Evidence mapPaperPMID 36389798Full record

ArticleFrontiers in immunology2022

Identify the immune characteristics and immunotherapy value of CD93 in the pan-cancer based on the public data sets.

Aiyuan Guo, Jingwei Zhang, Yuqiu Tian, Yun Peng, Peng Luo, Jian Zhang, Zaoqu Liu, Wantao Wu, Hao Zhang, Quan Cheng

Open access · goldAbstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

16 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
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  12. Structural insight into CD93 recognition by IGFBP7.Structure (London, England : 1993) · 2024
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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

10 authors at 7 institutions in 1 country.

Aiyuan GuoDepartment of Dermatology, The Third Xiangya Hospital, Central South University, Changsha, China.
Jingwei ZhangDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
Yuqiu TianDepartment of Infectious Disease, Zhuzhou Central Hospital, Zhuzhou, China.
Yun PengDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
Peng LuoDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Jian ZhangDepartment of Oncology, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
Zaoqu LiuDepartment of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Wantao WuDepartment of Oncology, Xiangya Hospital, Central South University, Changsha, China.
Hao ZhangDepartment of Neurosurgery, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Quan ChengDepartment of Neurosurgery, Xiangya Hospital, Central South University, Changsha, China.
Central South University · CNXiangya Hospital Central South University · CNFirst Affiliated Hospital of Zhengzhou University · CNSecond Affiliated Hospital of Chongqing Medical University · CNSouthern Medical University · CNZhujiang Hospital · CNZhuzhou Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CD93 is a transmembrane receptor that is mainly expressed on endothelial cells. A recent study found that upregulated CD93 in tumor vessels is essential for tumor angiogenesis in several cancers. However, the underlying mechanisms are largely unexplored. Our present research systematically analyzed the characteristics of CD93 in tumor immunotherapy among 33 cancers. CD93 levels and co-expression of CD93 on cancer and stromal cells were detected using public databases and multiple immunofluorescence staining. The Kaplan-Meier (KM) analysis identified the predictive role of CD93 in these cancer types. The survival differences between CD93 mutants and WT, CNV groups, and methylation were also investigated. The immune landscape of CD93 in the tumor microenvironment was analyzed using the SangerBox, TIMER 2.0, and single-cell sequencing. The immunotherapy value of CD93 was predicted through public databases. CD93 mRNA and protein levels differed significantly between cancer samples and adjacent control tissues in multiply cancer types. CD93 mRNA expression associated with patient prognosis in many cancers. The correlation of CD93 levels with mutational status of other gene in these cancers was also analyzed. CD93 levels significantly positively related to three scores (immune, stromal, and extimate), immune infiltrates, immune checkpoints, and neoantigen expression.. Additionally, single-cell sequencing revealed that CD93 is predominantly co-expressed on tumor and stromal cells, such as endothelial cells, cancer-associated fibroblasts (CAFs), neutrophils, T cells, macrophages, M1 and M2 macrophages. Several immune-related signaling pathways were enriched based on CD93 expression, including immune cells activation and migration, focal adhesion, leukocyte transendothelial migration, oxidative phosphorylation, and complement. Multiple immunofluorescence staining displayed the relationship between CD93 expression and CD8, CD68, and CD163 in these cancers. Finally, the treatment response of CD93 in many immunotherapy cohorts and sensitive small molecules was predicted from the public datasets. CD93 expression is closely associated with clinical prognosis and immune infiltrates in a variety of tumors. Targeting CD93-related signaling pathways in the tumor microenvironment may be a novel therapeutic strategy for tumor immunotherapy.

Indexed as

NeoplasmsReceptors, ComplementEndothelial CellsHumansImmunologic FactorsImmunotherapyMembrane GlycoproteinsRNA, MessengerTumor MicroenvironmentImmunologic FactorsMembrane GlycoproteinsReceptors, ComplementRNA, MessengerCD93immunotherapymacrophagespan-cancerT cellstumor microenvironment

Identifiers

PMID36389798
PMCPMC9646793
OpenAlexW4307446350

What Socratic holds

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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 Socratic graph.