Evidence map›Paper›PMID 28248456›Full record

ArticleMolecular oncology2017

A three-microRNA signature identifies two subtypes of glioblastoma patients with different clinical outcomes.

Giovanna Marziali, Mariachiara Buccarelli, Alessandro Giuliani, Ramona Ilari, Sveva Grande, Alessandra Palma, Quintino G D'Alessandris, Maurizio Martini, Mauro Biffoni, Roberto Pallini and 1 more

Open access · goldAbstract read
In one paragraph

Article in Molecular oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
1.8field-weighted citation impact, top 17% 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

23 citing papers in PubMed, 35 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 3 institutions in 1 country.

Giovanna MarzialiDepartment of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy.
Mariachiara BuccarelliDepartment of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy.
Alessandro GiulianiDepartment of Environment and Health, Istituto Superiore di Sanità, Rome, Italy.
Ramona IlariDepartment of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy.
Sveva GrandeDepartment of Technology and Health, Istituto Superiore di Sanità, Rome, Italy.
Alessandra PalmaDepartment of Technology and Health, Istituto Superiore di Sanità, Rome, Italy.
Quintino G D'AlessandrisInstitute of Neurosurgery, Università Cattolica del Sacro Cuore, Rome, Italy.
Maurizio MartiniInstitute of Pathology, Università Cattolica del Sacro Cuore, Rome, Italy.
Mauro BiffoniDepartment of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy.
Roberto PalliniInstitute of Neurosurgery, Università Cattolica del Sacro Cuore, Rome, Italy.
Lucia Ricci-VitianiDepartment of Hematology, Oncology and Molecular Medicine, Istituto Superiore di Sanità, Rome, Italy.
Istituto Superiore di Sanità · ITUniversità Cattolica del Sacro Cuore · ITIstituto Nazionale di Fisica Nucleare · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Glioblastoma multiforme (GBM) is the most common and malignant primary brain tumor in adults, characterized by aggressive growth, limited response to therapy, and inexorable recurrence. Because of the extremely unfavorable prognosis of GBM, it is important to develop more effective diagnostic and therapeutic strategies based on biologically and clinically relevant patient stratification systems. Analyzing a collection of patient-derived GBM stem-like cells (GSCs) by gene expression profiling, nuclear magnetic resonance spectroscopy, and signal transduction pathway activation, we identified two GSC clusters characterized by different clinical features. Due to the widely documented role played by microRNAs (miRNAs) in the tumorigenesis process, in this study we explored whether these two GBM patient subtypes could also be discriminated by different miRNA signatures. Global miRNA expression pattern was analyzed by oblique principal component analysis and principal component analysis. By a combined inferential strategy on PCA results, we identified a reduced set of three miRNAs - miR-23a, miR-27a, and miR-9* (miR-9-3p) - able to discriminate the proneural- and mesenchymal-like GSC phenotypes as well as mesenchymal and proneural subtypes of primary GBM included in The Cancer Genome Atlas (TCGA) data set. Kaplan-Meier analysis showed a significant correlation between the selected miRNAs and overall survival in 429 GBM specimens from TCGA-identifying patients who had an unfavorable outcome. The survival prognostic capability of the three-miRNA signatures could have important implications for the understanding of the biology of GBM subtypes and could be useful in patient stratification to facilitate interpretation of results from clinical trials.

Indexed as

Gene Expression ProfilingAdultAgedAged, 80 and overBrain NeoplasmsCluster AnalysisCohort StudiesFemaleGene Expression Regulation, NeoplasticGenes, NeoplasmGlioblastomaHumansKaplan-Meier EstimateMaleMesodermMicroRNAsMicroRNAsglioblastomaglioblastoma stem-like cellsmicroRNAspatient stratification

Identifiers

PMID28248456
PMCPMC5579331
OpenAlexW2593923765

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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.