Department of Pathology, Thomas Jefferson University, Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors.

BACKGROUND: Although numerous mouse models of breast carcinomas have been developed, we do not know the extent to which any faithfully represent clinically significant human phenotypes. To address this need, we characterized mammary tumor gene expression profiles from 13 different murine models using DNA microarrays and compared the resulting data to those from human breast tumors. RESULTS: Unsupervised hierarchical clustering analysis showed that six models (TgWAP-Myc, TgMMTV-Neu, TgMMTV-PyMT, TgWAP-Int3, TgWAP-Tag, and TgC3(1)-Tag) yielded tumors with distinctive and homogeneous expression patterns within each strain. However, in each of four other models (TgWAP-T121, TgMMTV-Wnt1, Brca1Co/Co;TgMMTV-Cre;p53+/- and DMBA-induced), tumors with a variety of histologies and expression profiles developed. In many models, similarities to human breast tumors were recognized, including proliferation and human breast tumor subtype signatures. Significantly, tumors of several models displayed characteristics of human basal-like breast tumors, including two models with induced Brca1 deficiencies. Tumors of other murine models shared features and trended towards significance of gene enrichment with human luminal tumors; however, these murine tumors lacked expression of estrogen receptor (ER) and ER-regulated genes. TgMMTV-Neu tumors did not have a significant gene overlap with the human HER2+/ER- subtype and were more similar to human luminal tumors. CONCLUSION: Many of the defining characteristics of human subtypes were conserved among the mouse models. Although no single mouse model recapitulated all the expression features of a given human subtype, these shared expression features provide a common framework for an improved integration of murine mammary tumor models with human breast tumors

Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors

Comparison of mammary tumor gene-expression profiles from thirteen murine models using microarrays and with that of human breast tumors showed that many of the defining characteristics of human subtypes were conserved among mouse models

The Effects of Various Frequencies of Low-Level Mechanical Vibration on Retention in an Orthodontic Relapse Model in Mice

ABSTRACT Objectives: The aim of this study is to study the effect of mechanical vibration on retention following orthodontic tooth movement (OTM) in a mouse orthodontic relapse model. We applied various frequencies of vibration to the maxillary right first molar during relapse, and monitored changes to the alveolar bone and molar root. Materials and Methods: Thirty-four male CD1 mice were placed in 4 groups. The Control Group underwent OTM for 7 days. The other three groups received OTM for 7 days, followed by a relapse phase of 7 days. OTM was performed with a 10g Ni-Ti spring. The Relapse Group did not receive vibration during relapse, while Relapse + 10 Hz and Relapse + 30 Hz Groups received intermittent vibration throughout their relapse phases. Micro-CT imaging was performed for bone volume fraction (BVF), tissue density (TD), first molar movement (M1-M2 Distance), and mesial root volume (MRV). Results: Differences in M1-M2 Distance were statistically significant between control and experimental groups. No significant findings were observed between controls and experimental groups for BVF, TD, and MRV. No significant differences were observed between relapse and relapse with vibration groups for BVD, TD, M1-M2 Distance, and MRV. Non-significant measurements demonstrated Relapse + 10 Hz vibration increased relapse while Relapse + 30 Hz vibration decreased relapse. Conclusion: Our findings demonstrate that 10 Hz and 30 Hz mechanical vibration have no statistically significant effects on retention based on a mouse relapse model. Further research is necessary to understand the effects of mechanical vibration on retention

A role for the vitamin D pathway in non-intestinal lesions in genetic and carcinogen models of colorectal cancer and in familial adenomatous polyposis.

Vitamin D is implicated in the etiology of cancers of the gastrointestinal tract, usually characterized by alteration in the APC/β-catenin/TCF tumor suppressor pathway. The vitamin D receptor (VDR) is also implicated in cardiovascular and skin diseases as well as in immunity. Activated VDR can indirectly alter β-catenin nuclear localization and directly suppress β-catenin/TCF mediated transcriptional activity. We treated VDR null mice with the carcinogen azoxymethane (AOM) and generated mice bearing a mutated APC (hypomorph) on a VDR null background (Apc1638N/+Vdr-/-). VDR null mice do not develop GI or extra-colonic tumors but loss of VDR decreased intestinal tumor latency and increased progression to adenocarcinoma in both models. AOM treatment of VDR null mice also caused squamous cell carcinoma of the anus. Although levels and distribution of total or activated β-catenin in the epithelial component of tumors were unaffected by loss of VDR, β-catenin dependent cyclin D1 expression was affected suggesting a direct VDR effect on β-catenin co-activator activity. Extra-colonic mucosa manifestations in Apc1638N/+Vdr-/- animals included increased nuclear β-catenin in submucosal stromal cells, spleno- and cardiomegaly and large epidermoid cysts characteristic of the FAP variant, Gardner's syndrome. Consistent with this, SNPs in the VDR, vitamin D binding protein and CYP24 as well as mutations in APC distal to codon 850 were strongly associated with Gardners syndrome in a cohort of 457 FAP patients, This work suggests that alterations in the vitamin D/VDR axis are important in Gardner's syndrome, as well as in the etiology of anal cancer

Predicting New Indications for Approved Drugs Using a Proteochemometric Method

The most effective way to move from target identification to the clinic is to identify already approved drugs with the potential for activating or inhibiting unintended targets (repurposing or repositioning). This is usually achieved by high throughput chemical screening, transcriptome matching, or simple in silico ligand docking. We now describe a novel rapid computational proteochemometric method called “train, match, fit, streamline” (TMFS) to map new drug–target interaction space and predict new uses. The TMFS method combines shape, topology, and chemical signatures, including docking score and functional contact points of the ligand, to predict potential drug–target interactions with remarkable accuracy. Using the TMFS method, we performed extensive molecular fit computations on 3671 FDA approved drugs across 2335 human protein crystal structures. The TMFS method predicts drug–target associations with 91% accuracy for the majority of drugs. Over 58% of the known best ligands for each target were correctly predicted as top ranked, followed by 66%, 76%, 84%, and 91% for agents ranked in the top 10, 20, 30, and 40, respectively, out of all 3671 drugs. Drugs ranked in the top 1–40 that have not been experimentally validated for a particular target now become candidates for repositioning. Furthermore, we used the TMFS method to discover that mebendazole, an antiparasitic with recently discovered and unexpected anticancer properties, has the structural potential to inhibit VEGFR2. We confirmed experimentally that mebendazole inhibits VEGFR2 kinase activity and angiogenesis at doses comparable with its known effects on hookworm. TMFS also predicted, and was confirmed with surface plasmon resonance, that dimethyl celecoxib and the anti-inflammatory agent celecoxib can bind cadherin-11, an adhesion molecule important in rheumatoid arthritis and poor prognosis malignancies for which no targeted therapies exist. We anticipate that expanding our TMFS method to the >27 000 clinically active agents available worldwide across all targets will be most useful in the repositioning of existing drugs for new therapeutic targets