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Background <p>It is worthwhile to establish a prognostic prediction model based on microenvironment cells (MCs) infiltration and explore new treatment strategies for triple-negative breast cancer (TNBC).</p> Methods <p>The xCell algorithm was used to quantify the cellular components of the TNBC microenvironment based on bulk RNA sequencing (bulk RNA-seq) data. The MCs index (MCI) was constructed using the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression analysis. Single-cell RNA sequencing (scRNA-seq), spatially resolved transcriptomics (SRT), and multiplex immunofluorescence (mIF) staining analyses verified MCI. The mechanism of action of the MCI was investigated in tumor-bearing mice.</p> Results <p>MCI consists of the six types of MCs, which can precisely predict the prognosis of the TNBC patients. scRNA-seq, SRT, and mIF analyses verified the existence and proportions of these cells. Furthermore, combined with the spatial distribution characteristics of the six types of MCs, an MCI-enhanced (MCI-e) model was constructed, which could predict the prognosis of the TNBC patients more accurately. More importantly, inhibition of the insulin signaling pathway activated in the cancer cells of the MCI<sup>high</sup> the TNBC patients significantly prolonged the survival time of tumor-bearing mice.</p> Conclusions <p>Overall, our results demonstrate that MCs infiltration can be exploited as a novel indicator for the prognosis and therapeutic regimen selection of the TNBC patients.</p>

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The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月13日

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  • Xian-Yan Yang,
  • Nian Chen,
  • Qian Wen,
  • Yu Zhou,
  • Tao Zhang,
  • Ji Zhou,
  • Cheng-Hui Liang,
  • Li-Ping Han,
  • Xiao-Ya Wang,
  • Qing-Mei Kang,
  • Xiao-Xia Zheng,
  • Xue-Jia Zhai,
  • Hong-Ying Jiang,
  • Tian-Hua Shen,
  • Jin-Wei Xiao,
  • Yu-Xin Zou,
  • Yun Deng,
  • Shuang Lin,
  • Jiang-Jie Duan,
  • Jun Wang,
  • Shi-Cang Yu

摘要

Background

It is worthwhile to establish a prognostic prediction model based on microenvironment cells (MCs) infiltration and explore new treatment strategies for triple-negative breast cancer (TNBC).

Methods

The xCell algorithm was used to quantify the cellular components of the TNBC microenvironment based on bulk RNA sequencing (bulk RNA-seq) data. The MCs index (MCI) was constructed using the least absolute shrinkage and selection operator Cox (LASSO-Cox) regression analysis. Single-cell RNA sequencing (scRNA-seq), spatially resolved transcriptomics (SRT), and multiplex immunofluorescence (mIF) staining analyses verified MCI. The mechanism of action of the MCI was investigated in tumor-bearing mice.

Results

MCI consists of the six types of MCs, which can precisely predict the prognosis of the TNBC patients. scRNA-seq, SRT, and mIF analyses verified the existence and proportions of these cells. Furthermore, combined with the spatial distribution characteristics of the six types of MCs, an MCI-enhanced (MCI-e) model was constructed, which could predict the prognosis of the TNBC patients more accurately. More importantly, inhibition of the insulin signaling pathway activated in the cancer cells of the MCIhigh the TNBC patients significantly prolonged the survival time of tumor-bearing mice.

Conclusions

Overall, our results demonstrate that MCs infiltration can be exploited as a novel indicator for the prognosis and therapeutic regimen selection of the TNBC patients.