A novel PD-1/PD-L1 pathway-related seven-gene signature for the development and validation of the prognosis...

Area of Science:

• Oncology
• Immunology
• Genetics

Background:

• Breast cancer (BC) is the most prevalent cancer in women, with a low 5-year survival rate for stage IV disease.
• Effective therapies remain a challenge for a significant portion of BC patients, highlighting the need for novel biomarkers.
• The programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) pathway is a key regulator of immune responses and a target in cancer therapy.

Purpose of the Study:

• To investigate the association between the PD-1/PD-L1 pathway status and clinical outcomes in breast cancer patients.
• To identify novel biomarkers for predicting prognosis and guiding therapy in BC.
• To explore the relationship between PD-1/PD-L1 pathway-related subtypes and the tumor immune microenvironment, ferroptosis, and N6-methyladenosine (m6A) modification.

Main Methods:

• Utilized clinical and transcriptome data from The Cancer Genome Atlas (TCGA) for BC patients.
• Applied consensus clustering to segregate patients into distinct subtypes based on gene expression.
• Employed Least Absolute Shrinkage and Selection Operator (LASSO) regression to develop a prognostic gene signature related to the PD-1/PD-L1 pathway.

Main Results:

• Identified two distinct BC patient clusters (low-risk C1 and high-risk C2) based on PD-1/PD-L1 pathway-related gene expression.
• Found significant differences in immune-related pathways, ferroptosis, and m6A modification between the identified clusters.
• Developed a 7-gene signature (including MAP2K6, NFKBIA, NFKBIE, IFNG, TIRAP, CHUK, CSNK2A3) that accurately predicted overall survival in BC patients, with AUC values for 1-, 3-, and 5-year survival ranging from 0.651 to 0.658.

Conclusions:

• PD-1/PD-L1 pathway-related subtypes of breast cancer are linked to specific immune microenvironment, ferroptosis, and m6A profiles.
• The developed 7-gene signature shows potential for distinguishing BC subtypes and predicting patient prognosis.
• This gene signature may serve as a valuable tool for personalized medicine approaches in breast cancer management.