Peroxisome proliferator-activated receptor gamma agonists have been proposed as breast cancer preventives. Individuals who carry a mutated copy of BRCA1, DNA repair-associated gene, are at increased risk for development of breast cancer. Published data in the field suggest there could be interactions between peroxisome proliferator-activated receptor gamma and BRCA1 that could influence the activity of peroxisome proliferator-activated receptor gamma agonists for prevention. This review explores these possible interactions between peroxisome proliferator-activated receptor gamma, peroxisome proliferator-activated receptor gamma agonists and BRCA1 and discusses feasible experimental directions to provide more definitive information on the potential connections.
Priscilla A Furth
Sarah A Dabydeen and Priscilla A Furth
The majority of human breast cancers are estrogen receptor-positive (ER+), but this has proven challenging to model in genetically engineered mice. This review summarizes information on 21 mouse models that develop ER+ mammary cancer. Where available, information on cancer pathology and gene expression profiles is referenced to assist in understanding which histological subtype of ER+ human cancer each model might represent. ESR1, CCDN1, prolactin, TGFα, AIB1, ESPL1, and WNT1 overexpression, PIK3CA gain of function, as well as loss of P53 (Trp53) or STAT1 are associated with ER+ mammary cancer. Treatment with the PPARγ agonist efatutazone in a mouse with Brca1 and p53 deficiency and 7,12-dimethylbenz(a)anthracene exposure in combination with an activated myristoylated form of AKT1 also induce ER+ mammary cancer. A spontaneous mutant in nude mice that develops metastatic ER+ mammary cancer is included. Age of cancer development ranges from 3 to 26 months and the percentage of cancers that are ER+ vary from 21 to 100%. Not all models are characterized as to their estrogen dependency and/or response to anti-hormonal therapy. Strain backgrounds include C57Bl/6, FVB, BALB/c, 129S6/SvEv, CB6F1, and NIH nude. Most models have only been studied on one strain background. In summary, while a range of models are available for studies of pathogenesis and therapy of ER+ breast cancers, many could benefit from further characterization, and opportunity for development of new models remains.
Shahin Assefnia, Keunsoo Kang, Svenja Groeneveld, Daisuke Yamaji, Sarah Dabydeen, Ahmad Alamri, Xuefeng Liu, Lothar Hennighausen and Priscilla A Furth
Transformation-related protein 63 (Trp63), the predominant member of the Trp53 family, contributes to epithelial differentiation and is expressed in breast neoplasia. Trp63 features two distinct promoters yielding specific mRNAs encoding two major TRP63 isoforms, a transactivating transcription factor and a dominant negative isoform. Specific TRP63 isoforms are linked to cell cycle arrest, apoptosis, survival, and epithelial mesenchymal transition (EMT). Although TRP63 overexpression in cultured cells is used to elucidate functions, little is known about Trp63 regulation in normal and cancerous mammary tissues. This study used ChIP-seq to interrogate transcription factor binding and histone modifications of the Trp63 locus in mammary tissue and RNA-seq and immunohistochemistry to gauge gene expression. H3K4me2 and H3K4me3 marks coincided only with the proximal promoter, supporting RNA-seq data showing the predominance of the dominant negative isoform. STAT5 bound specifically to the Trp63 proximal promoter and Trp63 mRNA levels were elevated upon deleting Stat5 from mammary tissue, suggesting its role as a negative regulator. The dominant negative TRP63 isoform was localized to nuclei of basal mammary epithelial cells throughout reproductive cycles and retained in a majority of the triple-negative cancers generated from loss of full-length Brca1. Increased expression of dominant negative isoforms was correlated with developmental windows of increased progesterone receptor binding to the proximal Trp63 promoter and decreased expression during lactation was correlated with STAT5 binding to the same region. TRP63 is present in the majority of triple-negative cancers resulting from loss of Brca1 but diminished in less differentiated cancer subtypes and in cancer cells undergoing EMT.
Ahmad M Alamri, Keunsoo Kang, Svenja Groeneveld, Weisheng Wang, Xiaogang Zhong, Bhaskar Kallakury, Lothar Hennighausen, Xuefeng Liu and Priscilla A Furth
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.