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Discovery of an independent poor-prognosis subtype associated with tertiary lymphoid structures in breast cancer.
Liu, Ruiqi; Huang, Xiaoqian; Yang, Shiwei; Du, Wenbo; Chen, Xiaozhou; Li, Huamei.
Afiliación
  • Liu R; School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China.
  • Huang X; School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China.
  • Yang S; School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China.
  • Du W; Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
  • Chen X; School of Mathematics and Computer Science, Yunnan Minzu University, Kunming, China.
  • Li H; Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Front Immunol ; 15: 1364506, 2024.
Article en En | MEDLINE | ID: mdl-38571938
ABSTRACT

Introduction:

Tertiary lymphoid structures (TLSs) are ectopic lymphoid formations that arise in non-lymphoid tissues due to chronic inflammation. The pivotal function of TLSs in regulating tumor invasion and metastasis has been established across several cancers, such as lung cancer, liver cancer, and melanoma, with a positive correlation between increased TLS presence and improved prognosis. Nevertheless, the current research about the clinical significance of TLSs in breast cancer remains limited.

Methods:

In our investigation, we discovered TLS-critical genes that may impact the prognosis of breast cancer patients, and categorized breast cancer into three distinct subtypes based on critical gene expression profiles, each exhibiting substantial differences in prognosis (p = 0.0046, log-rank test), with Cluster 1 having the best prognosis, followed by Cluster 2, and Cluster 3 having the worst prognosis. We explored the impact of the heterogeneity of these subtypes on patient prognosis, the differences in the molecular mechanism, and their responses to drug therapy and immunotherapy. In addition, we designed a machine learning-based classification model, unveiling highly consistent prognostic distinctions in several externally independent cohorts.

Results:

A notable marker gene CXCL13 was identified in Cluster 3, potentially pivotal in enhancing patient prognosis. At the single-cell resolution, we delved into the adverse prognosis of Cluster 3, observing an enhanced interaction between fibroblasts, myeloid cells, and basal cells, influencing patient prognosis. Furthermore, we identified several significantly upregulated genes (CD46, JAG1, IL6, and IL6R) that may positively correlate with cancer cells' survival and invasive capabilities in this subtype.

Discussion:

Our study is a robust foundation for precision medicine and personalized therapy, presenting a novel perspective for the contemporary classification of breast cancer.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Estructuras Linfoides Terciarias / Neoplasias Hepáticas / Neoplasias Pulmonares Límite: Female / Humans Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Estructuras Linfoides Terciarias / Neoplasias Hepáticas / Neoplasias Pulmonares Límite: Female / Humans Idioma: En Revista: Front Immunol Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza