Model for predicting immunotherapy based on M2 macrophage infiltration in TNBC.

Area of Science:

• Oncology
• Immunology
• Genetics

Background:

• Triple-negative breast cancer (TNBC) presents a significant clinical challenge due to its aggressive nature and limited treatment options.
• Current immunotherapies for TNBC are restricted, highlighting the need for novel therapeutic strategies and predictive biomarkers.

Purpose of the Study:

• To identify key genes associated with M2 macrophage infiltration in TNBC.
• To develop a prognostic model for TNBC patients based on identified genes.
• To explore potential immunotherapy drug sensitivity in different risk groups.

Main Methods:

• Analysis of gene co-expression with M2 macrophages using TCGA and GEO databases.
• Gene Ontology (GO) and KEGG pathway analysis.
• Lasso regression for prognostic model construction and validation.
• Screening of immunotherapy drugs based on patient risk stratification.

Main Results:

• Identified OLFML2B, MS4A7, SPARC, POSTN, THY1, and CD300C as significantly influencing TNBC prognosis.
• Developed a prognostic model using MS4A7, SPARC, and CD300C with high predictive accuracy.
• Screened 50 immunotherapy drugs, assessing their potential therapeutic significance in different risk groups.

Conclusions:

• The prognostic model based on MS4A7, SPARC, and CD300C demonstrates high precision and clinical applicability for TNBC.
• The identification of potential immunotherapy drugs offers a novel approach for treating TNBC patients.
• This study provides a foundation for personalized immunotherapy strategies in TNBC.