Development and Validation of a Toxoplasma Infection-Associated Risk Model for Prognostic Stratification and Treatment Guidance in Glioma.

Overview

1. Yunnan Provincial Key Laboratory of Animal Nutrition and Feed, Faculty of Animal Science and Technology, Yunnan Agricultural University, Kunming 650201, China
2. Hangzhou Xiaoshan Donghai Aquaculture Co. Ltd. Hangzhou 311200, China; (Q.Y.); (X.Z.); (Y.C.)
3. Center for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, 110 Xiangya Road, Changsha 410078, China

Abstract

Gliomas are aggressive brain tumors with poor prognosis. The contribution of Toxoplasma gondii (T. gondii)-related transcriptional programs to glioma remains unclear. We identified T. gondii infection-related genes from neuroepithelial cell transcriptomes, mapped them to TCGA and CGGA glioma datasets, and validated their expression via RT-qPCR. A prognostic signature (TGRisk) was constructed via Cox and LASSO regression and validated across independent cohorts. Functional, immune, and drug sensitivity analyses were conducted. Forty infection-related genes were identified, enriched in stress responses, microRNA regulation, ribosome biogenesis, and metabolism. The 13-gene TGRisk model significantly separated survival between high- and low-risk groups. A nomogram combining TGRisk with clinical features improved prediction accuracy. High-risk tumors showed immune activation and higher infiltration of CD8+ T cells, Tregs, macrophages, and neutrophils, while low-risk tumors showed enhanced neuronal signaling and NK cell activity. Drug sensitivity prediction suggested low-risk patients were more responsive to temozolomide and bortezomib, whereas high-risk patients were more sensitive to dasatinib and ruxolitinib. We developed a novel T. gongdii infection-related gene signature that stratifies glioma patients by prognosis, immune features, and therapeutic vulnerabilities. These findings suggest host–T. gondii interactions and a potential biomarker for patient stratification and personalized therapy.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Data

Datasets cited

• geo:GSE22986, at NCBI GEO; found in “Data Availability Statement”

Data Availability Statement

The datasets supporting the conclusions of this study are publicly available. TCGA data can be accessed via https://portal.gdc.cancer.gov (accessed on 1 December 2025, CGGA data via http://www.cgga.org.cn/ (accessed on 1 December 2025), and GEO data under accession GSE22986 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22986) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE22986 (accessed on 1 December 2025).

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 29 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 7 authors, 4 keywords, 1 funder, 47 references.

Cite

This paper

Pan, L., Hu, Q., Yu, Q., Zhang, X., Chen, Y., Chen, F., & Deng, W. (2026). Development and Validation of a Toxoplasma Infection-Associated Risk Model for Prognostic Stratification and Treatment Guidance in Glioma. Biology, 15(8), 633. https://doi.org/10.3390/biology15080633

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