ArticleProceedings of the National Academy of Sciences of the United States of America2024
Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Privacy and Security Throughout the Health Data Life Cycle: From Primary Care to Research Networks.Annual review of biomedical data science · 2026Review
- A Mechanistic Framework Integrating Renal QSP-PK-PD and Machine Learning for Baseline-Informed Stratification of Diuretic Resistance.The AAPS journal · 2026Article
- Multiscale modeling reveals synergy between CCL19 and PD-1 blockade in reshaping the TNBC microenvironment.NPJ systems biology and applications · 2026Article
- Quo Vadis translational neuroscience?Translational neuroscience · 2026Review
- Exploring tumor dynamics and responses of prostate cancer to IL-27 based treatment combinations through biodynamic imaging and RNA sequencing analyses.Scientific reports · 2025Article
- Directions of Immunotherapy for Non-Small-Cell Lung Cancer Treatment: Past, Present and Possible Future.International journal of molecular sciences · 2025Review
- Quantitative Calibration of a Spatial QSP Model Identifies Fibroblast Impact on HCC Immunotherapy.bioRxiv : the preprint server for biology · 2025Article
- Beyond RECIST: mathematical modeling and Bayesian inference reveal the importance of immune parameters in metastatic breast cancer.bioRxiv : the preprint server for biology · 2025Article
- Using mathematical modelling and AI to improve delivery and efficacy of therapies in cancer.Nature reviews. Cancer · 2025Review
- Combination of vascular surgery with novel vascular targeting agents as cancer therapeutics.Frontiers in oncology · 2025Review
- Digital patient modeling identifies predictive biomarkers of regorafenib response in elderly metastatic colorectal cancer.Frontiers in systems biology · 2025Article
- Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Identifying biomarkers for treatment of uveal melanoma by T cell engager using a QSP model.NPJ systems biology and applications · 2024Article
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Authors and funding
9 authors.
Funding
Abstract
Patients with metastatic triple-negative breast cancer (TNBC) show variable responses to PD-1 inhibition. Efficient patient selection by predictive biomarkers would be desirable but is hindered by the limited performance of existing biomarkers. Here, we leveraged in silico patient cohorts generated using a quantitative systems pharmacology model of metastatic TNBC, informed by transcriptomic and clinical data, to explore potential ways to improve patient selection. We evaluated and quantified the performance of 90 biomarker candidates, including various cellular and molecular species, at different cutoffs by a cutoff-based biomarker testing algorithm combined with machine learning-based feature selection. Combinations of pretreatment biomarkers improved the specificity compared to single biomarkers at the cost of reduced sensitivity. On the other hand, early on-treatment biomarkers, such as the relative change in tumor diameter from baseline measured at two weeks after treatment initiation, achieved remarkably higher sensitivity and specificity. Further, blood-based biomarkers had a comparable ability to tumor- or lymph node-based biomarkers in identifying a subset of responders, potentially suggesting a less invasive way for patient selection.
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