Evidence map›Paper›PMID 41451199›Full record

ReviewFrontiers in immunology2025

Traditional Chinese medicine as potential adjuvants for tumor vaccines: a review of types, mechanisms, and forms.

Yongjia Cui, Lutian Gong, Lei Chang, Wenping Lu, Siqing Zhao, Zhili Zhuo, Xiangyang Zhang

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Yongjia Cui *Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Lutian Gong *Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Lei Chang *Guang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Wenping LuGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Siqing ZhaoGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Zhili ZhuoGuang'anmen Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xiangyang ZhangBeijing University of Chinese Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapeutic cancer vaccines are increasingly recognized as a highly promising approach for tumor treatment; however, their clinical efficacy critically depends on the rational design of vaccine adjuvants. Natural compounds derived from Traditional Chinese Medicine (TCM) have emerged as attractive candidates for next-generation tumor vaccine adjuvants. In this review, we systematically summarize the chemical constituents of TCM-derived adjuvants reported in current research and categorize their mechanisms of action into four functional modalities: (i) immunostimulatory adjuvants that activate innate immune pathways; (ii) delivery-enhancing systems that improve antigen stability and facilitate targeting to antigen-presenting cells; (iii) integrated platforms that combine both immunostimulatory and delivery-enhancing functions; and (iv) other mechanisms involving non-canonical immunomodulatory activities. We further discuss current challenges in standardization, regulatory approval, and clinical translation, offering a roadmap for harnessing the potential of TCM in the rational design of cancer vaccines.

Indexed as

Adjuvants, ImmunologicCancer VaccinesDrugs, Chinese HerbalMedicine, Chinese TraditionalNeoplasmsAnimalsHumansAdjuvants, ImmunologicCancer VaccinesDrugs, Chinese Herbaladjuvantcold tumorsimmunotherapytraditional Chinese medicinetumor vaccines

Identifiers

PMID41451199
PMCPMC12727925

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.