Mining of transcriptome identifies CD109 and LRP12 as possible biomarkers and deregulation mechanism of T cell receptor pathway in Acute Myeloid Leukemia

Abstract

Acute Myeloid Leukemia (AML) is a heterogeneous disease with highest mortality compared to other types of leukemia. There is a need to find the gene abnormalities and mechanisms behind them due to their heterogenic nature. The present study is aimed to understand genes, pathways and biomarker proteins influenced by transcriptomic deregulation due to AML. Differentially expressed gene (DEG), protein-protein interaction network, gene ontology, KEGG pathway, variant analysis and secretome analyses were performed using different AML RNAseq datasets. A total of 655 DEGs including 291 up-regulated and 364 down-regulated genes, which were satisfied with a fold change of 1.5 were identified. Top hub genes for AML were identified as TP53, PTPRC and AKT1. This integrative bioinformatics approach revealed the deregulation of T Cell Receptor (TCR) pathway and altered immune response related genes. The survival analysis revealed the associated deregulation of multiple TCR pathway related genes. Variant analysis identified the benign and likely benign nature of many important target genes and markers screened, which were found to have an important role in the progression of AML. DEGs and secretome analysis found out a set of seven molecules represents potential biomarkers for AML. In vitro analytical validation showed overexpression pattern of CD109 and LRP12 in AML cell line and HL-60 cells than the normal human bone marrow-derived stromal cell line HS-5. Here we report first time for CD109 and LRP12 as a possible biomarkers for the diagnostic significance. Amino acid substitutions detected by variant analysis and deregulation of immune checkpoint molecules revealed their role in reducing immune response and inability to fight cancer cells. In conclusion, this study highlights the possibility of new biomarkers for AML and the mechanism of decrease in immune response due to the downregulation of co-stimulatory immune molecules, which needs further clinical validation investigations.

Keywords

• Acute myeloid leukemia
• Network analysis
• Differential gene expression
• Gene ontology
• Secretome analysis
• Variant analysis