Evidence map›Paper›PMID 29511313›Full record

ArticleCancer gene therapy2018

Evaluation of FOXC1 as a therapeutic target for basal-like breast cancer.

Landon Mott, Kai Su, Daniel W Pack

Abstract read
PubMed Publisher
In one paragraph

Article in Cancer gene therapy, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

3 authors at 1 institution in 1 country.

Landon MottDepartment of Chemical and Materials Engineering, University of Kentucky, Lexington, KY, 40506, USA.
Kai SuDepartment of Pharmaceutical Sciences, University of Kentucky, Lexington, KY, 40536, USA.
Daniel W PackDepartment of Chemical and Materials Engineering, University of Kentucky, Lexington, KY, 40506, USA. dan.pack@uky.edu.ORCID http://orcid.org/0000-0003-0410-0423
University of Kentucky · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Basal-like breast cancer (BLBC) is a malignant carcinoma with aggressive motility and rapid growth. Accounting for 15% of breast cancers, BLBC often exhibits a poor prognosis and tends to metastasize to the brain and lungs. Because most BLBC display a triple-negative phenotype (ER-, PR-, and HER2-), conventional cytotoxic chemotherapy remains the only treatment option despite poor success and high rate of relapse. The overexpression of the forkhead-box transcription factor C1 (FOXC1) was recently identified as a biomarker of BLBC. Increased expression of FOXC1 was linked to excessive mobility and growth of BLBC cell lines, suggesting FOXC1 as a therapeutic target. In this study, siRNA-mediated knockdown of FOXC1 was confirmed to decrease the proliferation rate, migration, and invasion in a model BLBC-like cell line (4T1). 4T1 and 4T1-∆FOXC1 cells lacking FOXC1 expression (generated by CRISPR/Cas9) were used to evaluate the effects of FOXC1 expression in an orthotopic murine model of BLBC. No statistically significant difference in tumor volume was observed between 4T1 and 4T1-∆FOXC1 tumors. Furthermore, tumors metastasized to the liver and lungs to a similar degree regardless of FOXC1 expression. These data suggest that, despite positive results in vitro, FOXC1 may not be a promising therapeutic target for BLBC.

Indexed as

Forkhead Transcription FactorsGene Expression Regulation, NeoplasticMammary Neoplasms, AnimalNeoplasm ProteinsAnimalsCell Line, TumorFemaleMiceNeoplasm MetastasisForkhead Transcription FactorsFoxc1 protein, mouseNeoplasm Proteins

Identifiers

PMID29511313
OpenAlexW2792586190

What OpenQuestion holds

Textmetadata
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.