Screening and prevention of ovarian cancer

Sideris, Michail; Menon, Usha; Manchanda, Ranjit

doi:10.5694/mja2.52227

Cited by 3 publications

(1 citation statement)

References 90 publications

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“…Consequently, higher death rates and the limited availability of effective treatment strategies have garnered significant attention from researchers worldwide. Given the grave statistics, with an estimated 314,000 new cases of ovarian cancer and 207,000 deaths annually worldwide, ovarian cancer stands as the most lethal gynecological malignancy ( Sideris et al, 2024 ). Alarmingly, in Australia, the incidence of ovarian cancer cases and deaths is projected to increase by 42% and 55%, respectively, by the year 2040, underscoring an urgent need for effective therapeutic strategies.…”

Section: Introductionmentioning

confidence: 99%

From desert flora to cancer therapy: systematic exploration of multi-pathway mechanisms using network pharmacology and molecular modeling approaches

Alblihy

2024

Front. Pharmacol.

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Ovarian cancer, often labeled a “silent killer,” remains one of the most compelling and challenging areas of cancer research. In 2019 alone, a staggering 222,240 new cases of ovarian cancer were reported, with nearly 14,170 lives tragically lost to this relentless disease. The absence of effective diagnostic methods, increased resistance to chemotherapy, and the heterogeneous nature of ovarian cancer collectively contribute to the unfavorable prognosis observed in the majority of cases. Thus, there is a pressing need to explore therapeutic interventions that offer superior efficacy and safety, thereby enhancing the survival prospects for ovarian cancer patients. Recognizing this potential, our research synergizes bioinformatics with a network pharmacology approach to investigate the underlying molecular interactions of Saudi Arabian flora (Onopordum heteracanthum, Acacia ehrenbergiana, Osteospermum vaillantii, Cyperus rotundus, Carissa carandas, Carissa spinarum, and Camellia sinensis) in ovarian cancer treatment. At first, phytoconstituents of indigenous flora and their associated gene targets, particularly those pertinent to ovarian cancer, were obtained from open-access databases. Later, the shared targets of plants and diseases were compared to identify common targets. A protein–protein interaction (PPI) network of predicted targets was then constructed for the identification of key genes having the highest degree of connectivity among networks. Following that, a compound–target protein–pathway network was constructed, which uncovered that, namely, hispidulin, stigmasterol, ascorbic acid, octopamine, cyperene, kaempferol, pungenin, citric acid, d-tartaric acid, beta-sitosterol, (−)-epicatechin gallate, and (+)-catechin demonstrably influence cell proliferation and growth by impacting the AKT1 and VEGFA proteins. Molecular docking, complemented by a 20-ns molecular dynamic (MD) simulation, was used, and the binding affinity of the compound was further validated. Molecular docking, complemented by a 20-ns MD simulation, confirmed the binding affinity of these compounds. Specifically, for AKT1, ascorbic acid showed a docking score of −11.1227 kcal/mol, interacting with residues Ser A:240, Leu A:239, Arg A:243, Arg C:2, and Glu A:341. For VEGFA, hispidulin exhibited a docking score of −17.3714 kcal/mol, interacting with Asn A:158, Val A:190, Gln B:160, Ser A:179, and Ser B:176. To sum up, both a theoretical and empirical framework were established by this study, directing more comprehensive research and laying out a roadmap for the potential utilization of active compounds in the formulation of anti-cancer treatments.

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Section: Introductionmentioning

confidence: 99%