58 research outputs found

    View Vertically: A Hierarchical Network for Trajectory Prediction via Fourier Spectrums

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    Understanding and forecasting future trajectories of agents are critical for behavior analysis, robot navigation, autonomous cars, and other related applications. Previous methods mostly treat trajectory prediction as time sequence generation. Different from them, this work studies agents' trajectories in a "vertical" view, i.e., modeling and forecasting trajectories from the spectral domain. Different frequency bands in the trajectory spectrums could hierarchically reflect agents' motion preferences at different scales. The low-frequency and high-frequency portions could represent their coarse motion trends and fine motion variations, respectively. Accordingly, we propose a hierarchical network V2^2-Net, which contains two sub-networks, to hierarchically model and predict agents' trajectories with trajectory spectrums. The coarse-level keypoints estimation sub-network first predicts the "minimal" spectrums of agents' trajectories on several "key" frequency portions. Then the fine-level spectrum interpolation sub-network interpolates the spectrums to reconstruct the final predictions. Experimental results display the competitiveness and superiority of V2^2-Net on both ETH-UCY benchmark and the Stanford Drone Dataset.Comment: Accepted to ECCV 202

    CUL4A overexpression enhances lung tumor growth and sensitizes lung cancer cells to Erlotinib via transcriptional regulation of EGFR

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    BackgroundCUL4A has been proposed as oncogene in several types of human cancer, but its clinical significance and functional role in human non-small cell lung cancer (NSCLC) remain unclear.MethodsExpression level of CUL4A was examined by RT-PCR and Western blot. Forced expression of CUL4A was mediated by retroviruses, and CUL4A silencing by shRNAs expressing lentiviruses. Growth capacity of lung cancer cells was measured by MTT in vitro and tumorigenesis in vivo, respectively.ResultsWe found that CUL4A was highly expressed in human lung cancer tissues and lung cancer cell lines, and this elevated expression positively correlated with disease progression and prognosis. Overexpression of CUL4A in human lung cancer cell lines increased cell proliferation, inhibited apoptosis, and subsequently conferred resistance to chemotherapy. On other hand, silencing CUL4A expression in NSCLC cells reduced proliferation, promoted apoptosis and resulted in tumor growth inhibition in cancer xenograft model. Mechanistically, we revealed CUL4A regulated EGFR transcriptional expression and activation, and subsequently activated AKT. Targeted inhibition of EGFR activity blocked these CUL4A induced oncogenic activities.ConclusionsOur results highlight the significance of CUL4A in NSCLC and suggest that CUL4A could be a promising therapy target and a potential biomarker for prognosis and EGFR target therapy in NSCLC patients

    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
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