Evidence map›Paper›PMID 34604069›Full record

ArticleFrontiers in oncology2021

Identification of Potential Biomarkers for Liver Cancer Through Gene Mutation and Clinical Characteristics.

Yunlong Cui, Hua Li, Hongjie Zhan, Tao Han, Yixuan Dong, Caijuan Tian, Yixian Guo, Fang Yan, Dong Dai, Pengfei Liu

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
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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

10 authors at 3 institutions in 1 country.

Yunlong CuiDepartment of Hepatobiliary Oncology, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Hua LiDepartment of Endoscopy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Hongjie ZhanDepartment of Gastric Cancer, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Tao HanCollege of Engineering, Peking University, Beijing, China.
Yixuan DongGraduate School, Tianjin Academy of Traditional Chinese Medicine, Tianjin, China.
Caijuan TianTianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd., Tianjin, China.
Yixian GuoTianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd., Tianjin, China.
Fang YanTianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd., Tianjin, China.
Dong DaiDepartment of Molecular Imaging and Nuclear Medicine, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Pengfei LiuDepartment of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin, China.
Tianjin Medical University Cancer Institute and Hospital · CNPeking University · CNTianjin University of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver cancer is a common malignant tumor worldwide, which is a serious threat to the health of people. We try to investigate some mutations and clinical indicators as candidate markers for the development of liver cancer through targeted region capture technology combined with next-generation sequencing. We collected peripheral blood and liver cancer tissue samples from 32 liver patients concurrently. The SeqCap EZ Prime Choice Probe was used to perform the targeted enrichment; this probe captures 1,000 known cancer-associated genes. We calculated the tumor mutation burden (TMB) for each patient. The high-frequency mutations and these relative genes were identified. Eventually, survival analysis was performed based on the mutations and clinical indicators. In 32 liver patients, a total of 29 high-frequency mutations were investigated. They were located in 25 genes, which were enriched in 9 cellular components (CCs), 6 molecular functions (MFs), and 21 biological processes (BPs). Among them, EZH2 c.1544A>G and CCND1 c.839A>T had the highest mutation frequency (5/32). In the protein-protein interaction (PPI) network, EZH2-DNMT3A, NOTCH1-CCND1, and ABL1-CCND1 were the top three pairs. The survival analysis showed that there were significant differences in progression-free survival (PFS) and overall survival (OS) between the Karnofsky performance score (KPS) groups. The PFS and OS in the TMB high group were higher than those in the TMB low group. OS and tumor stage had a remarkable relationship. In conclusion, EZH2 c.1544A>G and CCND1 c.839A>T might be potential biomarkers of liver cancer. TMB might be used as a prognosis and survival indicator of liver cancer.

Indexed as

circulating tumor DNA (ctDNA)gene mutationliver cancersurvival analysistumor mutation burden (TMB)

Identifiers

PMID34604069
PMCPMC8484954
OpenAlexW3201326691

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.