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<p>Research indicates that cancer cells reprogram their metabolic pathways for their own benefit. This study examined gene expression changes in the arginine-proline metabolism pathway in breast cancer (BC) and their impact on prognosis and subtype classification. The KEGG database identified 54 genes related to this study. Using data from The Cancer Genome Atlas (TCGA), gene expression patterns and their associations with prognosis and BC subtypes were analyzed. A protein-protein interaction network identified <i>AZIN2</i> and <i>AOC1</i> as hub genes. Prognostic evaluations were performed using Cox regression and Kaplan-Meier analyses. TCGA data also revealed gene expression clusters associated with clinical features. Two main subgroups, C1 and C2, were identified, with C1 showing higher expression of arginine-proline metabolism genes. C1 was strongly linked to the triple-negative breast cancer (TNBC) subtype and showed elevated expression of proliferation-related genes. Among the 54 genes, 17 were upregulated, and nine were downregulated in BC. High expression of <i>NOS1</i>, <i>NOS2</i>, and <i>P4HA2</i> was associated with poor prognosis. RT-qPCR validation on 65 BC and 20 healthy tissue samples confirmed upregulation of <i>AOC1</i> and <i>AZIN2</i>, particularly in TNBC. Cluster analysis revealed a significant correlation between C1 and TNBC, as well as its aggressive behavior. These findings suggest that the arginine-proline metabolism pathway plays a crucial role in BC progression, especially in TNBC, linking metabolic reprogramming to poor prognosis. Targeting this pathway could provide new therapeutic opportunities and prognostic insights in TNBC management.</p>

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Arginine-proline metabolism as a prognostic and therapeutic target in triple-negative breast cancer: an in silico and ex vivo investigation

  • 期刊论文

  • 发表日期：

    2025年12月17日

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  • Zeinab Golestani,
  • Zahra Mohammadi,
  • Ensieh Sagheb Sadeghi,
  • Atefeh Zamani,
  • Mohammad Mahdevar

摘要

Research indicates that cancer cells reprogram their metabolic pathways for their own benefit. This study examined gene expression changes in the arginine-proline metabolism pathway in breast cancer (BC) and their impact on prognosis and subtype classification. The KEGG database identified 54 genes related to this study. Using data from The Cancer Genome Atlas (TCGA), gene expression patterns and their associations with prognosis and BC subtypes were analyzed. A protein-protein interaction network identified AZIN2 and AOC1 as hub genes. Prognostic evaluations were performed using Cox regression and Kaplan-Meier analyses. TCGA data also revealed gene expression clusters associated with clinical features. Two main subgroups, C1 and C2, were identified, with C1 showing higher expression of arginine-proline metabolism genes. C1 was strongly linked to the triple-negative breast cancer (TNBC) subtype and showed elevated expression of proliferation-related genes. Among the 54 genes, 17 were upregulated, and nine were downregulated in BC. High expression of NOS1, NOS2, and P4HA2 was associated with poor prognosis. RT-qPCR validation on 65 BC and 20 healthy tissue samples confirmed upregulation of AOC1 and AZIN2, particularly in TNBC. Cluster analysis revealed a significant correlation between C1 and TNBC, as well as its aggressive behavior. These findings suggest that the arginine-proline metabolism pathway plays a crucial role in BC progression, especially in TNBC, linking metabolic reprogramming to poor prognosis. Targeting this pathway could provide new therapeutic opportunities and prognostic insights in TNBC management.