Scholarlink

Objective <p>Lactate metabolism, a key feature of the tumor microenvironment, plays a crucial role in cancer progression and immune suppression. However, the prognostic implication of lactate metabolism-related genes in breast cancer (BC) is not fully understood. This study aimed to explore key lactate metabolism-related genes related to the prognosis and immune cell clusters in BC.</p> Methods <p>Based on The Cancer Genome Atlas (TCGA) RNA-seq data, lactate-related differentially expressed genes in BC were identified from lactate gene sets from MSigDB. A prognostic risk model was built through univariate and LASSO Cox regression analyses and validated in an independent Gene Expression Omnibus (GEO) cohort. Based on single-cell RNA-seq datasets from GEO database, immune infiltration was assessed via CIBERSORT, MCP-counter, and ssGSEA. Single-cell data analysis using Seurat, Monocle3, and CellChat elucidated cellular heterogeneity, developmental trajectories, and cell-cell communication.</p> Results <p>A 15-gene lactate-related prognostic signature was established. High-risk scores correlated significantly with poorer overall survival, advanced pathological stage, and lymph node metastasis. Single-cell analysis revealed nine major cell types. Cancer-associated fibroblasts promoted ECM remodeling via COL1A1, while tumor epithelial cells engaged in immunosuppressive interactions. Key molecules such as the lactate transporters MCT1/4 and CD147 axis were associated with poor prognosis. Immune regulatory pathways involving macrophage migration inhibitory factor-CD74 and MDK-SDC4 were linked to tumor migration and immune evasion, representing potential therapeutic targets.</p> Conclusion <p>This study established a robust lactate metabolism-related gene signature for prognostic stratification in BC and highlighted its link to an immunosuppressive microenvironment, offering novel insights for developing targeted therapeutic strategies.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Lactate metabolism gene signature predicts prognosis in breast cancer using bulk and single cell sequencing data

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月16日

查看全文
  • Yimeng Yang,
  • Rui Jiang,
  • Yue Zhang,
  • Yazhou Zhang,
  • Beibei Lv,
  • Zhaoyuan Meng,
  • Lin Lv,
  • Jiawen Xu

摘要

Objective

Lactate metabolism, a key feature of the tumor microenvironment, plays a crucial role in cancer progression and immune suppression. However, the prognostic implication of lactate metabolism-related genes in breast cancer (BC) is not fully understood. This study aimed to explore key lactate metabolism-related genes related to the prognosis and immune cell clusters in BC.

Methods

Based on The Cancer Genome Atlas (TCGA) RNA-seq data, lactate-related differentially expressed genes in BC were identified from lactate gene sets from MSigDB. A prognostic risk model was built through univariate and LASSO Cox regression analyses and validated in an independent Gene Expression Omnibus (GEO) cohort. Based on single-cell RNA-seq datasets from GEO database, immune infiltration was assessed via CIBERSORT, MCP-counter, and ssGSEA. Single-cell data analysis using Seurat, Monocle3, and CellChat elucidated cellular heterogeneity, developmental trajectories, and cell-cell communication.

Results

A 15-gene lactate-related prognostic signature was established. High-risk scores correlated significantly with poorer overall survival, advanced pathological stage, and lymph node metastasis. Single-cell analysis revealed nine major cell types. Cancer-associated fibroblasts promoted ECM remodeling via COL1A1, while tumor epithelial cells engaged in immunosuppressive interactions. Key molecules such as the lactate transporters MCT1/4 and CD147 axis were associated with poor prognosis. Immune regulatory pathways involving macrophage migration inhibitory factor-CD74 and MDK-SDC4 were linked to tumor migration and immune evasion, representing potential therapeutic targets.

Conclusion

This study established a robust lactate metabolism-related gene signature for prognostic stratification in BC and highlighted its link to an immunosuppressive microenvironment, offering novel insights for developing targeted therapeutic strategies.