Evidence map›Paper›PMID 35710862›Full record

ArticleScientific reports2022

Integrated analysis reveals the pivotal interactions between immune cells in the melanoma tumor microenvironment.

Jiawei Chen, Shan Hu, Huiqi Wang, Tingxiu Zhao, Yue Song, Xueying Zhong, Qingling Luo, Mansi Xu, Lina He, Qiugu Chen and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.9field-weighted citation impact, top 12% 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

14 citing papers in PubMed, 19 citations in OpenAlex.

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  9. Review
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  14. Article
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

13 authors at 1 institution in 1 country.

Jiawei Chen *Research Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Shan Hu *Research Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Huiqi Wang *Research Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Tingxiu ZhaoDepartment of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Yue SongResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Xueying ZhongResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Qingling LuoResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Mansi XuResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Lina HeResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Qiugu ChenResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China.
Biaoyan DuDepartment of Pathology, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China. dubiaoyan@gzucm.edu.cn.
Jianyong XiaoResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China. jianyongxiao@gzucm.edu.cn.
Kun WangResearch Center of Integrative Medicine, School of Basic Medical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China. wangkun@gzucm.edu.cn.
Guangzhou University of Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Melanoma is the most lethal type of skin cancer. Despite the breakthroughs in the clinical treatment of melanoma using tumor immunotherapy, many patients do not benefit from these immunotherapies because of multiple immunosuppressive mechanisms. Therefore, there is an urgent need to determine the mechanisms of tumor-immune system interactions and their molecular determinants to improve cancer immunotherapy. In this study, combined analysis of microarray data and single-cell RNA sequencing data revealed the key interactions between immune cells in the melanoma microenvironment. First, differentially expressed genes (DEGs) between normal and malignant tissues were obtained using GEO2R. The DEGs were then subjected to downstream analyses, including enrichment analysis and protein-protein interaction analysis, indicating that these genes were associated with the immune response of melanoma. Then, the GEPIA and TIMER databases were used to verify the differential expression and prognostic significance of hub genes, and the relationship between the hub genes and immune infiltration. In addition, we combined single cell analysis from GSE123139 to identify immune cell types, and validated the expression of the hub genes in these immune cells. Finally, cell-to-cell communication analysis of the proteins encoded by the hub genes and their interactions was performed using CellChat. We found that the CCL5-CCR1, SELPLG-SELL, CXCL10-CXCR3, and CXCL9-CXCR3 pathways might play important roles in the communication between the immune cells in tumor microenvironment. This discovery may reveal the communication basis of immune cells in the tumor microenvironment and provide a new idea for melanoma immunotherapy.

Indexed as

MelanomaSkin NeoplasmsBiomarkers, TumorGene Expression Regulation, NeoplasticHumansPrognosisTranscriptomeTumor MicroenvironmentBiomarkers, Tumor

Identifiers

PMID35710862
PMCPMC9203818
OpenAlexW4282981052

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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.