Evidence map›Paper›PMID 40794333›Full record

ArticleDiscover oncology2025

Construction and validation of a cell-in-cell related prognostic signature for hepatocellular carcinoma.

Hao Zhong, Dong Wang, Yisheng Chen, Danhong Zhan, Chenxi Wang, Rongqi Lin, Wen Li, Qiang Sun, Ruizhi Wang, Meifang He

Abstract read
In one paragraph

Article in Discover oncology, 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

10 authors.

Hao Zhong *Laboratory of General Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
Dong Wang *Laboratory of General Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
Yisheng Chen *Department of Neurology, Shanghang county hospital, Longyan, 364299, China.
Danhong ZhanLaboratory of General Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
Chenxi WangInstitute of Biotechnology, Research Unit of Cell Death Mechanism, 2021RU008, Academy of Military Medical Science, Chinese Academy of Medical Science, Beijing, 100071, China.
Rongqi LinDepartment of Pharmacy, Shanghang county hospital, Longyan, 364299, China.
Wen LiLaboratory of General Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China.
Qiang SunInstitute of Biotechnology, Research Unit of Cell Death Mechanism, 2021RU008, Academy of Military Medical Science, Chinese Academy of Medical Science, Beijing, 100071, China.
Ruizhi WangDivision of Laboratory Medicine, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510062, China. wangrzh3@mail.sysu.edu.cn.
Meifang HeLaboratory of General Surgery, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, 510080, China. hemeifang@mail.sysu.edu.cn.

Funding

CAMS Innovation Fund for Medical Sciences 2021-I2M-5-008GuangDong Medical Products Administration Science and Technology Project, Medical Science and Technology Research Foundation of GuangDong Province No. 2023ZDZ02, 2023YDZ02 and 2023YDZ04, No. B2022285, B2022321 and B2023363the National Natural Science Foundation of China, GuangDong Basic and Applied Basic Research Foundation, Science and Technology Program of Guangzhou No. 82373069, No. 2022A1515220130, 2024A04J6489
6 · The paper itself

Abstract

Cell-in-cell structures (CICs) and their biological roles contribute to disease development, particularly in cancer. However, the roles of CIC-associated genes (CICGs) in hepatocellular carcinoma (HCC) are largely unknown. This study sought to establish a a CICGs-linked HCC signature and assess its predictive significance. We acquired gene expression profiling data for tumor and normal tissues of HCC patients from The Cancer Genome Atlas (TCGA) for training and from the International Cancer Genome Consortium (ICGC) for validation. Consensus clustering was employed to delineate patient cohorts with varying prognoses, categorizing HCC patients into two distinct groups. A selection of fifty CICGs was compiled from the literature, revealing their association with CIC development through functional studies. Six predictive genes were ultimately identified through univariate Cox proportional hazards regression (Cox) and least absolute shrinkage and selection operator (LASSO) analyses. This prognostic signature, resulting from a multivariate Cox, subsequently segmented TCGA and ICGC cohort individuals into high- and low-risk categories. Our verification of the signature's precision involved survival analysis contrasts between those at high and low risk. Quantitative real-time PCR (qRT-PCR) analysis revealed markedly elevated expression levels of these six genes in HCC tumors compared to neighboring healthy tissue, underscoring their potential role in tumor development. This experimentally reinforces the accuracy of the genetic profile. We also examined variations in the composition of immune cells and immunological responses across high-risk and low-risk cohorts. This study established and verified prognostic variables connected to cell-in-cell (CIC), potentially improving personalized survival forecasts for patients with HCC.

Indexed as

Cell-in-cellHCCImmune cellsPrognosis signature

Identifiers

PMID40794333
PMCPMC12344039

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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.