Abstract PO1-07-04: Multiomics analysis reveals the landscape of PD-L1 expression in triple-negative breast cancer

Abstract Background: Tumor-infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) remain controversial in predicting clinical outcomes of triple-negative breast cancer (TNBC), as outcomes do not always correlate with the expression of these biomarkers. Genomic and transcriptomic alterations that might contribute to the expression of these biomarkers remain incompletely uncovered. Methods: We evaluated PD-L1 immunohistochemistry (IHC) scores (SP142 and 28-8) and TILs in our TNBC multiomics dataset and two immunotherapy clinical trial cohorts. Then, we analyzed genomic and transcriptomic alterations correlated with TILs, PD-L1 expression and patient outcomes. Results: Despite TILs serving as a decent predictor for TNBC clinical outcomes, there remained exceptions. Our study revealed that several genomic alterations were correlated with unexpected events. Particularly, PD-L1 expression may cause a paradoxical relationship between TILs and prognosis in certain patients. Consequently, we classified TNBCs into four groups based on PD-L1 and TIL levels. The TIL-PD-L1+ and TIL+PD-L1- groups were not typical “hot” tumors; both were associated with worse prognoses and lower immunotherapy efficacy than TIL+PD-L1+ tumors. Copy number variation of PD-L1 and oncogenic signaling activation were correlated with PD-L1 expression in the TIL-PD-L1+ group, whereas GSK3B-induced degradation might cause undetectable PD-L1 expression in the TIL+PD-L1- group. These factors have the potential to affect the predictive function of both PD-L1 and TILs. Conclusions: Several genomic and transcriptomic alterations may cause paradoxical effects among TILs, PD-L1 expression and prognosis in TNBC. Investigating and targeting these factors will advance precision immunotherapy for TNBC patients. Keywords: Triple-negative breast cancer, PD-L1 expression, Tumor-infiltrating lymphocytes, Multiomics, Immunotherapy Citation Format: Han Wang, Xiao-Hong Ding, Cheng-Lin Liu, Yi Xiao, Ruo-Hong Shui, Yan-Ping Li, Chen Chen, Wen-Tao Yang, Zhi-Ming Shao, Yi-Zhou Jiang. Multiomics analysis reveals the landscape of PD-L1 expression in triple-negative breast cancer abstract. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-07-04.