Evidence map›Paper›PMID 34234857›Full record

ReviewJournal of Cancer2021

Potential impact and mechanism of Long Non-coding RNAs on cancer and associated T cells.

Wenxiu Chen, Shuna Liu, Fang Wang

Open access · goldAbstract readReview
In one paragraph

Review in Journal of Cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.1field-weighted citation impact, top 25% 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

12 citing papers in PubMed, 17 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
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.

Wenxiu ChenDepartment of Laboratory Medicine, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 210029.
Shuna LiuDepartment of Laboratory Medicine, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 210029.
Fang WangDepartment of Laboratory Medicine, the First Affiliated Hospital of Nanjing Medical University, Nanjing, China, 210029.
Nanjing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The discovery of many aberrant expressions of long non-coding RNAs (lncRNAs) in various cancers has focused attention on the effects of lncRNA on cancer cells themselves, including cell proliferation, growth inhibition, cell migration, cell immortality, vascular regeneration and cell viability. But with the increasing role of immunotherapy in cancer therapy, a large number of studies have revealed that the regulatory role of lncRNAs in immunity such as differentiation of immune cells can also influence the development and progression of cancer. In particular, recent publications have suggested that lncRNAs play critical roles in T-lymphocyte activation, proliferation, differentiation, function, apoptosis and metabolism. To elucidate the actual functions of lncRNAs at the molecular level of cancer pathogenesis, we summarize some of the current lncRNA regulatory mechanisms associated with T cell to discuss their effects in cancer in the hope of providing potential cancer therapeutic targets or cancer biomarkers. However, we all know that the differentiation and function of T cells is an extremely complex process that involves the expression and regulation of multiple lncRNAs. As a result, more regulatory mechanisms of lncRNAs need to be further studied.

Indexed as

cancerLong non-coding RNAsT cell

Identifiers

PMID34234857
PMCPMC8247393
OpenAlexW3174756009

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.