Phase II study of concomitant radiotherapy with atezolizumab in oligometastatic soft tissue sarcomas: STEREOSARC trial protocol.

INTRODUCTION: Up to 50% of soft tissue sarcoma (STS) patients develop metastases in the course of their disease. Cytotoxic therapy is a standard treatment in this setting but yields average tumour response rates of 25% at first line and ≤10% at later lines. In oligometastatic stage, stereotactic body radiation therapy (SBRT) allows reaching high control rates at treated sites (≥80%) and is potentially equally effective to surgery in term of overall survival. In order to shift the balance towards antitumour immunity by multisite irradiation, radiation could be combined with inhibitors of the immunosuppressive pathways. METHODS AND ANALYSIS: STEREOSARC is a prospective, multicentric, randomised phase II, designed to evaluate the efficacy of SBRT associated with immunotherapy versus SBRT only. Randomisation is performed with a 2:1 ratio within two arms. The primary objective is to evaluate the efficacy, in term of progression-free survival (PFS) rate at 6 months, of immunomodulated stereotactic multisite irradiation in oligometastatic sarcoma patients. The secondary objectives include PFS by immune response criteria, overall survival, quality-of-life evaluation and developing mathematical models of tumour growth and dissemination predictive of oligometastatic versus polymetastatic evolution. Patients will be randomised in two groups: SBRT with atezolizumab and SBRT alone. The total number of included patients should be 103. TRIAL REGISTRATION: The trial is registered on ClinicalTrials.gov (ID: NCT03548428). ETHICS AND DISSEMINATION: This study has been approved by Comité de Protection des Personnes du sud-ouest et outre-mer 4 on 18 October 2019 (Reference CPP2019-09-076-PP) and from National Agency for Medical and Health products Safety (Reference: MEDAECNAT-2019-08-00004_2017-004239-35) on 18 September 2019.The results will be disseminated to patients upon individual request or through media release from scientific meetings. The results will be communicated through scientific meetings and publications.

Mathematical modeling of peripheral blood neutrophil kinetics to predict CLAD after lung transplantation.

BACKGROUND: The presence of neutrophils in the lung was identified as a factor associated with CLAD but requires invasive samples. The aim of this study was to assess the kinetics of peripheral blood neutrophils after lung transplantation as early predictor of CLAD. METHODS: We retrospectively included all recipients transplanted in our center between 2009 and 2014. Kinetics of blood neutrophils were evaluated to predict early CLAD by mathematical modeling using unadjusted and adjusted analyses. RESULTS: 103 patients were included, 80 in the stable group and 23 in the CLAD group. Bacterial infections at 1 year were associated with CLAD occurrence. Neutrophils demonstrated a high increase postoperatively and then a progressive decrease until normal range. Recipients with CLAD had higher neutrophil counts (mixed effect coefficient beta over 3 years = +1.36 G/L, 95% Confidence Interval [0.99-1.92], p < .001). A coefficient of celerity (S for speed) was calculated to model the kinetics of return to the norm before CLAD occurrence. After adjustment, lower values of S (slower decrease of neutrophils) were associated with CLAD (Odds Ratio = 0.26, 95% Confidence Interval [0.08-0.66], p = .01). CONCLUSION: A slower return to the normal range of blood neutrophils was early associated with CLAD occurrence.

Immunologically effective dose: a practical model for immuno-radiotherapy.

OBJECTIVES: Concomitant radiotherapy with immune checkpoint blockade could be synergistic. Out-of-field effects could improve survival by slowing or blocking metastatic spreading. However, not much is known about the optimal size per fraction and inter-fraction time in that new context. METHODS: The new concept of Immunologically Effective Dose (IED) is proposed: it models an intrinsic immunogenicity of radiotherapy schedules, i.e. the fraction of immunogenicity that results from the choice of the dosing regimen. The IED is defined as the single dose, given in infinitely low dose rate, that produces the same amount of abscopal response as the radiation schedule being considered. The IED uses the classic parameters of the BED formula and adds two parameters for immunogenicity that describe the local availability of immune effectors within the tumor micro-environment. Fundamentally, the IED adds a time dimension in the BED formula and describes an intrinsic immunogenicity level for radiotherapy. RESULTS: The IED is positively related to the intensity of the out-of-field, radiotherapy-mediated, immune effects described in some preclinical data. Examples of numerical simulations are given for various schedules. A web-based calculator is freely available. CONCLUSIONS: Out-of-field effects of radiotherapy with immune checkpoint blockers might be better predicted and eventually, radiotherapy schedules with better local and systemic immunogenicity could be proposed. ADVANCES IN KNOWLEDGE: A model for the intrinsic level of immunogenicity of radiotherapy schedules, referred to as the Immunologically Effective Dose (IED), that is independent of the type of immunotherapy.

Mathematical modeling of disease dynamics in SDHB- and SDHD-related paraganglioma: Further step in understanding hereditary tumor differences and future therapeutic strategies.

Succinate dehydrogenase subunit B and D (SDHB and SDHD) mutations represent the most frequent cause of hereditary pheochromocytoma and paraganglioma (PPGL). Although truncation of the succinate dehydrogenase complex is thought to be the disease causing mechanism in both disorders, SDHB and SDHD patients exihibit different phenotypes. These phenotypic differences are currently unexplained by molecular genetics. The aim of this study is to compare disease dynamics in these two conditions via a Markov chain model based on 4 clinically-defined steady states. Our model corroborates at the population level phenotypic observations in SDHB and SDHD carriers and suggests potential explanations associated with the probabilities of disease maintenance and regression. In SDHB-related syndrome, PPGL maintenance seems to be reduced compared to SDHD (p = 0.04 vs 0.95) due to higher probability of tumor cell regression in SDHB vs SDHD (p = 0.87 vs 0.00). However, when SDHB-tumors give rise to metastases, metastatic cells are able to thrive with decreased probability of regression compared with SDHD counterparts (p = 0.17 vs 0.89). By constrast, almost all SDHD patients develop PGL (mainly head and neck) that persist throughout their lifetime. However, compared to SDHB, maintenance of metastatic lesions seems to be less effective for SDHD (p = 0.83 vs 0.11). These findings align with data suggesting that SDHD-related PPGL require less genetic events for tumor initiation and maintenance compared to those related to SDHB, but fail to initiate biology that promotes metastatic spread and metastatic cell survival in host tissues. By contrast, the higher number of genetic abnormalities required for tumor initiation and maintenance in SDHB PPGL result in a lower penetrance of PGL, but when cells give rise to metastases they are assumed to be better adapted to sustain survival. These proposed differences in disease progression dynamics between SDHB and SDHD diseases provide new cues for future exploration of SDHx PPGL behavior, offering considerations for future specific therapeutic and prevention strategies.

Mathematical modeling for Phase I cancer trials: A study of metronomic vinorelbine for advanced non-small cell lung cancer (NSCLC) and mesothelioma patients.

INTRODUCTION: Using mathematical modelling allows to select a treatment's regimen across infinite possibilities. Here, we report the phase I assessment of a new schedule for metronomic vinorelbine in treating refractory advanced NSCLC and mesothelioma patients. RESULTS: Overall, 13 patients were screened and 12 were treated (50% male, median age: 68yrs), including 9 NSCLC patients. All patients received at least one week (3 doses) of treatment. At data cut-off, the median length of treatment was 6.5 weeks (1-32+). All the patients presented with at least one adverse event (AE) and six patients with a severe AE (SAE). One partial response and 5 stable diseases were observed. The median OS was 6.4 months (95% CI, 4.8 to 12 months). The median and mean vinorelbine's AUC were 122 ng/ml*h and 159 ng/ml*h, respectively, with the higher plasmatic vinorelbine exposure associated with the best ORR (difference of AUC comparison between responders and non-responders, p-value 0.017). MATERIALS AND METHODS: The mathematical modelling determined the administration of vinorelbine, 60 mg on Day 1, 30 mg on Day 2 and 60 mg on Day 4 weekly until progression, as the best schedule. Advanced NSCLC or mesothelioma patients progressing after standard treatment were eligible for the trial. NCT02555007. CONCLUSIONS: Responses with acceptable safety profile were observed in heavily pretreated NSCLC and mesothelioma patients using oral vinorelbine at this metronomic dosage based on a mathematic modeling. This study demonstrates the feasibility of this new type of approach, as mathematical modeling may help to rationally decide the better regimen to be clinically tested across infinite possibilities.

Modeling therapeutic response to radioiodine in metastatic thyroid cancer: a proof-of-concept study for individualized medicine.

PURPOSE: Radioiodine therapy (RAI) has traditionally been used as treatment for metastatic thyroid cancer, based on its ability to concentrate iodine. Propositions to maximize tumor response with minimizing toxicity, must recognize the infinite possibilities of empirical tests. Therefore, an approach of this study was to build a mathematical model describing tumor growth with the kinetics of thyroglobulin (Tg) concentrations over time, following RAI for metastatic thyroid cancer. EXPERIMENTAL DESIGN: Data from 50 patients with metastatic papillary thyroid carcinoma treated within eight French institutions, followed over 3 years after initial RAI treatments, were included in the model. A semi-mechanistic mathematical model that describes the tumor growth under RAI treatment was designed. RESULTS: Our model was able to separate patients who responded to RAI from those who did not, concordant with the physicians' determination of therapeutic response. The estimated tumor doubling-time (Td was found to be the most informative parameter for the distinction between responders and non-responders. The model was also able to reclassify particular patients in early treatment stages. CONCLUSIONS: The results of the model present classification criteria that could indicate whether patients will respond or not to RAI treatment, and provide the opportunity to perform personalized management plans.

Mathematical Modeling of Cancer Immunotherapy and Its Synergy with Radiotherapy.

Combining radiotherapy with immune checkpoint blockade may offer considerable therapeutic impact if the immunosuppressive nature of the tumor microenvironment (TME) can be relieved. In this study, we used mathematical models, which can illustrate the potential synergism between immune checkpoint inhibitors and radiotherapy. A discrete-time pharmacodynamic model of the combination of radiotherapy with inhibitors of the PD1-PDL1 axis and/or the CTLA4 pathway is described. This mathematical framework describes how a growing tumor first elicits and then inhibits an antitumor immune response. This antitumor immune response is described by a primary and a secondary (or memory) response. The primary immune response appears first and is inhibited by the PD1-PDL1 axis, whereas the secondary immune response happens next and is inhibited by the CTLA4 pathway. The effects of irradiation are described by a modified version of the linear-quadratic model. This modeling offers an explanation for the reported biphasic relationship between the size of a tumor and its immunogenicity, as measured by the abscopal effect (an off-target immune response). Furthermore, it explains why discontinuing immunotherapy may result in either tumor recurrence or a durably sustained response. Finally, it describes how synchronizing immunotherapy and radiotherapy can produce synergies. The ability of the model to forecast pharmacodynamic endpoints was validated retrospectively by checking that it could describe data from experimental studies, which investigated the combination of radiotherapy with immune checkpoint inhibitors. In summary, a model such as this could be further used as a simulation tool to facilitate decision making about optimal scheduling of immunotherapy with radiotherapy and perhaps other types of anticancer therapies. Cancer Res; 76(17); 4931-40. ©2016 AACR.