9 research outputs found

    31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

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    Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

    The relative value of Pre-Implementation stages for successful implementation of evidence-informed programs

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    Abstract Background Most implementations fail before the corresponding services are ever delivered. Measuring implementation process fidelity may reveal when and why these attempts fail. This knowledge is necessary to support the achievement of positive implementation milestones, such as delivering services to clients (program start-up) and competency in treatment delivery. The present study evaluates the extent to which implementation process fidelity at different implementation stages predicts achievement of those milestones. Methods Implementation process fidelity data—as measured by the Stages of Implementation Completion (SIC)—from 1287 implementing sites across 27 evidence-informed programs were examined in mixed effects regression models with sites nested within programs. Implementation process fidelity, as measured by the proportion of implementation activities completed during the three stages of the SIC Pre-Implementation phase and overall Pre-Implementation (Phase 1) and Implementation (Phase 2) proportion scores, was assessed as a predictor of sites achieving program start-up (i.e., delivering services) and competency in program delivery. Results The predicted probability of start-up across all sites was low at 35% (95% CI [33%, 38%]). When considering the evidence-informed program being implemented, that probability was nearly twice as high (64%; 95% CI [42%, 82%]), and 57% of the total variance in program start-up was attributable to the program. Implementation process fidelity was positively and significantly associated with achievement of program start-up and competency. The magnitude of this relationship varied significantly across programs for Pre-Implementation Stage 1 (i.e., Engagement) only. Compared to other stages, completing more Pre-Implementation Stage 3 (Readiness Planning) activities resulted in the most rapid gains in probability of achieving program start-up. The predicted probability of achieving competency was very low unless sites had high scores in both Pre-Implementation and Implementation phases. Conclusions Strong implementation process fidelity—as measured by SIC Pre-Implementation and Implementation phase proportion scores—was associated with sites’ achievement of program start-up and competency in program delivery, with early implementation process fidelity being especially potent. These findings highlight the importance of a rigorous Pre-Implementation process

    Age estimation via face images: a survey

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