Evidence map›Paper›PMID 26282073›Full record

ArticleScientific reports2015

Systemic modeling myeloma-osteoclast interactions under normoxic/hypoxic condition using a novel computational approach.

Zhiwei Ji, Dan Wu, Weiling Zhao, Huiming Peng, Shengjie Zhao, Deshuang Huang, Xiaobo Zhou

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 32 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Zhiwei Ji1] 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.
Dan WuDivision of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Weiling ZhaoDivision of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Huiming PengDivision of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Shengjie ZhaoSchool of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China 201804.
Deshuang HuangSchool of Electronics and Information Engineering, Tongji University, Shanghai, P.R. China 201804.
Xiaobo ZhouDivision of Radiologic Sciences - Center for Bioinformatics and Systems Biology, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA 27157.
Wake Forest University · USTongji University · CN

Funding

Modelling the Growth of the MIC Niche at the System LevelU01CA166886 · NCI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ZHOU, XIAOBO · 2012 to 2016
$2.2M
itNETZ: Integrative and Translational Network-based Cellular Signature AnalyzerU01HL111560 · NHLBI · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ZHOU, XIAOBO · 2011 to 2013
$1.1M
NCI NIH HHS U01 CA166886NCI NIH HHS U01CA166886-03NHLBI NIH HHS U01HL111560-04
6 · The paper itself

Abstract

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.

Indexed as

Cell CommunicationModels, BiologicalAlgorithmsBone MarrowCell HypoxiaCell Line, TumorComputer SimulationHumansMultiple MyelomaNeoplasm ProteinsOsteoclastsOxygenProgramming, LinearTumor MicroenvironmentNeoplasm ProteinsOxygen

Identifiers

PMID26282073
PMCPMC4539608
OpenAlexW1202305710

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.