2024
DOI: 10.1007/s00432-024-06001-z
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Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients

Xiliang Zhang,
Hanjie Guo,
Xiaolong Li
et al.

Abstract: Background Breast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis. Methods We used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to s… Show more

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