Evidence map›Paper›PMID 42877405›Full record

ArticleFrontiers in oncology2026

Integrated machine learning and multi-dataset analysis identify SDS as a diagnostic and immune-related hub gene in hepatoblastoma.

Dan Chen, Baixue Zhang, Yanlong Zhang, Na Li, Ang Li, Wei Gao

Abstract read
In one paragraph

Article in Frontiers in oncology, 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
0cells of the map it votes in
0citing 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

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

6 authors.

Dan Chen *Department of Pediatric Hematology and Oncology, Xingtai People's Hospital, Xingtai, China.
Baixue Zhang *Department of Oncology, Second Affiliated Hospital of Xingtai Medical College, Xingtai, China.
Yanlong ZhangDepartment of Cardiology, Xingtai People's Hospital, Xingtai, China.
Na LiDepartment of Pediatric Hematology and Oncology, Xingtai People's Hospital, Xingtai, China.
Ang LiDepartment of Public Health, Jining Medical University, Jining, China.
Wei GaoDepartment of Pediatric Hematology and Oncology, Xingtai People's Hospital, Xingtai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Current clinical diagnostic models lack sufficient sensitivity and specificity for Hepatoblastoma (HB) individualized prediction. This study aimed to identify robust hub genes for HB diagnosis and molecular subtyping by integrating multiple transcriptomic datasets and machine learning algorithms. Methods: Four merged GEO hepatoblastoma datasets (GSE131329, GSE132037, GSE104766, GSE133039) were analyzed by differential expression and WGCNA to identify HB-related genes. Further use three algorithms (LASSO, SVM-RFE, Random Forest) to identify central genes. In addition, consensus clustering was used for molecular typing, and four deconvolution algorithms (TIMER, MCPcounter, xCell, quanTIseq) were used to characterize the tumor microenvironment. The biological function of SDS in hepatoblastoma was elucidated through Results: A total of 268 differentially expressed genes (77 up, 191 down) were identified. WGCNA revealed the blue module as most correlated with HB (correlation coefficient 0.66). Three machine learning algorithms jointly selected four hub genes (CLEC1B, ITGA6, SDS, TTC36). Consensus clustering based on these four genes stratified HB into two subtypes (Clust1, Clust2). Clust1 exhibited enhanced immune infiltration and activation of complement, IFN-α, and IL6-JAK-STAT3 pathways. Low SDS expression associated with cell cycle pathways, whereas high SDS expression associated with immune-related pathways. Functionally, SDS overexpression significantly suppressed HB cell proliferation, migration, invasion, and colony formation, while promoting apoptosis Conclusion: Integrated machine learning identified CLEC1B, ITGA6, SDS, and TTC36 as robust diagnostic genes for hepatoblastoma. SDS, in particular, exerts a tumor-suppressive role and is closely linked to the immune microenvironment, making it a promising diagnostic biomarker and therapeutic target in HB.

Indexed as

diagnostic markershepatoblastomaimmune microenvironmentmachine learningSDS

Identifiers

PMID42877405
PMCPMC13662425

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.