BCL6 is a transcriptional repressor that recognizes DNA target sequences similar to those recognized by signal transducer and activator of transcriptions 5 (Stat5). BCL6 disrupts differentiation of breast epithelia, is downregulated during lactation, and is upregulated in poorly differentiated breast cancer. In contrast, Stat5a mediates prolactin-induced differentiation of mammary epithelia, and loss of Stat5 signaling in human breast cancer is associated with undifferentiated histology and poor prognosis. Here, we identify the mammary cell growth factor prolactin as a potent suppressor of BCL6 protein expression in human breast cancer through a mechanism that requires Stat5a, but not prolactin-activated Stat5b, MEK-ERK, or PI3K-AKT pathways. Prolactin rapidly suppressed BCL6 mRNA in T47D, MCF7, ZR75.1, and SKBr3 breast cancer cell lines, followed by prolonged reduction of BCL6 protein levels within 3 hours. Prolactin suppression of BCL6 was enhanced by overexpression of Stat5a but not Stat5b, was mimicked by constitutively active Stat5a, but did not require the transactivation domain of Stat5a. Stat5 chromatin immunoprecipitation demonstrated physical interaction with a BCL6 gene regulatory region, and BCL6 transcript repression required histone deacetylase activity based on sensitivity to trichostatin A. Functionally, BCL6 overexpression disrupted prolactin induction of Stat5 reporter genes. Prolactin suppression of BCL6 was extended to xenotransplant tumors in nude mice in vivo and to freshly isolated human breast cancer explants ex vivo. Quantitative immunohistochemistry revealed elevated BCL6 in high-grade and metastatic breast cancer compared with ductal carcinoma in situ and nonmalignant breast, and cellular BCL6 protein levels correlated negatively with nuclear Stat5a (r = −0.52; P < 0.001) but not with Stat5b. Loss of prolactin-Stat5a signaling and concomitant upregulation of BCL6 may represent a regulatory switch facilitating undifferentiated histology and poor prognosis of breast cancer.

Prolactin (PRL) receptors (PRLRs) have been considered selective activators of Janus tyrosine kinase (Jak)2 but not Jak1, Jak3, or Tyk2. We now report marked PRL-induced tyrosine phosphorylation of Jak1, in addition to Jak2, in a series of human breast cancer cell lines, including T47D, MCF7, and SKBR3. In contrast, PRL did not activate Jak1 in immortalized, noncancerous breast epithelial lines HC11, MCF10A, ME16C, and HBL-100, or in CWR22Rv1 prostate cancer cells or MDA-MB-231 breast cancer cells. However, introduction of exogenous PRLR into MCF10A, ME16C, or MDA-MB-231 cells reconstituted both PRL-Jak1 and PRL-Jak2 signals. In vitro kinase assays verified that PRL stimulated enzymatic activity of Jak1 in T47D cells, and PRL activated Jak1 and Jak2 with indistinguishable time and dose kinetics. Relative Jak2 deficiency did not cause PRLR activation of Jak1, because overexpression of Jak2 did not interfere with PRL activation of Jak1. Instead, PRL activated Jak1 through a Jak2-dependent mechanism, based on disruption of PRL activation of Jak1 after Jak2 suppression by 1) lentiviral delivery of Jak2 short hairpin RNA, 2) adenoviral delivery of dominant-negative Jak2, and 3) AG490 pharmacological inhibition. Finally, suppression of Jak1 by lentiviral delivery of Jak1 short hairpin RNA blocked PRL activation of ERK and signal transducer and activator of transcription (Stat)3 and suppressed PRL activation of Jak2, Stat5a, Stat5b, and Akt, as well as tyrosine phosphorylation of PRLR. The data suggest that PRL activation of Jak1 represents a novel, Jak2-dependent mechanism that may serve as a regulatory switch leading to PRL activation of ERK and Stat3 pathways, while also serving to enhance PRL-induced Stat5a/b and Akt signaling.

Prolactin controls the development and function of milk-producing breast epithelia but also supports growth and differentiation of breast cancer, especially luminal subtypes. A principal signaling mediator of prolactin, Stat5, promotes cellular differentiation of breast cancer cells in vitro, and loss of active Stat5 in tumors is associated with anti-estrogen therapy failure in patients. In luminal breast cancer progesterone induces a cytokeratin-5 (CK5)-positive basal cell-like population. This population possesses characteristics of tumor stem cells including quiescence, therapy-resistance, and tumor-initiating capacity. Here we report that prolactin counteracts induction of the CK5-positive population by the synthetic progestin R5020 in luminal breast cancer cells both in vitro and in vivo. CK5-positive cells were chemoresistant as determined by four-fold reduced rate of apoptosis following docetaxel exposure. Progestin-induction of CK5 was preceded by marked up-regulation of BCL6, an oncogene and transcriptional repressor critical for the maintenance of leukemia-initiating cells. Knockdown of BCL6 prevented induction of CK5-positive cell population by progestin. Prolactin suppressed progestin-induced BCL6 through Jak2-Stat5 but not Erk- or Akt-dependent pathways. In premenopausal but not postmenopausal patients with hormone receptor-positive breast cancer, tumor protein levels of CK5 correlated positively with BCL6, and high BCL6 or CK5 protein levels were associated with unfavorable clinical outcome. Suppression of progestin-induction of CK5-positive cells represents a novel pro-differentiation effect of prolactin in breast cancer. The present progress may have direct implications for breast cancer progression and therapy since loss of prolactin receptor-Stat5 signaling occurs frequently and BCL6 inhibitors currently being evaluated for lymphomas may have value for breast cancer.

BackgroundProlactin (PRL) is essential for normal mammary gland development. PRL promotes mammary tumor formation in rodents and elevated serum prolactin is associated with increased risk of estrogen-receptor positive breast cancer in women. On the other hand, PRL may also exert pro-differentiation effects and act to suppress invasive features of established breast cancer. Previously published limited global transcript profiling analyses of prolactin-regulated gene expression in human breast cancer cells have exclusively been performed in vitro. The present study aimed to shed new light on how PRL modulates estrogen receptor (ER)-positive breast cancer through global transcript profiling of a human breast cancer xenograft model in vivo.MethodsThe prolactin-responsive human T47D breast cancer cell line was xenotransplanted into nude mice and global transcript profiling was carried out following treatment with or without human PRL for 48 h. A subset of PRL-modulated transcripts was further validated using qRT-PCR and immunohistochemistry.ResultsThe in vivo analyses identified 130 PRL-modulated transcripts, 75 upregulated and 55 downregulated, based on fold change >1.6 and P-value <0.05. From this initial panel of transcripts, a subset of 18 transcripts with established breast cancer-relevance were selected and validated by qRT-PCR. Some but not all of the transcripts were also PRL-modulated in vitro. The selected PRL-modulated transcripts were tested for dependence on Stat5, Jak1 or Jak2 activation, and for co-regulation by 17β-estradiol (E2). The protein encoded by one of the PRL-regulated transcripts, PTHrP, was examined in a panel of 92 human breast cancers and found by in situ quantitative immunofluorescence analysis to be highly positively correlated with nuclear localized and tyrosine phosphorylated Stat5. Gene Ontology analysis revealed that PRL-upregulated genes were enriched in pathways involved in differentiation. Finally, a gene signature based on PRL-upregulated genes was associated with prolonged relapse-free and metastasis-free survival in breast cancer patients.ConclusionsThis global analysis identified and validated a panel of PRL-modulated transcripts in an ER-positive human breast cancer xenotransplant model, which may have value as markers of relapse-free and metastasis-free survival. Gene products identified in the present study may facilitate ongoing deciphering of the pleiotropic effects of PRL on human breast cancer.

We present a sectioning and bonding technology to make ultrahigh density microarrays of solid samples, cutting edge matrix assembly (CEMA). Maximized array density is achieved by a scaffold-free, self-supporting construction with rectangular array features that are incrementally scalable. This platform technology facilitates arrays of >10,000 tissue features on a standard glass slide, inclusion of unique sample identifiers for improved manual or automated tracking, and oriented arraying of stratified or polarized samples.

Introduction Value-based contracts (VBCs) that link drug payments to disease-related performance metrics aim to increase the value and lower the cost of medications by aligning incentives and sharing risk between payers and pharmaceutical manufacturers. This study sought to identify outcome measures that are meaningful to key stakeholders to inform VBCs for coronary artery disease (CAD) medications. Methods We administered a modified Delphi survey to gather expert opinion from a diverse panel of patients ( n = 9), cardiologists ( n = 4), primary care physicians ( n = 5), payers ( n = 2), pharmacy benefits managers ( n = 3), and pharmaceutical company representatives ( n = 2). A list of 16 CAD-associated clinical indicators was generated from the literature and expert consultation. Delphi participants rated the importance of each outcome on a five-point Likert scale, and selected the three most meaningful outcomes. We defined consensus as ≥ 75% agreement on the importance of an outcome (Likert scores 4 or 5 or selection of an outcome as most meaningful). Results Eleven of 13 outcomes reached consensus for importance on the Likert scale. “Preventing heart attacks” was selected as the most meaningful outcome (80%) while “preventing death” ranked second (76%). Conclusions Our study results verify the utility of a widely used clinical CAD outcome measure, myocardial infarction events, for the purpose of pharmaceutical value-based contracting. Electronic supplementary material The online version of this article (10.1007/s40119-019-0132-7) contains supplementary material, which is available to authorized users.

Objective: The objective of this study was to describe national changes in utilization and associated costs of antidiabetic medications in the United States from 2014 to 2019, across different drug classes and insurance plans. Research Design and Methods: This retrospective, cross-sectional study examined administrative claims from a large national pharmacy benefits manager from January 1, 2014, to December 31, 2019. Patients aged 18 years and above enrolled in commercial, Medicare, or Medicaid health plans who filled ≥1 prescription claim for an antidiabetic medication(s) during the 6-year period were included. Utilization was examined as the total number of 30-day adjusted prescription fills per user per month (PUPM). Gross costs were calculated as the sum of plan costs (net of rebates) and member out-of-pocket costs. Differences in mean utilization and costs PUPM between 2014 and 2019 for each medication class were calculated. Results: The final analytic sample increased from 745,290 patients in 2014 to 1,596,006 in 2019. Antidiabetic medication utilization increased by 8.8% from 2014 to 2019, driven by increases in sodium-glucose cotransporter 2 inhibitor (48.7%; P<0.001), glucagon-like peptide 1 receptor agonist (11.8%; P<0.001), insulin (8.1%; P<0.001), and metformin (2.9%; P<0.05) utilization. Average costs PUPM rose 47.5% (P<0.001), from $126.52 in 2014 to $186.58 in 2019. Sodium-glucose cotransporter 2 inhibitors, glucagon-like peptide 1 receptor agonists, and combination drugs contributed significantly to these increased costs, with 6-year cost differences of 57.3%, 46.9%, and 47.2%, respectively (all P<0.001). Conclusion: Our study demonstrates a shift in antidiabetic medication class utilization from 2014 to 2019, where associated costs net of rebates significantly increased to a disproportionately greater extent than the significant increase in utilization PUPM.

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