Stereotactic Body Radiation Therapy for Lung and Liver Oligometastases from Breast Cancer: Toxicity Data of a Prospective Non-Randomized Phase II Trial.

AIMS: We report the mature toxicity data of a phase II non-randomized trial on the use of SBRT for lung and liver oligometastases. METHODS: Oligometastatic patients from breast cancer were treated with SBRT for up to five lung and/or liver lesions. Inclusion criteria were: age > 18 years, ECOG 0-2, diagnosis of breast cancer, less than five lung/liver lesions (with a maximum diameter <5 cm), metastatic disease confined to the lungs and liver or extrapulmonary or extrahepatic disease stable or responding to systemic therapy. Various dose-fractionation schedules were used. Then, a 4D-CT scan and FDG-CTPET were acquired for simulation and fused for target definition. RESULTS: From 2015 to 2021, 64 patients and a total of 90 lesions were irradiated. Treatment was well tolerated, with no G 3-4 toxicities. No grade ≥3 toxicities were registered and the coprimary endpoint of the study was met. Median follow-up was 19.4 months (range 2.6-73.1). CONCLUSIONS: The co-primary endpoint of this phase II trial was met, showing excellent tolerability of SBRT for lung and liver oligometastatic in breast cancer patients. Until efficacy data will mature with longer follow-up, SBRT should be regarded as an opportunity for oligometastatic breast cancer patients.

Locally Advanced Non-Small Cell Lung Cancer: Clinical Outcome, Toxicity and Predictive Factors in Patients Treated with Hypofractionated Sequential or Exclusive Radiotherapy.

BACKGROUND: This study evaluated the outcome, toxicity and predictive factors in patients unfit for concurrent chemo-radiotherapy (CT-RT) treated with hypofractionated sequential CT-RT or exclusive radiotherapy (RT) for locally advanced non-small cell lung cancer (LA-NSCLC). METHODS: We included patients affected by LA-NSCLC (stage IIA-IVA) treated with a total dose of 50-60 Gy in 20 fractions. The primary outcomes were local control (LC), distant metastasis-free survival (DMFS), progression-free survival (PFS) and overall survival (OS). Univariate analysis was used to correlate outcomes with prognostic factors. RESULTS: Between 2011 and 2019, 210 patients were treated, 113 (53.8%) with sequential CT-RT and 97 (46.2%) with exclusive RT. After a median follow-up of 15.3 months, 74 patients (35.2%) had a local progression and 133 (63.3%) had a distant progression. The one-, two- and five-year LC were 73.6%, 55.3% and 47.9%, respectively. At the time of analysis, 167 patients (79.5%) died. The one-, two- and five-year OS were 64.7%, 36% and 20%, respectively. PTV volume correlated with PFS (p = 0.001) and LC (p = 0.005). Acute and late toxicity occurred in 82% and 26% of patients. CONCLUSIONS: Albeit with the known limitations of a retrospective and heterogeneous study, our work shows that hypofractionated sequential CT-RT or exclusive RT offer a good local control and toxicity profile and a promising survival rate in LA-NSCLC patients unfit for the concurrent CT-RT scheme.

Monte Carlo Models for Sub-Chronic Repeated-Dose Toxicity: Systemic and Organ-Specific Toxicity.

The risk-characterization of chemicals requires the determination of repeated-dose toxicity (RDT). This depends on two main outcomes: the no-observed-adverse-effect level (NOAEL) and the lowest-observed-adverse-effect level (LOAEL). These endpoints are fundamental requirements in several regulatory frameworks, such as the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) and the European Regulation of 1223/2009 on cosmetics. The RDT results for the safety evaluation of chemicals are undeniably important; however, the in vivo tests are time-consuming and very expensive. The in silico models can provide useful input to investigate sub-chronic RDT. Considering the complexity of these endpoints, involving variable experimental designs, this non-testing approach is challenging and attractive. Here, we built eight in silico models for the NOAEL and LOAEL predictions, focusing on systemic and organ-specific toxicity, looking into the effects on the liver, kidney and brain. Starting with the NOAEL and LOAEL data for oral sub-chronic toxicity in rats, retrieved from public databases, we developed and validated eight quantitative structure-activity relationship (QSAR) models based on the optimal descriptors calculated by the Monte Carlo method, using the CORAL software. The results obtained with these models represent a good achievement, to exploit them in a safety assessment, considering the importance of organ-related toxicity.

Oligoprogressive castration-resistant prostate cancer treated with metastases-directed stereotactic body radiation therapy: predictive factors for patients' selection.

Oligoprogression is defined as limited metastatic clone resistant to on-going systemic treatment that grows in a background of stable or responding systemic disease. Aim of the present study was to analyze oligoprogressive prostate cancer (PC) patients treated with stereotactic body radiation therapy (SBRT) during systemic treatment to identify predictive factors and improve patients' selection. We included PC patients treated with SBRT on a maximum of 3 sites of oligoprogression during systemic therapy. Endpoints were freedom from polymetastatic progression (FPP), local control (LC), distant progression free survival (DPFS), overall survival (OS), and next systemic therapy free survival (NEST-FS). Fifty-three patients were treated on 85 oligoprogressive metastases. Lymph nodes were the most common sites (56.47%), followed by bone (39.29%). Median follow-up was 24.9 months. Rates of FPP at 1- and 2-year were 80.1% and 68.9%, respectively. Median time to polymetastatic progression was 33.7 months. Disease free interval (p = 0.004), site of metastases (p = 0.011), and type of systemic therapy (p = 0.003) were significant for FPP. Switch or intensification of systemic therapy after SBRT was observed in 29 (54.72%) patients with a median NEST-FS of 15.2 months. LC at 1- and 2-year was 94.0% and 92.0%, with PSA doubling time resulted to be significantly associated (p = 0.047). Median DPFS was 8.93 months and median OS was 50.6 months. In conclusion, we confirmed the efficacy of SBRT for oligoprogression from PC, with the potential to prolong the on-going systemic therapy and interrupt the metastatic cascade.

In Silico Models for Developmental Toxicity.

Modeling developmental toxicity has been a challenge for (Q)SAR model developers due to the complexity of the endpoint. Recently, some new in silico methods have been developed introducing the possibility to evaluate the integration of existing methods by taking advantage of various modeling perspectives. It is important that the model user is aware of the underlying basis of the different models in general, as well as the considerations and assumptions relative to the specific predictions that are obtained from these different models for the same chemical. The evaluation on the predictions needs to be done on a case-by-case basis, checking the analogues (possibly using structural, physicochemical, and toxicological information); for this purpose, the assessment of the applicability domain of the models provides further confidence in the model prediction. In this chapter, we present some examples illustrating an approach to combine human-based rules and statistical methods to support the prediction of developmental toxicity; we also discuss assumptions and uncertainties of the methodology.

Inverse Reinforcement Learning Intra-Operative Path Planning for Steerable Needle.

OBJECTIVE: This paper presentsa safe and effective keyhole neurosurgery intra-operative planning framework for flexible neurosurgical robots. The framework is intended to support neurosurgeons during the intra-operative procedure to react to a dynamic environment. METHODS: The proposed system integrates inverse reinforcement learning path planning algorithm combined with 1) a pre-operative path planning framework for fast and intuitive user interaction, 2) a realistic, time-bounded simulator based on Position-based Dynamics (PBD) simulation that mocks brain deformations due to catheter insertion and 3) a simulated robotic system. RESULTS: Simulation results performed on a human brain dataset show that the inverse reinforcement learning intra-operative planning method can guide a steerable needle with bounded curvature to a predefined target pose with an average targeting error of 1.34 ± 0.52 (25 th = 1.02, 75 th = 1.36) mm in position and 3.16 ± 1.06 (25 th = 2, 75 th = 4.94) degrees in orientation under a deformable simulated environment, with a re-planning time of 0.02 sec and a success rate of 100%. CONCLUSION: With this work, we demonstrate that the presented intra-operative steerable needle path planner is able to avoid anatomical obstacles while optimising surgical criteria. SIGNIFICANCE: The results demonstrate that the proposed method is fast and can securely steer flexible needles with high accuracy and robustness.

Quantitative Structure-Activity Relationship Modeling of the Amplex Ultrared Assay to Predict Thyroperoxidase Inhibitory Activity.

The thyroid system plays a major role in the regulation of several physiological processes. The dysregulation of the thyroid system caused by the interference of xenobiotics and contaminants may bring to pathologies like hyper- and hypothyroidism and it has been recently correlated with adverse outcomes leading to cancer, obesity, diabetes and neurodevelopmental disorders. Thyroid disruption can occur at several levels. For example, the inhibition of thyroperoxidase (TPO) enzyme, which catalyses the synthesis of thyroid hormones, may cause dysfunctions related to hypothyroidism. The inhibition of the TPO enzyme can occur as a consequence of prolonged exposure to chemical compounds, for this reason it is of utmost importance to identify alternative methods to evaluate the large amount of pollutants and other chemicals that may pose a potential hazard to the human health. In this work, quantitative structure-activity relationship (QSAR) models to predict the TPO inhibitory potential of chemicals are presented. Models are developed by means of several machine learning and data selection approaches, and are based on data obtained in vitro with the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay. Balancing methods and feature selection are applied during model development. Models are rigorously evaluated through internal and external validation. Based on validation results, two models based on Balanced Random Forest (BRF) and K-Nearest Neighbours (KNN) algorithms were selected for a further validation phase, that leads predictive performance (BA = 0.76-0.78 on external data) that is comparable with the reported experimental variability of the AUR-TPO assay (BA ∼0.70). Finally, a consensus between the two models was proposed (BA = 0.82). Based on the predictive performance, these models can be considered suitable for toxicity screening of environmental chemicals.

Dose coverage impacts local control in ultra-central lung oligometastases treated with stereotactic radiotherapy.

INTRODUCTION: The use of Stereotactic Body Radiotherapy (SBRT) is controversial in Ultra-Central lung tumors, a subset of central lung tumors characterized by proximity to critical mediastinal structures. This is of interest in oligometastatic (≤3 metastases) patients, who can yield survival benefit from local treatments. The aim of our study is to assess the determinants of efficacy and toxicity in this setting. MATERIALS AND METHODS: Clinical and dosimetric parameters were reviewed in a cohort of oligometastatic patients treated with SBRT for ultra-central tumors. Local control rate (LC) and toxicity were assessed. Statistical Analysis was carried out to assess the impact of those predictors on local recurrence and adverse events. RESULTS: One-hundred-nine consecutive patients were included. A median Biologic Effective Dose (BED) of 105 (75-132) Gy10 was prescribed. At a median follow-up of 17 (range 3-78) months, 2-year LC was 87%. Improved LC was correlated to Planning Treatment Volume (PTV) covered by 95% of the prescription dose (V95% PTV) > 85% (HR 0.15, 95%CI 0.05-0.49, p = 0.0017) and to Gross Tumor Volume (GTV) < 90 cm3 (HR 0.2, 95%CI 0.07-0.56, p = 0.0021). Overall and grade ≥ 3 toxicity incidence was 20% and 5%, respectively. Patients experiencing acute and late toxicities received significantly higher dose to 1 cm3 (D1cm3) of esophagus and lung volume receiving ≥5 Gy (V5Gy) (p = 0.016 and p = 0.013), and higher dose to 0.1 cm3 (D0.1cm3) of heart (p = 0.036), respectively. CONCLUSION: V95% PTV > 85% and GTV < 90 cm3 are independent predictors of LC. Dose to esophagus, lung and heart should be carefully assessed to minimize treatment-related toxicities.

Integrated In Silico Models for the Prediction of No-Observed-(Adverse)-Effect Levels and Lowest-Observed-(Adverse)-Effect Levels in Rats for Sub-chronic Repeated-Dose Toxicity.

Repeated-dose toxicity (RDT) is a critical endpoint for hazard characterization of chemicals and is assessed to derive safe levels of exposure for human health. Here we present the first attempt to model simultaneously no-observed-(adverse)-effect level (NO(A)EL) and lowest-observed-(adverse)-effect level (LO(A)EL). Classification and regression models were derived based on rat sub-chronic repeated dose toxicity data for 327 compounds from the Fraunhofer RepDose database. Multi-category classification models were built for both NO(A)EL and LO(A)EL though a consensus of statistics- and fragment-based algorithms, while regression models were based on quantitative relationships between the endpoints and SMILES-based attributes. NO(A)EL and LO(A)EL models were integrated, and predictions were compared to exclude inconsistent values. This strategy improved the performance of single models, leading to R2 greater than 0.70, root-mean-square error (RMSE) lower than 0.60 (for regression models), and accuracy of 0.61-0.73 (for classification models) on the validation set, based on the endpoint and the threshold applied for selecting predictions. This study confirms the effectiveness of the modeling strategy presented here for assessing RDT of chemicals using in silico models.

Preliminary Results of a Randomized Study on Postmenopausal Women With Early Stage Breast Cancer: Adjuvant Hypofractionated Whole Breast Irradiation Versus Accelerated Partial Breast Irradiation (HYPAB Trial).

BACKGROUND: The purpose of this study was to report preliminary data of a randomized phase III trial comparing hypofractionated whole breast irradiation (HWBI) and accelerated partial breast irradiation (APBI) using volumetric modulated arc therapy (VMAT). MATERIAL AND METHODS: The HYPAB trial enrolled postmenopausal women with biopsy-proven infiltrating breast cancer, clinically negative axilla, single T1 to T2 tumors, who were treated with breast-conserving surgery. Patients were randomized 1:1 after surgery to HWBI (40.5 Gy whole breast, 48.0 Gy to surgical bed, 15 fractions over 3 weeks) or APBI (30 Gy delivered in 5 fractions of 6 Gy given on alternate days on the surgical bed). Cosmetic outcome was the primary end point of the study. RESULTS: A total of 172 patients were enrolled. After a median follow-up of 36 months, 5 local failures and 3 locoregional failures were recorded, with no difference between the 2 treatment arms. Use of HWBI as compared with APBI was significantly correlated with increased incidence of overall (62% vs. 14%; P < .001) and grade 2 (18% vs. 1%; P < .001) acute skin toxicity. APBI was correlated with a lower incidence of overall late toxicity as compared with HWBI (18% vs. 41%; P = .001), but no significant difference was found in term of occurrence of grade 2 events (1% vs. 4%; P = NS). At comparative assessment between baseline and post-radiotherapy evaluation, impairment in cosmetic outcome was reported in 19 (11%) patients. Owing to premature closure of the study, no per-protocol comparison between the treatment arms was performed. CONCLUSION: APBI with the VMAT technique is safe and feasible, with lower acute toxicity when compared with HWBI.

Pesticides, cosmetics, drugs: identical and opposite influences of various molecular features as measures of endpoints similarity and dissimilarity.

The similarity is an important category in natural sciences. A measure of similarity for a group of various biochemical endpoints is suggested. The list of examined endpoints contains (1) toxicity of pesticides towards rainbow trout; (2) human skin sensitization; (3) mutagenicity; (4) toxicity of psychotropic drugs; and (5) anti HIV activity. Further applying and evolution of the suggested approach is discussed. In particular, the conception of the similarity (dissimilarity) of endpoints can play the role of a "useful bridge" between quantitative structure property/activity relationships (QSPRs/QSARs) and read-across technique.

Salvage radiotherapy for oligo-progressive malignant pleural mesothelioma.

OBJECTIVES: No standard treatment option is available for patients with unresectable malignant pleural mesothelioma (MPM) progressing after upfront chemotherapy. We aimed to explore the role of focal radiotherapy (FRT) as a treatment modality for oligo-progressive MPM. MATERIALS AND METHODS: In this retrospective study, consecutive patients pretreated with ≥1 lines of chemotherapy were included. Oligo-progressive MPM was defined as an unresectable disease with radiological progression at ≤3 sites according to a chest-abdominal contrast-enhanced computed tomography. Patients were treated with either stereotactic body radiotherapy (SBRT, ≥5 Gy per fraction) or hypo-fractionated radiotherapy (hypoRT, <5 Gy per fraction). Time to further systemic therapy (TFST) and local control (LC) after FRT were the primary endpoints. Biologically effective dose (BED) was calculated using three different alpha/beta models (1.5 Gy, 3 Gy and 10 Gy). RESULTS: From April 2006 to March 2019, 37 patients were treated on 43 pleural lesions; 16/37 (43 %) had undergone upfront multimodality treatment (MMT) including surgery. FRT was given in 22/37 (59.5 %) after one line of chemotherapy. SBRT was delivered for 26/43 lesions (60.5 %), hypoRT for 17/43 (39.5 %). Median TFST was 6 months (95 % CI 4.9-7.1). LC at 6 months and 1 year was 84 % and 76 %, respectively. Median TFST was longer in patients treated after 1 vs >1 line of chemotherapy (9 vs 4 months, p = 0.001) and in patients pretreated with MMT (6 vs 3 months, p = 0.021). Six-month LC was better in patients treated with a BED > 100 using alpha/beta 1.5 and 3. No ≥ G3 acute or late toxicities were reported. CONCLUSION: FRT was feasible in selected patients with oligo-progressive MPM, allowing delay of further systemic therapies, with no severe toxicity. FRT was more effective when performed at progression after one line of systemic therapy. Our results suggest a radio-resistant behavior of MPM.

Zebrafish AC50 modelling: (Q)SAR models to predict developmental toxicity in zebrafish embryo.

Developmental toxicity refers to the occurrence of adverse effects on a developing organism as a consequence of exposure to hazardous chemicals. The assessment of developmental toxicity has become relevant to the safety assessment process of chemicals. The zebrafish embryo developmental toxicology assay is an emerging test used to screen the teratogenic potential of chemicals and it is proposed as a promising test to replace teratogenic assays with animals. Supported by the increased availability of data from this test, the developmental toxicity assay with zebrafish has become an interesting endpoint for the in silico modelling. The purpose of this study was to build up quantitative structure-activity relationship (QSAR) models. In this work, new in silico models for the evaluation of developmental toxicity were built using a well-defined set of data from the ToxCastTM Phase I chemical library on the zebrafish embryo. Categorical and continuous QSAR models were built by gradient boosting machine learning and the Monte Carlo technique respectively, in accordance with Organization for Economic Co-operation and Development principles and their statistical quality was satisfactory. The classification model reached balanced accuracy 0.89 and Matthews correlation coefficient 0.77 on the test set. The regression model reached correlation coefficient R2 0.70 in external validation and leave-one-out cross-validated Q2 0.73 in internal validation.

Stereotactic Radiotherapy for Ultra-Central Lung Oligometastases in Non-Small-Cell Lung Cancer.

BACKGROUND: Stereotactic body radiotherapy (SBRT) in ultra-central (UC) lung tumors, defined in the presence of planning target volume (PTV) overlap or direct tumor abutment to the central bronchial tree or esophagus, may be correlated to a higher incidence of severe adverse events. Outcome and toxicity in oligometastatic (≤3 metastases) non-small-cell lung cancer (NSCLC) patients receiving SBRT for UC tumors were evaluated. METHODS: Oligometastatic NSCLC patients treated with SBRT for UC were retrospectively reviewed. Local control (LC), distant metastasis-free survival (DMFS), progression-free survival (PFS) and overall survival (OS) were calculated. Incidence and grade of toxicity were evaluated. Statistical analysis was performed to assess the impact of clinical and treatment-related variables on outcome and toxicity occurrence. RESULTS: Seventy-two patients were treated to a median biologically effective dose (BED) of 105 (75-132) Gy10. Two-year LC, DMFS, PFS, and OS were 83%, 46%, 43%, and 49%. BED>75 Gy10 was correlated to superior LC (p = 0.02), PFS (p = 0.036), and OS (p < 0.001). Grade ≥3 toxicity rate was 7%, including one fatal esophagitis. No variables were correlated to DMFS or to occurrence of overall and grade ≥3 toxicity. CONCLUSIONS: SBRT using dose-intensive schedules improves outcome in NSCLC patients. Overall toxicity is acceptable, although rare but potentially fatal toxicities may occur.

Use of the index of ideality of correlation to improve aquatic solubility model.

Models for water solubility are built up using so-called correlation weights of fragments of simplified molecular input-line entry system (SMILES), 2D graph invariants, and hierarchy of rings present in molecules. The approach is based on Monte Carlo optimization of the molecular features. Two versions of the optimization were examined: (i) the traditional version; and (ii) the Index of Ideality of Correlation (IIC) version. The statistical quality of models obtained with use of the IIC is comparable with models built up with application of physico-chemical endpoints and quantum mechanics descriptors recently suggested in the literature.

QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors.

Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure-activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predict both human and rat carcinogenicity, but there are few models to quantitatively assess carcinogenicity in humans. To our knowledge, slope factor (SF), a parameter describing carcinogenicity potential used especially for human risk assessment of contaminated sites, has never been modeled for both inhalation and oral exposures. In this study, we developed classification and regression models for inhalation and oral SFs using data from the Risk Assessment Information System (RAIS) and different machine learning approaches. The models performed well in classification, with accuracies for the external set of 0.76 and 0.74 for oral and inhalation exposure, respectively, and r2 values of 0.57 and 0.65 in the regression models for oral and inhalation SFs in external validation. These models might therefore support regulators in (de)prioritizing substances for regulatory action and in weighing evidence in the context of chemical safety assessments. Moreover, these models are implemented on the VEGA platform and are now freely downloadable online.

QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors.

In the recent years, ecotoxicological hazard potential of biocidal products has been receiving increasing attention in the industries and regulatory agencies. Biocides/pesticides are currently one of the most studied groups of compounds, and their registration cannot be done without the empirical toxicity information. In view of limited experimental data available for these compounds, we have developed Quantitative Structure-Activity Relationship (QSAR) models for the toxicity of biocides to fish and Daphnia magna following principles of QSAR modeling recommended by the OECD (Organization for Economic Cooperation and Development). The models were developed using simple and interpretable 2D descriptors and validated using stringent tests. Both models showed encouraging statistical quality in terms of determination coefficient R2 (0.800 and 0.648), cross-validated leave-one-out Q2 (0.760 and 0.602) and predictive R2pred or Q2ext (0.875 and 0.817) for fish (nTraining = 66, nTest = 22) and Daphnia magna (nTraining = 100, nTest = 33) toxicity datasets, respectively. These models should be applicable for data gap filling in case of new or untested biocidal compounds falling within the applicability domain of the models. In general, the models indicate that the toxicity increases with lipophilicity and decreases with polarity, branching and unsaturation. We have also developed interspecies toxicity models for biocides using the daphnia and fish toxicity data and used the models for data gap filling.

Impact of REACH legislation on the production and importation of CMR (carcinogen, mutagen and reproductive) and explosive chemicals in Italy from 2011 to 2015.

On 1 June 2007, the European Commission issued the Registration, Evaluation, Authorization and Restriction of Chemicals (REACH) to protect both the environment and human health. We analyzed the impact of REACH in the Italian market considering the presence of chemicals, their diversity, importation and production during the period 2011-2015, with particular attention to products with toxic or explosive properties. There was a reduction of the chemicals on the market, in terms of tons but also the absolute numbers of types of compounds. The production reduction was particularly noticeable for explosive chemicals: -14.7%. CMR products did not show any statistically significant reduction in term of tons: -2.3%.