Evidence map›Paper›PMID 37609076›Full record

ReviewFrontiers in immunology2023

Post-translational modifications and immune responses in liver cancer.

You-Wei Wang, Jia-Chen Zuo, Chong Chen, Xiao-Hong Li

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 19 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

4 authors at 2 institutions in 1 country.

You-Wei WangAcademy of Medical Engineering and Translational Medicine, Medical College of Tianjin University, Tianjin, China.
Jia-Chen ZuoAcademy of Medical Engineering and Translational Medicine, Medical College of Tianjin University, Tianjin, China.
Chong ChenAcademy of Medical Engineering and Translational Medicine, Medical College of Tianjin University, Tianjin, China.
Xiao-Hong LiAcademy of Medical Engineering and Translational Medicine, Medical College of Tianjin University, Tianjin, China.
Tianjin University · CNTianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Post-translational modification (PTM) refers to the covalent attachment of functional groups to protein substrates, resulting in structural and functional changes. PTMs not only regulate the development and progression of liver cancer, but also play a crucial role in the immune response against cancer. Cancer immunity encompasses the combined efforts of innate and adaptive immune surveillance against tumor antigens, tumor cells, and tumorigenic microenvironments. Increasing evidence suggests that immunotherapies, which harness the immune system's potential to combat cancer, can effectively improve cancer patient prognosis and prolong the survival. This review presents a comprehensive summary of the current understanding of key PTMs such as phosphorylation, ubiquitination, SUMOylation, and glycosylation in the context of immune cancer surveillance against liver cancer. Additionally, it highlights potential targets associated with these modifications to enhance the response to immunotherapies in the treatment of liver cancer.

Indexed as

Liver NeoplasmsGlycosylationHumansImmunologic SurveillancePhosphorylationProtein Processing, Post-TranslationalTumor Microenvironmentglycosylationhepatocellular carcinomaimmune surveillancephosphorylationpost-translational modificationsSUMOylationubiquitination

Identifiers

PMID37609076
PMCPMC10441662
OpenAlexW4383912561

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.