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| 1 | A homologous and molecular dual-targeted biomimetic nanocarrier for EGFR-related non-small cell lung cancer therapy显示文摘The abnormal activation of epidermal growth factor receptor(EGFR)drives the development of non-small cell lung cancer(NSCLC).The EGFR-targeting tyrosine kinase inhibitor osimertinib is frequently used to clinically treat NSCLC and exhibits marked efficacy in patients with NSCLC who have an EGFR mutation.However,free osimertinib administration exhibits an inadequate response in vivo,with only~3%patients demonstrating a complete clinical response.Consequently,we designed a biomimetic nanoparticle(CMNP^(@Osi))comprising a polymeric nanoparticle core and tumor cell-derived membrane-coated shell that combines membrane-mediated homologous and molecular targeting for targeted drug delivery,thereby supporting a dual-target strategy for enhancing osimertinib efficacy.After intravenous injection,CMNP^(@Osi)accumulates at tumor sites and displays enhanced uptake into cancer cells based on homologous targeting.Osimertinib is subsequently released into the cytoplasm,where it suppresses the phosphorylation of upstream EGFR and the downstream AKT signaling pathway and inhibits the proliferation of NSCLC cells.Thus,this dual-targeting strategy using a biomimetic nanocarrier can enhance molecular-targeted drug delivery and improve clinical efficacy. | Bin Xu Fanjun Zeng Jialong Deng Lintong Yao Shengbo Liu Hengliang Hou Yucheng Huang Hongyuan Zhu Shaowei Wu Qiaxuan Li Weijie Zhan Hongrui Qiu Huili Wang Yundong Li Xianzhu Yang Ziyang Cao Yu Zhang Haiyu Zhou | 2023 | Bioactive Materials2023，，9： | 1 |
| 2 | MiR-516a-3p is a Novel Mediator of Hepatocellular Carcinoma Oncogenic Activity and Cellular Metabolism显示文摘Hepatocellular carcinoma(HCC)remains one of the most lethal malignancies.We previously demonstrated that the chromosome 19 microRNA cluster(C19MC)was associated with tumor burden and prognosis in patients with HCC.In the current study,we aim to explore the role of miR-516a-3p-an identical mature microRNA(miRNA)co-spliced by four oncogenic pre-miRNAs of C19MC(i.e.,mir-516a-1,mir-516a-2,mir-516b-1,and mir-516b-2)-in HCC.In our cohort of HCC patients,miR-516a-3p was highly expressed in HCC tissues in comparison with adjacent non-tumor tissues.High expression of tumor miR-516a-3p significantly correlated with advanced tumor stages,distinguished high HCC recurrence and mortality,and independently predicted poor prognosis.We further found that miR-516a-3p enhanced the proliferation,migration,and invasiveness of HCC cells in vitro and promoted tumor growth and metastasis in vivo.Among cancer cells,miR-516a-3p could be delivered via exosomes or extracellular vesicles and increased the oncogenic activity of recipient cells.Moreover,we performed comprehensive transcriptomics,proteomics,and metabolomics analysis on the potential mechanism underlying miR-516a-3p-promoted oncogenicity.MixOmic DIABLO analysis showed a close correlation and strong cluster consistency between the proteomics and metabolomics datasets.We further confirmed six proteins(i.e.,LMBR1,CHST9,RBM3,SLC7A6,PTGFRN,and NOL12)as the direct targets of miR-516a-3p and as central players in miR-516a-3p-mediated metabolism regulation.The integrated multi-omics and co-enriched pathway analysis showed that miR-516a-3p regulates the metabolic pathways of HCC cells,particularly purine and pyrimidine metabolism.In conclusion,our findings suggest that miR-516a-3p promotes malignant behaviors in HCC cells by regulating cellular metabolism and affecting neighboring cells via the exosome delivery system.Thus,we suggest miR-516a-3p as a novel molecular target for HCC therapy. | Tao Rui Xueyou Zhang Shi Feng Haitao Huang Shaowei Zhan Haiyang Xie Lin Zhou Shusen Zheng Qi Ling | 2022 | Engineering2022，，9： | 0 |
| 3 | LINDA:multi-agent local information decomposition for awareness of teammates显示文摘In cooperative multi-agent reinforcement learning(MARL),where agents only have access to partial observations,efficiently leveraging local information is critical.During long-time observations,agents can build awareness for teammates to alleviate the restriction of partial observability.However,previous MARL methods usually neglect awareness learning from local information for better collaboration.To address this problem,we propose a novel framework,multi-agent local information decomposition for awareness of teammates(LINDA),with which agents learn to decompose local information and build awareness for each teammate.We model the awareness as stochastic random variables and perform representation learning to ensure the informativeness of awareness representations by maximizing the mutual information between awareness and the actual trajectory of the corresponding agent.LINDA is agnostic to specific algorithms and can be flexibly integrated with different MARL methods.Sufficient experiments show that the proposed framework learns informative awareness from local partial observations for better collaboration and significantly improves the learning performance,especially on challenging tasks. | Jiahan CAO Lei YUAN Jianhao WANG Shaowei ZHANG Chongjie ZHANG Yang YU De-Chuan ZHAN | 2023 | Science China(Information Sciences)2023，66，8： | 0 |
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