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Acute myeloid leukaemia (AML) is a blood cancer with a heterogeneous genomic landscape. This study aimed to mine bioinformatics data generated by RNA sequencing to unveil an AML case transcriptome profile and identify novel therapeutic targets and markers. In this study, we have determined the transcriptomic profile and analysed gene variants of an AML patient at the time of diagnosis and validated some genes by quantitative reverse transcriptase polymerase chain reaction. ADAMTS14, ARHGAP22, and ependymin-related protein 1 (EPDR1) were markedly upregulated compared to the corresponding control. In addition, novel exonic single-nucleotide and insertion/deletion variants were identified in these genes. Hence, ADAMTS14, ARHGAP22, and EPDR1 can be proposed as potential novel targets in AML, and their exact roles should be further explored.