A groundbreaking study has emerged from leading researchers at Fudan University Shanghai Cancer Center and the Shanghai Institute for Biomedical and Pharmaceutical Technologies, illuminating a transformative pathway in the treatment of triple-negative breast cancer (TNBC). This aggressive breast cancer subtype, characterized by the absence of estrogen receptor, progesterone receptor, and HER2 expression, has long defied targeted therapies, leaving immunotherapy as a beacon of hope with unpredictable outcomes. The team’s latest research harnesses the power of plasma proteomics to predict patient responses to immunotherapy with unprecedented accuracy, setting the stage for a revolution in personalized oncological care.
The crux of this study lies in the systemic analysis of immune-related proteins circulating in the plasma of TNBC patients. By meticulously profiling 92 proteins from blood samples taken before, during, and after immunotherapy treatment in a cohort of 195 patients, the researchers identified several key biomarkers—most notably ARG1, NOS3, and CD28—that correlate strongly with treatment outcomes. These proteins, intricately linked to immune activation and suppression pathways, provide a window into the patient’s systemic immune landscape, a dimension often overlooked in tumor-centric analyses.
The innovation of this research extends beyond biomarker identification. The authors introduce the Plasma Immuno Prediction Score (PIPscore), a sophisticated predictive model integrating six immune-related plasma proteins. Achieving a compelling accuracy of 85.8% in forecasting therapeutic response, the PIPscore represents a highly precise, non-invasive tool potentially capable of reshaping clinical decision-making. By stratifying patients into high- and low-response categories prior to treatment initiation, this scoring system empowers oncologists to tailor therapies more effectively, sparing non-responders from futile immunotherapy-associated toxicities and financial burdens.
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Historically, prognostication for TNBC response to immunotherapy has relied on biomarkers such as PD-L1 expression and tumor mutational burden, parameters fraught with inconsistency and invasive sampling requirements. This study addresses these limitations by leveraging the convenience and repeatability of liquid biopsy approaches. Plasma proteomics circumvents the intrinsic heterogeneity and sampling bias of tumor biopsies, offering a dynamic view of systemic immunity—critical for understanding the complex interplay between the tumor microenvironment and host immune mechanisms.
The temporal dynamics of plasma proteins revealed fascinating insights. Post-treatment samples from patients who achieved pathologic complete response exhibited elevated levels of immune-stimulatory molecules like CXCL9 and interferon-gamma (IFN-γ), emphasizing active immune engagement. Conversely, the observed expression pattern of ARG1 and CD28—upregulated in responders—and NOS3—downregulated in responders—highlights the nuanced balance of immune activation and suppression influencing therapeutic efficacy. These findings suggest that proteins like ARG1 play crucial roles in arginine metabolism pathways that potentiate T-cell functionality, while elevated NOS3 may contribute to an immunosuppressive milieu by limiting CD8+ T-cell infiltration into tumors.
Delving further, the integration of single-cell RNA sequencing data afforded a granular perspective linking circulating protein levels with cellular heterogeneity within the tumor microenvironment. The inverse relationship between NOS3 plasma concentrations and intratumoral CD8+ T-cell abundance underscores the relevance of systemic immunosuppression markers. This holistic, multi-omic approach bridges peripheral blood immune signatures with intratumoral cellular landscapes, offering robust validation of peripheral biomarkers as surrogates for tumor immune status.
The practical implications of the PIPscore extend to prognostic assessment. The model demonstrated remarkable prognostic power by accurately predicting 12-month progression-free survival with 96% precision. Such performance signals a paradigm shift from reactive treatment adjustments toward proactive patient stratification and real-time monitoring, enhancing the adaptability and responsiveness of immunotherapy regimens in clinical settings.
Dr. Yizhou Jiang, co-corresponding author of the study, emphasizes the transformative nature of this research: “Our findings transcend the tumor microenvironment, highlighting systemic immunity as the pivotal driver of immunotherapy outcomes in TNBC. By distilling complex plasma proteomics into the clinically actionable PIPscore, we have forged a bridge connecting cutting-edge research with tangible therapeutic decision-making.” This statement encapsulates the study’s dual contribution to scientific understanding and clinical utility.
The study’s implications transcend the borders of TNBC, suggesting a broader applicability of plasma proteomic profiling in predicting immunotherapy responses across diverse malignancies. Given the variability in patient responses to immune checkpoint inhibitors in cancers such as melanoma, lung, and bladder carcinoma, non-invasive predictive tools like the PIPscore could substantially enhance personalized treatment paradigms and resource allocation.
Technically, the research employed state-of-the-art high-sensitivity immunoassays for protein quantification, ensuring the detection of low-abundance proteins critical to immune function. Validation of proteomic data through enzyme-linked immunosorbent assays (ELISA) bolstered the reliability of the platform. The integration of temporal sampling, multi-protein analytics, and omics data fusion underscores a sophisticated methodological framework setting new standards for translational cancer immunology studies.
Moreover, the work highlights metabolic pathways—such as arginine metabolism modulated by ARG1—that may serve as future therapeutic targets. Understanding how metabolic modulation affects T-cell efficacy paves the way for combined therapeutic approaches that augment immunotherapy with metabolic interventions, potentially overcoming resistance mechanisms that have plagued TNBC management.
The non-invasive nature of plasma-based monitoring holds promise for revolutionizing patient management by enabling frequent, real-time assessment of immune status without the risks and discomfort associated with repeated biopsies. Dynamic monitoring of PIPscore during the treatment course may facilitate timely therapeutic modifications, maximizing benefit while minimizing unnecessary exposure to ineffective treatments.
This comprehensive study addresses critical gaps in the immunotherapy landscape for TNBC by demonstrating that systemic immunity, rather than tumor-localized immune signatures alone, dictates treatment success. The PIPscore, as a clinically translatable tool, epitomizes the convergence of advanced proteomics technology, systems biology, and precision medicine, heralding a new era in cancer immunotherapy grounded in individualized patient profiling.
With ongoing validation and prospective clinical trials anticipated, the PIPscore stands poised to become an indispensable instrument in oncology clinics worldwide. Its capacity to optimize patient selection, improve treatment outcomes, and reduce healthcare costs marks a significant leap toward truly personalized, immune-based cancer therapies.
Subject of Research: Immunotherapy response prediction in triple-negative breast cancer through plasma proteomics.
Article Title: High-precision immune-related plasma proteomics profiling predicts response to immunotherapy in patients with triple-negative breast cancer.
News Publication Date: July 4, 2025.
References: DOI 10.20892/j.issn.2095-3941.2025.0038.
Image Credits: Cancer Biology & Medicine.
Keywords: Immunotherapy, plasma proteomics, triple-negative breast cancer, ARG1, NOS3, CD28, PIPscore, systemic immunity, precision medicine.
Tags: ARG1 NOS3 CD28 biomarkersbiomarkers for personalized oncologyFudan University cancer researchimmune-related proteins in TNBCimmunotherapy response predictionimmunotherapy success in triple-negative breast cancerinnovative approaches to cancer therapyplasma proteomics in cancer treatmentprecision medicine in breast cancerpredictive models for immunotherapy outcomessystemic immune landscape analysistransformative pathways in cancer treatment
