Evidence map›Paper›PMID 37653016›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2023

[Exploration of the Perturbation of PKIG in Lung Squamous Cell Carcinoma and the Role in Tumor Microenvironment Based on Bioinformatics Method].

Qing Liu, Haitian Li, Bin Li, Meiyu Ren, Zhenqing Li, Yuzhen Chen, Zhizhong Zheng, Yuqi Meng, Haiming Feng

Open access · greenAbstract readEnglish Abstract
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 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 citations in OpenAlex.

  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

9 authors at 2 institutions in 1 country.

Qing LiuDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Haitian LiDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Bin LiDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Meiyu RenDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Zhenqing LiDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Yuzhen ChenDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Zhizhong ZhengDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Yuqi MengDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Haiming FengDepartment of Thoracic Surgery, Lanzhou University Second Hospital, Lanzhou University Second Clinical Medical College, 
Lanzhou 730030, China.
Lanzhou University Second Hospital · CNLanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is the leading cause of cancer-related death worldwide, and patients have limited survival benefits from traditional treatments such as surgery, radiotherapy and chemotherapy. As a new treatment for lung cancer, immunotherapy has significantly prolonged the overall survival (OS) of patients. However, only some patients can benefit from it. We need to explore immunotherapy biomarkers more deeply to screen for advantages.

methodsThe original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, and the immunological and prognostic genes of lung squamous cell carcinoma (LUSC) were screened using R software and TIMER database. The expression of target genes was studied in TCGA and GEO databases, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and correlation analysis with tumor immune characteristics were performed by R software and TISIDB database.

resultsWe screened out a gene related to immunity and prognosis, cAMP dependent protein kinase inhibitor γ (PKIG), which is significantly differentially expressed in LUSC and normal tissues, and has important reference value for the diagnosis and prognosis assessment of LUSC. PKIG differential genes are mainly concentrated in the regulation of humoral immune response and other processes. The expression of PKIG was positively correlated with the infiltration level of regulatory T cells (Tregs) (r=0.340, P<0.001). In addition, the expression level of PKIG was positively correlated with the expression of chemokines/chemokine receptors such as chemokine C-C motif ligand 2 (CCL2) (r=0.503, P<0.001), CXC chemokine ligand 12 (CXCL12) (r=0.386, P<0.001) and CXC-chemokine receptor 4 (CXCR4) (r=0.492, P<0.001), and immunoinhibitors such as programmed cell death protein 1 (PDCD1) (r=0.359, P<0.001), cytotoxic T-lymphocyte associated antigen 4 (CTLA4) (r=0.375, P<0.001) and T cell immunoglobulin and ITIM domains (TIGIT) (r=0.305, P<0.001) in LUSC.

conclusionsThe immunological and prognostic gene PKIG in lung squamous cell carcinoma was screened through bioinformatics analysis. PKIG is highly correlated with LUSC prognosis and immune microenvironment, and is expected to be a potential biomolecular marker for LUSC immunotherapy.

Indexed as

Carcinoma, Non-Small-Cell LungCarcinoma, Squamous CellLung NeoplasmsHumansLigandsLungTumor MicroenvironmentLigandsBioinformaticscAMP-dependent protein kinase inhibitor γImmunotherapyLung neoplasmsTumor microenvironment

Identifiers

PMID37653016
PMCPMC10476207
OpenAlexW4386346745

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.