Evidence map›Paper›PMID 31051015›Full record

ReviewJournal of molecular signaling2016

Chronic Inflammation in Skin Malignancies.

Lihua Tang, Kepeng Wang

Abstract readReview
In one paragraph

Review in Journal of molecular signaling, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 pooled it
–field-weighted citation impact
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

38 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Review
  7. Article
  8. Anti-Inflammatory Effects ofPharmaceutics · 2024
    Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review: The Key Factors to Melanomagenesis.Life (Basel, Switzerland) · 2023
    Review
  15. Article
  16. Article
  17. Photo-Protective and Anti-Inflammatory Effects ofMolecules (Basel, Switzerland) · 2022
    Article
  18. Article
  19. Article
  20. 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

2 authors.

Lihua TangDepartment of Dermatology, 303 Hospital of People's Liberation Army, Nanning, Guangxi Province, China.
Kepeng WangDepartment of Immunology, School of Medicine, University of Connecticut Health Center, Farmington, Connecticut, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic inflammation is linked to the development and progression of multiple cancers, including those of the lung, stomach, liver, colon, breast and skin. Inflammation not only drives the oncogenic transformation of epithelial cells under the stress of chronic infection and autoimmune diseases, but also promotes the growth, progression and metastatic spread of cancers. Tumor-infiltrating inflammatory cells are comprised of a diverse population of myeloid and immune cell types, including monocytes, macrophages, dendritic cells, T and B cells, and others. Different myeloid and lymphoid cells within tumor microenvironment exert diverse, often contradicting, effects during skin cancer development and progression. The nature of tumor-immune interaction determines the rate of cancer progression and the outcome of cancer treatment. Inflammatory environment within skin tumor also inhibits naturally occurring anti-tumor immunity and limits the efficacy of cancer immunotherapy. In this article we aim to give an overview on the mechanism by which inflammation interferes with the development and therapeutic intervention of cancers, especially those of the skin.

Indexed as

cancer immunotherapycytokineinflammationskin cancer

Identifiers

PMID31051015
PMCPMC4911907

What OpenQuestion holds

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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.