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Background <p>Triple-negative breast cancer (TNBC), defined by the lack of expression of Estrogen Receptor (ER), Progesterone Receptor (PR), and Human Epidermal Growth Factor Receptor 2 (HER2), is associated with increased rates of recurrence and mortality. Alterations in energy metabolism often accompany malignant transformation of cells, a process closely linked to mitochondrial function. Ageing contributes to tumor progression through multiple mechanisms. This study aims to explore the mechanisms by which mitochondrial function and ageing influence TNBC, providing new targets and strategies for its diagnosis and treatment.</p> Methods <p>This study identified mitochondrial ageing-related differentially expressed genes (MAR-DEGs) and constructed a prognostic prediction model based on the TCGA-TNBC (training set) and GSE58812 (validation set) datasets. Differential expression analysis, Log-rank test, univariate Cox regression, random forest, and LASSO regression were employed for screen gene sets with diagnostic and prognostic value. A mitochondrial ageing-related risk score (MARS) model was constructed based on LASSO regression. Further analyses were conducted to examine the correlations between MARS and clinicopathological features, copy number variations, drug sensitivity, immune checkpoint expression, and tumor microenvironment. Finally, bioinformatics analysis was conducted to identify PYCR1 expression and potential functions in TNBC.</p> Results <p>Based on 52 MAR-DEGs in TNBC, a prognostic signature composed of 4 MAR-DEGs (PYCR1, MAPT, CEBPA, and BCL2A1) was developed. The nomogram incorporating this signature accurately predicted 3-year, 5-year, and 7-year survival rates. Copy number variation (CNV), drug sensitivity, and tumor immune microenvironment analyses revealed that the high-risk group had higher tumor purity and lower immune cell infiltration, as well as lower immunotherapy sensitivity. Immunohistochemical validation of clinical samples revealed that PYCR1 is significantly overexpressed in TNBC tissues. In vitro functional experiments confirmed that knockdown of PYCR1 significantly inhibits the proliferation, migration, and invasion capabilities of TNBC cells.</p> Conclusions <p>By integrating multi-omics data and experimental validation, we successfully developed a MARS model with significant prognostic value. We confirmed the high expression of PYCR1 in TNBC and its function in promoting tumor progression, providing new insights for the precision treatment of TNBC.</p>

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Multi-omics analyses related to mitochondria and ageing in triple-negative breast cancer implicate PYCR1 potentiates tumor progression

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月26日

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  • Jia-nan Huang,
  • Jingxi Hu,
  • Chao Shi,
  • Chunyan Chu,
  • Haolin Hu

摘要

Background

Triple-negative breast cancer (TNBC), defined by the lack of expression of Estrogen Receptor (ER), Progesterone Receptor (PR), and Human Epidermal Growth Factor Receptor 2 (HER2), is associated with increased rates of recurrence and mortality. Alterations in energy metabolism often accompany malignant transformation of cells, a process closely linked to mitochondrial function. Ageing contributes to tumor progression through multiple mechanisms. This study aims to explore the mechanisms by which mitochondrial function and ageing influence TNBC, providing new targets and strategies for its diagnosis and treatment.

Methods

This study identified mitochondrial ageing-related differentially expressed genes (MAR-DEGs) and constructed a prognostic prediction model based on the TCGA-TNBC (training set) and GSE58812 (validation set) datasets. Differential expression analysis, Log-rank test, univariate Cox regression, random forest, and LASSO regression were employed for screen gene sets with diagnostic and prognostic value. A mitochondrial ageing-related risk score (MARS) model was constructed based on LASSO regression. Further analyses were conducted to examine the correlations between MARS and clinicopathological features, copy number variations, drug sensitivity, immune checkpoint expression, and tumor microenvironment. Finally, bioinformatics analysis was conducted to identify PYCR1 expression and potential functions in TNBC.

Results

Based on 52 MAR-DEGs in TNBC, a prognostic signature composed of 4 MAR-DEGs (PYCR1, MAPT, CEBPA, and BCL2A1) was developed. The nomogram incorporating this signature accurately predicted 3-year, 5-year, and 7-year survival rates. Copy number variation (CNV), drug sensitivity, and tumor immune microenvironment analyses revealed that the high-risk group had higher tumor purity and lower immune cell infiltration, as well as lower immunotherapy sensitivity. Immunohistochemical validation of clinical samples revealed that PYCR1 is significantly overexpressed in TNBC tissues. In vitro functional experiments confirmed that knockdown of PYCR1 significantly inhibits the proliferation, migration, and invasion capabilities of TNBC cells.

Conclusions

By integrating multi-omics data and experimental validation, we successfully developed a MARS model with significant prognostic value. We confirmed the high expression of PYCR1 in TNBC and its function in promoting tumor progression, providing new insights for the precision treatment of TNBC.