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Article

Development of a machine learning-based radiomics signature for estimating breast cancer TME phenotypes and predicting anti-PD-1/PD-L1 immunotherapy response.

Breast cancer research : BCR - 29 Jan 2024

Han Xiaorui, Guo Yuan, Ye Huifen, Chen Zhihong, Hu Qingru, Wei Xinhua, Liu Zaiyi, Liang Changhong

Abstract excerpt

BACKGROUNDS: Since breast cancer patients respond diversely to immunotherapy, there is an urgent need to explore novel biomarkers to precisely predict clinical responses and enhance therapeutic efficacy. The purpose of our present research was to construct and independently validate a biomarker of tumor microenvironment (TME) phenotypes via a machine learning-based radiomics way. The interrelationship between the...

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Identifiers

PMID: 38287356
DOI: 10.1186/s13058-024-01776-y
PMCID: PMC10823720

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