A novel immune-related long noncoding RNA (lncRNA) pair model to predict the prognosis of triple-negative breast...

Area of Science:

• Oncology
• Immunology
• Genomics

Background:

• Breast cancer (BC) is a leading cause of cancer death in women.
• Anti-programmed cell death protein 1/programmed cell death ligand 1 (PD-1/PD-L1) immunotherapy shows promise in metastatic triple-negative breast cancer (TNBC).
• Immune-related long noncoding RNAs (irlncRNAs) may influence PD-1/PD-L1 pathway efficacy in cancer immune escape.

Purpose of the Study:

• To explore the regulatory mechanisms of irlncRNAs in PD-1/PD-L1 immunotherapy for TNBC.
• To develop a predictive model for immunotherapy efficacy in TNBC patients.
• To identify specific irlncRNAs associated with immune responses and PD-L1 expression.

Main Methods:

• Transcriptome profiling data from The Cancer Genome Atlas (TCGA) was analyzed.
• Differentially expressed irlncRNA (DEirlncRNA) pairs were identified.
• A risk assessment model was constructed using Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis.

Main Results:

• The developed risk model demonstrated potential as a predictive tool for TNBC patients, validated by ROC curve analysis.
• Clinical stage and risk score were identified as independent prognostic predictors.
• The lncRNA USP30-AS1 was identified and found to be positively correlated with PD-L1 expression and associated with immune responses.

Conclusions:

• A novel risk assessment model based on irlncRNA pairs can predict immunotherapy efficacy in TNBC.
• The lncRNA USP30-AS1 is a potential therapeutic target for TNBC, linked to PD-L1 expression and immune responses.