Evidence map›Paper›PMID 40574862›Full record

ReviewFrontiers in immunology2025

Advances and challenges in neoantigen prediction for cancer immunotherapy.

Yi Zhang, Ting-Ting Chen, Xiong Li, Ai-Lin Lan, Peng-Fei Ji, Ya-Juan Zhu, Xue-Yao Ma

Abstract readReview
PubMed Full text at PMC Publisher
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 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

  1. Personalized neoantigen mRNA vaccines for pancreatic cancer: the role of lipid nanoparticle delivery systems.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
    Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. 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.

Yi Zhang *The First Clinical Medical College of Lanzhou University, Lanzhou, China.
Ting-Ting Chen *Department of Gastroenterology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China.
Xiong Li *Department of Gastroenterology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Ai-Lin Lan *The First Clinical Medical College of Lanzhou University, Lanzhou, China.
Peng-Fei JiDepartment of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China.
Ya-Juan ZhuDepartment of Biotherapy and Cancer Center, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China.
Xue-Yao MaDepartment of Gynecology, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neoantigens, derived from tumor-specific mutations, are promising targets of cancer immunotherapy by eliciting tumor-specific T-cell responses while sparing normal cells. Accurate neoantigen prediction relies on immunogenomics and immunopeptidomics. Immunogenomics identifies tumor-specific mutations via next-generation sequencing. Immunopeptidomics detects MHC-presented peptides using mass spectrometry. Integrating these two methods enhances prediction accuracy but faces challenges due to tumor heterogeneity, HLA diversity, and immune evasion. Future advancements will focus on dynamic tumor microenvironment monitoring, multi-omics integration, improved computational models and algorithms to refine neoantigen prediction, and developing optimized personalized vaccines.

Indexed as

Antigens, NeoplasmImmunotherapyNeoplasmsAnimalsCancer VaccinesHumansMutationTumor MicroenvironmentAntigens, NeoplasmCancer Vaccinesbioinformaticscancer immunotherapyimmune evasionimmunopeptidomicsneoantigen predictionnext-generation sequencing

Identifiers

PMID40574862
PMCPMC12198247

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.