Cognitive Techniques as a Means for Facilitating Supervisee Development

During periods of uncertainty or psychological distress, a supervisee may encounter or develop rigid or unhelpful thinking patterns that could delay development by promoting discouraging realities and experiences. Such cognitive experiences often are so subtle that they occur outside the supervisee\u27s immediate awareness. This article explores how the cognitive model of counseling could be used in supervision as a guide to help the supervisor and supervisee discover and modity negative thought processes

Freund's vaccine adjuvant promotes Her2/Neu breast cancer

<p>Abstract</p> <p>Background</p> <p>Inflammation has been linked to the etiology of many organ-specific cancers. Indirect evidence suggests a possible role for inflammation in breast cancer. We investigated whether the systemic inflammation induced by Freund's adjuvant (FA) promotes mammary carcinogenesis in a rat model in which cancer is induced by the <it>neu </it>oncogene.</p> <p>Methods</p> <p>The effects of FA on hyperplastic mammary lesions and mammary carcinomas were determined in a <it>neu</it>-induced rat model. The inflammatory response to FA treatment was gauged by measuring acute phase serum haptoglobin. In addition, changes in cell proliferation and apoptosis following FA treatment were assessed.</p> <p>Results</p> <p>Rats receiving FA developed twice the number of mammary carcinomas as controls. Systemic inflammation following FA treatment is chronic, as shown by a doubling of the levels of the serum biomarker, haptoglobin, 15 days following initial treatment. We also show that this systemic inflammation is associated with the increased growth of hyperplastic mammary lesions. This increased growth results from a higher rate of cellular proliferation in the absence of changes in apoptosis.</p> <p>Conclusion</p> <p>Our data suggests that systemic inflammation induced by Freund's adjuvant (FA) promotes mammary carcinogenesis. It will be important to determine whether adjuvants currently used in human vaccines also promote breast cancer.</p

An insulator loop resides between the synthetically interacting elements of the human/rat conserved breast cancer susceptibility locus MCS5A/Mcs5a

Many low-penetrance breast cancer susceptibility loci are found to be located in non-protein-coding regions, suggesting their involvement in gene expression regulation. We identified the human/rat-conserved breast cancer susceptibility locus MCS5A/Mcs5a. This locus has been shown to act in a non-mammary cell-autonomous fashion through the immune system. The resistant Mcs5a allele from the Wistar–Kyoto (WKy) rat strain consists of two non-protein-coding genetic elements that must be located on the same chromosome to elicit the phenotype. In this study, we show the presence of a conserved higher order chromatin structure in MCS5A/Mcs5a located in between the synthetically interacting genetic elements. The looped elements are shown to be bound by CTCF and cohesin. We identify the downregulation of Fbxo10 expression in T cells as a strong candidate mechanism through which the interacting genetic elements of the resistant Mcs5a allele modulate mammary carcinoma susceptibility. Finally, we show that the human MCS5A polymorphisms associated with breast cancer risk are located at both sides of the looped structure and functionally interact to downregulate transcriptional activity, similar to rat Mcs5a. We propose a mechanistic model for MCS5a/Mcs5a in which a CTCF-mediated insulator loop encompassing the TOMM5/Tomm5 gene, resides in between and brings into closer physical proximity the synthetically and functionally interacting resistant genetic variants

Physical Confirmation and Mapping of Overlapping Rat Mammary Carcinoma Susceptibility QTLs, Mcs2 and Mcs6

Only a portion of the estimated heritability of breast cancer susceptibility has been explained by individual loci. Comparative genetic approaches that first use an experimental organism to map susceptibility QTLs are unbiased methods to identify human orthologs to target in human population-based genetic association studies. Here, overlapping rat mammary carcinoma susceptibility (Mcs) predicted QTLs, Mcs6 and Mcs2, were physically confirmed and mapped to identify the human orthologous region. To physically confirm Mcs6 and Mcs2, congenic lines were established using the Wistar-Furth (WF) rat strain, which is susceptible to developing mammary carcinomas, as the recipient (genetic background) and either Wistar-Kyoto (WKy, Mcs6) or Copenhagen (COP, Mcs2), which are resistant, as donor strains. By comparing Mcs phenotypes of WF.WKy congenic lines with distinct segments of WKy chromosome 7 we physically confirmed and mapped Mcs6 to ∼33 Mb between markers D7Rat171 and gUwm64-3. The predicted Mcs2 QTL was also physically confirmed using segments of COP chromosome 7 introgressed into a susceptible WF background. The Mcs6 and Mcs2 overlapping genomic regions contain multiple annotated genes, but none have a clear or well established link to breast cancer susceptibility. Igf1 and Socs2 are two of multiple potential candidate genes in Mcs6. The human genomic region orthologous to rat Mcs6 is on chromosome 12 from base positions 71,270,266 to 105,502,699. This region has not shown a genome-wide significant association to breast cancer risk in pun studies of breast cancer susceptibility

Quantification of Epithelial Cell Differentiation in Mammary Glands and Carcinomas from DMBA- and MNU-Exposed Rats

Rat mammary carcinogenesis models have been used extensively to study breast cancer initiation, progression, prevention, and intervention. Nevertheless, quantitative molecular data on epithelial cell differentiation in mammary glands of untreated and carcinogen-exposed rats is limited. Here, we describe the characterization of rat mammary epithelial cells (RMECs) by multicolor flow cytometry using antibodies against cell surface proteins CD24, CD29, CD31, CD45, CD49f, CD61, Peanut Lectin, and Thy-1, intracellular proteins CK14, CK19, and FAK, along with phalloidin and Hoechst staining. We identified the luminal and basal/myoepithelial populations and actively dividing RMECs. In inbred rats susceptible to mammary carcinoma development, we quantified the changes in differentiation of the RMEC populations at 1, 2, and 4 weeks after exposure to mammary carcinogens DMBA and MNU. DMBA exposure did not alter the percentage of basal or luminal cells, but upregulated CD49f (Integrin α6) expression and increased cell cycle activity. MNU exposure resulted in a temporary disruption of the luminal/basal ratio and no CD49f upregulation. When comparing DMBA- or MNU-induced mammary carcinomas, the RMEC differentiation profiles are indistinguishable. The carcinomas compared with mammary glands from untreated rats, showed upregulation of CD29 (Integrin β1) and CD49f expression, increased FAK (focal adhesion kinase) activation especially in the CD29hi population, and decreased CD61 (Integrin β3) expression. This study provides quantitative insight into the protein expression phenotypes underlying RMEC differentiation. The results highlight distinct RMEC differentiation etiologies of DMBA and MNU exposure, while the resulting carcinomas have similar RMEC differentiation profiles. The methodology and data will enhance rat mammary carcinogenesis models in the study of the role of epithelial cell differentiation in breast cancer

On the Statistical Analysis of Allelic-Loss Data

This article is concerned with the statistical analysis of certain binary data arising in molecular studies of cancer. In allelic-loss experiments, tumor cell genomes are analyzed at informative molecular marker loci to identify deleted chromosomal regions. The resulting binary data are used to infer properties of putative suppressor genes, genes involved in normal cell cycling. Various factors can complicate this inference, including background loss of heterozygousity, spatial (i.e., within chromosome) dependence of the binary responses, non-informativeness of markers, covariates such as protein levels or tumor histology, heterogeneity of cells within tumors, and measurement error. We focus on the first three factors, discussing methods for statistical inference that separate background loss from significant loss. The extension to other inferences is outlined, such as comparison questions and the relationship to covariates. Using characteristic features of tumorigenesis, we present a framework for the stochastic modeling of allelic-loss data, and build models within this framework; in particular, we propose a simple model having chromosome breaks at locations of a Poisson process, and preferential selection of cells with inactivated suppressor genes. We demonstrate these methods on allelic-loss data from induced rat mammary tumors and human bladder cancers. 1 Introductio