Genetic expression in cancer research: Challenges and complexity

Abstract

Cancer research is profoundly influenced by the complex interplay of gene expression, yet conventional studies often emphasize genes with high expression levels, potentially overlooking those that contribute subtly to tumorigenesis. This review challenges the standard paradigms by questioning the direct causality often attributed to high gene expression in cancer progression and underscores the importance of distinguishing correlation from causation. It highlights how traditional bulk data analysis might mask crucial cell-specific gene activities, a limitation increasingly addressed by emerging single-cell and spatial transcriptomics, albeit with their own inherent challenges. Additionally, the review delves into the critical roles of both oncogenes and tumor driver genes, advocating for a precise differentiation in research and therapy. Furthermore, it discusses the revolutionary impact of CRISPR technology in identifying essential genes for cancer cell survival, which, while crucial, may not necessarily drive cancer. The complexities of epigenetic regulation and the discrepancies between mRNA and protein expression levels are also explored, emphasizing the necessity for integrated approaches that combine transcriptomics, proteomics, and computational models. This integrated perspective is vital for developing targeted therapies that address the multifaceted nature of gene expression and its regulation in cancer, aiming to refine therapeutic strategies and enhance clinical outcomes.