ReviewFrontiers in oncology2026
Biomarkers for predicting and monitoring the efficacy of cancer vaccines.
Review in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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0 citing papers in PubMed.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cancer vaccines are a modern approach to personalized anti-tumor therapy for malignant neoplasms based on stimulating the patient's immune system to target tumor cells. Many studies have demonstrated the impressive efficacy of anti-tumor vaccines in treating patients with different localization, type and stage of neoplasm. One of the major obstacles to the widespread implementation of cancer vaccines into clinical practice is the lack of reproducible biomarkers to evaluate and predict the efficacy of tumor vaccine therapy. The most commonly used methods for assessing a patient's immune status are ELISA and flow cytometry, which make it possible to assess the activation of the patient's immune system. However, multiple clinical trials have not yet demonstrated the reproducibility of these study results. This review includes description of efficacy biomarkers and methods for their evaluation used in a number of tumor vaccines' clinical and preclinical trials, and discuss the challenges of applying the biomarkers in real-world clinical practice.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.