Evidence map›Paper›PMID 41681894›Full record

ArticleCancers2026

Comprehensive Characterization of Stem Cell Landscape Identifies Novel Stemness-Relevant Genes for Nasopharyngeal Carcinoma Therapy.

Dahua Xu, Bocen Chen, Yutong Shen, Guoqing Deng, Peihu Li, Jiale Cai, Jiayao Chen, Jing Bai, Yuyue Tian, Man Xiao and 5 more

Abstract read
In one paragraph

Article in Cancers, 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
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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

15 authors.

Dahua XuSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Bocen ChenKey Laboratory of Biochemistry and Molecular Biology, Hainan Medical University, Haikou 571000, China.
Yutong ShenSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Guoqing DengSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Peihu LiSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Jiale CaiSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Jiayao ChenKey Laboratory of Biochemistry and Molecular Biology, Hainan Medical University, Haikou 571000, China.
Jing BaiSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Yuyue TianSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Man XiaoKey Laboratory of Biochemistry and Molecular Biology, Hainan Medical University, Haikou 571000, China.
Hong WangSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Hongyan JiangSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
Wangwei CaiKey Laboratory of Biochemistry and Molecular Biology, Hainan Medical University, Haikou 571000, China.
Bo WangSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.ORCID 0009-0009-4597-4750
Kongning LiSchool of Intelligent Medicine and Technology, Big Data Research Center, Hainan General Hospital and Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.ORCID 0000-0002-4928-6922

Funding

Hainan Provincial Natural Science Foundation of China 825QN315, 822RC698Major Science and Technology Program of Hainan Province ZDKJ2021040National Natural Science Foundation of China 32160152, 32460161
6 · The paper itself

Abstract

backgroundMetastasis and recurrence account for the failure of nasopharyngeal carcinoma (NPC) treatment. Growing evidence indicates the dominant roles of cancer stem cells (CSCs) in tumor progression and therapy resistance. However, the heterogeneity of CSCs and potential stemness-related markers in NPC patients are still largely unknown.

methodsConsensus clustering was first applied to identify robust stemness subtypes for NPC patients based on the activities of stem cell gene sets. The differences in clinical outcomes, tumor immune microenvironment (TIME), and drug response were compared between subtypes. The stemness-related markers were prioritized via weighted gene correlation network analysis (WGCNA) and Cox regression, and verified through in vitro experiments.

resultsNPC patients were classified into C1 and C2 subtypes. The C2 subtype exhibited higher activities of stem cell gene sets, worse prognosis, and aggressive tumor progression thus defined as stem cell-like tumor phenotype. The exclusionary relationships between tumor stemness and TIME infiltration were observed. The efficacy of several drugs and immunotherapy varied between NPC stemness subtypes. Through the WGCNA and survival analysis, we found that PSMC3IP, NABP2, CDC45, and HJURP were stemness-relevant genes. Sphere formation assays and analysis of the protein expression of stem cell markers by Western blotting revealed the roles of PSMC3IP, NABP2, CDC45, and HJURP in promoting CSC properties. Moreover, these genes were found to be related to the therapeutic effect of telomerase inhibitor in CCK8 experiments.

conclusionsThis study systematically characterized two NPC subtypes with distinct stemness features, clinical outcomes, and TIME features. Novel stemness-related markers will provide valuable targets against metastatic or recurrent NPC.

Indexed as

drug responseNPCprognosisstemnesstumor immune microenvironment

Identifiers

PMID41681894
PMCPMC12896439

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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.