Evidence map›Paper›PMID 37266876›Full record

ArticleBiochemical genetics2024

Comprehensive Analysis of TICRR in Hepatocellular Carcinoma Based on Bioinformatics Analysis.

Jing-Jing Chen, Lu-Lu Zhang, Zhen Liu, Wan Qi Men, Fang Chen, Jilu Shen

Open access · hybridAbstract read
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Article in Biochemical genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

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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

3 citing papers in PubMed, 5 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

6 authors at 3 institutions in 1 country.

Jing-Jing Chen *Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Lu-Lu Zhang *Public Center of Experimental Technology, The School of Basic Medical, Science and Southwest Medical University, Luzhou, Sichuan, China.
Zhen Liu *Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Wan Qi Men *Department of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Fang ChenUItrasonic Diagnosis Deparment, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Jilu ShenDepartment of Clinical Laboratory, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China. shenjilu@126.com.
Anhui Medical University · CNFirst Affiliated Hospital of Anhui Medical University · CNSouthwest Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is one of the leading cause of cancer-associated death in the world. However, due to the complexity of HCC, it is urgent for us to find a reliable and accurate biomarker for HCC gene therapy.TopBP1-interacting checkpoint and replication regulator (TICRR), known as Treslin in vertebrate and sld3 in yeast, is involved in the tumorigenesis, progression, matastasis, diagnosis, and predicting prognosis of HCC. Disappointingly, the mechanism of TICRR expression in HCC is still not described in detail and requires further analysis. In this study, TCGA ( www.tcga-data.nci.nih.gov/tcga/ ) datasets and GEO ( www.ncbi.nlm.nih.gov/geo ) datasets were used to analyze the expression of TICRR in HCC, the relevance of TICRR mRNA expression and clinicopathological characteristics in patients with HCC, and the relationship between TICRR expression and immune infiltration level in Patients with HCC. Based on MethSurv database, the impact of TICRR in patients with HCC was investigated. In addition, GO/KEGG enrichment analysis of TICRR co-expression was performed using the R package. TICRR was found drastically highly expressed in a variety of cancer types including HCC.ROC curve analysis showed that TICRR had higher accuracy in predicting HCC compared with AFP. The expression level of TICRR was marked positively correlated with tumor stage and prognosis in Patients with HCC.GO/KEGG enrichment analysis showed that TICRR was associated with cell division and cell cycle as well as p53 signaling pathway. In addition, patients with high TICRR methylation of cg05841809, cg09403165, and cg03312532 CpG sites were significantly correlated with poor prognosis of HCC. This study demonstrated that increased TICRR expression in HCC might play an important role in the tumorigenesis, progression, diagnosis, and predicting prognosis of HCC. Therefore, TICRR might be used as a promising diagnostic and prognostic biomarker for HCC gene therapy.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsBiomarkersCarcinogenesisCell Cycle ProteinsComputational BiologyHumansBiomarkersCell Cycle ProteinsTICRR protein, humanHCCHepatocellular carcinomaImmune infiltrationMethylationPrognosisT-cell exhaustion

Identifiers

PMID37266876
PMCPMC10902024
OpenAlexW4379095365

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LicenceCC BY
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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.