Evidence map›Paper›PMID 23721800›Full record

ArticleGynecologic oncology2013

Targeting CD133 in an in vivo ovarian cancer model reduces ovarian cancer progression.

Amy P N Skubitz, Elizabeth P Taras, Kristin L M Boylan, Nate N Waldron, Seunguk Oh, Angela Panoskaltsis-Mortari, Daniel A Vallera

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Gynecologic oncology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
55citing papers in PubMed, 1 pooled it
4.2field-weighted citation impact, top 5% 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

55 citing papers in PubMed, 1 synthesis or guideline pooled it, 106 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. A Journey to Reach the Ovary Using Next-Generation Technologies.International journal of molecular sciences · 2023
    Review
  8. Review
  9. Targeting ovarian cancer stem cells: a new way out.Stem cell research & therapy · 2023
    Review
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Review
  18. Ovarian Cancer Stem Cells: Characterization and Role in Tumorigenesis.Advances in experimental medicine and biology · 2021
    Article
  19. Article
  20. Stem Cells in Ovarian Cancer and Potential Therapies.Proceedings of stem cell research and oncogenesis · 2020
    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

7 authors at 2 institutions in 1 country.

Amy P N SkubitzDepartment of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA. skubi002@umn.edu
Elizabeth P Taras
Kristin L M Boylan
Nate N Waldron
Seunguk Oh
Angela Panoskaltsis-Mortari
Daniel A Vallera
University of Minnesota · USUniversity of Minnesota Medical Center · US

Funding

Women's CancerP30CA077598 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI Douglas Yee · 1998 to 2026
$100.4M
IMMUNOTOXINS IN HUMAN BONE MARROW TRANSPLANTATIONR01CA036725 · NCI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI VALLERA, DANIEL A · 1985 to 2015
$3.3M
NCI NIH HHS P30 CA077598NCI NIH HHS P30 CA77598NCI NIH HHS R01 CA036725NCI NIH HHS R01-CA36725
6 · The paper itself

Abstract

objectivesWhile most women with ovarian cancer will achieve complete remission after treatment, the majority will relapse within two years, highlighting the need for novel therapies. Cancer stem cells (CSC) have been identified in ovarian cancer and most other carcinomas as a small population of cells that can self-renew. CSC are more chemoresistant and radio-resistant than the bulk tumor cells; it is likely that CSC are responsible for relapse, the major problem in cancer treatment. CD133 has emerged as one of the most promising markers for CSC in ovarian cancer. The hypothesis driving this study is that despite their low numbers in ovarian cancer tumors, CSC can be eradicated using CD133 targeted therapy and tumor growth can be inhibited.

methodsOvarian cancer cell lines were evaluated using flow cytometry for expression of CD133. In vitro viability studies with an anti-CD133 targeted toxin were performed on one of the cell lines, NIH:OVCAR5. The drug was tested in vivo using a stably transfected luciferase-expressing NIH:OVCAR5 subline in nude mice, so that tumor growth could be monitored by digital imaging in real time.

resultsOvarian cancer cell lines showed 5.6% to 16.0% CD133 expression. dCD133KDEL inhibited the in vitro growth of NIH:OVCAR5 cells. Despite low numbers of CD133-expressing cells in the tumor population, intraperitoneal drug therapy caused a selective decrease in tumor progression in intraperitoneal NIH:OVCAR5-luc tumors.

conclusionsDirectly targeting CSC that are a major cause of drug resistant tumor relapse with an anti-CD133 targeted toxin shows promise for ovarian cancer therapy.

Indexed as

AC133 AntigenAnimalsAntibodies, MonoclonalAntigens, CDBiomarkers, TumorCell Line, TumorCell ProliferationCytotoxinsDisease Models, AnimalDisease ProgressionFemaleGlycoproteinsHumansMiceMice, NudeMolecular Targeted TherapyAC133 AntigenAntibodies, MonoclonalAntigens, CDBiomarkers, TumorCytotoxinsGlycoproteinsPeptidesPROM1 protein, humanProm1 protein, mouseaaAbamino acidantibodyCancer stem cellsCD133CD19CD45cluster of differentiation 19cluster of differentiation 45dCD133KDELdeimmunized pseudomonas exotoxin fused to anti-CD133 scFv with a KDEL terminusendoplasmic reticulumERFITCfluorescein isothiocyanateKDELLys-Asp-Glu-LeumAbmonoclonal antibodyOvarian cancerPEphotons per second per square centimeter per steradianphotons/s/cm(2)/srpseudomonas exotoxinrecombinant single chain VH and VL domainscFvTargeted toxinXenograft model

Identifiers

PMID23721800
PMCPMC3906852
OpenAlexW2077587951

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.