Evidence map›Paper›PMID 41003950›Full record

ArticleDiscover oncology2025

Identification of immunoheterogeneous key prognostic protein ZC3H12D in OSCC and analysis of prognostic models and drug resistance.

Qianqian Wang, Shuai Qi, Jing He, Danyang Li, Taoli Deng

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In one paragraph

Article in Discover oncology, 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.

Qianqian Wang *Department of Oncology, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Shuai Qi *Department of stomatology, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Jing HeDepartment of Oncology, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Danyang LiDepartment of Pharmacology, College of Pharmacy, Harbin Medical University, Harbin, 150081, Heilongjiang, P.R. China.
Taoli DengDepartment of stomatology, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China. 280166329@qq.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe constructed a nomogram model utilizing key clinical and molecular biological variables to predict the 1-year, 3-year, and 5-year survival probabilities for patients with oral squamous cell carcinoma (OSCC). The model's predictive efficacy was assessed through calibration curves. Additionally, a detailed Spearman correlation analysis of the ZC3H12D gene was executed, with patient data stratified into high and low expression categories based on its expression levels for differential gene analysis. Following this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, as well as Gene Set Enrichment Analysis (GSEA), were performed on the identified differentially expressed genes to delineate their specific contributions to biological processes and metabolic pathways.

resultsThe nomogram model demonstrated a high degree of predictive accuracy, effectively predicting the survival probabilities of oral cancer. patientsThe correlation analysis of the ZC3H12D gene revealed significant correlations with various immune cell types. A total of 439 significantly differentially expressed genes were identified through differential gene analysis. GO and KEGG enrichment analyses, along with GSEA analysis, further elucidated the specific roles of these differentially expressed genes in biological processes and metabolic pathways. Moreover, immune infiltration analysis indicated significant differences between the high and low expression groups of ZC3H12D in terms of immune cell infiltration, immune scores, and ESTIMATE scores.

conclusionThe nomogram model constructed in this study provides a practical tool for prognostic assessment in OSCC patients. Additionally, the in-depth analysis of the ZC3H12D gene reveals its significant role in the occurrence and development of oral cancer, providing data support and a theoretical basis for further research.

Identifiers

PMID41003950
PMCPMC12474792

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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.