Virtual patient analysis identifies strategies to improve the performance of predictive biomarkers for PD-1 blockade.

Autor:	Arulraj T; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205., Wang H; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205., Deshpande A; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Bloomberg Kimmel Immunology Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205., Varadhan R; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205., Emens LA; Kaiser Permanente, South Sacramento, CA 95823., Jaffee EM; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Bloomberg Kimmel Immunology Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205., Fertig EJ; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Convergence Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Bloomberg Kimmel Immunology Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Department of Applied Mathematics and Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218., Santa-Maria CA; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205., Popel AS; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205.; Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD 21205.
Jazyk:	angličtina
Zdroj:	Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2024 Nov 05; Vol. 121 (45), pp. e2410911121. Date of Electronic Publication: 2024 Oct 28.
DOI:	10.1073/pnas.2410911121
Abstrakt:	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. Competing Interests: Competing interests statement:L.A.E. has served as a paid consultant for F. Hoffmann-La Roche, Genentech, Macrogenics, Lilly, Chugai, Silverback, Shionogi, CytomX, GPCR, Immunitas, DNAMx, Gilead, Mersana, Immutep, and BioLineRx. L.A.E. also has an executive role at the Society for Immunotherapy of Cancer and has ownership interest in MolecuVax. L.A.E. is a former employee of Ankyra Therapeutics with the potential for future stock options. E.M.J. reports personal fees from Genocea, Achilles, DragonFly, Candel Therapeutics, Carta, NextCure. E.M.J. has had other support from Abmeta, the Parker Institute, and grants and other support from Lustgarten, Genentech, AstraZeneca, and Break Through Cancer outside of the submitted work. E.J.F. is on the Scientific Advisory Board of Viosera Therapeutics/Resistance Bio and is a consultant to Mestag Therapeutics. C.A.S.-M. has research funding from Pfizer, AstraZeneca, Merck, GSK/Tesaro, Novartis, and Bristol Myers Squibb and has served on advisory boards for Bristol Myers Squibb, Merck, Genomic Health, Seattle Genetics, Athenex, Halozyme, and Polyphor. A.S.P. is a consultant to Incyte, J&J/Janssen, and is co-founder and consultant to AsclepiX Therapeutics; he receives research funding from Merck. The terms of these arrangements are being managed by the Johns Hopkins University in accordance with its conflict-of-interest policies.
Databáze:	MEDLINE
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