Evidence map›Paper›PMID 26935058›Full record

ArticleTumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine2016

Highly and moderately aggressive mouse ovarian cancer cell lines exhibit differential gene expression.

Fengkun Du, Yan Li, Wensheng Zhang, Shubha P Kale, Harris McFerrin, Ian Davenport, Guangdi Wang, Elena Skripnikova, Xiao-Lin Li, Nathan J Bowen and 5 more

Open access · greenAbstract read
In one paragraph

Article in Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.1field-weighted citation impact, top 10% 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

9 citing papers in PubMed, 19 citations in OpenAlex.

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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

15 authors at 5 institutions in 2 countries.

Fengkun Du *Department of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Yan Li *Department of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Wensheng ZhangDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Shubha P KaleDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Harris McFerrinDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Ian DavenportDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Guangdi WangDepartment of Chemistry, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Elena SkripnikovaDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Xiao-Lin LiDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Nathan J BowenDepartment of Biology Sciences, Clark Atlanta University, 23 James P. Brawley Drive, SW, Atlanta, GA 30314, USA.
Leticia B McDanielsDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Yuan-Xiang MengDepartment of Family Medicine, Morehouse School of Medicine, 1513 E. Cleveland Ave. Building 100, East Point, GA 30344, USA.
Paula PolkResearch Core Facility, LSUHSC Health Sciences Center - Shreveport, 1501 Kings Hwy, Shreveport, LA 71103, USA.
Yong-Yu LiuDepartment of Basic Pharmaceutical Sciences, University of Louisiana at Monroe, 700 University Avenue, Monroe, LA 71209, USA.
Qian-Jin ZhangDepartment of Biology, Xavier University of Louisiana, 1 Drexel Drive, New Orleans, LA 70125, USA.
Xavier University of Louisiana · USClark Atlanta University · USLouisiana State University Health Sciences Center New Orleans · USMorehouse School of Medicine · USUniversity of Louisiana at Monroe · US

Funding

Xavier's RCMI Cancer Research ProgramG12MD007595 · NIMHD · XAVIER UNIVERSITY OF LOUISIANA · PI D'AMOUR, GENE, WANG, GUANGDI · 2012 to 2018
$15.7M
Technologies/Resources for Core LaboratoriesG12MD007590 · NIMHD · CLARK ATLANTA UNIVERSITY · PI KHAN, SHAFIQ A · 2012 to 2018
$7.6M
NIMHD NIH HHS G12 MD007590NIMHD NIH HHS G12 MD007595
6 · The paper itself

Abstract

Patients with advanced epithelial ovarian cancer often experience disease recurrence after standard therapies, a critical factor in determining their five-year survival rate. Recent reports indicated that long-term or short-term survival is associated with varied gene expression of cancer cells. Thus, identification of novel prognostic biomarkers should be considered. Since the mouse genome is similar to the human genome, we explored potential prognostic biomarkers using two groups of mouse ovarian cancer cell lines (group 1: IG-10, IG-10pw, and IG-10pw/agar; group 2: IG-10 clones 2, 3, and 11) which display highly and moderately aggressive phenotypes in vivo. Mice injected with these cell lines have different survival time and rates, capacities of tumor, and ascites formations, reflecting different prognostic potentials. Using an Affymetrix Mouse Genome 430 2.0 Array, a total of 181 genes were differentially expressed (P < 0.01) by at least twofold between two groups of the cell lines. Of the 181 genes, 109 and 72 genes were overexpressed in highly and moderately aggressive cell lines, respectively. Analysis of the 109 and 72 genes using Ingenuity Pathway Analysis (IPA) tool revealed two cancer-related gene networks. One was associated with the highly aggressive cell lines and affiliated with MYC gene, and another was associated with the moderately aggressive cell lines and affiliated with the androgen receptor (AR). Finally, the gene enrichment analysis indicated that the overexpressed 89 genes (out of 109 genes) in highly aggressive cell lines had a function annotation in the David database. The cancer-relevant significant gene ontology (GO) terms included Cell cycle, DNA metabolic process, and Programmed cell death. None of the genes from a set of the 72 genes overexpressed in the moderately aggressive cell lines had a function annotation in the David database. Our results suggested that the overexpressed MYC and 109 gene set represented highly aggressive ovarian cancer potential biomarkers while overexpressed AR and 72 gene set represented moderately aggressive ovarian cancer potential biomarkers. Based on our knowledge, the current study is first time to report the potential biomarkers relevant to different aggressive ovarian cancer. These potential biomarkers provide important information for investigating human ovarian cancer prognosis.

Indexed as

TranscriptomeAnimalsBiomarkers, TumorCarcinoma, Ovarian EpithelialDisease Models, AnimalFemaleGene Expression ProfilingGene Regulatory NetworksMiceMice, Inbred C57BLNeoplasms, Glandular and EpithelialOligonucleotide Array Sequence AnalysisOvarian NeoplasmsReal-Time Polymerase Chain ReactionBiomarkers, TumorBioinformaticsOvarian cancerPrognostic biomarkers

Identifiers

PMID26935058
PMCPMC5292133
OpenAlexW2292780217

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.