Correlation study between osteoporosis and hematopoiesis in the context of adjuvant chemotherapy for breast cancer.

This retrospective study attempts to establish if a correlation exists between osteoporosis and hematopoiesis before and after adjuvant chemotherapy in the context of non-metastatic breast cancer. Osteoporosis is interpreted both as a direct marker of osteoblastic decline and as an indirect marker of increased bone marrow adiposity within the hematopoietic microenvironment. Patients from the "Centre du Sein" at CHUV (Centre Hospitalier Universitaire Vaudois) undergoing adjuvant chemotherapy were included in this study. Evolution of blood counts was studied in correlation with the osteoporosis status. Toxicity of chemotherapy was coded according to published probability of febrile neutropenia. One hundred forty-three women were included: mean age 52.1 ± 12.5 years, mean BMI (body mass index) 24.4 ± 4.1. BMD (bone mineral density) scored osteoporotic in 32% and osteopenic in 45%. Prior to chemotherapy, BMD was positively correlated with neutrophil (p < 0.001) and thrombocyte (p = 0.01) count; TBS (trabecular bone score) was not correlated with blood count. After the first cycle of chemotherapy, an increase of one point in TBS correlated with a decrease of 57% on the time to reach leucocyte nadir (p = 0.004). There was a positive correlation between BMD and risk of infection (p < 0.001). Our data demonstrates an association between osteoporosis and lower blood counts in a younger cohort than previously published, extending it for the first time to neutrophil counts in females. Our results suggest that the healthier the bone, the earlier the lowest leucocyte count value, prompting further research on this area.

Induction of an interferon response by RNAi vectors in mammalian cells.

DNA vectors that express short hairpin RNAs (shRNAs) from RNA polymerase III (Pol III) promoters are a promising new tool to reduce gene expression in mammalian cells. shRNAs are processed to small interfering RNAs (siRNAs) of 21 nucleotides (nt) that guide the cleavage of the cognate mRNA by the RNA-induced silencing complex. Although siRNAs are thought to be too short to induce interferon expression, we report here that a substantial number of shRNA vectors can trigger an interferon response.

An oestrogen-dependent model of breast cancer created by transformation of normal human mammary epithelial cells.

INTRODUCTION: About 70% of breast cancers express oestrogen receptor alpha (ESR1/ERalpha) and are oestrogen-dependent for growth. In contrast with the highly proliferative nature of ERalpha-positive tumour cells, ERalpha-positive cells in normal breast tissue rarely proliferate. Because ERalpha expression is rapidly lost when normal human mammary epithelial cells (HMECs) are grown in vitro, breast cancer models derived from HMECs are ERalpha-negative. Currently only tumour cell lines are available to model ERalpha-positive disease. To create an ERalpha-positive breast cancer model, we have forced normal HMECs derived from reduction mammoplasty tissue to express ERalpha in combination with other relevant breast cancer genes. METHODS: Candidate genes were selected based on breast cancer microarray data and cloned into lentiviral vectors. Primary HMECs prepared from reduction mammoplasty tissue were infected with lentiviral particles. Infected HMECs were characterised by Western blotting, immunofluorescence microscopy, microarray analysis, growth curves, karyotyping and SNP chip analysis. The tumorigenicity of the modified HMECs was tested after orthotopic injection into the inguinal mammary glands of NOD/SCID mice. Cells were marked with a fluorescent protein to allow visualisation in the fat pad. The growth of the graft was analysed by fluorescence microscopy of the mammary glands and pathological analysis of stained tissue sections. Oestrogen dependence of tumour growth was assessed by treatment with the oestrogen antagonist fulvestrant. RESULTS: Microarray analysis of ERalpha-positive tumours reveals that they commonly overexpress the Polycomb-group gene BMI1. Lentiviral transduction with ERalpha, BMI1, TERT and MYC allows primary HMECs to be expanded in vitro in an oestrogen-dependent manner. Orthotopic xenografting of these cells into the mammary glands of NOD/SCID mice results in the formation of ERalpha-positive tumours that metastasise to multiple organs. The cells remain wild type for TP53, diploid and genetically stable. In vivo tumour growth and in vitro proliferation of cells explanted from tumours are dependent on oestrogen. CONCLUSION: We have created a genetically defined model of ERalpha-positive human breast cancer based on normal HMECs that has the potential to model human oestrogen-dependent breast cancer in a mouse and enables the study of mechanisms involved in tumorigenesis and metastasis.

Identification of molecular apocrine breast tumours by microarray analysis.

Previous microarray studies on breast cancer identified multiple tumour classes, of which the most prominent, named luminal and basal, differ in expression of the oestrogen receptor alpha gene (ER). We report here the identification of a group of breast tumours with increased androgen signalling and a 'molecular apocrine' gene expression profile. Tumour samples from 49 patients with large operable or locally advanced breast cancers were tested on Affymetrix U133A gene expression microarrays. Principal components analysis and hierarchical clustering split the tumours into three groups: basal, luminal and a group we call molecular apocrine. All of the molecular apocrine tumours have strong apocrine features on histological examination (P=0.0002). The molecular apocrine group is androgen receptor (AR) positive and contains all of the ER-negative tumours outside the basal group. Kolmogorov-Smirnov testing indicates that oestrogen signalling is most active in the luminal group, and androgen signalling is most active in the molecular apocrine group. ERBB2 amplification is commoner in the molecular apocrine than the other groups. Genes that best split the three groups were identified by Wilcoxon test. Correlation of the average expression profile of these genes in our data with the expression profile of individual tumours in four published breast cancer studies suggest that molecular apocrine tumours represent 8-14% of tumours in these studies. Our data show that it is possible with microarray data to divide mammary tumour cells into three groups based on steroid receptor activity: luminal (ER+ AR+), basal (ER- AR-) and molecular apocrine (ER- AR+).