Evidence map›Paper›PMID 40658315›Full record

ArticleCellular oncology (Dordrecht, Netherlands)2025

A diagnostic model based on transcriptomic analysis reveals inflammation as a potential prognosis factor for hepatoblastoma with hepatocellular carcinoma features.

Yuhua Shan, Min Zhang, Hongxiang Gao, Lei Zhang, Chenjie Xie, Jiquan Zhou, Liyuan Yang, Ji Ma, Qiuhui Pan, Zhen Zhang and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cellular oncology (Dordrecht, Netherlands), 2025. 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

12 authors.

Yuhua ShanDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China.
Min ZhangPediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China.
Hongxiang GaoDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China.
Lei ZhangDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China.
Chenjie XieDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China.
Jiquan ZhouDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China.
Liyuan YangDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China.
Ji MaDepartment of Laboratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China.
Qiuhui PanDepartment of Laboratory Medicine, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China.
Zhen ZhangPediatric Translational Medicine Institute, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China.
Min XuDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China. jackxm1236@126.com.
Song GuDepartment of Surgery, Shanghai Children's Medical Center, School of Medicine, Shanghai Jiao Tong University, 1678 Dongfang Road, Shanghai Pudong District, Shanghai, 200127, P. R. China. gusong@shsmu.edu.cn.

Funding

National Clinical Key Specialty Project Foundation 2021National Natural Science Foundation of China 82072375National Natural Science Foundation of China 82293662National Natural Science Foundation of China 82370505Shanghai Anti-Cancer Association SACA-CY20C11Shanghai Jiao Tong University YG2022QN093
6 · The paper itself

Abstract

introductionHepatoblastoma (HB) with hepatocellular carcinoma (HCC) features (HBHF) is a rare liver malignancy. Due to its rarity and diverse histological presentations, the prognosis of HBHF remains controversial, and diagnostic differentiation poses significant challenges. To enable more accurate outcome evaluation and targeted therapeutic strategies, rapid, comprehensive, and cost-effective methods are needed to complement histopathological evaluation.

methodsIn this study, we conducted transcriptomic profiling on an HBHF cohort from our center and developed a machine-learning algorithm to quantify HCC-like expression features in HB tumors. Given overlapping histopathological and molecular charateristicss between HBHF and HCC, we further investigated shared risk factors associated with HBHF prognosis.

resultsSignificantly poorer outcomes in HBHF patients suggest fundamental biological distinctions from classical HB. Transcriptomic analysis revealed comparable somatic mutation profiles between HB and HBHF cohorts but identified inflammation activation, rather than specific mutations, as a key high-risk factor in HBHF. Clinical outcomes aligned with risk stratification generated by our quantification model.

conclusionsHBHF represents a distinct transitional entity between HB and HCC, exhibiting markedly worse clinical outcomes than HB. Our transcriptome-based computational model effectively discriminates HBHF and predicts its prognostic risk. Importantly, inflammatory activation emerges as a critical driver of tumor aggressiveness in this subtype.

Indexed as

Carcinoma, HepatocellularGene Expression ProfilingHepatoblastomaInflammationLiver NeoplasmsTranscriptomeFemaleGene Expression Regulation, NeoplasticHumansMachine LearningMaleMiddle AgedPrognosisRisk FactorsHBHFHepatoblastomaMachine learning scoring modelTranscriptomic sequencing

Identifiers

PMID40658315
PMCPMC12528353

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.