Identification of integrated stress response-related prognostic genes in high-grade serous ovarian cancer using Mendelian randomization, single-cell RNA sequencing, and bulk RNA sequencing

BackgroundThe integrated stress response (ISR) can cause high-grade serous ovarian cancer (HGSOC) cells to arrest in G1 phase, significantly suppressing their hyperproliferation. Nevertheless, the specific molecular mechanisms of the ISR in HGSOC remain unclear.MethodsThis study integrated HGSOC- and ISR-related data. Prognostic genes were identified via differential expression, Mendelian randomization, and univariate Cox analyses. The risk model was constructed and evaluated using the risk score. Then, gene set enrichment analysis, drug sensitivity analyses, and single-cell RNA sequencing were used to explore risk model-related mechanisms, and reverse transcription quantitative polymerase chain reaction (RT-qPCR), western blotting, and immunohistochemical staining were applied to detect prognostic gene expression.ResultsFour prognostic genes (NUP35, CASP3, BAG5, and DNAJB1) for HGSOC were identified. Using the risk score to classify patients into high- and low-risk groups, the model accurately predicted patients’ prognoses. The PPAR signaling pathway was significantly enriched in both risk groups. The half-maximum inhibition concentration of NPK76-II-72–1 was positively correlated with DNAJB1 expression. Moreover, BAG5 and DNAJB1 expression changed dynamically during epithelial cell differentiation. RT-qPCR, western blotting, and immunohistochemical staining demonstrated that NUP35, CASP3, and BAG5 were upregulated in HGSOC, consistent with the results of Wilcoxon’s analysis.ConclusionsThis study developed an ISR-associated prognostic model for HGSOC, which could improve patient prognosis.