Evidence map›Paper›PMID 28322348›Full record

ArticleScientific reports2017

Several microRNAs could predict survival in patients with hepatitis B-related liver cancer.

Ye Zhen, Zhao Xinghui, Wu Chao, Zhao Yi, Chen Jinwen, Gao Ruifang, Zhang Chao, Zhao Min, Guo Chunlei, Fang Yan and 5 more

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 1 pooled it
–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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

15 authors.

Ye ZhenDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Zhao XinghuiLaboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing 100071, China.
Wu ChaoDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Zhao YiKey Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Chen JinwenKey Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, 100190, China.
Gao RuifangDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Zhang ChaoCollege of Information Science and Engineering, Shandong Agriculture University, Tai'an 271000, China.
Zhao MinDepartment of Infectious Disease, Tai'an Central Hospital, Tai'an 271000, China.
Guo ChunleiDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Fang YanDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Du LingfangDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Shen LongDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Shen WenzhiDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Luo XiaoheDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.
Xiang RongDepartment of Tumor Molecular Biology, Nankai University School of Medicine, Tianjin 371000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

MicroRNAs as biomarkers play an important role in the tumorigenesis process, including hepatocellular carcinomas (HCCs). In this paper, we used The Cancer Genome Atlas (TCGA) database to mine hepatitis B-related liver cancer microRNAs that could predict survival in patients with hepatitis B-related liver cancer. There were 93 cases of HBV-HCC and 49 cases of adjacent normal controls included in the study. Kaplan-Meier survival analysis of a liver cancer group versus a normal control group of differentially expressed genes identified eight genes with statistical significance. Compared with the normal liver cell line, hepatocellular carcinoma cell lines had high expression of 8 microRNAs, albeit at different levels. A Cox proportional hazards regression model for multivariate analysis showed that four genes had a significant difference. We established classification models to distinguish short survival time and long survival time of liver cancers. Eight genes (mir9-3, mir10b, mir31, mir519c, mir522, mir3660, mir4784, and mir6883) were identified could predict survival in patients with HBV-HCC. There was a significant correlation between mir10b and mir31 and clinical stages (p < 0.05). A random forests model effectively estimated patient survival times.

Indexed as

Biomarkers, TumorCarcinoma, HepatocellularCell Line, TumorFemaleHepatitis BHumansLiver NeoplasmsMaleMicroRNAsMiddle AgedBiomarkers, TumorMicroRNAs

Identifiers

PMID28322348
PMCPMC5359660

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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.