Evidence map›Paper›PMID 32183025›Full record

ArticleCancers2020

Identification of PLK1 as a New Therapeutic Target in Mucinous Ovarian Carcinoma.

Roberta Affatato, Laura Carrassa, Rosaria Chilà, Monica Lupi, Valentina Restelli, Giovanna Damia

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

23 citing papers in PubMed, 37 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Review
  17. Options for the Treatment of Mucinous Ovarian Carcinoma.Current treatment options in oncology · 2021
    Review
  18. Review
  19. Article
  20. 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

6 authors at 1 institution in 1 country.

Roberta AffatatoLaboratory of Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Via Mario Negri 2, 20156 Milan, Italy.
Laura CarrassaCore Research Laboratory-ISPRO, Viale Pieraccini 6, 50139 Firenze, Italy.
Rosaria ChilàIstituto FIRC di Oncologia Molecolare (IFOM)-Via Adamello 16, 20139 Milan, Italy.
Monica LupiLaboratory of Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Via Mario Negri 2, 20156 Milan, Italy.
Valentina RestelliLaboratory of Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Via Mario Negri 2, 20156 Milan, Italy.
Giovanna DamiaLaboratory of Molecular Pharmacology, Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Via Mario Negri 2, 20156 Milan, Italy.
Mario Negri Institute for Pharmacological Research · IT

Funding

Associazione Italiana per la Ricerca sul Cancro 19797
6 · The paper itself

Abstract

Mucinous epithelial ovarian cancer (mEOC) is a rare subset of epithelial ovarian cancer. When diagnosed at a late stage, its prognosis is very poor, as it is quite chemo-resistant. To find new therapeutic options for mEOC, we performed high-throughput screening using a siRNA library directed against human protein kinases in a mEOC cell line, and polo-like kinase1 (PLK1) was identified as the kinase whose downregulation interfered with cell proliferation. Both PLK1 siRNA and two specific PLK1 inhibitors (onvansertib and volasertib) were able to inhibit cell growth, induce apoptosis and block cells in the G2/M phase of the cell cycle. We evaluated,

Indexed as

mucinous ovarian carcinomaPLK1screening

Identifiers

PMID32183025
PMCPMC7140026
OpenAlexW3011759723

What Socratic 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 Socratic graph.