C Tavares Ludgero, Amorim Ricardo, Teixeira José, Oliveira Paulo J, Carvalho Rui A
CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal.; CIBB - Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal; CIVG - Vasco da Gama Research Center, University School Vasco da Gama - EUVG, 3020-210 Coimbra, Portugal.
CNC-UC, Center for Neuroscience and Cell Biology, University of Coimbra, Portugal.; CIBB - Centre for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal; PDBEB - Doctoral Programme in Experimental Biology and Biomedicine, Institute of Interdisciplinary Research, University of Coimbra, Portugal; CIQUP/Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, Porto, Portugal.
Biochim Biophys Acta Mol Basis Dis. 2025 Oct;1871(7):167949. doi: 10.1016/j.bbadis.2025.167949. Epub 2025 Jun 6.
The metabolic remodeling occurring in carcinogenesis cells is firmly established. However, to understand the connection between the cellular metabolic profile and carcinogenesis, an accurate measurement of metabolic fluxes is required. In order to quantify the fluxes in these metabolic pathways, stable isotope tracers and nuclear magnetic resonance (NMR) techniques were employed. For that purpose, two human non-small lung cancer cell lines (A549 and H1299) were used. For the quantification of carbon intermediary metabolism cells were grown in C labelled glucose while for de novo lipogenesis (DNL) assessment HO was supplemented to the culture media. To better understand and characterize cellular bioenergetics, mitochondrial membrane potential, oxygen consumption, and energy charge were also assessed. Finally, to establish a bridge between metabolic fluxes and cancer proliferation, substrate dependency studies were performed. Several metabolic inhibitors were also tested, targeting glycolysis, TCA cycle, pentose phosphate pathway (PPP) and transaminases. Our results showed the occurrence of metabolic heterogeneity between the two non-small lung cancer cell lines: H1299 exhibited a relatively active TCA cycle, while A549 showed a more glycolytic phenotype. The overall mitochondrial bioenergetic parameters were in agreement with the metabolic profiles. The mitochondrial network was polarized and active in all cell lines, although the H1299 cell line exhibited higher basal oxygen consumption and spare respiratory capacity. Nonetheless, DNL rate did not differ in H1299 and A549 lung cancer cell lines. Additionally, α-ketoglutarate availability was proven a key determinant for H1299 non-small cell lung cancer cells survival and proliferation. In conclusion, this work revealed that cells derived from a lymph node metastasis (H1299) have a more active TCA cycle and altered oxidative stress levels when compared to cells derived from a primary tumor (A549). In the process, we successfully implemented a new H enrichment method for DNL assessment for the first time in in vitro cancer research.
致癌细胞中发生的代谢重塑已得到确凿证实。然而，为了理解细胞代谢谱与致癌作用之间的联系，需要准确测量代谢通量。为了量化这些代谢途径中的通量，采用了稳定同位素示踪剂和核磁共振（NMR）技术。为此，使用了两种人非小细胞肺癌细胞系（A549和H1299）。为了量化碳中间代谢，细胞在含碳标记葡萄糖的培养基中培养，而对于从头脂肪生成（DNL）评估，向培养基中添加了HO。为了更好地理解和表征细胞生物能量学，还评估了线粒体膜电位、耗氧量和能量电荷。最后，为了在代谢通量与癌症增殖之间建立联系，进行了底物依赖性研究。还测试了几种代谢抑制剂，它们分别作用于糖酵解、三羧酸循环（TCA）、磷酸戊糖途径（PPP）和转氨酶。我们的结果显示，两种非小细胞肺癌细胞系之间存在代谢异质性：H1299表现出相对活跃的TCA循环，而A549表现出更具糖酵解特征的表型。总体线粒体生物能量学参数与代谢谱一致。尽管H1299细胞系表现出更高的基础耗氧量和备用呼吸能力，但所有细胞系中的线粒体网络均呈极化且活跃状态。尽管如此，H1299和A549肺癌细胞系中的DNL速率并无差异。此外，已证明α-酮戊二酸的可用性是H1299非小细胞肺癌细胞存活和增殖的关键决定因素。总之，这项工作表明，与源自原发性肿瘤的细胞（A549）相比，源自淋巴结转移的细胞（H1299）具有更活跃的TCA循环和改变的氧化应激水平。在此过程中，我们首次在体外癌症研究中成功实施了一种用于DNL评估的新的H富集方法。
