Abstract

Acral Lentiginous Melanoma (ALM) is a rare and aggressive form of melanoma that predominantly affects individuals with darker skin tones, posing significant challenges in both diagnosis and treatment. The growing demand for more personalized and effective treatments has led to the exploration of innovative approaches to tackle these challenges. This study integrates in silico drug design with comprehensive statistical analysis to identify and validate therapeutic targets specific to ALM. Key genes such as PLD1, CDKN2A, KIT, TERT, and NRAS were identified using advanced bioinformatics tools like DisGeNET, PANTHER DB, Network Analyst, and STRING DB. In parallel, a detailed demographic analysis involving 248 patients was conducted using SPSS, shedding light on factors influencing knowledge and awareness of ALM within affected populations. The findings from this dual approach emphasize the critical need for tailored therapeutic strategies that account for both genetic factors and patient demographics. The projected increase in ALM cases and the associated need for targeted therapies underscore the importance of continuing research into specialized treatments that can address the unique characteristics of this melanoma subtype. By advancing our understanding of ALM’s genetic profile and epidemiology, this study lays the foundation for the development of precision medicine solutions that could significantly improve patient outcomes and overall management of this aggressive disease.

Keywords

acral lentiginous melanoma, in-silico drug design, bioinformatics, targeted therapy, gene classification, biomarkers, genetic variation, signal transduction, tumour suppression, personalized medicine