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Background <p>M2-like tumor-associated macrophages (M2-like TAMs) function crucially in the tumor microenvironment (TME) and cancer development. This study developed a prognostic signature based on M2-like TAM-related genes for breast cancer (BRCA) applying transcriptome and scRNA-seq analysis.</p> Methods <p>TCGA-BRCA, GSE20685, and GSE176078 datasets were downloaded from UCSC xena and GEO databases. AUCell score of immune-related genes (IRGs) was calculated using R package. Genes related to M2-like TAMs were screened by WGCNA. Prognostic genes were further identified by univariate Cox and LASSO regression analyses to form a RiskScore model, which was validated in external dataset. Furthermore, a nomogram was established by integrating RiskScore and clinical characteristics, and correlation analysis between the RiskScore and TME or chemotherapeutic drugs was conducted. Finally, the mRNA expression levels of the key genes identified were verified using quantitative real time polymerase chain reaction (qRT-PCR).</p> Results <p>As macrophages exhibited the highest AUCell score of IRGs in single-cell transcriptomic atlas of BRCA, the cells were further classified into Macrophages C1 and C2 subtypes, with the C1 subtype showing a high expression of M2 macrophage marker genes. <i>ARHGAP26</i>, <i>RILP</i>, <i>KLRB1</i>, <i>CSTA</i>, <i>KLHDC7B</i>, <i>PSMB8</i>, <i>KYNU</i>, <i>RNASE1</i>, <i>LONRF3</i>, and <i>TRPM2</i> were screened as the prognostic signature genes from a total of 903 M2-like TAM-related genes to establish a robust RiskScore model. Furthermore, a nomogram with a strong predictive performance was constructed combining stage, Age, and RiskScore, and&#xa0;we found that most immune cells showed a negative correlation with RiskScore. Multiple drugs were closely associated with the RiskScore, notably, Ribociclib_1632 had higher a half-maximal inhibitory concentration (IC50) value in high-risk group. Finally, qRT-PCR demonstrated that the mRNA expression levels of the 10 genes were significantly different in control and BRCA cell lines.</p> Conclusion <p>We identified 10 M2-like TAM-related prognostic signature genes for BRCA, providing potential therapeutic targets for the treatment of the cancer.</p>

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Applying integrated transcriptome and single-cell sequencing analysis to develop a prognostic signature based on M2-like tumor-associated macrophages for breast cancer

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  • 发表日期：

    2025年3月25日

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  • Yanghaochen Xu,
  • Peiyan Lin,
  • Ye Zhu,
  • Qing Zhang,
  • Jinhong Zhou

摘要

Background

M2-like tumor-associated macrophages (M2-like TAMs) function crucially in the tumor microenvironment (TME) and cancer development. This study developed a prognostic signature based on M2-like TAM-related genes for breast cancer (BRCA) applying transcriptome and scRNA-seq analysis.

Methods

TCGA-BRCA, GSE20685, and GSE176078 datasets were downloaded from UCSC xena and GEO databases. AUCell score of immune-related genes (IRGs) was calculated using R package. Genes related to M2-like TAMs were screened by WGCNA. Prognostic genes were further identified by univariate Cox and LASSO regression analyses to form a RiskScore model, which was validated in external dataset. Furthermore, a nomogram was established by integrating RiskScore and clinical characteristics, and correlation analysis between the RiskScore and TME or chemotherapeutic drugs was conducted. Finally, the mRNA expression levels of the key genes identified were verified using quantitative real time polymerase chain reaction (qRT-PCR).

Results

As macrophages exhibited the highest AUCell score of IRGs in single-cell transcriptomic atlas of BRCA, the cells were further classified into Macrophages C1 and C2 subtypes, with the C1 subtype showing a high expression of M2 macrophage marker genes. ARHGAP26, RILP, KLRB1, CSTA, KLHDC7B, PSMB8, KYNU, RNASE1, LONRF3, and TRPM2 were screened as the prognostic signature genes from a total of 903 M2-like TAM-related genes to establish a robust RiskScore model. Furthermore, a nomogram with a strong predictive performance was constructed combining stage, Age, and RiskScore, and we found that most immune cells showed a negative correlation with RiskScore. Multiple drugs were closely associated with the RiskScore, notably, Ribociclib_1632 had higher a half-maximal inhibitory concentration (IC50) value in high-risk group. Finally, qRT-PCR demonstrated that the mRNA expression levels of the 10 genes were significantly different in control and BRCA cell lines.

Conclusion

We identified 10 M2-like TAM-related prognostic signature genes for BRCA, providing potential therapeutic targets for the treatment of the cancer.