Exploring the anticancer potential of new pyrazolopyrimidine analogues as multi-target directed EGFR/STAT3 downregulatory candidates with apoptotic potential

Abstract

Cancer causes about 8 million deaths each year. The EGFR plays a pivotal role in prompting cells to grow and survive, making it a major target for cancer treatment. Besides, STAT3 is essential for the development, growth, and maintenance of tumors. Moreover, multitarget-directed ligands can potentially offer better treatment results and improve the health of patients. Hence, novel pyrazolopyrimidine analogues (6a–l) were designed to effectively inhibit both EGFR and STAT3 for cancer therapy by preserving the principal pharmacophores of EGFR and STAT3 inhibitors. Growth inhibition (GI)% of the pyrazolopyrimidines (6a–l) was recorded towards eleven cancer and one normal cell lines. Obviously, compound 6k revealed the highest mean GI% (65.61%) in comparison to doxorubicin (76.41%). Besides, compound 6k exhibited notably the lowest IC₅₀ (48.11 μM) in MDA-MB-468 cells in comparison to doxorubicin (11.39 μM), whereas compound 6h showed the lowest IC₅₀ (27.84 μM) in MDA-MB-231 cells surpassing doxorubicin (30.74 μM). In addition, compounds 6e and 6h displayed the most prominent inhibitory potential among the assessed compounds by remarkably downregulating EGFR and STAT3 protein expression, respectively. Furthermore, the apoptotic potential of compound 6k was pursued. The protein expressions of caspases 3, 8, and 9 as apoptotic markers were increased by 1.77, 1.36, and 1.25-fold, respectively. Besides, the protein expressions of CDK-2, 4, and 6 as anti-apoptotic markers were downregulated by 0.36, 0.70, and 0.66-fold, respectively. Furthermore, it was shown that compound 6k halted the G0 and S phases of the cell cycle by increasing the cellular levels to 13.84 and 28.22%, compared to 8.47 and 20.02% of the control cells, respectively. Accordingly, the afforded analogues can be considered lead anticancer ligands acting as dual EGFR/STAT3 inhibitors for further optimization.