Evidence map›Paper›PMID 37118933›Full record

ArticleThe Prostate2023

Upregulation of TLR5 indicates a favorable prognosis in prostate cancer.

Hongbin Liang, Lin Zhang, Ziying Liu, Bettina Hoden, David DeRubeis, Yifan Zhang, Fen Wang, Dekai Zhang

Open access · hybridAbstract read
In one paragraph

Article in The Prostate, 2023. 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
0.8field-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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Review
  3. 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

8 authors at 1 institution in 1 country.

Hongbin LiangDepartment of Translational Medical Sciences, Center for Infectious and Inflammatory Diseases, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
Lin ZhangDepartment of Translational Medical Sciences, Center for Infectious and Inflammatory Diseases, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
Ziying LiuDepartment of Translational Medical Sciences, Center for Translational Cancer Research, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
Bettina HodenDepartment of Translational Medical Sciences, Center for Infectious and Inflammatory Diseases, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
David DeRubeisDepartment of Translational Medical Sciences, Center for Infectious and Inflammatory Diseases, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
Yifan ZhangDepartment of Translational Medical Sciences, Center for Infectious and Inflammatory Diseases, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
Fen WangDepartment of Translational Medical Sciences, Center for Translational Cancer Research, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.
Dekai ZhangDepartment of Translational Medical Sciences, Center for Infectious and Inflammatory Diseases, Institute of Bioscience and Technology, Texas A&M University, Houston, Texas, USA.ORCID 0000-0002-6815-8571
Texas A&M University · US

Funding

Targeting tumor cell Toll-like receptorR21CA176698 · NCI · TEXAS A&M UNIVERSITY HEALTH SCIENCE CTR · PI ZHANG, DEKAI · 2014 to 2015
$341k
NCI NIH HHS R21 CA176698NIH HHS
6 · The paper itself

Abstract

backgroundToll-like receptors (TLRs) are the key sensors of innate immunity for triggering immune responses against infections. TLRs are well known to be expressed and activated in innate immune cells, such as macrophage and dendritic cells, but we and others have found that some TLRs are also functional in epithelial cells. However, the role of an epithelial TLR in prostate cancer remains elusive.

methodsTLR5 expression in messenger RNA and protein level in prostate cancer was determined by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). The activation of TLR5 signaling in epithelial cells was detected upon nuclear factor-κB activation by luciferase assay and western blot analysis, and proinflammatory cytokine activation by RT-qPCR. Distinguishing between the TLR5 and NLRC4 pathways, both recognizing flagellin, is determined by small interfering RNA and proinflammatory cytokine activation. The role of TLR5 in prostate cancer was analyzed by IHC and bioinformatics using a general and single-cell database.

resultsIn the present study, we show that TLR5, among other TLRs, is exceedingly expressed in human prostate cancer cells. This cancer epithelial cell TLR5 functions to activate the TLR5 signaling pathway in human prostate cancer cells, as it does with innate immune cell TLR5. The bacterial protein flagellin induces a robust immune response in prostate cancer cells in a TLR5-dependent but NLRC4-independent manner. TLR5 is highly expressed in prostate cancer patient specimens, and high TLR5 expression in prostate cancer patients indicates a favorable prognosis.

conclusionsTLR5, as an innate immunity receptor, is a functional TLR in human prostate cancer epithelial cells. TLR5 plays an important role in prostate cancer development and is a new potential prognosis biomarker. TLR5 may represent a novel immunotherapy target against prostate cancer.

Indexed as

Prostatic NeoplasmsToll-Like Receptor 5CytokinesFlagellinHumansMalePrognosisToll-Like ReceptorsUp-RegulationCytokinesFlagellinToll-Like Receptor 5Toll-Like Receptorscancer immunityflagellininnate immunityprognosisprostate cancerToll-like receptor 5

Identifiers

PMID37118933
PMCPMC10330358
OpenAlexW4367368541

What OpenQuestion holds

Textmetadata
LicenceTDM
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.