Evidence map›Paper›PMID 25232831›Full record

ArticlePloS one2014

The transcriptional profiling of glycogenes associated with hepatocellular carcinoma metastasis.

Tianhua Liu, Shu Zhang, Jie Chen, Kai Jiang, Qinle Zhang, Kun Guo, Yinkun Liu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

27 citing papers in PubMed, 44 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

7 authors at 3 institutions in 1 country.

Tianhua LiuLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China; Cancer Research Center, Institute of Biomedical Science, Fudan University, Shanghai, People's Republic of China.
Shu ZhangLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Jie ChenLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Kai JiangLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China; Cancer Research Center, Institute of Biomedical Science, Fudan University, Shanghai, People's Republic of China.
Qinle ZhangLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China; Cancer Research Center, Institute of Biomedical Science, Fudan University, Shanghai, People's Republic of China.
Kun GuoLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China.
Yinkun LiuLiver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, People's Republic of China; Cancer Research Center, Institute of Biomedical Science, Fudan University, Shanghai, People's Republic of China.
The First Affiliated Hospital, Sun Yat-sen University · CNSun Yat-sen University · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveMetastasis is one of the important reasons for the poor prognosis of hepatocellular carcinoma (HCC), abnormal glycosylation plays a pivotal role in HCC metastasis. The goal of this study was to screen and validate the transcriptional profiling of glycogenes associated with HCC metastasis. METHODOLOGY: The differentially transcribed glycogenes were screened out by the Human Glycosylation RT2 Profiler PCR Array, and were identified by qRT-PCR in human HCC cell lines and their orthotopic xenograft tumors. Further analyses were performed with K-mean clustering, Gene Ontology (GO) and ingenuity pathways analysis (IPA). Four differentially transcribed glycogenes were validated in clinical cancer specimens by qRT-PCR.

resultsA total of thirty-three differentially transcribed glycogenes were obtained by comparison the transcription in the metastatic human HCC cell lines (MHCC97L, MHCC97H and HCCLM3) with the transcription in the non-metastatic HCC cell line Hep3B. Seven differentially transcribed glycogenes were selected to further identification in human HCC cell lines and their orthotopic xenograft tumors. According to their trends by K-mean clustering, all of the differentially transcribed glycogenes were classified in six clusters. GO analysis of the differentially transcribed glycogenes described them in biological process, subcellular location and molecular function. Furthermore, the partial regulatory network of the differentially transcribed glycogenes was acquired through the IPA. The transcription levels of galnt3, gcnt3, man1a1, mgat5b in non-metastatic and metastatic HCC clinical cancer specimens showed the same changing trends with the results in human HCC cell lines and their orthotopic xenograft tumors, and the divergent transcription levels of gcnt3 and mgat5b were statistically significant.

conclusionsThe transcriptional profiling of glycogenes associated with HCC metastasis was obtained and validated in this study and it might provide novel drug targets and potential biological markers for HCC metastasis.

Indexed as

AnimalsBiomarkers, TumorCarcinoma, HepatocellularCell Line, TumorGene Expression ProfilingGene OntologyGene Regulatory NetworksGlycoproteinsHumansLiver NeoplasmsMaleMice, Inbred BALB CMice, NudeNeoplasm TransplantationTranscriptomeBiomarkers, TumorGlycoproteins

Identifiers

PMID25232831
PMCPMC4169445
OpenAlexW2028961063

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.