Evidence map›Paper›PMID 27267121›Full record

ArticleEndocrine-related cancer2016

Primary cancer cell culture: mammary-optimized vs conditional reprogramming.

Ahmad M Alamri, Keunsoo Kang, Svenja Groeneveld, Weisheng Wang, Xiaogang Zhong, Bhaskar Kallakury, Lothar Hennighausen, Xuefeng Liu, Priscilla A Furth

Abstract read
In one paragraph

Article in Endocrine-related cancer, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
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

19 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Application and Progress of Cultured Models of Gallbladder Carcinoma.Journal of clinical and translational hepatology · 2023
    Review
  8. Review
  9. Review
  10. Article
  11. Conditional Cell Reprogramming in Modeling Digestive System Diseases.Frontiers in cell and developmental biology · 2021
    Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Responsiveness ofCancer prevention research (Philadelphia, Pa.) · 2017
    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

9 authors.

Ahmad M AlamriDepartment of OncologyLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA Department of Clinical Laboratory SciencesCollege of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia.
Keunsoo KangLaboratory of Genetics and PhysiologyNational Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 8 Center Drive, Bethesda, Maryland, USA Department of MicrobiologyDankook University, Cheonan, Republic of Korea.
Svenja GroeneveldDepartment of OncologyLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA Department PharmazieLudwig-Maximilians-Universität München, Munich, Germany.
Weisheng WangDepartment of OncologyLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA.
Xiaogang ZhongDepartment of BiostatisticsBioinformatics and Biomathematics, Georgetown University, Washington, District of Columbia, USA.
Bhaskar KallakuryDepartment of PathologyLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA.
Lothar HennighausenLaboratory of Genetics and PhysiologyNational Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 8 Center Drive, Bethesda, Maryland, USA.
Xuefeng LiuDepartment of PathologyLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA.
Priscilla A FurthDepartment of OncologyLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA Department of MedicineLombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA Paf3@georgetown.edu.

Funding

Tissue Culture Shared ResourceP30CA051008 · NCI · GEORGETOWN UNIVERSITY · PI Louis M Weiner · 1990 to 2026
$71.5M
Genetic Approaches To Understanding Organ Development and FunctionZIADK061000 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI HENNIGHAUSEN, LOTHAR · 2009 to 2025
$24.7M
Genomics Core FacilityZICDK071001 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI HANOVER, JOHN A. · 2009 to 2023
$16.6M
Progression and regression of mammary preneoplasiaR01CA112176 · NCI · GEORGETOWN UNIVERSITY · PI FURTH, PRISCILLA A. · 2005 to 2018
$3.1M
NCI NIH HHS P30 CA051008NCI NIH HHS R01 CA112176
6 · The paper itself

Abstract

The impact of different culture conditions on biology of primary cancer cells is not always addressed. Here, conditional reprogramming (CRC) was compared with mammary-optimized EpiCult-B (EpiC) for primary mammary epithelial cell isolation and propagation, allograft generation, and genome-wide transcriptional consequences using cancer and non-cancer mammary tissue from mice with different dosages of Brca1 and p53 Selective comparison to DMEM was included. Primary cultures were established with all three media, but CRC was most efficient for initial isolation (P<0.05). Allograft development was faster using cells grown in EpiC compared with CRC (P<0.05). Transcriptome comparison of paired CRC and EpiC cultures revealed 1700 differentially expressed genes by passage 20. CRC promoted Trp53 gene family upregulation and increased expression of epithelial differentiation genes, whereas EpiC elevated expression of epithelial-mesenchymal transition genes. Differences did not persist in allografts where both methods yielded allografts with relatively similar transcriptomes. Restricting passage (<7) reduced numbers of differentially expressed genes below 50. In conclusion, CRC was most efficient for initial cell isolation but EpiC was quicker for allograft generation. The extensive culture-specific gene expression patterns that emerged with longer passage could be limited by reducing passage number when both culture transcriptomes were equally similar to that of the primary tissue. Defining impact of culture condition and passage on the transcriptome of primary cells could assist experimental design and interpretation. For example, differences that appear with passage and culture condition are potentially exploitable for comparative studies targeting specific biological networks in different transcriptional environments.

Indexed as

Mammary Glands, AnimalMammary Neoplasms, ExperimentalAnimalsEpithelial CellsEpithelial-Mesenchymal TransitionFemaleGene Expression ProfilingMice, Inbred C57BLMice, TransgenicPrimary Cell CultureTranscriptomeTumor Cells, CulturedBrca1genetically engineered mouse modelsmammary cancerprimary cell culturetranscriptome

Identifiers

PMID27267121
PMCPMC4962879

What OpenQuestion holds

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Registered trials

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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.