Evidence map›Paper›PMID 31558872›Full record

ArticleWorld journal of gastroenterology2019

Significance of tumor-infiltrating immunocytes for predicting prognosis of hepatitis B virus-related hepatocellular carcinoma.

Qi-Feng Chen, Wang Li, Pei-Hong Wu, Lu-Jun Shen, Zi-Lin Huang

Abstract read
In one paragraph

Article in World journal of gastroenterology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Comparison ofCancer science · 2025
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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

5 authors.

Qi-Feng ChenDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China.
Wang LiDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China.
Pei-Hong WuDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China.
Lu-Jun ShenDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China.
Zi-Lin HuangDepartment of Medical Imaging and Interventional Radiology, Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, Guangdong Province, China. huangzl@sysucc.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHepatitis B virus (HBV) has been recognized as a leading cause of hepatocellular carcinoma (HCC). Numerous reports suggest that immune infiltration can predict the prognosis of HCC. Nonetheless, no creditable markers for prognosis of HBV-related HCC have been established by systematically assessing the immune-related markers based on tumor transcriptomes.

aimTo establish an immune-related marker based on the cell compositions of immune infiltrate obtained based on tumor transcriptomes, so as to enhance the prediction accuracy of HBV-related HCC prognosis.

methodsRNA expression patterns as well as the relevant clinical data of HCC patients were obtained from The Cancer Genome Atlas. Twenty-two immunocyte fraction types were estimated by cell type identification by estimating relative subsets of RNA transcripts. Subsequently, the least absolute shrinkage and selection operator (LASSO) Cox regression model was employed to construct an immunoscore based on the immunocyte fraction types. Afterwards, the receiver operating characteristic (ROC) curve, Kaplan-Meier, and multivariate Cox analyses were performed. Additionally, a nomogram for prognosis that integrated the immunoscore as well as the clinical features was established. Meanwhile, the correlation of immunoscore with immune genes was also detected, and gene set enrichment analysis (GSEA) of the immunoscore was conducted.

resultsA total of 22 immunocyte fraction types were predicted and compared among the tumor as well as non-tumor samples. An immunoscore was constructed through adopting the LASSO model, which contained eight immunocyte fraction types. Meanwhile, the areas under the ROC curves for the immunoscore biomarker prognostic model were 0.971, 0.912, and 0.975 for 1-, 3-, and 5-year overall survival (OS), respectively. Difference in OS between the high-immunoscore group and the low-immunoscore group was statistically significant [hazard ratio (HR) = 66.007, 95% confidence interval (CI): 8.361-521.105;

conclusionThe established immunoscore can potentially serve as a candidate marker to estimate the OS for HBV-related HCC cases.

Indexed as

NomogramsAdultAgedCarcinoma, HepatocellularDatasets as TopicFemaleGene Expression ProfilingHepatitis B virusHumansKaplan-Meier EstimateLiverLiver NeoplasmsLymphocytes, Tumor-InfiltratingMaleMiddle AgedPrognosisCell type identification by estimating relative subsets of RNA transcriptsHepatitis B virusHepatocellular carcinomaImmune risk scorePrognostic signature

Identifiers

PMID31558872
PMCPMC6761238

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