Evidence map›Paper›PMID 28404949›Full record

ArticleOncotarget2017

Metabolomics uncovers a link between inositol metabolism and osteosarcoma metastasis.

Ling Ren, Ellen S Hong, Arnulfo Mendoza, Sameer Issaq, Christine Tran Hoang, Michael Lizardo, Amy LeBlanc, Chand Khanna

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
2.4field-weighted citation impact, top 10% 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

36 citing papers in PubMed, 47 citations in OpenAlex.

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  16. Grading of endometrial cancer usingScientific reports · 2021
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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

8 authors at 3 institutions in 1 country.

Ling RenComparative Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Ellen S HongComparative Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Arnulfo MendozaMolecular Oncology Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Sameer IssaqMolecular Oncology Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Christine Tran HoangComparative Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Michael LizardoMolecular Oncology Section, Pediatric Oncology Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Amy LeBlancComparative Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Chand KhannaComparative Oncology Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA.
Center for Cancer Research · USMolecular Oncology (United States) · USNational Cancer Institute · US

Funding

COP LaboratoryZIABC011692 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI LEBLANC, AMY · 2016 to 2025
$15.5M
6 · The paper itself

Abstract

Cancer development and progression are characterized by complex molecular events. The acquisition of these events is primarily believed to result from alterations in gene and protein expression/function. Recent studies have also suggested the role of metabolic alterations, or "metabolic reprogramming," that may similarly contribute to these events. Indeed, our previous investigations in osteosarcoma (OS) identified metabolic changes uniquely linked to metastasis. Based on those findings, here we sought to build a more detailed understanding of the specific alterations in metabolites or metabolic pathways that may be responsible for the observed metastasis-associated metabolic alterations, suggested by gene expression data. This was pursued using a combination of high-throughput liquid- and gas-chromatography-based mass spectrometry (LC/MS and GC/MS) for a global metabolic profiling/subtraction of four pairs of high/low metastatic OS cell lines. By comparing the identity and level of the metabolites between high/low metastatic cells, several metabolic pathways were identified to be differentially activated, such as arginine, glutathione, inositol and fatty acid metabolic pathways. To further interrogate these results, we investigated the effects of inositol pathway dysregulation, through the exposure of metastatic OS cells to IP6 (inositol hexaphosphate). Although IP6 exposures had modest to minimal effects on cell proliferation, we observed reduced cellular glycolysis, down-regulation of PI3K/Akt signaling and suppression of OS metastatic progression. Collectively these data supported further investigation of metabolic sensitivities as anti-metastatic strategies in a clinical setting as well as investigation of altered metabolomics associated with metastatic progression.

Indexed as

AnimalsBone NeoplasmsCell Line, TumorHeterograftsHumansInositolMetabolomicsMiceNeoplasm InvasivenessOsteosarcomaPhytic AcidInositolPhytic AcidIP6metabolismmetastasisosteosarcoma

Identifiers

PMID28404949
PMCPMC5503552
OpenAlexW2594796113

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.