IT-ENABLED WGCNA FOR CRITICAL GENE MODULE MAPPING AND THERAPY OPTIMIZATION: ADVANCING LEUKEMIA CARE

Abstract

Acquiring a profound comprehension of the complex correlation between genes is essential for progressing treatment and diagnostics in acute leukemia research. This work utilizes WGCNA to analyze the gene expression data obtained from 72 patients diagnosed with acute leukemia. This approach has not been widely employed in this particular setting previously. Our first objective was to identify essential gene modules and core genes that could offer a novel insight into the fundamental causes of the disease. To ensure the precision of the gene expression data, a thorough pre-processing is carried out, which includes normalization and quality control techniques. The WGCNA technique produces a gene co-expression network that targets explicitly differentially expressed genes (DEGs). This network is designed primarily to exploit pairwise correlations, as the underlying data is meant to create such a network. The modules identified via hierarchical clustering are assigned distinct colors to aid in recognizing gene expression patterns and associations that may not be readily apparent when examining individual genes in isolation. An essential component of our research involved identifying pivotal genes inside these modules using several centrality metrics, including degree, closeness, and betweenness centralities. These genes are suspected to have a crucial role in starting and progressing acute leukemia. We must mention that genes such as M91438_at and S82362_s_at came out as significant, in line with their centrality in the network analysis. However, it is privileged that these results hold a promise for further validation. The study throws open trails for future research, especially in experimental validation of these genes. These findings indeed have the potential to contribute to the development of targeted therapies and improvement in diagnostic methods, resulting in better patient outcomes in acute leukemia. This study also highlights the applicability of WGCNA towards unraveling leukemia's genomics, underscoring the continued exploration in this critical area of medical research.