Evidence map›Paper›PMID 36765733›Full record

ReviewCancers2023

Genetics and RNA Regulation of Uveal Melanoma.

Cristina Barbagallo, Michele Stella, Giuseppe Broggi, Andrea Russo, Rosario Caltabiano, Marco Ragusa

Abstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 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

21 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. The multiple roles of autophagy in uveal melanoma and the microenvironment.Journal of cancer research and clinical oncology · 2024
    Pooled it
  2. Pooled it
  3. Gene therapy for uveal melanoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
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  5. Article
  6. Article
  7. Article
  8. Article
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  10. Co-occurrence ofAmerican journal of ophthalmology case reports · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Review
  18. Review
  19. Machine Learning Methods for Gene Selection in Uveal Melanoma.International journal of molecular sciences · 2024
    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

6 authors.

Cristina BarbagalloDepartment of Biomedical and Biotechnological Sciences-Section of Biology and Genetics, University of Catania, 95123 Catania, Italy.ORCID 0000-0002-6769-4516
Michele StellaDepartment of Biomedical and Biotechnological Sciences-Section of Biology and Genetics, University of Catania, 95123 Catania, Italy.ORCID 0000-0002-3852-9933
Giuseppe BroggiDepartment of Medical, Surgical Sciences and Advanced Technologies G.F. Ingrassia-Section of Anatomic Pathology, University of Catania, 95123 Catania, Italy.ORCID 0000-0003-2576-6523
Andrea RussoDepartment of Ophthalmology, University of Catania, 95123 Catania, Italy.ORCID 0000-0002-7725-5971
Rosario CaltabianoDepartment of Medical, Surgical Sciences and Advanced Technologies G.F. Ingrassia-Section of Anatomic Pathology, University of Catania, 95123 Catania, Italy.ORCID 0000-0001-8591-8010
Marco RagusaDepartment of Biomedical and Biotechnological Sciences-Section of Biology and Genetics, University of Catania, 95123 Catania, Italy.ORCID 0000-0002-4282-920X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Uveal melanoma (UM) is the most common intraocular malignant tumor and the most frequent melanoma not affecting the skin. While the rate of UM occurrence is relatively low, about 50% of patients develop metastasis, primarily to the liver, with lethal outcome despite medical treatment. Notwithstanding that UM etiopathogenesis is still under investigation, a set of known mutations and chromosomal aberrations are associated with its pathogenesis and have a relevant prognostic value. The most frequently mutated genes are

Indexed as

cancercircRNAdriver mutationseyelncRNAmelanomamiRNAmRNA

Identifiers

PMID36765733
PMCPMC9913768

What OpenQuestion holds

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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.