# Transcriptomic Profile of Glioblastoma Cells Infected with Zika Virus: A Systematic Review and Pathway Analysis

## TL;DR

This study reviews how Zika virus affects gene expression in glioblastoma cells and identifies key genes and pathways involved.

## Contribution

The paper identifies consistently upregulated genes and interferon-related pathways affected by Zika virus in glioblastoma models.

## Key findings

- 12 genes were consistently upregulated across studies, including DNAJB9, SESN2, and IFNB1.
- Pathway analysis revealed 23 commonly enriched pathways, mostly related to interferon signaling.
- Methodological differences among studies limit the comparability of results.

## Abstract

Glioblastoma (GBM) is an aggressive tumor with limited therapeutic options. Zika virus (ZIKV) has demonstrated activity against GBM; however, the cellular pathways behind this interaction remain unclear. We systematically reviewed open-access primary studies assessing differentially expressed genes (DEGs) in GBM models infected with wild-type or engineered ZIKV using transcriptomic approaches (inclusion criteria); reviews, restricted-access studies, commentaries, preprints, abstracts, and articles lacking data or not meeting these conditions were excluded (PROSPERO CRD420251077092). We performed a pathway analysis of reported DEGs. PubMed and Google Scholar were searched up to 5 March 2025; 139 records were identified and 5 met the eligibility criteria. Risk of bias was evaluated using an adapted ToxRTool for in vitro experiments and the SYRCLE RoB tool for in vivo models. Altogether, 4360 genes were reported as upregulated and 2072 as downregulated; 12 genes (DNAJB9, SESN2, PMAIP1, PPP1R15A, KLF4, ATF3, IFNB1, IFNL1, ANKRD33B, ZC3HAV1, OASL, and CCL5) were consistently upregulated, none were consistently downregulated. Pathway analysis of the studies providing complete DEG lists identified 23 commonly enriched pathways mostly related to interferon signaling. These findings may help guide future research in this field; nevertheless, methodological heterogeneity limits comparability, reinforcing the need for standardized protocols. Funding: ITpS, CNPq, and FAPEMIG.