Evidence map›Paper›PMID 38546286›Full record

ArticleEnvironmental toxicology2025

Exploring gene biomarkers and targeted drugs for ferroptosis and cuproptosis in osteosarcoma: A bioinformatic approach.

Yingnan Ji, Lv Liu, Yu Liu, Yudong Ma, Zhenhua Ji, Xiaodan Wu, Qi Zhu

Open access · hybridAbstract read
In one paragraph

Article in Environmental toxicology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 5 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

7 authors at 2 institutions in 1 country.

Yingnan JiCentral Hospital Affiliated to Shenyang Medical College, Shenyang, China.
Lv LiuBenxi Central Hospital, Benxi, China.
Yu LiuCentral Hospital Affiliated to Shenyang Medical College, Shenyang, China.
Yudong MaCentral Hospital Affiliated to Shenyang Medical College, Shenyang, China.
Zhenhua JiCentral Hospital Affiliated to Shenyang Medical College, Shenyang, China.
Xiaodan WuCentral Hospital Affiliated to Shenyang Medical College, Shenyang, China.
Qi ZhuCentral Hospital Affiliated to Shenyang Medical College, Shenyang, China.ORCID https://orcid.org/0009-0007-0257-6408
Central Hospital Affiliated to Shenyang Medical College · CNXian Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteosarcoma predominantly affects adolescents and young adults and is characterized as a malignant bone tumor. In recent decades, substantial advancements have been achieved in both diagnosing and treating osteosarcoma. Resulting in enhanced survival rates. Despite these advancements, the intricate relationship between ferroptosis and cuproptosis genes in osteosarcoma remains inadequately understood. Leveraging TARGET and GEO datasets, we conducted Cox regression analysis to select prognostic genes from a cohort of 71 candidates. Subsequently, a novel prognostic model was engineered using the LASSO algorithm. Kaplan-Meier analysis demonstrated that patients stratified as low risk had a substantially better prognosis compared with their high-risk counterparts. The model's validity was corroborated by the area under the receiver operating characteristic (ROC) curve. Additionally, we ascertained independent prognostic indicators, including clinical presentation, metastatic status, and risk scores, and crafted a clinical scoring system via nomograms. The tumor immune microenvironment was appraised through ESTIMATE, CIBERSORT, and single-sample gene set enrichment analysis. Gene expression within the model was authenticated through PCR validation. The prognostic model, refined by Cox regression and the LASSO algorithm, comprised two risk genes. Kaplan-Meier curves confirmed a significantly improved prognosis for the low-risk group in contrast to those identified as high-risk. For the training set, the ROC area under the curve (AUC) values stood at 0.636, 0.695, and 0.729 for the 1-, 3-, and 5-year checkpoints, respectively. Although validation set AUCs were 0.738, 0.668, and 0.596, respectively. Immune microenvironmental analysis indicated potential immune deficiencies in high-risk patients. Additionally, sensitivity to three small molecule drugs was investigated in the high-risk cohort, informing potential immunotherapeutic strategies for osteosarcoma. PCR analysis showed increased mRNA levels of the genes FDX1 and SQLE in osteosarcoma tissues. This study elucidates the interaction of ferroptosis and cuproptosis genes in osteosarcoma and paves the way for more targeted immunotherapy.

Indexed as

Biomarkers, TumorBone NeoplasmsFerroptosisOsteosarcomaAdolescentComputational BiologyFemaleGenetic MarkersHumansMalePrognosisYoung AdultBiomarkers, TumorGenetic Markerscuproptosisferroptosisosteosarcomaprognostic marker

Identifiers

PMID38546286
PMCPMC12069744
OpenAlexW4393259373

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.