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Updated: May 28, 2026

Intracellular Phosphoflow Cytometry of Acute Myeloid Leukemia Patient-Derived Xenotransplants
Published on: June 6, 2025
Integrated Genomic Profiling of Newly Diagnosed and Relapsed Acute Myeloid Leukemia Identifies Driver Genes,
Harsh Goel1, Avanish Kumar Pandey1, Anshul Arya1
1Laboratory Oncology Unit, Dr. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences, New Delhi 110029, India.
Background/Objectives:
Acute myeloid leukemia (AML) is a hematologic malignancy of substantial genetic heterogeneity that exhibits clonal growth and blocked differentiation of myeloid progenitor cells in the bone marrow (BM). Genetic alterations play a vital role in the progression, initiation, and recurrence of AML. The aim of this study was to identify the somatic mutational landscape, pathway perturbations, mutational signatures, and druggability of baseline (at diagnosis) and relapsed AML to determine possible treatment options.
Methods:
Between 2020 and 2026, 120 diagnostic BM or PB samples were prospectively collected from baseline (at diagnosis) AML patients at AIIMS, New Delhi. WES was conducted of 10 BM samples from five baseline (at diagnosis) and five relapsed patients with AML. Somatic variations were identified by GATK-Mutect2 and annotated by ANNOVAR. Driver genes and pathways were analyzed using Maftools, OncodriveCLUST, and clusterProfiler. Extraction of mutational signatures was performed with the help of SigProfilerExtractor, and evaluation of drug-gene interactions was carried out with the help of DGIdb. In addition, RT-PCR was performed to estimate the expression level of TET1. The recurrent TET1 variation was validated using Sanger sequencing and PCR amplification.
Results:
Missense mutations were the most common variant type in the cohort, and C > T transitions were the predominant nucleotide substitution pattern. There were recurrent mutations in core AML driver genes, including TET1, FLT3, and TP53, and relapsed samples demonstrated increased involvement and complexity of the signaling system. Pathway analysis revealed widespread dysregulation of carcinogenic networks, including RTK-RAS, WNT, TP53, and PI3K signaling. Mutational signature analysis identified COSMIC SBS5, SBS8, and SBS40, which are associated with mechanisms involving oxidative damage. A large number of actionable targets were identified through druggability screening, particularly involving epigenetic regulators and kinase-associated pathways. RT-PCR analysis also supported altered TET1 expression in AML samples. The TET1 A256V variant was detected and experimentally validated.
Conclusions:
This study highlights the somatic mutational landscape of baseline (at diagnosis) and relapsed AML and identifies recurrent driver genes, altered signaling pathways, mutational signatures, and actionable targets with possible therapeutic relevance. The integration of mutational and expression analyses further supports a potential role for TET1 in AML biology, although the functional significance of specific variants such as A256V remains uncertain.
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