Glyoxalase 1: Emerging biomarker and therapeutic target in cervical cancer progression

Abstract

Introduction: Cervical cancer presents a significant global health challenge, disproportionately impacting underserved populations with limited access to healthcare. Early detection and effective management are vital in addressing this public health concern. This study focuses on Glyoxalase-1 (GLO1), an enzyme crucial for methylglyoxal detoxification, in the context of cervical cancer.

Methods: We assessed GLO1 expression in cervical cancer patient samples using immunohistochemistry. In vitro experiments using HeLa cells were conducted to evaluate the impact of GLO1 inhibition on cell viability and migration. Single-cell RNA sequencing (scRNA-seq) and gene set variation analysis were utilized to investigate the role of GLO1 in the metabolism of cervical cancer. Additionally, public microarray data were analyzed to determine GLO1 expression across various stages of cervical cancer.

Results: Our analysis included 58 cervical cancer patients, and showed that GLO1 is significantly upregulated in cervical cancer tissues compared to normal cervical tissues, independent of pathological findings and disease stage. In vitro experiments indicated that GLO1 inhibition by S-p-bromobenzylglutathione cyclopentyl diester decreased cell viability and migration in cervical cancer cell lines. Analyses of scRNA-seq data and public gene expression datasets corroborated the overexpression of GLO1 and its involvement in cancer metabolism, particularly glycolysis. An examination of expression data from precancerous lesions revealed a progressive increase in GLO1 expression from normal tissue to invasive cervical cancer.

Conclusions: This study highlights the critical role of GLO1 in the progression of cervical cancer, presenting it as a potential biomarker and therapeutic target. These findings contribute valuable insights towards personalized treatment approaches and augment the ongoing efforts to combat cervical cancer. Further research is necessary to comprehensively explore GLO1's potential in clinical applications.

Fig 1. Analysis of GLO1 expression in gynecological cancer tissue through IHC staining.

(A) Representative GLO1 staining of cervix, endometrium and ovary tissues (scale bar, 50 μm). (B) GLO1 IHC score comparison between cervical cancer and normal tissues. Statistical analysis of data was performed using the t-test (**** P<0.0001).

Fig 2. Effect of GLO1 inhibition and knockdown on viability and migration of HeLa cells.

(A) The wound healing assay evaluating the effect of GLO1 inhibitor (BBGC) on the HeLa cell migration ability at 24h, 48h and 72 hours (scale bar, 200 μm). (B) Quantitative analysis of the wound closure of HeLa cells. (C) The effect of GLO1 inhibitor (8 μM and 10 μM) on HeLa cell viability by MTT assay. (D) After 48h of treatment with GLO1 inhibitor, the mRNA levels of GLO1, BCL2 and BAX in the HeLa cell lysates were analyzed by qPCR. (E) The wound healing assay evaluating the effect of GLO1 knockdown with siRNA on HeLa cell migration ability at 24, 48, and 72 h (scale bar, 200 μm). (F) Quantitative analysis of the wound closure of HeLa cells. (G) The effect of GLO1 knockdown on HeLa cell viability by MTT assay. (H) The mRNA levels of GLO1, BCL2 and BAX in HeLa cell lysates after 48 h of GLO1 knockdown using GLO1 siRNA were analyzed by qPCR. Data are presented as mean ± SD. *P<0.05, **P<0.01. Statistical analysis of data was performed using the one-way ANOVA (***P<0.001; **P<0.01; *P<0.05) (three independent experiments).

Fig 3. Single-cell analysis of the expression of Glo1 in adjacent normal and tumor samples from patients with cervical squamous cell carcinoma.

(A) UMAP plot of the 44,848 cells, colored by cell types. (B) Distribution of 23,636 normal and 21,212 tumor cells in the UMAP plot. (C) GLO1 expression in epithelial cells from normal and tumor tissues. Cells not expressing GLO1 were excluded, resulting in 512 normal and 9,883 tumor cells. (D) Heatmap of GSVA enrichment scores for Wikipathways gene sets. Each column represents epithelial cells from normal and tumor tissues. Top 10 pathways are shown according to the logFC of average GSVA scores between tumor and normal epithelial cells.

Fig 4. GLO1 expression in normal, cervical intraepithelial neoplasia (CIN1 to CIN3), and cervical cancer tissue samples by microarray analysis.

Microarray data from the GEO database (GSE63514) were downloaded and visualized in the violin plots for 24 normal, 14 CIN1, 22 CIN2, 40 CIN3, and 28 cervical cancer samples. The Kruskal-Wallis test was used for global comparison across 5 subtypes, where the Dunn’s test was used for pairwise comparisons.