Evidence map›Paper›PMID 42512292›Full record

ArticleCancers2026

MRPL23 Overexpression Predicts Poor Survival and Is Associated with Mitochondrial Respiratory Signatures in Glioblastoma.

Justyna Durślewicz, Marek Zdrenka, Łukasz Szylberg, Jędrzej Borowczak

Abstract read
In one paragraph

Article in Cancers, 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
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0citing papers in PubMed
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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

4 authors.

Justyna DurślewiczFaculty of Medicine, Bydgoszcz University of Science and Technology, Aleje Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland.ORCID 0000-0001-7301-5324
Marek ZdrenkaDepartment of Tumor Pathology and Pathomorphology, Oncology Centre-Prof. Franciszek Łukaszczyk Memorial Hospital, 85-796 Bydgoszcz, Poland.
Łukasz SzylbergDepartment of Tumor Pathology and Pathomorphology, Oncology Centre-Prof. Franciszek Łukaszczyk Memorial Hospital, 85-796 Bydgoszcz, Poland.ORCID 0000-0003-1349-5906
Jędrzej BorowczakFaculty of Medicine, Bydgoszcz University of Science and Technology, Aleje Prof. S. Kaliskiego 7, 85-796 Bydgoszcz, Poland.

Funding

Bydgoszcz University of Science and Technology none
6 · The paper itself

Abstract

backgroundGlioblastoma (GBM) is the most aggressive primary brain tumor in adults and is characterized by poor prognosis and marked molecular heterogeneity. Mitochondrial ribosomal proteins have emerged as regulators of cancer metabolism, yet the clinical significance of MRPL23 in GBM remains unclear. This study aimed to evaluate the prognostic relevance of MRPL23 expression in glioblastoma and its association with patient survival and mitochondrial functional profiles.

methodsMRPL23 protein expression was assessed by immunohistochemistry in tissue microarrays derived from 89 patients with primary glioblastoma and 36 samples of adjacent non-tumorous brain tissue. Survival analyses were performed using Kaplan-Meier estimates and Cox proportional hazards models. In silico validation was conducted using transcriptomic and proteomic data from 296 IDH-wildtype glioblastomas from The Cancer Genome Atlas. Correlation analyses were used to explore associations between MRPL23 expression and mitochondrial respiratory chain components.

resultsMRPL23 protein expression was significantly upregulated in glioblastoma compared with non-tumorous brain tissue (

conclusionsMRPL23 is overexpressed in glioblastoma and is associated with unfavorable patient outcomes. These findings identify MRPL23 as a potential prognostic biomarker and highlight mitochondrial translation as a relevant biological process in aggressive glioblastoma.

Indexed as

glioblastomaMRPL23prognostic biomarker

Identifiers

PMID42512292
PMCPMC13406341

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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.