Transcriptomic insights into skin cancer: A bioinformatics and network biology approach to biomarker identification

Abstract

Skin cancer is a widespread malignancy that primarily affects light-skinned populations globally, categorized into melanoma and non-melanoma skin cancers (NMSCs). Basal cell carcinoma and squamous cell carcinoma are the most common subtypes within NMSCs, with the global incidence of NMSCs projected to reach 2–3 million cases annually across regions like Europe, Canada, the USA, and Australia. Despite this prevalence, the genetic mechanisms behind skin cancer remain poorly understood. This study presents a novel gene discovery approach, leveraging transcriptome data from Next-Generation Sequencing datasets sourced from the European Nucleotide Archive to uncover new genes and pathways linked to skin cancer. The novelty of this research lies in its comprehensive approach that combines differential gene expression analysis with gene network and pathway enrichment analysis to identify actionable therapeutic targets. By utilizing bioinformatics tools such as DESeq2, Gene Set Enrichment Analysis (GSEA), and Cytoscape, we revealed critical gene interactions and pathways that have been underexplored in the context of skin cancer. Following rigorous quality control using FastQC and transcriptome-seq data alignment to the human genome (hg38), we identified 19 differentially expressed genes, including 2 down-regulated and 17 up-regulated. Key genes such as IL6, CCND2, PLAUR, and CD44 were found to be involved in important pathways like IL6_JAK_STAT3_SIGNALING, ANGIOGENESIS, and APICAL_SURFACE. These findings provide valuable insights into skin cancer pathogenesis and offer potential therapeutic targets, laying the groundwork for future research aimed at improving treatment outcomes.

Keywords

• DESeq analysis
• Transcriptome analysis
• Enrichment analysis
• GSEA