Nature's Pharmacy: Harnessing Plant and Animal-Derived Agents for Cancer Therapy
Objective and Background: Studies have shown that phytochemicals from plants like flavonoids, terpenes, and alkaloids and peptides from animal sources can be very effective in cancers remission. Current review explores the potential of natural compounds from plants and animal sources in cancer treatment and examining how they complement or serve as alternatives to traditional therapies. Methods: In order to conduct the review; literature has been collected from 2004-2024 by pre-defined literature inclusion criteria. Literatures included based upon PRISMA and quality assessed by GRADE criteria. Findings: Flavonoids, terpenes, and alkaloids from plants and peptides from animal sources demonstrated strong anticancer activity by persuading apoptosis, inhibiting tumor cell growth, and preventing metastasis with potentially lower toxicity than conventional treatments. Paclitaxel from Taxus brevifolia, curcuma from Curcuma longa, asparaguses from Asparagus racemosus, vinblastine from Catharanthus roseus, solamargine from Solanum nigrum, ß-carotenoids from Moringa olefera, silamyrin from Silybum marianum, apigenin from Apium graveolens, plumbagin from Plumbago zeylanica, and many others have shown efficacy in inhibiting tumor growth of breast, colon, and prostate. Animal-derived products; melittin from bee venom, brevinin-2 and esculentin-1 from frog’s skin, chlorotoxin from scorpion venom, l-amino acid oxiase from snake venom, halichondrin B from marine sponge has inhibited cancer cells migration in multiple types of cancers. Conclusion: The integration of these natural compounds in oncology could yield more accessible, effective, and less toxic treatment options and contribute to sustainable, innovative approaches in healthcare. Nature’s pharmacy offers a plethora of natural remedies that are beneficial in oncological intervention.
Institutions
- Hamdard University (PK)
- Dow University of Health Sciences (PK)
Publication Details
- Journal
- SHILAP Revista de lepidopterología
- Published
- 2025-10-01
- Primary Topic
- Advanced Graph Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00