Evidence map›Paper›PMID 26967245›Full record

ArticleOncotarget2016

Exploring the role of sphingolipid machinery during the epithelial to mesenchymal transition program using an integrative approach.

Anastasia Meshcheryakova, Martin Svoboda, Ammar Tahir, Harald C Köfeler, Alexander Triebl, Felicitas Mungenast, Georg Heinze, Christopher Gerner, Philip Zimmermann, Markus Jaritz and 1 more

Open access · diamondAbstract read
In one paragraph

Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

19 citing papers in PubMed, 29 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

11 authors at 5 institutions in 1 country.

Anastasia MeshcheryakovaDepartment of Pathophysiology and Allergy Research, Medical University of Vienna, Vienna, Austria.
Martin SvobodaDepartment of Pathophysiology and Allergy Research, Medical University of Vienna, Vienna, Austria.
Ammar TahirInstitute of Analytical Chemistry, University of Vienna, Vienna, Austria.
Harald C KöfelerCore Facility for Mass Spectrometry, Center for Medical Research, Medical University of Graz, Graz, Austria.
Alexander TrieblCore Facility for Mass Spectrometry, Center for Medical Research, Medical University of Graz, Graz, Austria.
Felicitas MungenastDepartment of Pathophysiology and Allergy Research, Medical University of Vienna, Vienna, Austria.
Georg HeinzeSection for Clinical Biometrics, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University Vienna, Vienna, Austria.
Christopher GernerInstitute of Analytical Chemistry, University of Vienna, Vienna, Austria.
Philip ZimmermannNebion AG, Zürich, Switzerland.
Markus JaritzResearch Institute of Molecular Pathology, Vienna Biocenter, Vienna, Austria.
Diana MechtcheriakovaDepartment of Pathophysiology and Allergy Research, Medical University of Vienna, Vienna, Austria.
Medical University of Vienna · ATMedical University of Graz · ATUniversity of Vienna · ATResearch Institute of Molecular Pathology · ATStatistics Austria · AT

Funding

Austrian Science Fund FWF P 22441Austrian Science Fund FWF P 23228
6 · The paper itself

Abstract

The epithelial to mesenchymal transition (EMT) program is activated in epithelial cancer cells and facilitates their ability to metastasize based on enhanced migratory, proliferative, anti-apoptotic, and pluripotent capacities. Given the fundamental impact of sphingolipid machinery to each individual process, the sphingolipid-related mechanisms might be considered among the most prominent drivers/players of EMT; yet, there is still limited knowledge. Given the complexity of the interconnected sphingolipid system, which includes distinct sphingolipid mediators, their synthesizing enzymes, receptors and transporters, we herein apply an integrative approach for assessment of the sphingolipid-associated mechanisms underlying EMT program. We created the sphingolipid-/EMT-relevant 41-gene/23-gene signatures which were applied to denote transcriptional events in a lung cancer cell-based EMT model. Based on defined 35-gene sphingolipid/EMT-attributed signature of regulated genes, we show close associations between EMT markers, genes comprising the sphingolipid network at multiple levels and encoding sphingosine 1-phosphate (S1P)-/ceramide-metabolizing enzymes, S1P and lysophosphatidic acid (LPA) receptors and S1P transporters, pluripotency genes and inflammation-related molecules, and demonstrate the underlying biological pathways and regulators. Mass spectrometry-based sphingolipid analysis revealed an EMT-attributed shift towards increased S1P and LPA accompanied by reduced ceramide levels. Notably, using transcriptomics data across various cell-based perturbations and neoplastic tissues (24193 arrays), we identified the sphingolipid/EMT signature primarily in lung adenocarcinoma tissues; besides, bladder, colorectal and prostate cancers were among the top-ranked. The findings also highlight novel regulatory associations between influenza virus and the sphingolipid/EMT-associated mechanisms. In sum, data propose the multidimensional contribution of sphingolipid machinery to pathological EMT and may yield new biomarkers and therapeutic targets.

Indexed as

Cell Line, TumorEpithelial-Mesenchymal TransitionGene Regulatory NetworksHumansLipid MetabolismNeoplasmsSphingolipidsTranscriptomeSphingolipidsepithelial to mesenchymal transitionlung cancermultigene signaturesphingolipid-related targetssphingosine 1-phosphate/ceramide rheostat

Identifiers

PMID26967245
PMCPMC5008362
OpenAlexW2294944558

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.