RB1 Is an Immune-Related Prognostic Biomarker for Ovarian Cancer

Biao Xie; Guangqing Tan; Jingyi Ren; Weiyu Lu; Sadaf Pervaz; Xinyi Ren; Antonia Adwoa Otoo; Jing Tang; Fangfang Li; Yingxiong Wang; Meijiao Wang

doi:10.3389/fonc.2022.830908

RB1 Is an Immune-Related Prognostic Biomarker for Ovarian Cancer

Front Oncol. 2022 Mar 1:12:830908. doi: 10.3389/fonc.2022.830908. eCollection 2022.

Authors

Biao Xie¹, Guangqing Tan², Jingyi Ren², Weiyu Lu², Sadaf Pervaz³, Xinyi Ren², Antonia Adwoa Otoo³, Jing Tang⁴, Fangfang Li³, Yingxiong Wang³, Meijiao Wang^{2

3}

Affiliations

¹ Department of Biostatistics, School of Public Health and Management, Chongqing Medical University, Chongqing, China.
² Department of Physiology, School of Basic Medical Science, Chongqing Medical University, Chongqing, China.
³ Joint International Research Laboratory of Reproduction and Development of the Ministry of Education of China, School of Public Health and Management, Chongqing Medical University, Chongqing, China.
⁴ Department of Bioinformatics, School of Basic Medical Science, Chongqing Medical University, Chongqing, China.

Abstract

Background: Ovarian cancer (OC) is one of the most lethal gynecologic malignancies and a leading cause of death in the world. Thus, this necessitates identification of prognostic biomarkers which will be helpful in its treatment.

Methods: The gene expression profiles from The Cancer Genome Atlas (TCGA) and GSE31245 were selected as the training cohort and validation cohort, respectively. The Kaplan-Meier (KM) survival analysis was used to analyze the difference in overall survival (OS) between high and low RB transcriptional corepressor 1 (RB1) expression groups. To confirm whether RB1 was an independent risk factor for OC, we constructed a multivariate Cox regression model. Gene Ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analyses were conducted to identify the functions of differentially expressed genes (DEGs). The associations of RB1 with immune infiltration and immune checkpoints were studied by the Tumor Immune Estimation Resource (TIMER 2.0) and the Gene Expression Profiling Interactive Analysis (GEPIA). The immunohistochemistry (IHC) was performed to compare the expression level of RB1 in normal tissues and tumor samples, and to predict the prognosis of OC.

Results: The KM survival curve of the TCGA indicated that the OS in the high-risk group was lower than that in the low-risk group (HR = 1.61, 95% CI: 1.28-2.02, P = 3×10^-5), which was validated in GSE31245 (HR = 4.08, 95% CI: 1.21-13.74, P = 0.01) and IHC. Multivariate Cox regression analysis revealed that RB1 was an independent prognostic biomarker (HR = 1.66, 95% CI: 1.31-2.10, P = 2.02×10^-5). Enrichment analysis suggested that the DEGs were mainly involved in cell cycle, DNA replication, and mitochondrial transition. The infiltration levels of fibroblast, neutrophil, monocyte and macrophage were positively correlated with RB1. Furthermore, RB1 was associated with immune checkpoint molecules (CTLA4, LAG3, and CD274). The IHC staining revealed higher expression of RB1 in tumor tissues as compared to that in normal tissues (P = 0.019). Overexpression of RB1 was associated with poor prognosis of OC (P = 0.01).

Conclusion: These findings suggest that RB1 was a novel and immune-related prognostic biomarker for OC, which may be a promising target for OC treatment.

Keywords: RB1; immune infiltration; ovarian cancer; overall survival; prognosis.