Evaluating the prognostic potential of telomerase signature in breast cancer through advanced machine learning model

Our findings highlight the utility of MLTS as a robust prognostic biomarker for breast cancer. The ability of MLTS to predict patient outcomes and its association with key genomic and cellular features underscore its potential as a target for personalized therapy. Future research may focus on integrating MLTS with additional molecular signatures to enhance its clinical application in precision oncology.

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Publication Details

Journal
Frontiers in Immunology
Published
2024-11-28
DOI
https://doi.org/10.3389/fimmu.2024.1462953
Citations
1
Primary Topic
Telomeres, Telomerase, and Senescence
Type
article
Field-Weighted Citation Impact
0.33
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article

Evaluating the prognostic potential of telomerase signature in breast cancer through advanced machine learning model

Xiao Guo, Jiaying Xing, Chuanbo Feng, Xinlin Shi et al.
1 citations
Frontiers in Immunology
Telomeres, Telomerase, and Senescence
0.33
article

Evaluating the prognostic potential of telomerase signature in breast cancer through advanced machine learning model

Xiao Guo, Jiaying Xing, Chuanbo Feng, Xinlin Shi, Yuyan Cao, Tao Wang
article en
1 citations

Abstract

Our findings highlight the utility of MLTS as a robust prognostic biomarker for breast cancer. The ability of MLTS to predict patient outcomes and its association with key genomic and cellular features underscore its potential as a target for personalized therapy. Future research may focus on integrating MLTS with additional molecular signatures to enhance its clinical application in precision oncology.

Frontiers in ImmunologyVol. 15
Beihua University (CN), Guizhou Provincial People's Hospital (CN)
Good health and well-being
Openalex Percentile: Top 35%
Telomeres, Telomerase, and Senescence
0.33
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