Immunologic response to the survivin-derived multi-epitope vaccine EMD640744 in patients with advanced solid tumors

PURPOSE Survivin is a member of the inhibitor-of-apoptosis family. Essential for tumor cell survival and overexpressed in most cancers, survivin is a promising target for anti-cancer immunotherapy. Immunogenicity has been demonstrated in multiple cancers. Nonetheless, few clinical trials have demonstrated survivin-vaccine-induced immune responses. EXPERIMENTAL DESIGN This phase I trial was conducted to test whether vaccine EMD640744, a cocktail of five HLA class I-binding survivin peptides in Montanide(®) ISA 51 VG, promotes anti-survivin T-cell responses in patients with solid cancers. The primary objective was to compare immunologic efficacy of EMD640744 at doses of 30, 100, and 300 μg. Secondary objectives included safety, tolerability, and clinical efficacy. RESULTS In total, 49 patients who received ≥2 EMD640744 injections with available baseline- and ≥1 post-vaccination samples [immunologic-diagnostic (ID)-intention-to-treat] were analyzed by ELISpot- and peptide/MHC-multimer staining, revealing vaccine-activated peptide-specific T-cell responses in 31 patients (63 %). This cohort included the per study protocol relevant ID population for the primary objective, i.e., T-cell responses by ELISpot in 17 weeks following first vaccination, as well as subjects who discontinued the study before week 17 but showed responses to the treatment. No dose-dependent effects were observed. In the majority of patients (61 %), anti-survivin responses were detected only after vaccination, providing evidence for de novo induction. Best overall tumor response was stable disease (28 %). EMD640744 was well tolerated; local injection-site reactions constituted the most frequent adverse event. CONCLUSIONS Vaccination with EMD640744 elicited T-cell responses against survivin peptides in the majority of patients, demonstrating the immunologic efficacy of EMD640744.

Stratification of high-risk prostate cancer into prognostic categories: a European multi-institutional study

BACKGROUND High-risk prostate cancer (PCa) is an extremely heterogeneous disease. A clear definition of prognostic subgroups is mandatory. OBJECTIVE To develop a pretreatment prognostic model for PCa-specific survival (PCSS) in high-risk PCa based on combinations of unfavorable risk factors. DESIGN, SETTING, AND PARTICIPANTS We conducted a retrospective multicenter cohort study including 1360 consecutive patients with high-risk PCa treated at eight European high-volume centers. INTERVENTION Retropubic radical prostatectomy with pelvic lymphadenectomy. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS Two Cox multivariable regression models were constructed to predict PCSS as a function of dichotomization of clinical stage (< cT3 vs cT3-4), Gleason score (GS) (2-7 vs 8-10), and prostate-specific antigen (PSA; ≤ 20 ng/ml vs > 20 ng/ml). The first "extended" model includes all seven possible combinations; the second "simplified" model includes three subgroups: a good prognosis subgroup (one single high-risk factor); an intermediate prognosis subgroup (PSA >20 ng/ml and stage cT3-4); and a poor prognosis subgroup (GS 8-10 in combination with at least one other high-risk factor). The predictive accuracy of the models was summarized and compared. Survival estimates and clinical and pathologic outcomes were compared between the three subgroups. RESULTS AND LIMITATIONS The simplified model yielded an R(2) of 33% with a 5-yr area under the curve (AUC) of 0.70 with no significant loss of predictive accuracy compared with the extended model (R(2): 34%; AUC: 0.71). The 5- and 10-yr PCSS rates were 98.7% and 95.4%, 96.5% and 88.3%, 88.8% and 79.7%, for the good, intermediate, and poor prognosis subgroups, respectively (p = 0.0003). Overall survival, clinical progression-free survival, and histopathologic outcomes significantly worsened in a stepwise fashion from the good to the poor prognosis subgroups. Limitations of the study are the retrospective design and the long study period. CONCLUSIONS This study presents an intuitive and easy-to-use stratification of high-risk PCa into three prognostic subgroups. The model is useful for counseling and decision making in the pretreatment setting.

Optimization of Schwinger pair production in colliding laser pulses

Recent studies of Schwinger pair production have demonstrated that the asymptotic particle spectrum is extremely sensitive to the applied field profile. We extend the idea of the dynamically assisted Schwinger effect from single pulse profiles to more realistic field configurations to be generated in an all-optical experiment searching for pair creation. We use the quantum kinetic approach to study the particle production and employ a multi-start method, combined with optimal control theory, to determine a set of parameters for which the particle yield in the forward direction in momentum space is maximized. We argue that this strategy can be used to enhance the signal of pair production on a given detector in an experimental setup.

Improved VMAT planning for head and neck tumors with an advanced optimization algorithm

OBJECTIVE In this study, the "Progressive Resolution Optimizer PRO3" (Varian Medical Systems) is compared to the previous version "PRO2" with respect to its potential to improve dose sparing to the organs at risk (OAR) and dose coverage of the PTV for head and neck cancer patients. MATERIALS AND METHODS For eight head and neck cancer patients, volumetric modulated arc therapy (VMAT) treatment plans were generated in this study. All cases have 2-3 phases and the total prescribed dose (PD) was 60-72Gy in the PTV. The study is mainly focused on the phase 1 plans, which all have an identical PD of 54Gy, and complex PTV structures with an overlap to the parotids. Optimization was performed based on planning objectives for the PTV according to ICRU83, and with minimal dose to spinal cord, and parotids outside PTV. In order to assess the quality of the optimization algorithms, an identical set of constraints was used for both, PRO2 and PRO3. The resulting treatment plans were investigated with respect to dose distribution based on the analysis of the dose volume histograms. RESULTS For the phase 1 plans (PD=54Gy) the near maximum dose D2% of the spinal cord, could be minimized to 22±5 Gy with PRO3, as compared to 32±12Gy with PRO2, averaged for all patients. The mean dose to the parotids was also lower in PRO3 plans compared to PRO2, but the differences were less pronounced. A PTV coverage of V95%=97±1% could be reached with PRO3, as compared to 86±5% with PRO2. In clinical routine, these PRO2 plans would require modifications to obtain better PTV coverage at the cost of higher OAR doses. CONCLUSION A comparison between PRO3 and PRO2 optimization algorithms was performed for eight head and neck cancer patients. In general, the quality of VMAT plans for head and neck patients are improved with PRO3 as compared to PRO2. The dose to OARs can be reduced significantly, especially for the spinal cord. These reductions are achieved with better PTV coverage as compared to PRO2. The improved spinal cord sparing offers new opportunities for all types of paraspinal tumors and for re-irradiation of recurrent tumors or second malignancies.

Response profiles of murine spiral ganglion neurons on multi-electrode arrays.

OBJECTIVE Cochlear implants (CIs) have become the gold standard treatment for deafness. These neuroprosthetic devices feature a linear electrode array, surgically inserted into the cochlea, and function by directly stimulating the auditory neurons located within the spiral ganglion, bypassing lost or not-functioning hair cells. Despite their success, some limitations still remain, including poor frequency resolution and high-energy consumption. In both cases, the anatomical gap between the electrode array and the spiral ganglion neurons (SGNs) is believed to be an important limiting factor. The final goal of the study is to characterize response profiles of SGNs growing in intimate contact with an electrode array, in view of designing novel CI devices and stimulation protocols, featuring a gapless interface with auditory neurons. APPROACH We have characterized SGN responses to extracellular stimulation using multi-electrode arrays (MEAs). This setup allows, in our view, to optimize in vitro many of the limiting interface aspects between CIs and SGNs. MAIN RESULTS Early postnatal mouse SGN explants were analyzed after 6-18 days in culture. Different stimulation protocols were compared with the aim to lower the stimulation threshold and the energy needed to elicit a response. In the best case, a four-fold reduction of the energy was obtained by lengthening the biphasic stimulus from 40 μs to 160 μs. Similarly, quasi monophasic pulses were more effective than biphasic pulses and the insertion of an interphase gap moderately improved efficiency. Finally, the stimulation with an external electrode mounted on a micromanipulator showed that the energy needed to elicit a response could be reduced by a factor of five with decreasing its distance from 40 μm to 0 μm from the auditory neurons. SIGNIFICANCE This study is the first to show electrical activity of SGNs on MEAs. Our findings may help to improve stimulation by and to reduce energy consumption of CIs and thereby contribute to the development of fully implantable devices with better auditory resolution in the future.

Differentiating the Multipoint Expected Improvement for Optimal Batch Design

This work deals with parallel optimization of expensive objective functions which are modelled as sample realizations of Gaussian processes. The study is formalized as a Bayesian optimization problem, or continuous multi-armed bandit problem, where a batch of q > 0 arms is pulled in parallel at each iteration. Several algorithms have been developed for choosing batches by trading off exploitation and exploration. As of today, the maximum Expected Improvement (EI) and Upper Confidence Bound (UCB) selection rules appear as the most prominent approaches for batch selection. Here, we build upon recent work on the multipoint Expected Improvement criterion, for which an analytic expansion relying on Tallis’ formula was recently established. The computational burden of this selection rule being still an issue in application, we derive a closed-form expression for the gradient of the multipoint Expected Improvement, which aims at facilitating its maximization using gradient-based ascent algorithms. Substantial computational savings are shown in application. In addition, our algorithms are tested numerically and compared to state-of-the-art UCB-based batchsequential algorithms. Combining starting designs relying on UCB with gradient-based EI local optimization finally appears as a sound option for batch design in distributed Gaussian Process optimization.