Evidence mapPaperPMID 42249376Full record

ReviewMolecular cancer2026

Insight of immune checkpoint blockades in melanoma: mechanism and clinical translation.

Qingyan Zhang, Chunhui Yuan, Lin Zhu, Shaobing Zheng, Yantao Xu, Xuanlin Che, Shiyu Xiao, Juan Liu, Hong Liu, Hui Li and 1 more

Abstract readReview
In one paragraph

Review in Molecular cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Qingyan Zhang *The Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Chunhui Yuan *The Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Lin Zhu *The Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Shaobing ZhengThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Yantao XuThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Xuanlin CheThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Shiyu XiaoThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Juan LiuNational Medical Metabolomics International Collaborative Research Center, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China.
Hong LiuThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China. hongliu1014@csu.edu.cn.
Hui LiThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China. lihuiscience@163.com.
Xiang ChenThe Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, 410008, China. chenxiangck@126.com.

Funding

Central South University Graduate Student Research and Innovation Project No. 1053320240167Central South University Research Programme of Advanced Interdisciplinary Studies 2023QYJC004Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China JYB2025XDXM603Innovation Research Group Project of the National Natural Science Foundation of China No. 82221002the key Program of National Natural Science Foundation of China U22A20329the Key Program of National Natural Science Foundation of China No. 82130090the National Natural Science Foundation of China No. 82573819the National Natural Science Foundation of China Nos.82504074the Natural Science Foundation of Changsha No.kq2403025the Natural Science Foundation of Hunan Province No. 2024JJ6684the Natural Science Foundation of Hunan Province for Distinguished Young Scholars No. 2023JJ10096the Scientific Research Program of FuRong Laboratory No. 2023SK2095the Youth Science Foundation of Xiangya Hospital No. 2023Q20
6 · The paper itself

Abstract

Melanoma, a malignant tumor originating from melanocytes, accounts for only 4% of all skin cancers but is responsible for 75% of skin cancer-related deaths. In recent years, its incidence has steadily increased. Targeted therapies and immunotherapies have made significant strides, emerging as the most effective treatments for metastatic melanoma. Immune checkpoint blockades (ICBs) have become a central component of systemic therapy for advanced melanoma. However, their clinical use is limited by immune-related toxicities, primary and acquired resistance, and marked inter-patient heterogeneity in response. As a result, personalized treatment approaches are urgently needed. This paper provides a comprehensive review of recent advancements in melanoma immunotherapy, synthesizing findings from existing research and clinical trials. It highlights the progress made in understanding various immune checkpoints in melanoma and the outcomes of clinical trials involving different ICBs. The aim is to inform clinicians and patients about the latest developments in ICBs therapy while underscoring the critical role of personalized medicine in addressing the diverse needs of patients. Ultimately, the research seeks to catalyze further exploration and innovation in melanoma treatment.

Indexed as

Immune Checkpoint InhibitorsMelanomaSkin NeoplasmsAnimalsClinical Trials as TopicHumansImmunotherapyMolecular Targeted TherapyTranslational Research, BiomedicalImmune Checkpoint InhibitorsClinical trialCombination therapyCTLA-4Immune checkpoint blockadesMelanomaPD-1PD-L1

Identifiers

PMID42249376
PMCPMC13471329

What Socratic holds

Textmetadata
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 Socratic graph.