Proximity-dependent pollen performance in Silene vulgaris.

BACKGROUND AND AIMS: Pollen and seed dispersal in herbaceous insect-pollinated plants are often restricted, inducing strong population structure. To what extent this influences mating within and among patches is poorly understood. This study investigates the influence of population structure on pollen performance using controlled pollinations and genetic markers. METHODS: Population structure was investigated in a patchily distributed population of gynodioecious Silene vulgaris in Switzerland using polymorphic microsatellite markers. Experimental pollinations were performed on 21 hermaphrodite recipients using pollen donors at three spatial scales: (a) self-pollination; (b) within-patch cross-pollinations; and (c) between-patch cross-pollinations. Pollen performance was then compared with respect to crossing distance. KEY RESULTS: The population of S. vulgaris was characterized by a high degree of genetic sub-structure, with neighbouring plants more related to one another than to distant individuals. Inbreeding probably results from both selfing and biparental inbreeding. Pollen performance increased with distance between mates. Between-patch pollen performed significantly better than both self- and within-patch pollen donors. However, no significant difference was detected between self- and within-patch pollen donors. CONCLUSIONS: The results suggest that population structure in animal-pollinated plants is likely to influence mating patterns by favouring cross-pollinations between unrelated plants. However, the extent to which this mechanism could be effective as a pre-zygotic barrier preventing inbred mating depends on the patterns of pollinator foraging and their influence on pollen dispersal.

Pharmacokinetics and safety of panobacumab: specific adjunctive immunotherapy in critical patients with nosocomial Pseudomonas aeruginosa O11 pneumonia.

Objectives Nosocomial Pseudomonas aeruginosa pneumonia remains a major concern in critically ill patients. We explored the potential impact of microorganism-targeted adjunctive immunotherapy in such patients. Patients and methods This multicentre, open pilot Phase 2a clinical trial (NCT00851435) prospectively evaluated the safety, pharmacokinetics and potential efficacy of three doses of 1.2 mg/kg panobacumab, a fully human monoclonal anti-lipopolysaccharide IgM, given every 72 h in 18 patients developing nosocomial P. aeruginosa (serotype O11) pneumonia. Results Seventeen out of 18 patients were included in the pharmacokinetic analysis. In 13 patients receiving three doses, the maximal concentration after the third infusion was 33.9 ± 8.0 μg/mL, total area under the serum concentration-time curve was 5397 ± 1993 μg h/mL and elimination half-life was 102.3 ± 47.8 h. Panobacumab was well tolerated, induced no immunogenicity and was detected in respiratory samples. In contrast to Acute Physiology and Chronic Health Evaluation II (APACHE II) prediction, all 13 patients receiving three doses survived, with a mean clinical resolution in 9.0 ± 2.7 days. Two patients suffered a recurrence at days 17 and 20. Conclusions These data suggest that panobacumab is safe, with a pharmacokinetic profile similar to that in healthy volunteers. It was associated with high clinical cure and survival rates in patients developing nosocomial P. aeruginosa O11 pneumonia. We concluded that these promising results warrant further trials.

Assessment of panobacumab as adjunctive immunotherapy for the treatment of nosocomial Pseudomonas aeruginosa pneumonia.

The fully human anti-lipopolysaccharide (LPS) immunoglobulin M (IgM) monoclonal antibody panobacumab was developed as an adjunctive immunotherapy for the treatment of O11 serotype Pseudomonas aeruginosa infections. We evaluated the potential clinical efficacy of panobacumab in the treatment of nosocomial pneumonia. We performed a post-hoc analysis of a multicenter phase IIa trial (NCT00851435) designed to prospectively evaluate the safety and pharmacokinetics of panobacumab. Patients treated with panobacumab (n = 17), including 13 patients receiving the full treatment (three doses of 1.2 mg/kg), were compared to 14 patients who did not receive the antibody. Overall, the 17 patients receiving panobacumab were more ill. They were an average of 72 years old [interquartile range (IQR): 64-79] versus an average of 50 years old (IQR: 30-73) (p = 0.024) and had Acute Physiology and Chronic Health Evaluation II (APACHE II) scores of 17 (IQR: 16-22) versus 15 (IQR: 10-19) (p = 0.043). Adjunctive immunotherapy resulted in an improved clinical outcome in the group receiving the full three-course panobacumab treatment, with a resolution rate of 85 % (11/13) versus 64 % (9/14) (p = 0.048). The Kaplan-Meier survival curve showed a statistically significantly shorter time to clinical resolution in this group of patients (8.0 [IQR: 7.0-11.5] versus 18.5 [IQR: 8-30] days in those who did not receive the antibody; p = 0.004). Panobacumab adjunctive immunotherapy may improve clinical outcome in a shorter time if patients receive the full treatment (three doses). These preliminary results suggest that passive immunotherapy targeting LPS may be a complementary strategy for the treatment of nosocomial O11 P. aeruginosa pneumonia.

Potential approaches for more successful dendritic cell-based immunotherapy.

INTRODUCTION: Dendritic cells (DCs) are the most important antigen-presenting cell population for activating antitumor T-cell responses; therefore, they offer a unique opportunity for specific targeting of tumors. AREAS COVERED: We will discuss the critical factors for the enhancement of DC vaccine efficacy: different DC subsets, types of in vitro DC manufacturing protocol, types of tumor antigen to be loaded and finally different adjuvants for activating them. We will cover potential combinatorial strategies with immunomodulatory therapies: depleting T-regulatory (Treg) cells, blocking VEGF and blocking inhibitory signals. Furthermore, recommendations to incorporate these criteria into DC-based tumor immunotherapy will be suggested. EXPERT OPINION: Monocyte-derived DCs are the most widely used DC subset in the clinic, whereas Langerhans cells and plasmacytoid DCs are two emerging DC subsets that are highly effective in eliciting cytotoxic T lymphocyte responses. Depending on the type of tumor antigens selected for loading DCs, it is important to optimize a protocol that will generate highly potent DCs. The future aim of DC-based immunotherapy is to combine it with one or more immunomodulatory therapies, for example, Treg cell depletion, VEGF blockage and T-cell checkpoint blockage, to elicit the most optimal antitumor immunity to induce long-term remission or even cure cancer patients.

Targeting the undruggable: immunotherapy meets personalized oncology in the genomic era.

Owing to recent advances in genomic technologies, personalized oncology is poised to fundamentally alter cancer therapy. In this paradigm, the mutational and transcriptional profiles of tumors are assessed, and personalized treatments are designed based on the specific molecular abnormalities relevant to each patient's cancer. To date, such approaches have yielded impressive clinical responses in some patients. However, a major limitation of this strategy has also been revealed: the vast majority of tumor mutations are not targetable by current pharmacological approaches. Immunotherapy offers a promising alternative to exploit tumor mutations as targets for clinical intervention. Mutated proteins can give rise to novel antigens (called neoantigens) that are recognized with high specificity by patient T cells. Indeed, neoantigen-specific T cells have been shown to underlie clinical responses to many standard treatments and immunotherapeutic interventions. Moreover, studies in mouse models targeting neoantigens, and early results from clinical trials, have established proof of concept for personalized immunotherapies targeting next-generation sequencing identified neoantigens. Here, we review basic immunological principles related to T-cell recognition of neoantigens, and we examine recent studies that use genomic data to design personalized immunotherapies. We discuss the opportunities and challenges that lie ahead on the road to improving patient outcomes by incorporating immunotherapy into the paradigm of personalized oncology.

Personalized approaches to active immunotherapy in cancer

Immunotherapy is emerging as a promising anti-cancer curative modality. However, in contrast to recent advances obtained employing checkpoint blockade agents and T cell therapies, clinical efficacy of therapeutic cancer vaccines is still limited. Most vaccination attempts in the clinic represent "off-the shelf" approaches since they target common "self" tumor antigens, shared among different patients. In contrast, personalized approaches of vaccination are tailor-made for each patient and in spite being laborious, hold great potential. Recent technical advancement enabled the first steps in the clinic of personalized vaccines that target patient-specific mutated neo-antigens. Such vaccines could induce enhanced tumor-specific immune response since neo-antigens are mutation-derived antigens that can be recognized by high affinity T cells, not limited by central tolerance. Alternatively, the use of personalized vaccines based on whole autologous tumor cells, overcome the need for the identification of specific tumor antigens. Whole autologous tumor cells could be administered alone, pulsed on dendritic cells as lysate, DNA, RNA or delivered to dendritic cells in-vivo through encapsulation in nanoparticle vehicles. Such vaccines may provide a source for the full repertoire of the patient-specific tumor antigens, including its private neo-antigens. Furthermore, combining next-generation personalized vaccination with other immunotherapy modalities might be the key for achieving significant therapeutic outcome.