medRxivGenetic & Genomic MedicinePreprint
Systematic review and network meta-analysis of drug combinations suggested by machine learning on genes and proteins, with the aim of improving the effectiveness of Ipilimumab in treating Melanoma.
Danial SafaeiiD, Ali Akbar KiaeiiD, Mahnaz BoushiD, Sadegh AbadijouiD, Alireza Khorramabadi, Nader SalariiD, Masoud Mohammadi, Elham Parichehreh
Abstract
Background(Importance)One of the most dangerous kinds of skin cancer, Melanoma, develops in the cells (melanocytes) that make melanin, the pigment responsible for giving your skin its color. As well as developing everywhere on the body, including the eyes, Melanoma can sporadic occur internally, such as in the nose or throat. It is unknown what causes all melanomas, although exposure to ultraviolet (UV) radiation from the sun, tanning salons, and lamps increases the risk of getting them. As a result, radiation exposure increases the chance of obtaining Melanoma. Limiting your exposure to UV radiation can help reduce your risk of Melanoma. (Objective) Due to the unknown nature of this disease and its severe impact on human genes, the use of safe and effective drug combinations for treatment is very important. Proposed drug combinations should be administered with the greatest positive effect on the genes involved. Therefore, it is important to suggest an effective drug combination that can significantly affect the genes involved. Method(Data sources) This systematic review and network meta-analysis searched various databases, including Science Direct, Embase, Scopus, PubMed, Web of Science (ISI), and Google Scholar, without a lower time limit and up until July 2022, for articles focused on drug combinations for managing Melanoma. The study utilized a network meta-analysis to explore the effectiveness of the proposed medication combination on genes and proteins that may act as potential targets for improving Melanoma treatment. ResultsThe results of this study show that the p-value between the proposed drug combination and Melanoma was 1.12E-08. This is while the p-value of Melanoma and only one drug has a maximum value of 0.0149. Therefore, the proposed drug combinations effectiveness for treating Melanoma has increased 74 times. A systematic review has investigated the validity of the proposed drug combinations, human genes network meta-analysis, and prescription drug information. ConclusionThe findings from this systematic review and meta-analysis suggest that the proposed drug combination reduces the p-value between Melanoma and genes that could potentially be targeted to slow the progression of the disease, ultimately improving its management. Therefore, selecting the appropriate drug combination is critical for enhancing community health and reducing per capita treatment expenses. HighlightsO_LIMelanoma is one of the most aggressive kinds of skin cancer, and it begins in the cells (melanocytes) responsible for producing melanin. C_LIO_LITherapy must make use of pharmacological combinations that are both safe and effective. C_LIO_LIAny proposed medication combinations must be delivered in a way that will have the maximum possible beneficial impact on the genes at play. C_LIO_LIIn this research, an effective pharmacological combination for the treatment of melanoma illness is investigated. C_LIO_LIThe results suggest that the suggested treatment combination is beneficial in the treatment of Melanoma, as it reduces the p-value between the disease and the genes identified as potential targets for therapy. This indicates that the proposed treatment approach has the potential to improve the management of Melanoma. C_LI
- organism: human
- assay: proteomics
- research focus: drug response / drug discovery
- approach: statistical model
- Citations
- 7
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