1. Academic Validation
  2. Prognostic value of amino acid metabolism-related gene expression in invasive breast carcinoma

Prognostic value of amino acid metabolism-related gene expression in invasive breast carcinoma

  • J Cancer Res Clin Oncol. 2023 Jun 21. doi: 10.1007/s00432-023-04985-8.
Zilin Wang # 1 Xinyu Guo # 1 Jingge Lian 1 Ying Ji 1 Kangan Li 2
Affiliations

Affiliations

  • 1 Department of Radiology, School of Medicine, Shanghai General Hospital, Shanghai Jiaotong University, No. 650 New Songjiang Road, Shanghai, 200080, People's Republic of China.
  • 2 Department of Radiology, School of Medicine, Shanghai General Hospital, Shanghai Jiaotong University, No. 650 New Songjiang Road, Shanghai, 200080, People's Republic of China. kangan.li@shsmu.edu.cn.
  • # Contributed equally.
Abstract

Background: An increasing number of studies indicated that metabolic reprogramming of amino acid metabolism may either promote or inhibit tumor progression. The purpose of this study was to investigate the ability of a gene risk signature associated with amino acid metabolism to predict the prognosis and immune characteristics of invasive breast carcinoma.

Methods: LASSO COX regression analysis was performed to construct and validate the prognostic risk signature based on the expression of 9 amino acid metabolism-related genes. The predictive value of the signature, immune characteristics, and chemotherapeutic drugs was also predicted. Finally, 9 significant genes were examined in MDA-MB-231 and MCF-7 cells, and the predicted chemotherapeutic drugs were also verified.

Results: The prognosis of the low-risk group was better than that of the high-risk group. The areas under the curve (AUCs) at 1, 2, and 3 years were 0.852, 0.790, and 0.736, respectively. In addition, the GSEA results for KEGG and GO revealed that samples with a high-risk score exhibited a variety of highly malignant manifestations. The high-risk group was characterized by an increased number of M2 macrophages, a high level of tumor purity, low levels of APC co-stimulation, cytolytic activity, HLA, para-inflammation, and type I IFN response. Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) confirmed that MDA-MB-231 and MCF-7 cells express 9 amino acid metabolism-related genes differently. In addition, cell experiments were conducted to examine the effect of cephaeline-induced on cell viability, migration ability, and protein expression of the PI3K/Akt signaling pathway and HIF-1α.

Conclusion: We established a risk signature based on 9 amino acid metabolism-related genes for invasive breast carcinoma. Further analyses revealed that this risk signature is superior to other clinical indexes in survival prediction and that the subgroups identified by the risk signature exhibit distinct immune characteristics. Cephaeline was determined to be a superior option for patients in high-risk groups.

Keywords

Amino acid metabolism-related genes; Drug prediction; Invasive breast carcinoma; Prognosis; Risk signature; TCGA.

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