Evidence map›Paper›PMID 37808922›Full record

ReviewMolecular therapy. Nucleic acids2023

Translatomics to explore dynamic differences in immunocytes in the tumor microenvironment.

Yilin Guo, Shiqi Yan, Wenling Zhang

Open access · goldAbstract readReview
In one paragraph

Review in Molecular therapy. Nucleic acids, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Review
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

3 authors at 1 institution in 1 country.

Yilin GuoDepartment of Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, P.R. China.
Shiqi YanDepartment of Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, P.R. China.
Wenling ZhangDepartment of Laboratory Medicine, The Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, P.R. China.
Central South University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein is an essential component of all living organisms and is primarily responsible for life activities; furthermore, its synthesis depends on a highly complex and accurate translation system. For proteins, the regulation at the translation level exceeds the sum of that during transcription, mRNA degradation, and protein degradation. Therefore, it is necessary to study regulation at the translation level. Imbalance in the translation process may change the cellular landscape, which not only leads to the occurrence, maintenance, progression, invasion, and metastasis of cancer but also affects the function of immune cells and changes the tumor microenvironment. Detailed analysis of transcriptional and protein atlases is needed to better understand how gene translation occurs. However, a more rigorous direct correlation between mRNA and protein levels is needed, which somewhat limits further studies. Translatomics is a technique for capturing and sequencing ribosome-related mRNAs that can effectively identify translation changes caused by ribosome stagnation and local translation abnormalities during cancer occurrence to further understand the changes in the translation landscape of cancer cells themselves and immune cells in the tumor microenvironment, which can provide new strategies and directions for tumor treatment.

Indexed as

antitumor immunitymRNAMT: RNA/DNA EditingTMEtranslation changestranslatomicstumor microenvironment

Identifiers

PMID37808922
PMCPMC10551571
OpenAlexW4386898362

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.