Mammary stem cells, self-renewal pathways, and carcinogenesis

The mammary gland epithelial components are thought to arise from stem cells that undergo both self-renewal and differentiation. Self-renewal has been shown to be regulated by the Hedgehog, Notch, and Wnt pathways and the transcription factor B lymphoma Mo-MLV insertion region 1 (Bmi-1). We review data about the existence of stem cells in the mammary gland and the pathways regulating the self-renewal of these cells. We present evidence that deregulation of the self-renewal in stem cells/progenitors might be a key event in mammary carcinogenesis. If 'tumor stem cells' are inherently resistant to current therapies, targeting stem cell self-renewal pathways might provide a novel approach for breast cancer treatment

Segregation of myoblast fusion and muscle-specific gene expression by distinct ligand-dependent inactivation of GSK-3β

Myogenic differentiation involves myoblast fusion and induction of muscle-specific gene expression, which are both stimulated by pharmacological (LiCl), genetic, or IGF-I-mediated GSK-3β inactivation. To assess whether stimulation of myogenic differentiation is common to ligand-mediated GSK-3β inactivation, myoblast fusion and muscle-specific gene expression were investigated in response to Wnt-3a. Moreover, crosstalk between IGF-I/GSK-3β/NFATc3 and Wnt/GSK-3β/β-catenin signaling was assessed. While both Wnt-3a and LiCl promoted myoblast fusion, muscle-specific gene expression was increased by LiCl, but not by Wnt-3a or β-catenin over-expression. Furthermore, LiCl and IGF-I, but not Wnt-3a, increased NFATc3 transcriptional activity. In contrast, β-catenin-dependent transcriptional activity was increased by Wnt-3a and LiCl, but not IGF-I. These results for the first time reveal a segregated regulation of myoblast fusion and muscle-specific gene expression following stimulation of myogenic differentiation in response to distinct ligand-specific signaling routes of GSK-3β inactivation

A cluster randomized trial to improve adherence to evidence-based guidelines on diabetes and reduce clinical inertia in primary care physicians in Belgium: study protocol [NTR 1369]

Contains fulltext : 70617.pdf (publisher's version ) (Open Access)ABSTRACT: BACKGROUND: Most quality improvement programs in diabetes care incorporate aspects of clinician education, performance feedback, patient education, care management, and diabetes care teams to support primary care physicians. Few studies have applied all of these dimensions to address clinical inertia. AIM: To evaluate interventions to improve adherence to evidence-based guidelines for diabetes and reduce clinical inertia in primary care physicians. DESIGN: Two-arm cluster randomized controlled trial. PARTICIPANTS: Primary care physicians in Belgium. INTERVENTIONS: Primary care physicians will be randomly allocated to 'Usual' (UQIP) or 'Advanced' (AQIP) Quality Improvement Programs. Physicians in the UQIP will receive interventions addressing the main physician, patient, and office system factors that contribute to clinical inertia. Physicians in the AQIP will receive additional interventions that focus on sustainable behavior changes in patients and providers. OUTCOMES: Primary endpoints are the proportions of patients within targets for three clinical outcomes: 1) glycosylated hemoglobin < 7%; 2) systolic blood pressure differences </=130 mmHg; and 3) low density lipoprotein/cholesterol < 100 mg/dl. Secondary endpoints are individual improvements in 12 validated parameters: glycosylated hemoglobin, low and high density lipoprotein/cholesterol, total cholesterol, systolic blood pressure, diastolic blood pressure, weight, physical exercise, healthy diet, smoking status, and statin and anti-platelet therapy. PRIMARY AND SECONDARY ANALYSIS: Statistical analyses will be performed using an intent-to-treat approach with a multilevel model. Linear and generalized linear mixed models will be used to account for the clustered nature of the data, i.e., patients clustered withinimary care physicians, and repeated assessments clustered within patients. To compare patient characteristics at baseline and between the intervention arms, the generalized estimating equations (GEE) approach will be used, taking the clustered nature of the data within physicians into account. We will also use the GEE approach to test for differences in evolution of the primary and secondary endpoints for all patients, and for patients in the two interventions arms, accounting for within-patient clustering. TRIAL REGISTRATION: number: NTR 1369

Novel markers for differentiation of lobular and ductal invasive breast carcinomas by laser microdissection and microarray analysis

BACKGROUND: Invasive ductal and lobular carcinomas (IDC and ILC) are the most common histological types of breast cancer. Clinical follow-up data and metastatic patterns suggest that the development and progression of these tumors are different. The aim of our study was to identify gene expression profiles of IDC and ILC in relation to normal breast epithelial cells. METHODS: We examined 30 samples (normal ductal and lobular cells from 10 patients, IDC cells from 5 patients, ILC cells from 5 patients) microdissected from cryosections of ten mastectomy specimens from postmenopausal patients. Fifty nanograms of total RNA were amplified and labeled by PCR and in vitro transcription. Samples were analysed upon Affymetrix U133 Plus 2.0 Arrays. The expression of seven differentially expressed genes (CDH1, EMP1, DDR1, DVL1, KRT5, KRT6, KRT17) was verified by immunohistochemistry on tissue microarrays. Expression of ASPN mRNA was validated by in situ hybridization on frozen sections, and CTHRC1, ASPN and COL3A1 were tested by PCR. RESULTS: Using GCOS pairwise comparison algorithm and rank products we have identified 84 named genes common to ILC versus normal cell types, 74 named genes common to IDC versus normal cell types, 78 named genes differentially expressed between normal ductal and lobular cells, and 28 named genes between IDC and ILC. Genes distinguishing between IDC and ILC are involved in epithelial-mesenchymal transition, TGF-beta and Wnt signaling. These changes were present in both tumor types but appeared to be more prominent in ILC. Immunohistochemistry for several novel markers (EMP1, DVL1, DDR1) distinguished large sets of IDC from ILC. CONCLUSION: IDC and ILC can be differentiated both at the gene and protein levels. In this study we report two candidate genes, asporin (ASPN) and collagen triple helix repeat containing 1 (CTHRC1) which might be significant in breast carcinogenesis. Besides E-cadherin, the proteins validated on tissue microarrays (EMP1, DVL1, DDR1) may represent novel immunohistochemical markers helpful in distinguishing between IDC and ILC. Further studies with larger sets of patients are needed to verify the gene expression profiles of various histological types of breast cancer in order to determine molecular subclassifications, prognosis and the optimum treatment strategies