JOURNAL ARTICLE
Spatially Resolved Transcriptomic Profiling of PRAME Oncogene Expression in Skin Cutaneous Melanoma: Elucidating Dermato-Oncology Therapy through Molecular Docking.
Published In: Journal of Computational Biophysics & Chemistry, 2024, v. 23, n. 10. P. 1289 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Naveed, Muhammad; Jamil, Hamza; Aziz, Tariq; Makhdoom, Syeda Izma; Rehman, Muzammil Ur; Khan, Ayaz Ali; Alhomrani, Majid; Alsanie, Walaa F.; Alamri, Abdulhakeem S. 3 of 3
Abstract
Background: Skin cutaneous melanoma (SKCM) is a highly aggressive form of skin cancer characterized by rapid metastasis and poor prognosis. PRAME (Preferentially Expressed Antigen in Melanoma) is an oncogene overexpressed in various cancers, including melanoma, and is implicated in tumorigenesis and immune evasion. Understanding the spatial expression patterns of PRAME in SKCM can provide insights into the disease mechanism and therapeutic targets. Aim of the Study: This study aims to spatially resolve the transcriptomic profile of PRAME in SKCM and evaluate the therapeutic potential of selected dermato-oncology agents through molecular docking. Methods: Spatial transcriptomics was performed on SKCM tissue samples from 30 patients to map PRAME expression. Differential expression analysis and spatial clustering were conducted. Molecular docking using HDock assessed the binding affinities of PRAME with dermato-oncology agents: vemurafenib, dioxybenzone and octocrylene, as well as their conjugates (O-D: octocrylene-dioxybenzone, O-V: octocrylene-vemurafenib and D-V: dioxybenzone-vemurafenib). Chemsketch facilitated the creation of conjugates, and Pymol was used for visualization. Results: PRAME was significantly upregulated in SKCM tissues, with a mean expression level of 8.5 TPM compared to 1.2 TPM in normal tissues (p < 0.001). HDock analysis revealed that dioxybenzone had a binding energy of –106.08 kcal/mol, octocrylene –107.04 kcal/mol, and vemurafenib –114.15 kcal/mol. The conjugates showed improved binding affinities: O-D had –142.93 kcal/mol, O-V had –152.69 kcal/mol and D-V had –184.53 kcal/mol, with D-V showing the most substantial binding affinity. Conclusion: Spatial transcriptomic profiling highlights PRAME as a key biomarker in SKCM. The molecular docking results indicate that D-V conjugates (dioxybenzone-vemurafenib) possess the highest binding affinity (–184.53 kcal/mol), suggesting a promising therapeutic potential for SKCM treatment. These findings support further investigation into D-V conjugates as targeted treatments for melanoma. Future Prospects: Future research should focus on in vivo validation of the identified therapeutic agents and exploring the role of PRAME in SKCM pathogenesis. Additionally, combining spatial transcriptomics with other omics data could enhance our understanding of the tumor microenvironment and lead to novel therapeutic approaches. Spatial transcriptomic profiling reveals significant upregulation of the PRAME oncogene in SKCM tissues, highlighting its role in melanoma pathogenesis. Molecular docking analyses demonstrate that the dioxybenzone-vemurafenib (D-V) conjugate exhibits the strongest binding affinity to PRAME, suggesting a promising therapeutic candidate for targeted dermato-oncology treatment. This study underscores the potential of integrating spatial transcriptomics and molecular docking to identify effective therapies for melanoma. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Computational Biophysics & Chemistry. 2024/12, Vol. 23, Issue 10, p1289
- Document Type:Article
- Subject Area:Health and Medicine
- Publication Date:2024
- ISSN:2737-4165
- DOI:10.1142/S2737416524500431
- Accession Number:181120475
- Copyright Statement:Copyright of Journal of Computational Biophysics & Chemistry is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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