Evidence map›Paper›PMID 41059489›Full record

ReviewMedComm2025

The Role of Immune Checkpoint Inhibitors in Cancer Therapy: Mechanism and Therapeutic Advances.

Hengyi Chen, Hongling Yang, Lu Guo, Qingxiang Sun

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in MedComm, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 4 pooled it
–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

28 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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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

4 authors.

Hengyi ChenDepartment of Pulmonary and Critical Care Medicine The Seventh People's Hospital of Chongqing Chongqing China.
Hongling YangDepartment of Nephrology and Institute of Nephrology Sichuan Provincial People's Hospital School of Medicine Sichuan Clinical Research Centre for Kidney Diseases University of Electronic Science and Technology of China Chengdu China.
Lu GuoDepartment of Pulmonary and Critical Care Medicine Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China Chengdu China.
Qingxiang SunDepartment of Pulmonary and Critical Care Medicine Sichuan Provincial People's Hospital School of Medicine University of Electronic Science and Technology of China Chengdu China.ORCID https://orcid.org/0000-0002-9474-8882

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid development of immune checkpoint inhibitors has fundamentally changed the landscape of cancer treatment. These agents restore T cell-mediated antitumor immune responses by targeting key immune checkpoint molecules, thereby suppressing or eliminating tumors. However, their clinical application still faces multiple challenges, mainly including efficacy heterogeneity, drug resistance, immune-related adverse events. Furthermore, there is still a lack of reliable biomarkers for predicting efficacy and toxicity. More critically, there is absence of precise predictive models that can systematically integrate multiomics features, dynamic tumor microenvironment evolution, and patient individual differences to comprehensively address the above issues. This review systematically summarizes the latest advancements in this field. The main contents include emerging targets like lymphocyte activation gene 3, T cell immunoreceptor with immunoglobulin and tyrosine-based inhibitory motif domain, and mucin-domain-containing-3, combination strategies, and the current research status and limitations of various predictive biomarkers. Moreover, it focuses on the potential of microbiome regulation, metabolic reprogramming, and artificial intelligence-driven multiomics analysis technologies in achieving dynamic patient stratification and personalized treatment. By integrating the frontier research results and clinical insights, the review aims to provide a systematical theory framework and future directions for advancing precision immunotherapy.

Indexed as

combination therapyCTLA‐4drug resistanceimmune checkpoint inhibitorsPD‐1/PD‐L1precision immunotherapytumor microenvironment

Identifiers

PMID41059489
PMCPMC12497686

What OpenQuestion holds

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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.