Pivotal models and biomarkers related to the prognosis of breast cancer based on the immune cell interaction network
Rattachement africain : cn. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
The effect of breast cancer heterogeneity on prognosis of patients is still unclear, especially the role of immune cells in prognosis of breast cancer. In this study, single cell transcriptome sequencing data of breast cancer were used to analyze the relationship between breast cancer heterogeneity and prognosis. In this study, 14 cell clusters were identified in two single-cell datasets (GSE75688 and G118389). Proportion analysis of immune cells showed that NK cells were significantly aggregated in triple negative breast cancer, and the proportion of macrophages was significantly increased in primary breast cancer, while B cells, T cells, and neutrophils may be involved in the metastasis of breast cancer. The results of ligand receptor interaction network revealed that macrophages and DC cells were the most frequently interacting cells with other cells in breast cancer. The results of WGCNA analysis suggested that the MEblue module is most relevant to the overall survival time of triple negative breast cancer. Twenty-four prognostic genes in the blue module were identified by univariate Cox regression analysis and KM survival analysis. Multivariate regression analysis combined with risk analysis was used to analyze 24 prognostic genes to construct a prognostic model. The verification result of our prognostic model showed that there were significant differences in the expression of PCDH12, SLIT3, ACVRL1, and DLL4 genes between the high-risk group and the low-risk group, which can be used as prognostic biomarkers.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Pivotal models and biomarkers related to the prognosis of breast cancer based on the immune cell interaction network
- Date Crossref
- 11/08/2022
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
-
Kunming Medical University Department of Mammary Surgery I pays non établi dans la noticeUniversité ou école supérieure
-
Kunming University of Science and Technology Department of Blood Transfusion pays non établi dans la noticeUniversité ou école supérieure
-
First People's Hospital of Yunnan Province pays non établi dans la noticeÉtablissement de santé
-
Yunnan Maternal and Child Health pays non établi dans la noticeÉtablissement de santé
-
Kunming Women and Child Health Service Center/Kunming Women and Child Health Care Hospital pays non établi dans la noticeÉtablissement de santé
Department of Mammary Surgery I — Kunming Medical University, Department of Blood Transfusion — Kunming University of Science and Technology et First People's Hospital of Yunnan Province, avec 2 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.