Evidence map›Paper›PMID 39264525›Full record

ArticleMolecular biotechnology2025

Multi-omics and Single Cell Sequencing Analyses Reveal Associations of Mitophagy-Related Genes Predicting Clinical Prognosis and Immune Infiltration Characteristics in Osteosarcoma.

Shengquan Ren, Rongfang Pan, Zhengdan Wang

Abstract read
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In one paragraph

Article in Molecular biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Role of NEL‑like molecule‑1 in osteogenesis/chondrogenesis (Review).International journal of molecular medicine · 2025
    Review
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

3 authors.

Shengquan RenDepartment of Hand and Foot Microsurgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.ORCID http://orcid.org/0009-0002-8332-9428
Rongfang PanDepartment of Nutrition, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China.
Zhengdan WangDepartment of Hand and Foot Microsurgery, The Affiliated Hospital of Qingdao University, Qingdao, 266000, China. wangzhengdan@qdu.edu.cn.

Funding

Applied Basic Research Fund of Qingdao QDFYQN202201012
6 · The paper itself

Abstract

Despite recent advances in clinical treatments, identifying high-risk osteosarcoma (OS) patients remains an unresolved clinical challenge. Mitophagy, a specialized form of cellular autophagy, selectively reduces the number of mitochondria or repairs their abnormal functions in response to external stress, thereby ensuring mitochondrial quality and maintaining mitochondrial function. Mitophagy plays a crucial role in cancer development, including processes such as mitochondrial repair, homeostasis maintenance, and tumor metabolism. However, its impact on OS has not yet been reported. In this study, we collected 58 mitophagy-related genes (MPRGs) from the TARGET and GEO databases and bioinformatically screened for those associated with OS prognosis. By LASSO-multivariable Cox regression algorithm, we subsequently developed a novel scoring system, the MPRG score, and validated its significance in predicting OS prognosis. Immune landscape analysis showed patients in the low MPRG group had a higher immune infiltration level than those in the high MPRG group. Drug sensitivity differences highlighted the potential need for alternative therapeutic strategies based on MPRG scoring system. The distribution characteristics of the MPRG signature in different cell subtypes of OS were explored by single-cell sequencing analyses. In vitro experiments further confirmed the abnormal expression of screened targets in OS. Our findings highlight the role of mitophagy in OS and its potential as a therapeutic target.

Indexed as

Bone NeoplasmsMitophagyOsteosarcomaSingle-Cell AnalysisBiomarkers, TumorCell Line, TumorComputational BiologyFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMaleMitochondriaMultiomicsPrognosisBiomarkers, TumorDrug sensitivityImmunoinfiltration characteristicMitophagyMolecular subtypeOsteosarcomaSingle cell sequencing analysis

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