Analysis of Gene Expression Data of RPL10 Mutant T-Cell Leukemia by SEMsubPA

Abstract

This paper describes the analysis of T-cell acute lymphoblastic leukemia (T-ALL) samples with an R98S missense mutation in ribosomal protein L10 (RPL10) compared to samples affected by T-ALL but without the mutation. The goal was to characterize the effect of RPL10 mutations on mRNA gene expression level. To this end, a novel tool called SEMsubPA was used, which allowed to detect significant KEGG sub-pathways and differentially expressed genes (DEGs) in one step. The tool exploits the potential of multi-group structural equation modeling for the discovery of the significant sub-pathways. Furthermore, it allows to test the significance of the connections between the genes in each significant sub-pathway. The most relevant components of the final biological network were characterized by Gene Ontology enrichment analysis based on Biological Process (BP) and Molecular Functions (MF). The analysis revealed key sub-pathways involved in necroptosis, MAPK signaling pathway and T-cell receptor signaling pathways. In addition, the network and enrichment analyses discovered key cancer genes such as AKT1, RIPK1, RIPK3, MYC and H1F1A as well as important molecular functions such as cellular oxidative stress, protein folding and kinase activity. Finally, the performance of SEMsubPA was compared against 3 other pathway and one sub-pathway analysis method. SEMsubPA was by far the best, detecting 81% of the total number of reference pathways, whereas the maximum performance of the other methods was 5%.