Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach.
Interaction of myeloma cells with osteoclasts (OC) can enhance tumor cell expansion through activation of complex signaling transduction networks. Both cells reside in the bone marrow, a hypoxic niche. How OC-myeloma interaction in a hypoxic environment affects myeloma cell growth and their response to drug treatment is poorly understood. In this study, we i) cultured myeloma cells in the presence/absence of OCs under normoxia and hypoxia conditions and did protein profiling analysis using reverse phase protein array; ii) computationally developed an Integer Linear Programming approach to infer OC-mediated myeloma cell-specific signaling pathways under normoxic and hypoxic conditions. Our modeling analysis indicated that in the presence OCs, (1) cell growth-associated signaling pathways, PI3K/AKT and MEK/ERK, were activated and apoptotic regulatory proteins, BAX and BIM, down-regulated under normoxic condition; (2) β1 Integrin/FAK signaling pathway was activated in myeloma cells under hypoxic condition. Simulation of drug treatment effects by perturbing the inferred cell-specific pathways showed that targeting myeloma cells with the combination of PI3K and integrin inhibitors potentially (1) inhibited cell proliferation by reducing the expression/activation of NF-κB, S6, c-Myc, and c-Jun under normoxic condition; (2) blocked myeloma cell migration and invasion by reducing the expression of FAK and PKC under hypoxic condition.
1] School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China 201804 [2] Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Zhiwei
Z
Ji
Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Dan
D
Wu
Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Weiling
W
Zhao
Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Huiming
H
Peng
School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China 201804.
Shengjie
S
Zhao
School of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China 201804.
Deshuang
D
Huang
Division of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Xiaobo
X
Zhou
D000465:Algorithms; D001853:Bone Marrow / Q000378:metabolism / Q000473:pathology; D002450:Cell Communication; D015687:Cell Hypoxia; D045744:Cell Line, Tumor; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D009101:Multiple Myeloma / Q000378:metabolism* / Q000473:pathology; D009363:Neoplasm Proteins / Q000378:metabolism*; D010010:Osteoclasts / Q000378:metabolism* / Q000473:pathology; D010100:Oxygen / Q000378:metabolism*; D011382:Programming, Linear; D059016:Tumor Microenvironment
D009363:Neoplasm Proteins; D010100:Oxygen