Evidence map›Paper›PMID 40552012›Full record

ArticleFrontiers in genetics2025

Bioinformatics analysis identifies ZBTB16 as a potential immune biomarker for lung cancer and pan-cancer.

Danfei Shi, Yunxiang Cai, Di Zhu, Xinmin Li, Yong Li

Abstract read
In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Danfei ShiDepartment of Pathology, First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Huzhou, Zhejiang, China.
Yunxiang CaiDepartment of Clinical Laboratory, First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Huzhou, Zhejiang, China.
Di ZhuDepartment of Clinical Laboratory, First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Huzhou, Zhejiang, China.
Xinmin LiDepartment of Clinical Laboratory, Chongqing Hospital of Traditional Chinese Medicine, ChongQing, China.
Yong LiDepartment of Clinical Laboratory, First Affiliated Hospital of Huzhou University, The First People's Hospital of Huzhou City, Huzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Lung cancer (LC) is a deadly cancer and a challenging public health problem worldwide. The aim of this study is to use bioinformatics to analyze the potential of ZBTB16 as an immune biomarker in lung cancer and various other cancers. Methods: Overlapping differentially expressed genes (DEGs) in LC were selected from GSE3268, GSE 1987, GSE31547 and GSE18842 gene expression data sets. We conducted a comprehensive bioinformatics analysis of these differentially expressed genes, aiming to explore their enrichment functions and pathways, relative expression levels, interaction networks, and weighted gene co expression network (WGCNA) module analysis. Then, the potential role of ZBTB16 in the occurrence and progression of lung cancer was verified, and immune invasion analysis, pan-cancer analysis and mRNA-miRNA link analysis were performed. Results: There were 16 genes with increased expression and 100 genes with decreased expression. Among them, KEGG analysis showed that these DEGs were significantly involved in complement and coagulation cascades, as well as related pathways such as proximal tubular bicarbonate recovery. Previous studies have shown that ZBTB16 plays an important role in various systemic tumors, but its function in lung cancer has not been revealed. WGCNA analysis shows that ZBTB16 is significant in lung cancer. Therefore, we will focus our attention on ZBTB16. Then, TCGA database, Human Protein Atlas database, and whole blood qPCR testing were used to verify the differential expression of ZBTB16 in lung cancer, and immune invasion analysis of ZBTB16 in lung cancer, pan cancer analysis of ZBTB16, and mRNA miRNA linkage analysis of ZBTB16 were performed. Conclusion: Three validation methods and pan cancer analysis all showed that the expression of ZBTB16 was reduced in lung cancer and various cancers, which may be a key gene for the occurrence and development of lung cancer and various cancers.

Indexed as

DEGsimmune biomarkerlung cancerTCGAWGCNA

Identifiers

PMID40552012
PMCPMC12183232

What Socratic holds

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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.