申请人以肿瘤代谢紊乱为研究主线：1) 率先发现糖异生代谢酶与低氧诱导因子之间的反馈调节环路，揭示了低氧调控的糖代谢紊乱促进肿瘤发生的新机理 (Nature; Development)；2) 首次阐明谷氨酰胺缺乏导致细胞凋亡的分子机制，为干扰肿瘤代谢的治疗方法提供了新靶点 (Cancer Cell)；3) 首次报道了肿瘤脂代谢产生的微泡促进正常细胞恶性转变的新功能，证实阻断微泡生成是抑制肿瘤生长的有效手段 (PNAS 两篇; Oncogene)。以上研究系统阐述了代谢紊乱在肿瘤进展中的关键作用，不仅为现有的肿瘤形成理论增添了新的科学内容，而且为抗癌药物的研发提供了重要靶点。已发表（共同）第一/通讯作者论文9篇，篇均影响因子12.8；总他引348次，最高单篇他引96次。拟进一步探索糖异生代谢参与肿瘤进展的分子机制，应用动物模型研究糖异生下调对肿瘤形成的推动作用，并在代谢网络中鉴定肿瘤标志物。

The research work of the applicant has been mainly focused on tumor-associated metabolic disorders, which 1) discovered the feedback loop between gluconeogenic enzymes and hypoxia-inducible factors, and revealed a novel mechanism underlying hypoxia-mediated reprogramming of glucose metabolism during tumor initiation (Nature; Development); 2) dissected the molecular pathways whereby glutamine deprivation induces cell apoptosis, and provided novel targets for therapeutic intervention with tumor-specific metabolism (Cancer Cell); 3) reported that tumor-associated microvesicles generated via lipid metabolism are capable of inducing the oncogenic transformation of normal cells, and demonstrated that inhibition of macrovesicle biogenesis is an effective approach to suppress tumor growth (PNAS [two articles]; Oncogene). In summary, the aforementioned research systematically elucidated the key role of metabolic reprogramming in tumor progression. It not only added new scientific materials to the current theory of tumor formation, but also provided essential drug targets for the development of anti-cancer therapeutics. The applicant has published totally nine articles in scientific journals as the (co-) first or corresponding author, and the average impact factor of these journals is 12.8. All the publications from the applicant have been cited for 348 times by other researchers, and the highest citation number among them is 96. This proposal will continue to investigate the molecular details of gluconeogenesis-mediated cancer progression; to elucidate the tumor-promoting effect of inhibiting gluconeogenesis using animal model; and to identify tumor markers from the metabolic network.