Evidence map›Paper›PMID 31215439›Full record

ArticleJournal of translational medicine2019

Development and validation of a new tumor-based gene signature predicting prognosis of HBV/HCV-included resected hepatocellular carcinoma patients.

Gui-Qi Zhu, Yi Yang, Er-Bao Chen, Biao Wang, Kun Xiao, Shi-Ming Shi, Zheng-Jun Zhou, Shao-Lai Zhou, Zheng Wang, Ying-Hong Shi and 4 more

Open access · goldAbstract readValidation Study
In one paragraph

Article in Journal of translational medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.8field-weighted citation impact, top 6% 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

13 citing papers in PubMed, 29 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

14 authors at 3 institutions in 1 country.

Gui-Qi ZhuLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Yi YangLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Er-Bao ChenDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Biao WangLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Kun XiaoLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Shi-Ming ShiDepartment of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Zheng-Jun ZhouLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Shao-Lai ZhouLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Zheng WangLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Ying-Hong ShiLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Jia FanLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Jian ZhouLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Tian-Shu LiuDepartment of Medical Oncology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
Zhi DaiLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. dai.zhi@zs-hospital.sh.cn.
Fudan University · CNZhongshan Hospital · CNSun Yat-sen University · CN

Funding

National Natural Science Fund of China No. 81472218National Natural Science Fund of China No. 81672330
6 · The paper itself

Abstract

backgroundDue to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is still a challenge to determine patients' prognosis. We aim to identify new prognostic markers for resected HCC patients.

methods274 patients were retrospectively identified and samples collected from Zhongshan hospital, Fudan University. We analyzed the gene expression patterns of tumors and compared expression patterns with patient survival times. We identified a "9-gene signature" associated with survival by using the coefficient and regression formula of multivariate Cox model. This molecular signature was then validated in three patients cohorts from internal cohort (n = 69), TCGA (n = 369) and GEO dataset (n = 80).

resultsWe identified 9-gene signature consisting of ZC2HC1A, MARCKSL1, PTGS1, CDKN2B, CLEC10A, PRDX3, PRKCH, MPEG1 and LMO2. The 9-gene signature was used, combined with clinical parameters, to fit a multivariable Cox model to the training cohort (concordance index, ci = 0.85), which was successfully validated (ci = 0.86 for internal cohort; ci = 0.78 for in silico cohort). The signature showed improved performance compared with clinical parameters alone (ci = 0.70). Furthermore, the signature predicted patient prognosis than previous gene signatures more accurately. It was also used to stratify early-stage, HBV or HCV-infected patients into low and high-risk groups, leading to significant differences in survival in training and validation (P < 0.001).

conclusionsThe 9-gene signature, in which four were upregulated (ZC2HC1A, MARCKSL1, PTGS1, CDKN2B) and five (CLEC10A, PRDX3, PRKCH, MPEG1, LMO2) were downregulated in HCC with poor prognosis, stratified HCC patients into low and high risk group significantly in different clinical settings, including receiving adjuvant transarterial chemoembolization and especially in early stage disease. This new signature should be validated in prospective studies to stratify patients in clinical decisions.

Indexed as

TranscriptomeAdultAgedBiomarkers, TumorCarcinoma, HepatocellularCell Transformation, ViralCohort StudiesFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticGenes, NeoplasmHepacivirusHepatitis BHepatitis B virusHepatitis CHumansBiomarkers, TumorHepatocellular carcinomaLiver resectionMicroarray analysisMolecular classification

Identifiers

PMID31215439
PMCPMC6582497
OpenAlexW2950763333

What OpenQuestion holds

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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 OpenQuestion graph.