The hyaluronan-related genes HAS2, HYAL1-4, PH20 and HYALP1 are associated with prognosis, cell viability and spheroid formation capacity in ovarian cancer

Abstract

Purpose: Hyaluronan modulates tumour progression, including cell adhesion, cohesion, proliferation and invasion, and the cancer stem cell phenotype. In ovarian cancer, high levels of stromal hyaluronan are associated with poor prognosis. In this work, hyaluronan synthases (HAS1-3) and hyaluronidases (HYAL1-4, PH-20, HYALP1) were examined with regard to different levels of gene expression and its influence on ovarian cancer patients' survival. The impact of a siRNA depletion of HAS2 was investigated in vitro.

Methods: Using the Kaplan-Meier Plotter tool, we investigated the influence of hyaluronic synthases and hyaluronidases on the survival of a collective of 1435 ovarian cancer patients. Differences in gene expression between normal (n = 46) and cancerous (n = 744) ovarian tissue were examined using the TNMplot database. Following an evaluation of hyaluronan-related gene expression in the ATCC ovarian cancer panel, we studied SKOV3 and SW 626 ovarian cancer cells subjected to HAS2 siRNA or control siRNA treatment in terms of HAS1-3, HYAL2 and HYAL3 mRNA expression. We investigated the ability to form spheroids using the Hanging Drop method and the response to chemotherapy at different concentrations using the MTT Assay. By STRING analysis, interactions within the enzymes of the hyaluronic acid system and with binding partners were visualized.

Results: HAS1, HYAL1 and HYAL4 mRNA expression is significantly upregulated, whereas HAS2, HYAL2 and HYAL3 mRNA expression is significantly downregulated in ovarian cancer tissue compared to controls. HAS2 improves cell viability, the capability to form tumour spheroids and has a negative prognostic value regarding overall survival. Lower HAS2 expression and high expression of HYAL2 and HYAL3 favours the survival of ovarian cancer patients. HAS2 knockdown cells and control cells showed a moderate response to combinatorial in vitro chemotherapy with taxol and cisplatin.

Conclusion: In conclusion, our study shows that the hyaluronic acid system has a relevant influence on the survival of ovarian cancer patients and could therefore be considered as a possible prognostic factor.

Keywords: Gene expression; HAS2; Hyaluronan synthases; Hyaluronidases; Ovarian cancer; Survival analysis.

Fig. 1

The gene expression levels of HAS1, HAS2 and HYAL1-HYAL4 of normal ovarian tissue (n = 46) compared with tumour tissue of the ovary (n = 744). While HAS1, HYAL1 and HYAL4 expression levels were significantly lower in tumour tissue compared to control ovary, the expression of HAS2, HYAL2, and HYAL3 were significantly upregulated in tumours compared to controls. The data are derived from the TNMplot database (Bartha and Györffy 2021) (https://tnmplot.com/analysis/, accessed on 24 Feb 2022)

Fig. 2

Prognostic value of HAS2, HYAL2 and HYAL3 for the survival of patients with ovarian cancer. The analysis was done by the Kaplan–Meier-Plotter. For each enzyme the Kaplan–Meier-curve, the hazard ratio (95% confidence interval) and the p-value were given. a OS in correlation with HAS2 expression (n = 1656), b PFS in correlation with HAS2 expression (n = 1435), c PFS in correlation with HYAL2 (LuCA-2) (n = 1435), d PFS in correlation with HYAL3 (n = 1435)

Fig. 3

HAS1, HAS2, HAS3, HYAL2 and HYAL3 gene expression levels in SKOV3, Caov-3, SW 626 and PA-1ovarian cancer cells, as measured by qPCR. The mean value was given with the standard error. Data represent the results of 3 independent experiments with n = 2 or 3 independent replicates under the same conditions. The gene expression levels are shown relative to the expression in PA-1 cells, which were set to a mean value of 1

Fig. 4

Impact of HAS2 knockdown and its influence on HA production and the expression of HAS1, HAS3, HYAL2 and HYAL3 in SW 626 and SKOV3 ovarian cancer cells. a, b qPCR confirmation of HAS2 knockdown and impact on the expression of HA-related genes. The mean value is given with the standard error. Data represent the results of 4 independent experiments with n = 2 or 3 independent replicates under the same conditions. a The mean value was calculated out of 7 values, in 6 HAS2 knockdown samples the HAS2 expression levels were under the limit of detection. c Representative images of particle exclusion assay of SW 626 and SKOV3 pericellular space as readout of HA production. Cells were transfected for 24 h with 20 nM siRNA against HAS2 or scrambled control siRNA or treated with 2 U/ml Streptomyces hyalurolyticus hyaluronidase. d, e Quantification of HA pericellular matrix for SW 626 and SKOV3 cell lines. Data are shown as mean ± SEM of three independent experiments. Results are expressed as the ratio between the area of ECM delimited by red blood cells and the area of the cell by using ImageJ software. *p ≤ 0.05, ***p ≤ 0.0001

Fig. 5

Impact of HAS2-depletion on the sphere formation capacity of SKOV3 cells. Hanging drop method was used to show differences in cell cohesion and sphere formation capability of HAS2 knockdown SKOV3 cells compared to control SKOV3 cells. a, b Area and perimeter of the spheres excluding the diffuse edge. The area or perimeter of spheres of HAS2 knockdown and control cells was measured at day 4 and day 7. *p ≤ 0.05, c Representative pictures of spheres in drops of HAS2 knockdown cells and control cells. Note presence of a solid dark core and a light, diffuse edge. The values were built out of data of 4 experiments á 12 drops for HAS2 knockdown and control cells (n = 48). AU arbitrary unit

Fig. 6

Viability of HAS2 knockdown and control ovarian cancer cells at different concentrations of taxol and cisplatin, measured by MTT assay. a SKOV3 cells, b SW 626 cells. All values are given in % based on the concentration of control cells at 0.00 nM chemotherapy treatment. Results represent mean value ± SD for 3 experiments under same conditions. *p ≤ 0.05, **p ≤ 0.001

Fig. 7

STRING analysis for protein–protein interactions of HA pathway constituents. With the use of STRING database (https://string-db.org) the interactions of the proteins, analyzed in this study, are shown. Medium confidence threshold of 0.004