1. Academic Validation
  2. Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

  • Cell Res. 2022 May;32(5):477-490. doi: 10.1038/s41422-022-00614-0.
Yi Xiao  # 1 Ding Ma  # 1 Yun-Song Yang  # 1 2 Fan Yang  # 1 Jia-Han Ding 1 Yue Gong 1 Lin Jiang 1 Li-Ping Ge 1 Song-Yang Wu 1 Qiang Yu 1 Qing Zhang 3 François Bertucci 4 Qiuzhuang Sun 5 Xin Hu 1 Da-Qiang Li 1 Zhi-Ming Shao 6 Yi-Zhou Jiang 7
Affiliations

Affiliations

  • 1 Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
  • 2 Human Phenome Institute, Fudan University, Shanghai, China.
  • 3 Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • 4 Predictive Oncology team, Centre de Recherche en Cancérologie de Marseille (CRCM), INSERM UMR1068, CNRS UMR725, Aix-Marseille Université, Institut Paoli-Calmettes, Marseille, France.
  • 5 Department of Industrial Systems Engineering and Management, National University of Singapore, Singapore, Singapore.
  • 6 Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. [email protected].
  • 7 Key Laboratory of Breast Cancer in Shanghai, Department of Breast Surgery, Fudan University Shanghai Cancer Center; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China. [email protected].
  • # Contributed equally.
Abstract

Metabolic reprogramming is a hallmark of Cancer. However, systematic characterizations of metabolites in triple-negative breast Cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal Androgen Receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.

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