乳腺癌
医学
仿形(计算机编程)
肿瘤科
癌症研究
计算生物学
内科学
生物信息学
癌症
基因表达谱
疾病
作者
Ying Xu,Xin-Yi Liu,Hang Zhang,Li Jia Chen,Han Wang,Zhi-Ming Shao,Yi Xiao,Yi-Zhou Jiang
标识
DOI:10.1016/j.xcrm.2026.102659
摘要
The treatment of triple-negative breast cancer (TNBC) poses significant challenges, necessitating innovative approaches to identify therapeutic targets. This study presents a cohort of patients with early-stage TNBC receiving neoadjuvant chemotherapy or chemo-immunotherapy, leveraging single-cell RNA sequencing and metabolic analysis to elucidate the impact of metabolic reprogramming on treatment response. Our findings reveal metabolic heterogeneity at levels of metabolic genes, pathways, and fluxes. Cell-type-specific metabolic traits show stronger associations with therapeutic response compared with bulk metabolic features and the proportion of major cell types. We identify a dynamic collaboration between tumor cells and myeloid cells driven by differential glucose utilization and lactate production, which facilitates tumor progression. Monocarboxylate transporter 1 (MCT1) inhibitors disrupt their interaction, enhancing the efficacy of anti-PD-1 and antibody-drug conjugate (ADC) treatments in TNBC mouse models. Overall, our study delineates the single-cell metabolic landscape of TNBC and positions MCT1 as a promising target.
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