BackgroundLenvatinib combined with programmed cell death protein-1 (PD-1) inhibitors has resulted in good survival outcomes in the treatment of unresectable hepatocellular carcinoma (HCC). Hepatic artery infusion chemotherapy (HAIC) has also attracted attention due to its high response rates and favorable survival for advanced HCC patients. The present study aimed to compare the efficacy of HAIC combined with PD-1 inhibitors plus lenvatinib (HPL) and PD-1 inhibitors plus lenvatinib (PL) in patients with advanced HCC.MethodsBetween July 2018 and December 2019, patients diagnosed with advanced HCC who initially received HPL or PL treatment were reviewed for eligibility. Efficacy was evaluated according to tumor response and survival.ResultsIn total, 70 patients met the criteria and were included in the present study, and they were divided into the HPL group (n = 45) and PL group (n = 25). The overall response rate (40.0 vs. 16.0%, respectively; p = 0.038) and disease control rate (77.6 vs. 44.0%, respectively; p < 0.001) were higher in the HPL group than in the PL group. The median overall survival was 15.9 months in the HPL group and 8.6 months in the PL group (p = 0.0015; HR = 0.6; 95% CI 0.43–0.83). The median progression-free survival was 8.8 months in the HPL group and 5.4 months in the PL group (p = 0.0320; HR = 0.74; 95% CI 0.55–0.98).ConclusionCompared to PL, HPL was associated with a significantly better treatment response and survival benefits for patients with advanced HCC.
We investigate a distributed caching strategy based on multi-agent reinforcement learning (MARL) in a cache-aided network, where all wireless nodes have limited storage capacity and serve for certain coverage. The wireless nodes can collaboratively optimize distributed caching strategy to maximize the network performance measured by the average cache hit probability. Specifically, we firstly model the distributed caching strategy problem as a fully cooperative repeated game and then analyze how to improve the average cache hit probability under the MARL framework. We further propose the caching strategy based on the frequency maximum Q-value (FMQ) and the caching strategy based on the distributed Q-learning (DQ) to optimize the distributed caching strategy. The simulation results show that the proposed FMQ-based strategy significantly improves the average cache hit probability, while the proposed DQ-based strategy can converge to the optimal strategy with probability one. Moreover, the proposed FMQ-based and DQ-based strategies are not only superior to Q-learning based strategy but also superior to the probabilistic caching placement (PCP) and most popular content (MPC) strategies.INDEX TERMS Multi-agent reinforcement learning, distributed cache placement, cache hit probability, frequency maximum Q-value, distributed Q-learning.
Background Long non-coding RNAs (lncRNA) have an essential role in progression and chemoresistance of hepatocellular carcinoma (HCC). In-depth study of specific regulatory mechanisms is of great value in providing potential therapeutic targets. The present study aimed to explore the regulatory functions and mechanisms of lncRNA TINCR in HCC progression and oxaliplatin response. Methods The expression of TINCR in HCC tissues and cell lines was detected by quantitative reverse transcription PCR (qRT-PCR). Cell proliferation, migration, invasion, and chemosensitivity were evaluated by cell counting kit 8 (CCK8), colony formation, transwell, and apoptosis assays. Luciferase reporter assays and RNA pulldown were used to identify the interaction between TINCR and ST6 beta-galactoside alpha-2,6-sialyltransferase 1 (ST6GAL1) via miR-195-3p. The corresponding functions were verified in the complementation test and in vivo animal experiment. Results TINCR was upregulated in HCC and associated with poor patient prognosis. Silencing TINCR inhibited HCC proliferation, migration, invasion, and oxaliplatin resistance while overexpressing TINCR showed opposite above-mentioned functions. Mechanistically, TINCR acted as a competing endogenous (ceRNA) to sponge miR-195-3p, relieving its repression on ST6GAL1, and activated nuclear factor kappa B (NF-κB) signaling. The mouse xenograft experiment further verified that knockdown TINCR attenuated tumor progression and oxaliplatin resistance in vivo. Conclusions Our finding indicated that there existed a TINCR/miR-195-3p/ST6GAL1/NF-κB signaling regulatory axis that regulated tumor progression and oxaliplatin resistance, which might be exploited for anticancer therapy in HCC.
Cancer immunotherapy restores or enhances the effector function of T cells in the tumor microenvironment, but the efficacy of immunotherapy has been hindered by therapeutic resistance. Here, we identify the proto-oncogene serine/threonine protein kinase PIM2 as a novel negative feedback regulator of IFN-γ-elicited tumor inflammation, thus endowing cancer cells with aggressive features. Mechanistically, interleukin-1β (IL-1β) derived from IFN-γ-polarized tumor macrophages triggered PIM2 expression in cancer cells via the p38 MAPK/Erk and NF-κB signaling pathways. PIM2+ cancer cells generated by proinflammatory macrophages acquired the capability to survive, metastasize, and resist T-cell cytotoxicity and immunotherapy. A therapeutic strategy combining immune checkpoint blockade with IL-1β blockade or PIM2 kinase inhibition in vivo effectively and successfully elicited tumor regression. These results provide insight into the regulatory and functional features of PIM2+ tumors and suggest that strategies to influence the functional activities of inflammatory cells or PIM2 kinase may improve the efficacy of immunotherapy.
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