The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers
Abstract 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 micro...
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2025-01-01
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| Series: | Journal of Translational Medicine |
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| Online Access: | https://doi.org/10.1186/s12967-024-05950-w |
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| author | 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 |
| author_facet | 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 |
| author_sort | Xian-Yan Yang |
| collection | DOAJ |
| description | Abstract 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. |
| format | Article |
| id | doaj-art-289eb308361a4483ae1c22016de0edbd |
| institution | Kabale University |
| issn | 1479-5876 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj-art-289eb308361a4483ae1c22016de0edbd2025-01-19T12:37:14ZengBMCJournal of Translational Medicine1479-58762025-01-0123112410.1186/s12967-024-05950-wThe microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancersXian-Yan Yang0Nian Chen1Qian Wen2Yu Zhou3Tao Zhang4Ji Zhou5Cheng-Hui Liang6Li-Ping Han7Xiao-Ya Wang8Qing-Mei Kang9Xiao-Xia Zheng10Xue-Jia Zhai11Hong-Ying Jiang12Tian-Hua Shen13Jin-Wei Xiao14Yu-Xin Zou15Yun Deng16Shuang Lin17Jiang-Jie Duan18Jun Wang19Shi-Cang Yu20Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Department of Stem Cell and Regenerative Medicine, Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medical University)Abstract 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.https://doi.org/10.1186/s12967-024-05950-wTriple-negative breast cancerTumor microenvironmentCell infiltrationSpatial locationPrognosis predictionTherapeutic regimen |
| spellingShingle | 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 The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers Journal of Translational Medicine Triple-negative breast cancer Tumor microenvironment Cell infiltration Spatial location Prognosis prediction Therapeutic regimen |
| title | The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers |
| title_full | The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers |
| title_fullStr | The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers |
| title_full_unstemmed | The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers |
| title_short | The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers |
| title_sort | microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers |
| topic | Triple-negative breast cancer Tumor microenvironment Cell infiltration Spatial location Prognosis prediction Therapeutic regimen |
| url | https://doi.org/10.1186/s12967-024-05950-w |
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