Evidence map›Paper›PMID 42144879›Full record

ArticleBioscience reports2026

Lipid metabolism as a marker for glioma aggressiveness.

Hennrique Taborda Ribas, Guilherme Taborda Ribas, Arquimedes Paixão de Santana-Filho, Ana Gabriela Jungles, Clementina Mesaros, Dieval Guizelini, Glaucia R Martinez, Marina Trombetta-Lima, Guilherme Lanzi Sassaki, Sheila M B Winnischofer

Abstract read
In one paragraph

Article in Bioscience reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Hennrique Taborda RibasPostgraduate Program in Biochemistry Sciences, Sector of Biological Sciences, Federal University of Paraná, Curitiba, Brazil.
Guilherme Taborda RibasProfessional and Technological Education Sector, Federal University of Paraná, Curitiba, Paraná, Brazil.
Arquimedes Paixão de Santana-FilhoBiochemistry and Molecular Biology Department, Sector of Biological Sciences, Federal University of Paraná, Curitiba, Brazil.
Ana Gabriela JunglesPostgraduate Program in Biochemistry Sciences, Sector of Biological Sciences, Federal University of Paraná, Curitiba, Brazil.ORCID 0009-0001-1772-465X
Clementina MesarosDepartment of Systems Pharmacology and Translational Therapeutics (SPATT), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, U.S.A.ORCID 0000-0001-5117-2038
Dieval GuizeliniProfessional and Technological Education Sector, Federal University of Paraná, Curitiba, Paraná, Brazil.
Glaucia R MartinezPostgraduate Program in Biochemistry Sciences, Sector of Biological Sciences, Federal University of Paraná, Curitiba, Brazil.
Marina Trombetta-LimaFaculty of Science and Engineering, Department of Pharmaceutical Technology and Biopharmacy, Research Institute of Pharmacy (GRIP), University of Groningen, Groningen, Netherlands.ORCID 0000-0002-3687-6210
Guilherme Lanzi SassakiPostgraduate Program in Biochemistry Sciences, Sector of Biological Sciences, Federal University of Paraná, Curitiba, Brazil.
Sheila M B WinnischoferPostgraduate Program in Biochemistry Sciences, Sector of Biological Sciences, Federal University of Paraná, Curitiba, Brazil.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 307066/2012-6Conselho Nacional de Desenvolvimento Científico e Tecnológico 307066/2012-6; 311177/2021-2; 311259/2021-2; 408400/2025-0Conselho Nacional de Desenvolvimento Científico e Tecnológico 311177/2021-2Conselho Nacional de Desenvolvimento Científico e Tecnológico 311259/2021-2Conselho Nacional de Desenvolvimento Científico e Tecnológico 408400/2025-0Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.321693/2019-00Dutch Ministry of Education, Culture and Science (OCW) N/ADutch Ministry of Education, Culture and Science (OCW) Sector Plan Beta IIFederal University of Paraná 23075.045886/2021-85Federal University of Paraná 23075.045886/2021-85; 88887.311742/2018-00; 23075.045886/2021-85; 23075.061661/2025-08Federal University of Paraná 23075.061661/2025-08Federal University of Paraná 88887.311742/2018-00
6 · The paper itself

Abstract

Glioblastoma (GBM) is the most aggressive type of central nervous system tumor. There have been advances in glioma biology understanding; however, the current therapies are still inefficient. Additionally, new molecular markers are being explored for glioma grading, offering potential for novel diagnostic and drug targets. Considering the important role of lipid metabolism in tumorigenesis, understanding the lipid-related pathways in glioma could lead to new important markers. Here, lipid metabolism was analyzed by integrating two different data sources, the transcriptome data from The Cancer Genome Atlas and experimental data from tumor cells, to investigate how lipid metabolism is regulated in glioma. We compared the expression of 743 lipid-related genes in public RNAseq data of glioma patients (n = 681) to lipidomic analyses of glioblastoma cell lines (A172, U87MG, and T98G). We identified 29 lipid-related genes correlated to prognosis and constructed a risk signature based on these genes. Extracellular matrix-related genes were positively correlated to the risk score. Our findings revealed that aggressiveness is linked to alterations in membrane composition, characterized by an increase in phospholipids, coupled with a decrease in cholesterol and fatty acid unsaturation levels, which impact membrane physical properties. Modulation of critical signaling lipids, specifically sphingolipids, was also observed. Here, we identify lipid markers that may play a significant role in glioma. The converging axis involving sphingomyelinase and sphingosine-1-phosphate, mediated by the actions of sphingomyelinase SMPD1 and sphingosine-kinase SPHK1, emerged as a pivotal factor in glioma. The present study suggests that lipid membrane composition is pivotal for the GBM aggressiveness.

Indexed as

Biomarkers, TumorBrain NeoplasmsGene Expression Regulation, NeoplasticGlioblastomaLipid MetabolismCell Line, TumorCholesterolHumansPhospholipidsPrognosisSphingolipidsBiomarkers, TumorCholesterolPhospholipidsSphingolipidsgliomaLipid metabolismlipidomicplasma membrane

Identifiers

PMID42144879
PMCPMC13234697

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Registered trials

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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.