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Background <p>Dysregulation of small ubiquitin-like modifier ylation (SUMO-ylation) is closely associated with the development of different types of cancers. Growing evidence indicates that many SUMOylated genes (SRGs) play a role in the initiation and progression of breast cancer (BRCA). However, its prognostic value in BRCA remains inadequately explored.</p> Methods <p>This study explored prognostic genes related to SUMO-ylation in BRCA based on single-cell RNA sequencing (scRNA-seq) and transcriptome data, developed and validated a risk model. Furthermore, an analysis of clinical relevance was performed to determine independent prognostic factors associated with BRCA. Additionally, enrichment analysis, immune analysis, drug sensitivity analysis, and construction of molecular regulatory networks were executed to probe the potential molecular mechanisms of prognostic genes. Communication analysis and pseudo-time analysis of the prognostic genes were also conducted at the scRNA-seq level to further investigate cell interactions and differentiation trajectories of different cell subtypes. Finally, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was performed to validate the expression of the prognostic genes in BRCA and paracancerous tissues.</p> Results <p>Based on a series of analyses, 8 prognostic genes were identified, namely GPC1, CAPZA1, NUDCD1, MTDH, COX7A1, PLK3, FAM43A, and CEBPD. The risk model developed from these prognostic genes demonstrated good performance and broad applicability with area under the curve (AUC) values of 0.716, 0.677 and 0.657 at 1, 3, 5 years, respectively. The nomogram model constructed by combining the risk scores obtained from the above risk model with age, N-stage, and radiotherapy also has predictive ability, with AUC values exceeding 0.7 at all three time points. Furthermore, immune analysis identified the different infiltration proportions of CD8 T cells, NK cells, resting dendritic cells and M2 macrophages between high- and low-risk cohorts. IC<sub>50</sub> values of sorafenib and tipifarnib were higher in the high-risk group. Finally, both scRNA-seq data and RT-qPCR&#xa0;results demonstrated notable variances in the expression of these prognostic genes between BRCA and normal tissues. Among them, CAPZA1, NUDCD1, GPC1 and MTDH were upregulated while COX7A1 and CEBPD were significantly decreased in tumors.</p> Conclusions <p>In this study, 8 SUMO-ylation related prognostic genes were identified in BRCA, namely GPC1, CAPZA1, NUDCD1, MTDH, COX7A1, PLK3, FAM43A and CEBPD, offering fresh perspectives on the prognosis of BRCA.</p>

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Using single-cell and transcriptome data to identify prognostic genes associated with SUMO-ylation and their molecular regulatory mechanisms in breast cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月6日

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  • Ying Yang,
  • Yun Ma,
  • Fenglin Xue,
  • Jun Li,
  • Shiyue Liu,
  • Yingying Wu,
  • Yingxia Wang,
  • Li Bian,
  • Guoqing Pan

摘要

Background

Dysregulation of small ubiquitin-like modifier ylation (SUMO-ylation) is closely associated with the development of different types of cancers. Growing evidence indicates that many SUMOylated genes (SRGs) play a role in the initiation and progression of breast cancer (BRCA). However, its prognostic value in BRCA remains inadequately explored.

Methods

This study explored prognostic genes related to SUMO-ylation in BRCA based on single-cell RNA sequencing (scRNA-seq) and transcriptome data, developed and validated a risk model. Furthermore, an analysis of clinical relevance was performed to determine independent prognostic factors associated with BRCA. Additionally, enrichment analysis, immune analysis, drug sensitivity analysis, and construction of molecular regulatory networks were executed to probe the potential molecular mechanisms of prognostic genes. Communication analysis and pseudo-time analysis of the prognostic genes were also conducted at the scRNA-seq level to further investigate cell interactions and differentiation trajectories of different cell subtypes. Finally, reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) was performed to validate the expression of the prognostic genes in BRCA and paracancerous tissues.

Results

Based on a series of analyses, 8 prognostic genes were identified, namely GPC1, CAPZA1, NUDCD1, MTDH, COX7A1, PLK3, FAM43A, and CEBPD. The risk model developed from these prognostic genes demonstrated good performance and broad applicability with area under the curve (AUC) values of 0.716, 0.677 and 0.657 at 1, 3, 5 years, respectively. The nomogram model constructed by combining the risk scores obtained from the above risk model with age, N-stage, and radiotherapy also has predictive ability, with AUC values exceeding 0.7 at all three time points. Furthermore, immune analysis identified the different infiltration proportions of CD8 T cells, NK cells, resting dendritic cells and M2 macrophages between high- and low-risk cohorts. IC50 values of sorafenib and tipifarnib were higher in the high-risk group. Finally, both scRNA-seq data and RT-qPCR results demonstrated notable variances in the expression of these prognostic genes between BRCA and normal tissues. Among them, CAPZA1, NUDCD1, GPC1 and MTDH were upregulated while COX7A1 and CEBPD were significantly decreased in tumors.

Conclusions

In this study, 8 SUMO-ylation related prognostic genes were identified in BRCA, namely GPC1, CAPZA1, NUDCD1, MTDH, COX7A1, PLK3, FAM43A and CEBPD, offering fresh perspectives on the prognosis of BRCA.