Evidence map›Paper›PMID 37799074›Full record

ArticleHuman vaccines & immunotherapeutics2023

Identification of key immune cell-related genes involved in tumorigenesis and prognosis of cervical squamous cell carcinoma.

Chunxiao Yan, Yanyan Ma, Junyan Li, Xuejun Chen, Jiong Ma

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Human vaccines & immunotherapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Chunxiao YanSchool of Medicine, Department of Gynecology, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
Yanyan MaSchool of Medicine, Department of Gynecology, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
Junyan LiSchool of Medicine, Department of Gynecology, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
Xuejun ChenSchool of Medicine, Department of Gynecology, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.
Jiong MaSchool of Medicine, Department of Gynecology, The Second Affiliated Hospital of Zhejiang University, Hangzhou, China.ORCID 0000-0002-0537-4584

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The infiltration of immune cells can significantly affect the prognosis and immune therapy of patients with cervical squamous cell carcinoma (CSCC). This study aimed to explore key immune cell-related genes in the tumorigenesis and prognosis of CSCC. The module significantly related to immunity was screened by weighted gene co-expression network analysis (WGCNA) and ESTIMATE analysis, followed by correlation analysis with clinical traits. Key candidate genes were intersected with the protein-protein interaction (PPI) network genes for immune-related genes. The relationship between immune cell infiltration and key genes was analyzed. Tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) predicted the response to immunotherapy in CSCC patients. Clinically, quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry were manipulated for analyzing the changes in mRNA and protein expression of key genes in cancer. Western blot was conducted to assess the correlation between key genes and immune infiltration. The brown module was notably associated with the immune microenvironment of CSCC, from which three immune-related key genes (

Indexed as

Carcinoma, Squamous CellUterine Cervical NeoplasmsB-LymphocytesCarcinogenesisFemaleHumansPrognosisTumor Microenvironmentcervical squamous cell carcinomaESTIMATEimmunotherapyWGCNA

Identifiers

PMID37799074
PMCPMC10561582

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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.