Evidence map›Paper›PMID 35530333›Full record

ArticleFrontiers in oncology2022

DNA Hypermethylation-Regulated CX3CL1 Reducing T Cell Infiltration Indicates Poor Prognosis in Wilms Tumour.

Tao Mi, Liming Jin, Zhaoxia Zhang, Jinkui Wang, Mujie Li, Chenghao Zhanghuang, Xiaojun Tan, Zhang Wang, Xiaomao Tian, Bin Xiang and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
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

8 citing papers in PubMed, 13 citations in OpenAlex.

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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

11 authors at 4 institutions in 2 countries.

Tao MiDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Liming JinDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Zhaoxia ZhangDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Jinkui WangDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Mujie LiDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Chenghao ZhanghuangDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Xiaojun TanDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Zhang WangDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Xiaomao TianDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Bin XiangDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Dawei HeDepartment of Urology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Chongqing Medical University · CNNational Clinical Research · USChina International Science and Technology Cooperation · CNChildren's Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To investigate the role of chemokines in Wilms tumours, especially their chemotaxis to immune cells and the role of DNA methylation in regulating the expression level of chemokines. Methods: RNAseqV2 gene expression and clinical data were downloaded from the TARGET database. DNA methylation data were downloaded from the GEO and cBioPortal database. The difference analysis and Kaplan-Meier(KM) analysis of chemokines were performed by edgeR package. Then predictive model based on chemokines was constructed by lasso regression and multivariate COX regression. ROC curve, DCA curve, Calibration curve, and Nomogram were used to evaluate the prognostic model. MCPcounter and Cibersort algorithm was used to calculate the infiltration of immune cells in Wilms tumour and para-tumour samples. Then the difference analysis of the immune cells was performed. The relationship between chemokines and immune cells were calculated by Pearson correlation. In addition, DNA methylation differences between Wilms tumour and para-tumour samples was performed. The correlation between DNA methylation and mRNA expression was calculated by Pearson correlation. Western blot(WB)and immunofluorescence were used to confirm the differential expression of CX3CL1 and T cells, and the correlation between them. Results: A total of 16 chemokines were differentially expressed in tumour and para-tumour samples. A total of seven chemokines were associated with survival. CCL2 and CX3CL1 were positively correlated with prognosis, while high expression of CCL3, CCL8, CCL15, CCL18 and CXCL9 predicted poor prognosis. By lasso regression and multivariate COX regression, CCL3, CCL15, CXCL9 and CX3CL1 were finally included to construct a prediction model. The model shows good prediction ability. MCPcounter and Cibersort algorithm both showed that T cells were higher in para-tumour tissues than cancer tissues. Correlation analysis showed that CX3CL1 had a strong correlation with T cells. These were verified by Weston blot and immunofluorescence. DNA methylation analysis showed that various chemokines were different in para-tumours and tumours. CX3CL1 was hypermethylated in tumours, and the degree of methylation was negatively correlated with mRNA expression. Conclusion: 1. There is low T cell infiltration in nephroblastoma. 2. Chemokines such as CX3CL1 indicate a favourable prognosis and positively correlate with the number of T cells. 3. chemokines such as CX3CL1 are negatively regulated by DNA hypermethylation.

Indexed as

chemokineDNA methylationimmune infiltrationT cellsWilms tumour

Identifiers

PMID35530333
PMCPMC9072742
OpenAlexW4224300710

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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.