Primary cancer cell culture: mammary-optimized vs conditional reprogramming

    1. Priscilla A Furth1,8
    1. 1Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA
    2. 2Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, King Khalid University, Abha, Saudi Arabia
    3. 3Laboratory of Genetics and Physiology, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, 8 Center Drive, Bethesda, Maryland, USA
    4. 4Department of Microbiology, Dankook University, Cheonan, Republic of Korea
    5. 5Department Pharmazie, Ludwig-Maximilians-Universität München, Munich, Germany
    6. 6Department of Biostatistics, Bioinformatics and Biomathematics, Georgetown University, Washington, District of Columbia, USA
    7. 7Department of Pathology, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA
    8. 8Department of Medicine, Lombardi Comprehensive Cancer Center, Georgetown University, Washington, District of Columbia, USA
    1. Correspondence should be addressed to P A Furth; Email: Paf3{at}georgetown.edu

    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.

    Keywords
    • Received 10 May 2016
    • Accepted 6 June 2016
    • Made available online as an Accepted Preprint 1 July 2016
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