. The primary end point of stage II is late Common Terminology Criteria for Adverse Events grade 3 or worse toxicity aiming to exclude a rate of >20% (80% power and 5% alpha, one sided) in each DART fractionation cohort. Secondary end points include locoregional MIBC control, progression-free survival overall survival and patient-reported outcomes. ETHICS AND DISSEMINATION: This clinical trial is approved by the London-Surrey Borders Research Ethics Committee (15/LO/0539). The results when available will be disseminated via peer-reviewed scientific journals, conference presentations and submission to regulatory authorities. TRIAL REGISTRATION NUMBER: NCT02447549; Pre-results.

Radiological Response Heterogeneity Is of Prognostic Significance in Metastatic Renal Cell Carcinoma Treated with Vascular Endothelial Growth Factor-targeted Therapy.

BACKGROUND: Response evaluation criteria in solid tumours (RECIST) is widely used to assess tumour response but is limited by not considering disease site or radiological heterogeneity (RH). OBJECTIVE: To determine whether RH or disease site has prognostic significance in patients with metastatic clear-cell renal cell carcinoma (ccRCC). DESIGN, SETTING, AND PARTICIPANTS: A retrospective analysis was conducted of a second-line phase II study in patients with metastatic ccRCC (NCT00942877), evaluating 138 patients with 458 baseline lesions. INTERVENTION: The phase II trial assessed vascular endothelial growth factor-targeted therapy±Src inhibition. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: RH at week 8 was assessed within individual patients with two or more lesions to predict overall survival (OS) using Kaplan-Meier method and Cox regression model. We defined a high heterogeneous response as occurring when one or more lesion underwent a ≥10% reduction and one or more lesion underwent a ≥10% increase in size. Disease progression was defined by RECIST 1.1 criteria. RESULTS AND LIMITATIONS: In patients with a complete/partial response or stable disease by RECIST 1.1 and two or more lesions at week 8, those with a high heterogeneous response had a shorter OS compared to those with a homogeneous response (hazard ratio [HR] 2.01; 95% confidence interval [CI]: 1.39-2.92; p<0.001). Response by disease site at week 8 did not affect OS. At disease progression, one or more new lesion was associated with worse survival compared with >20% increase in sum of target lesion diameters only (HR 2.12; 95% CI: 1.43-3.14; p<0.001). Limitations include retrospective study design. CONCLUSIONS: RH and the development of new lesions may predict survival in metastatic ccRCC. Further prospective studies are required. PATIENT SUMMARY: We looked at individual metastases in patients with kidney cancer and showed that a variable response to treatment and the appearance of new metastases may be associated with worse survival. Further studies are required to confirm these findings.

Olaparib in patients with metastatic castration-resistant prostate cancer with DNA repair gene aberrations (TOPARP-B): a multicentre, open-label, randomised, phase 2 trial.

BACKGROUND: Metastatic castration-resistant prostate cancer is enriched in DNA damage response (DDR) gene aberrations. The TOPARP-B trial aims to prospectively validate the association between DDR gene aberrations and response to olaparib in metastatic castration-resistant prostate cancer. METHODS: In this open-label, investigator-initiated, randomised phase 2 trial following a selection (or pick-the-winner) design, we recruited participants from 17 UK hospitals. Men aged 18 years or older with progressing metastatic castration-resistant prostate cancer previously treated with one or two taxane chemotherapy regimens and with an Eastern Cooperative Oncology Group performance status of 2 or less had tumour biopsies tested with targeted sequencing. Patients with DDR gene aberrations were randomly assigned (1:1) by a computer-generated minimisation method, with balancing for circulating tumour cell count at screening, to receive 400 mg or 300 mg olaparib twice daily, given continuously in 4-week cycles until disease progression or unacceptable toxicity. Neither participants nor investigators were masked to dose allocation. The primary endpoint of confirmed response was defined as a composite of all patients presenting with any of the following outcomes: radiological objective response (as assessed by Response Evaluation Criteria in Solid Tumors 1.1), a decrease in prostate-specific antigen (PSA) of 50% or more (PSA50) from baseline, or conversion of circulating tumour cell count (from ≥5 cells per 7·5 mL blood at baseline to <5 cells per 7·5 mL blood). A confirmed response in a consecutive assessment after at least 4 weeks was required for each component. The primary analysis was done in the evaluable population. If at least 19 (43%) of 44 evaluable patients in a dose cohort responded, then the dose cohort would be considered successful. Safety was assessed in all patients who received at least one dose of olaparib. This trial is registered at ClinicalTrials.gov, NCT01682772. Recruitment for the trial has completed and follow-up is ongoing. FINDINGS: 711 patients consented for targeted screening between April 1, 2015, and Aug 30, 2018. 161 patients had DDR gene aberrations, 98 of whom were randomly assigned and treated (49 patients for each olaparib dose), with 92 evaluable for the primary endpoint (46 patients for each olaparib dose). Median follow-up was 24·8 months (IQR 16·7-35·9). Confirmed composite response was achieved in 25 (54·3%; 95% CI 39·0-69·1) of 46 evaluable patients in the 400 mg cohort, and 18 (39·1%; 25·1-54·6) of 46 evaluable patients in the 300 mg cohort. Radiological response was achieved in eight (24·2%; 11·1-42·3) of 33 evaluable patients in the 400 mg cohort and six (16·2%; 6·2-32·0) of 37 in the 300 mg cohort; PSA50 response was achieved in 17 (37·0%; 23·2-52·5) of 46 and 13 (30·2%; 17·2-46·1) of 43; and circulating tumour cell count conversion was achieved in 15 (53·6%; 33·9-72·5) of 28 and 13 (48·1%; 28·7-68·1) of 27. The most common grade 3-4 adverse event in both cohorts was anaemia (15 [31%] of 49 patients in the 300 mg cohort and 18 [37%] of 49 in the 400 mg cohort). 19 serious adverse reactions were reported in 13 patients. One death possibly related to treatment (myocardial infarction) occurred after 11 days of treatment in the 300 mg cohort. INTERPRETATION: Olaparib has antitumour activity against metastatic castration-resistant prostate cancer with DDR gene aberrations, supporting the implementation of genomic stratification of metastatic castration-resistant prostate cancer in clinical practice. FUNDING: Cancer Research UK, AstraZeneca, Prostate Cancer UK, the Prostate Cancer Foundation, the Experimental Cancer Medicine Centres Network, and the National Institute for Health Research Biomedical Research Centres.

VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography/Mass Spectrometry Data.

Metabolic profiling of breath analysis involves processing, alignment, scaling, and clustering of thousands of features extracted from gas chromatography/mass spectrometry (GC/MS) data from hundreds of participants. The multistep data processing is complicated, operator error-prone, and time-consuming. Automated algorithmic clustering methods that are able to cluster features in a fast and reliable way are necessary. These accelerate metabolic profiling and discovery platforms for next-generation medical diagnostic tools. Our unsupervised clustering technique, VOCCluster, prototyped in Python, handles features of deconvolved GC/MS breath data. VOCCluster was created from a heuristic ontology based on the observation of experts undertaking data processing with a suite of software packages. VOCCluster identifies and clusters groups of volatile organic compounds (VOCs) from deconvolved GC/MS breath with similar mass spectra and retention index profiles. VOCCluster was used to cluster more than 15 000 features extracted from 74 GC/MS clinical breath samples obtained from participants with cancer before and after a radiation therapy. Results were evaluated against a panel of ground truth compounds and compared to other clustering methods (DBSCAN and OPTICS) that were used in previous metabolomics studies. VOCCluster was able to cluster those features into 1081 groups (including endogenous and exogenous compounds and instrumental artifacts) with an accuracy rate of 96% (±0.04 at 95% confidence interval).

EPID-based in vivo dosimetry using Dosimetry Check™: Overview and clinical experience in a 5-yr study including breast, lung, prostate, and head and neck cancer patients.

BACKGROUND: Independent verification of the dose delivered by complex radiotherapy can be performed by electronic portal imaging device (EPID) dosimetry. This paper presents 5-yr EPID in vivo dosimetry (IVD) data obtained using the Dosimetry Check (DC) software on a large cohort including breast, lung, prostate, and head and neck (H&N) cancer patients. MATERIAL AND METHODS: The difference between in vivo dose measurements obtained by DC and point doses calculated by the Eclipse treatment planning system was obtained on 3795 radiotherapy patients treated with volumetric modulated arc therapy (VMAT) (n = 842) and three-dimensional conformal radiotherapy (3DCRT) (n = 2953) at 6, 10, and 15 MV. In cases where the dose difference exceeded ±10% further inspection and additional phantom measurements were performed. RESULTS: The mean and standard deviation ( µ ± σ ) of the percentage difference in dose obtained by DC and calculated by Eclipse in VMAT was: 0.19 ± 3.89 % in brain, 1.54 ± 4.87 % in H&N, and 1.23 ± 4.61 % in prostate cancer. In 3DCRT, this was 1.79 ± 3.51 % in brain, - 2.95 ± 5.67 % in breast, - 1.43 ± 4.38 % in bladder, 1.66 ± 4.77 % in H&N, 2.60 ± 5.35% in lung and - 3.62 ± 4.00 % in prostate cancer. A total of 153 plans exceeded the ±10% alert criteria, which included: 88 breast plans accounting for 7.9% of all breast treatments; 28 H&N plans accounting for 4.4% of all H&N treatments; and 12 prostate plans accounting for 3.5% of all prostate treatments. All deviations were found to be as a result of patient-related anatomical deviations and not from procedural errors. CONCLUSIONS: This preliminary data shows that EPID-based IVD with DC may not only be useful in detecting errors but has the potential to be used to establish site-specific dose action levels. The approach is straightforward and has been implemented as a radiographer-led service with no disruption to the patient and no impact on treatment time.

Terminal Pleistocene epoch human footprints from the Pacific coast of Canada.

Little is known about the ice age human occupation of the Pacific Coast of Canada. Here we present the results of a targeted investigation of a late Pleistocene shoreline on Calvert Island, British Columbia. Drawing upon existing geomorphic information that sea level in the area was 2-3 m lower than present between 14,000 and 11,000 years ago, we began a systematic search for archaeological remains dating to this time period beneath intertidal beach sediments. During subsurface testing, we uncovered human footprints impressed into a 13,000-year-old paleosol beneath beach sands at archaeological site EjTa-4. To date, our investigations at this site have revealed a total of 29 footprints of at least three different sizes. The results presented here add to the growing body of information pertaining to the early deglaciation and associated human presence on the west coast of Canada at the end of the Last Glacial Maximum.