Computational Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Physiology, Biophysics and Systems Biology Graduate Program, Weill Cornell Medicine, New York, NY, USA.
Computational Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA; Biochemistry, Structural Biology, Cell Biology, Developmental Biology and Molecular Biology Graduate Program, Weill Cornell Medicine, New York, NY, USA.
Cell Metab. 2023 Aug 8;35(8):1424-1440.e5. doi: 10.1016/j.cmet.2023.06.005. Epub 2023 Jul 5.
Tumor cell phenotypes and anti-tumor immune responses are shaped by local metabolite availability, but intratumoral metabolite heterogeneity (IMH) and its phenotypic consequences remain poorly understood. To study IMH, we profiled tumor/normal regions from clear cell renal cell carcinoma (ccRCC) patients. A common pattern of IMH transcended all patients, characterized by correlated fluctuations in the abundance of metabolites and processes associated with ferroptosis. Analysis of intratumoral metabolite-RNA covariation revealed that the immune composition of the microenvironment, especially the abundance of myeloid cells, drove intratumoral metabolite variation. Motivated by the strength of RNA-metabolite covariation and the clinical significance of RNA biomarkers in ccRCC, we inferred metabolomic profiles from the RNA sequencing data of ccRCC patients enrolled in 7 clinical trials, and we ultimately identifyied metabolite biomarkers associated with response to anti-angiogenic agents. Local metabolic phenotypes, therefore, emerge in tandem with the immune microenvironment, influence ongoing tumor evolution, and are associated with therapeutic sensitivity.
肿瘤细胞表型和抗肿瘤免疫反应受局部代谢物可用性的影响,但肿瘤内代谢物异质性(IMH)及其表型后果仍知之甚少。为了研究 IMH,我们对透明细胞肾细胞癌(ccRCC)患者的肿瘤/正常区域进行了分析。一种常见的 IMH 模式超越了所有患者,其特征是与铁死亡相关的代谢物丰度和相关过程的相关性波动。对肿瘤内代谢物-RNA 共变的分析表明,微环境的免疫组成,特别是髓样细胞的丰度,驱动了肿瘤内代谢物的变化。受 RNA-代谢物共变强度和 RNA 生物标志物在 ccRCC 中临床意义的启发,我们从 7 项临床试验中纳入的 ccRCC 患者的 RNA 测序数据中推断出代谢组学图谱,最终确定了与抗血管生成药物反应相关的代谢物生物标志物。因此,局部代谢表型与免疫微环境同时出现,影响肿瘤的持续进化,并与治疗敏感性相关。