Precision Immunotherapy for Triple-Negative Breast Cancer – Plasma Proteomics
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Plasma Proteomics Predicts Immunotherapy Response in Triple-Negative Breast Cancer
Table of Contents
understanding Triple-Negative Breast Cancer (TNBC)
Triple-negative breast cancer (TNBC) remains one of the most aggressive and difficult-to-treat subtypes of breast cancer due to the absence of estrogen receptor,progesterone receptor,and human epidermal growth factor receptor 2 (HER2) amplification. Even though immunotherapy has emerged as a promising option for TNBC, responses are highly variable, and many patients experience either limited benefit or eventual disease progression. This has placed meaningful emphasis on the identification of predictive biomarkers to guide treatment decisions and improve outcomes for patients.
The Promise of Plasma proteomics and the PIPscore
Recent studies highlight the potential of plasma proteomics to change the way clinicians assess and optimize immunotherapy for TNBC. High-precision immune-related plasma proteomics profiling has demonstrated its ability to predict patient response to immunotherapy, offering a minimally invasive and scalable approach to biomarker testing.1 Through the measurement of immune-regulation-related proteins in the blood, researchers have created the Plasma Immune Profiling score (PIPscore), which is a classification tool that can now allocate patients more accurately than relying only on tumor tissue-based methods.
“This study transforms how we approach TNBC immunotherapy,” said Yizhou Jiang, PhD, co-corresponding author. “By translating complex plasma proteomics into a practical score, we’ve bridged the gap between research and clinical utility. the PIPscore not only predicts response but also opens doors to targeting metabolic pathways like arginine deprivation to overcome resistance. These findings underscore that systemic immunity, not just the tumor microenvironment, dictates treatment success.”1,2
Challenges in Predicting Immunotherapy Response in TNBC
Biomarkers that can effectively predict response to therapy in TNBC have been difficult to locate due to the heterogeneity of the disease. TNBC is fundamentally different from hormone receptor-positive or HER2-positive breast cancers, as it has no singled-out molecular driver, resulting in widely different treatment responses even among patient groups. Immunotherapy-checkpoint inhibitors in particular-has received a positive reaction in certain patient subgroups; however, it has been difficult to detect which ones will benefit most.3 Conventional biomarkers like PD-L1 expression have been inconsistent in efficacy prediction,reflecting the urgency for more reliable tools.