Evidence map›Paper›PMID 31077268›Full record

ArticleNeuro-oncology2019

Proteomic analysis of meningiomas reveals clinically distinct molecular patterns.

Michail-Dimitrios Papaioannou, Ugljesa Djuric, Jennifer Kao, Shirin Karimi, Gelareh Zadeh, Kenneth Aldape, Phedias Diamandis

Abstract read
In one paragraph

Article in Neuro-oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
–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

24 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  10. Prognostic-Related Biomarkers in Pancreatic Ductal Adenocarcinoma Correlating with Immune Infiltrates Based on Proteomics.Medical science monitor : international medical journal of experimental and clinical research · 2023
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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.

Michail-Dimitrios PapaioannouPrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Ugljesa DjuricPrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Jennifer KaoPrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Shirin KarimiPrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Gelareh ZadehPrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Kenneth AldapePrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.
Phedias DiamandisPrincess Margaret Cancer Centre, MacFeeters Hamilton Centre for Neuro-Oncology Research, Toronto, Ontario, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMeningiomas represent one of the most common brain tumors and exhibit a clinically heterogeneous behavior, sometimes difficult to predict with classic histopathologic features. While emerging molecular profiling efforts have linked specific genomic drivers to distinct clinical patterns, the proteomic landscape of meningiomas remains largely unexplored.

methodsWe utilize liquid chromatography tandem mass spectrometry with an Orbitrap mass analyzer to quantify global protein abundances of a clinically well-annotated formalin-fixed paraffin embedded (FFPE) cohort (n = 61) of meningiomas spanning all World Health Organization (WHO) grades and various degrees of clinical aggressiveness.

resultsIn total, we quantify 3042 unique proteins comparing patterns across different clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic (n = 106 proteins, Welch's t-test, P < 0.01) and pathway-level (eg, Notch and PI3K/AKT/mTOR) differences between convexity and skull base meningiomas. Supervised comparative analyses of different pathological grades revealed distinct patterns between benign (grade I) and atypical/malignant (grades II‒III) meningiomas with specific oncogenes enriched in higher grade lesions. Independent of WHO grade, clinically aggressive meningiomas that rapidly recurred (<3 y) had distinctive protein patterns converging on mRNA processing and impaired activation of the matrisome complex. Larger sized meningiomas (>3 cm maximum tumor diameter) and those with previous radiation exposure revealed perturbed pro-proliferative (eg, epidermal growth factor receptor) and metabolic as well as inflammatory response pathways (mitochondrial activity, interferon), respectively.

conclusionsOur proteomic study demonstrates that meningiomas of different grades and clinical parameters present distinct proteomic profiles. These proteomic variations offer potential future utility in helping better predict patient outcome and in nominating novel therapeutic targets for personalized care.

Indexed as

Meningeal NeoplasmsMeningiomaSkull Base NeoplasmsHumansPhosphatidylinositol 3-KinasesProteomicsPhosphatidylinositol 3-Kinasesmass spectrometrymeningiomaneuro-oncologyproteome-wide analysisstratification

Identifiers

PMID31077268
PMCPMC6682208

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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.