Evidence map›Paper›PMID 24045973›Full record

ArticleMolecular cancer research : MCR2013

miR-106a represses the Rb tumor suppressor p130 to regulate cellular proliferation and differentiation in high-grade serous ovarian carcinoma.

Zhaojian Liu, Elizabeth Gersbach, Xiyu Zhang, Xiaofei Xu, Ruifen Dong, Peng Lee, Jinsong Liu, Beihua Kong, Changshun Shao, Jian-Jun Wei

Open access · bronzeAbstract read
In one paragraph

Article in Molecular cancer research : MCR, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

28 citing papers in PubMed, 43 citations in OpenAlex.

  1. Overview of miR-106a Regulatory Roles: from Cancer to Aging.Bioengineering (Basel, Switzerland) · 2023
    Review
  2. Review
  3. CircRNA circ_0000554 promotes ovarian cancer invasion and proliferation by regulating miR-567.Environmental science and pollution research international · 2022
    Article
  4. Article
  5. The G199X and V157fs mutations in theAnnals of translational medicine · 2021
    Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. MiR-381 inhibits epithelial ovarian cancer malignancy via YY1 suppression.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016
    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

10 authors at 5 institutions in 2 countries.

Zhaojian LiuDepartment of Pathology, Northwestern University School of Medicine, Feinberg 7-334, 251 East Huron Street, Chicago, IL 60611. jianjun-wei@northwestern.edu.
Elizabeth Gersbach
Xiyu Zhang
Xiaofei Xu
Ruifen Dong
Peng Lee
Jinsong Liu
Beihua Kong
Changshun Shao
Jian-Jun Wei
The University of Texas MD Anderson Cancer Center · USNew York University · USNorthwestern University · USShandong University · CNQilu Hospital of Shandong University · CN

Funding

Multidisciplinary Clinical and Translational Science (MCTS) Program (UL1)UL1TR000150 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI LLOYD-JONES, DONALD M · 2012 to 2013
$10.1M
MiR-182 overexpression in early tumorigenesis of high grade serous carcinomaR21CA167038 · NCI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI WEI, JIAN-JUN · 2013 to 2014
$365k
NCATS NIH HHS UL1 TR000150NCI NIH HHS R21 CA167038NCI NIH HHS R21CA167038
6 · The paper itself

Abstract

unlabelledThe degree of differentiation in human cancers generally reflects the degree of malignancy, with the most undifferentiated cancer being also the highest grade and the most aggressive. High-grade serous ovarian carcinomas (HGSOC) are poorly differentiated and fast-growing malignancies. The molecular mechanisms underlying the poor differentiation of HGSOC has not been completely characterized. Evidence suggests that miRNA, miR are dysregulated in HGSOC. Therefore, we focused on those miRNAs that are relevant to tumor differentiation. Expression profiling of miRNAs in HGSOC, indicated miR-106a and its family members were significantly upregulated. Upregulation of miR-106a was further validated by real-time reverse transcriptase PCR (qRT-PCR) and miRNA in situ hybridization in a large cohort of HGSOC specimens. Overexpression of miR-106a in benign and malignant ovarian cells significantly increased the cellular proliferation rate and expanded the side-population fraction. In particular, SKOV3 cells with miR-106a overexpression had significantly higher tumor initial/stem cell population (CD24- and CD133-positive cells) than control SKOV3 cells. Among many miR-106a predicated target genes, p130 (RBL2), an retinoblastoma (Rb) tumor suppressor family member, was not only confirmed as a specific target of miR-106a but also related to tumor growth and differentiation. The importance of mir-106a and RBL2 was further demonstrated in vivo, in which, SKOV3 cells overexpressing miR-106a formed poorly differentiated carcinomas and had reduced RBL2 levels. To our knowledge, this is the first study of miR-106a mediating proliferation and tumor differentiation in HGSOC. IMPLICATIONS: The current study suggests that the RB tumor suppressor pathway is a critical regulator of growth and differentiation in HGSOC.

Indexed as

AdultAgedAged, 80 and overAnimalsCase-Control StudiesCell DifferentiationCell Line, TumorCell ProliferationCystadenocarcinoma, SerousFemaleGene Expression Regulation, NeoplasticHumansMiceMice, NudeMicroRNAsMiddle AgedMicroRNAsMIRN106 microRNA, humanRBL2 protein, humanRetinoblastoma-Like Protein p130

Identifiers

PMID24045973
PMCPMC3911890
OpenAlexW2165947442

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.