Evidence map›Paper›PMID 38824202›Full record

ArticleScientific reports2024

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study.

Xingwang Zhou, Yuanguo Ling, Junshuan Cui, Xiang Wang, Niya Long, Wei Teng, Jian Liu, Xin Xiang, Hua Yang, Liangzhao Chu

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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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

10 authors.

Xingwang Zhou *Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Yuanguo Ling *Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Junshuan Cui *Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Xiang Wang *Department of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Niya LongDepartment of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Wei TengDepartment of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Jian LiuDepartment of Neurosurgery, Guizhou Provincial People's Hospital, Guiyang, Guizhou Province, People's Republic of China.
Xin XiangDepartment of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China.
Hua YangDepartment of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China. huayangmed@163.com.
Liangzhao ChuDepartment of Neurosurgery, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou Province, People's Republic of China. chulz_gymns@163.com.

Funding

Guizhou Science and Technology Plan Project Qiankehe 2016 Support[2905]National Natural Science Foundation of China 82360493National Natural Science Foundation of Guizhou Medical University Affiliated Hospital gyfynsfc-2022-26Science and Technology Fund Project of Guizhou Provincial Health Commission gzwkj[2022-090]the PhD Initiation Fund of Guizhou Medical University gyfybsky-2022-02the PhD Initiation Fund of Guizhou Medical University gyfybsky-2022-47
6 · The paper itself

Abstract

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

Indexed as

Brain NeoplasmsGliomaBiomarkers, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMitochondriaMultiomicsNeoplasm GradingPrognosisRNA, MitochondrialRNA Processing, Post-TranscriptionalTumor MicroenvironmentBiomarkers, TumorRNA, MitochondrialBulk RNA-seq analysisEpigenetic modificationLower grade gliomaMitochondrial RNA modificationSingle-cell analysis

Identifiers

PMID38824202
PMCPMC11144219

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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.