Expression of Adenosine A1, A2a, A2b, and A3 Receptors in Ovarian Cancer: Their Clinical Potential in Diagnosis and Prognosis Publisher Pubmed

Summary: Could adenosine receptors flag ovarian cancer? In a small tissue study, several receptor genes were more active in tumors and correlated with poorer survival. #OvarianCancer #Biomarkers

Azizi L ; Babaei Z ; Keyvanloo Shahrestanaki M ; Soltani S ; Panjehpour M ; Aghaei M
Source: Molecular Biology Reports Published:2026

Abstract

Background: Recent studies have emphasized the role of adenosine receptors (ADORs) in the malignant biological behaviors. Therefore, the expression and clinical significance of four subtypes of ADORs (ADORA1, ADORA2A, ADORA2B, and ADORA3) in ovarian tumors were analyzed. Methods and Results: The expression of ADORs in 24 pairs of ovarian tumor tissues and adjacent non-tumor tissues was measured by quantitative real-time PCR. The correlations between the investigated parameters and clinicopathological features were statistically tested. The diagnostic accuracy of ADORs was assessed using receiver operating characteristic curve analysis. Kaplan-Meier method was used to estimate the influence of ADORs expression on the prognosis of patients. Ovarian tumors showed higher expression of ADORA2A (1.5-fold), ADORA2B (2.2-fold), and ADORA3 (2.3-fold), but not ADORA1, compared to normal tissues. High expression of ADORA1 and ADORA2A was associated with younger age (≤ 48.5 years; P = 0.034) and clinical stage III-IV (P = 0.050), respectively. ADORA2B also showed moderate accuracy in ovarian tumors diagnosis (P = 0.001). Survival analyses further demonstrated that high expression of ADORA1 (P = 0.012) and ADORA2B (P = 0.027) was correlated with worse overall survival. Moreover, high ADORA3 expression (P = 0.042) was associated with poor post-progression survival. Conclusions: Our results demonstrated that adenosine A2A, A2B, and A3 receptors were differentially expressed between ovarian tumors and paired non-tumor tissues, and that ADORs may be clinically useful biomarkers for diagnosis and outcome prediction in ovarian cancer. © The Author(s), under exclusive licence to Springer Nature B.V. 2026.