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Predictive model of gene expression regulating invasion and migration of M2 macrophages in breast cancer: clinical prognosis and therapeutic implications.
Jiang, Chengjie; Luo, Jinlei; Jiang, Xiaoxue; Lv, Yujie; Dou, Jianwei.
Afiliación
  • Jiang C; Key Laboratory of Traditional Chinese Herbs and Prescription Innovation and Transformation of Gansu Province, Laboratory for TCM New Products Development Engineering of Gansu Province, Lanzhou, China.
  • Luo J; Key Laboratory of Traditional Chinese Herbs and Prescription Innovation and Transformation of Gansu Province, Laboratory for TCM New Products Development Engineering of Gansu Province, Lanzhou, China.
  • Jiang X; School of Chinese Clinical Medicine, Gansu University of Chinese Medicine, Lanzhou, China.
  • Lv Y; Key Laboratory of Traditional Chinese Herbs and Prescription Innovation and Transformation of Gansu Province, Laboratory for TCM New Products Development Engineering of Gansu Province, Lanzhou, China.
  • Dou J; School of Pharmacy, Xi'an Jiao Tong University, Xi'an, China.
Transl Cancer Res ; 13(8): 4187-4204, 2024 Aug 31.
Article en En | MEDLINE | ID: mdl-39262492
ABSTRACT

Background:

Breast cancer (BRCA) has surpassed lung cancer to become the malignant tumor with the highest incidence in female population. It occurs in malignant cells in breast tissue and is common worldwide. An increasing body of research indicates that M2 macrophages are critical to the occurrence and progression of BRCA. The aim of this work is to build a predictive model of genes related to invasion and migration of M2 macrophages, forecast the prognosis of patients with BRCA, and then evaluate the efficacy of some targeted treatments.

Methods:

The Gene Expression Omnibus (GEO; https//www.ncbi.nlm.nih.gov/geo/) database supplied the GSE20685 dataset, whereas the expression profile a clinical details of BRCA patients were obtained from The Cancer Genome Atlas (TCGA; https//portal.gdc.cancer.gov/) database. The genes linked to M2 macrophages and the differentially elevated genes of invasion and migration were found in GSE20685. To explore the prognosis-related invasion and migration M2 macrophage genes, the TCGA-BRCA dataset was merged with Cox regression and least absolute shrinkage and selection operator (LASSO) regression. GSE58812 was utilized for external validation. After calculating each patient's risk score, the prognostic model was examined by analyses of immune infiltration, medication sensitivity, mutation, and enrichment of the risk score.

Results:

The risk score had a strong correlation with both several immune cells and popular anti-tumor medications. Additionally, it was discovered that the risk score was a separate prognostic factor for BRCA.

Conclusions:

Based on invasion and migration-related M2 macrophage genes, we investigated and validated predictive characteristics in our study that may offer helpful insights into the progression and prognosis of BRCA.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Transl Cancer Res Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: China
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Transl Cancer Res Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: China