Evidence map›Paper›PMID 38684858›Full record

ArticleScientific reports2024

Importance of CD8 Tex cell-associated gene signatures in the prognosis and immunology of osteosarcoma.

Yining Lu, Nana Cao, Ming Zhao, Guochuan Zhang, Qi Zhang, Ling Wang

Open access · goldAbstract 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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 32% 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, 3 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

6 authors at 3 institutions in 1 country.

Yining Lu *Department of Orthopedic Research Center, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Nana Cao *Blood Transfusion Department of the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Ming ZhaoDepartment of Orthopedic Oncology, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Guochuan ZhangDepartment of Orthopedic Oncology, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China.
Qi ZhangDepartment of Orthopedic Research Center, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China. 18001666@hebmu.edu.cn.
Ling WangDepartment of Orthopedic Research Center, The Third Hospital of Hebei Medical University, Shijiazhuang, Hebei, People's Republic of China. wangling2016uw@126.com.
Third Hospital of Hebei Medical University · CNHebei Medical University · CNFourth Hospital of Hebei Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As a highly aggressive bone malignancy, osteosarcoma poses a significant therapeutic challenge, especially in the setting of metastasis or recurrence. This study aimed to investigate the potential of CD8-Tex cell-associated genes as prognostic biomarkers to reveal the immunogenomic profile of osteosarcoma and guide therapeutic decisions. mRNA expression data and clinical details of osteosarcoma patients were obtained from the TCGA database (TARGET-OS dataset). The GSE21257 dataset (from the GEO database) was used as an external validation set to provide additional information on osteosarcoma specimens. 84 samples from the TARGET-OS dataset were used as the training set, and 53 samples from the GSE21257 dataset served as the external validation cohort. Univariate Cox regression analysis was utilized to identify CD8 Tex cell genes associated with prognosis. The LASSO algorithm was performed for 1000 iterations to select the best subset to form the CD8 Tex cell gene signature (TRS). Final genes were identified using the multivariate Cox regression model of the LASSO algorithm. Risk scores were calculated to categorize patients into high- and low-risk groups, and clinical differences were explored by Kaplan-Meier survival analysis to assess model performance. Prediction maps were constructed to estimate 1-, 3-, and 5 year survival rates for osteosarcoma patients, including risk scores for CD8 Texcell gene markers and clinicopathologic factors. The ssGSEA algorithm was used to assess the differences in immune function between TRS-defined high- and low-risk groups. TME and immune cell infiltration were further assessed using the ESTIMATE and CIBERSORT algorithms. To explore the relationship between immune checkpoint gene expression levels and the two risk-defined groups. A CD8 Tex cell-associated gene signature was extracted from the TISCH database and prognostic markers including two genes were developed. The high-risk group showed lower survival, and model performance was validated by ROC curves and C-index. Predictive plots were constructed to demonstrate survival estimates, combining CD8 Tex cell gene markers and clinical factors. This study provides valuable insights into the molecular and immune characteristics of osteosarcoma and offers potential avenues for advances in therapeutic approaches.

Indexed as

Biomarkers, TumorBone NeoplasmsCD8-Positive T-LymphocytesOsteosarcomaAdolescentAdultFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMalePrognosisTranscriptomeBiomarkers, TumorImmunotherapyOsteosarcomaPrognostic signatureT cell exhaustionT cell-related genesTranscriptomics analysisTumor microenvironment

Identifiers

PMID38684858
PMCPMC11058769
OpenAlexW4396237858

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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 Socratic graph.