Molecular Systems Architecture of Interactome in the Acute Myeloid Leukemia Microenvironment

Abstract

A molecular systems architecture is presented for acute myeloid leukemia (AML) to provide a framework for organizing the complexity of biomolecular interactions. AML is a multifactorial disease resulting from impaired differentiation and increased proliferation of hematopoietic precursor cells involving genetic mutations, signaling pathways related to the cancer cell genetics, and molecular interactions between the cancer cell and the tumor microenvironment, including endothelial cells, fibroblasts, myeloid-derived suppressor cells, bone marrow stromal cells, and immune cells (e.g., T-regs, T-helper 1 cells, T-helper 17 cells, T-effector cells, natural killer cells, and dendritic cells). This molecular systems architecture provides a layered understanding of intra- and inter-cellular interactions in the AML cancer cell and the cells in the stromal microenvironment. The molecular systems architecture may be utilized for target identification and the discovery of single and combination therapeutics and strategies to treat AML.

Analysis of m6A-related signatures associated with the tumor immune microenvironment and predict survival in acute myeloid leukemia

“…AML is an aggressive clonal disease of hematopoietic stem cells and primitive progenitor cells that can prevent bone marrow differentiation and produce self-renewing leukemia stem cells (LSCs) ( 28 ). Paris et al revealed that the mRNA m6A reader YTHDF2 was overexpressed in a broad spectrum of human AML and was a unique therapeutic target that inhibited the selective targeting of LSCs and promoted hematopoietic stem cell amplification ( 29 , 30 ). To date, previous studies have mostly focused on the internal mechanisms of tumors, and little has been done to investigate the potential regulatory relationship between m6A methylation and TIME, including the unclear role of m6A regulators in AML prognosis.…”

The genesis and evolution of acute myeloid leukemia stem cells in the microenvironment: From biology to therapeutic targeting

“…(1) The CXCL12/CXCR4 axis plays a key role in LSC maintenance and can activate multiple signaling pathways, such as PI3K/AKT/mTOR, to regulate the survival and proliferation of LSC [ 98 ]; (2) The interaction between VLA4 from LSC cells and fibronectin (FN) from MSCs activates the PI3K/AKT/BCL2 pathway, allowing LSCs to be resistant to cytotoxic drugs [ 99 ]; (3) The binding of E-selectin to CD44 activates the Wnt [ 100 ] and PI3K/AKT/NF-κB signaling pathway [ 101 ], and promotes LSC survival; (4) The binding of Jagged to Notch activates the Notch signaling pathway, and the intracellular domain NICD of Notch is then released and translocated into the nucleus to activate the transcription of related genes [ 102 ]; (5) Hypoxia can promote the HIF-1α-VEGF signaling pathway and angiogenesis. In addition, NF-κB can promote the production of MMPs and VEGF, which in turn accelerates angiogenesis [ 103 ]; (6) LSC-secreted exosomes can induce the expression of DKK1 in MSCs, a suppressor of normal hematopoiesis and osteogenesis, thereby leading to the loss of osteoblasts [ 50 ]. BCL-2 B-cell lymphoma 2; Fn fibronectin; MMPs matrix metalloproteinases; mTOR mammalian target of rapamycin; NF-κB nuclear transcription factor-κB; OPN osteopontin; VLA4 very late antigen 4; Wnt wingless-type protein.…”

Mechanistic Understanding of D-Glucaric Acid to Support Liver Detoxification Essential to Muscle Health Using a Computational Systems Biology Approach

“…Emerging modern bioinformatics and computational systems biology methodologies, performed in silico-meaning on the computer, provide the opportunity to explore such complex systems. Once such platform is CytoSolve ® (version 5.204) which is a well-established computational systems biology framework of technology and processes that provide the capability to derive molecular mechanisms of action, to create quantitative and predictive models of those mechanisms, and to employ the resultant models to simulate complex biomolecular phenomena [ 22 , 23 , 24 , 25 , 26 , 27 ]. The study herein employs CytoSolve, a proven computational systems biology approach to: (1) identify potential molecular mechanisms involved in liver detoxification affected by GA; and (2) quantitatively predict the effect of GA in aiding liver detoxification.…”

“…The study herein employs CytoSolve, a proven computational systems biology approach to: (1) identify potential molecular mechanisms involved in liver detoxification affected by GA; and (2) quantitatively predict the effect of GA in aiding liver detoxification. Previous work has demonstrated the viability of using such a computational systems biology approach to model complex biomolecular phenomena [ 23 , 26 , 27 , 28 , 29 , 30 , 31 ].…”