Mapping and cloning of genes from portions of the human genome using somatic cell hybrids

Human x rodent somatic cell hybrids have played an important role in human genetics research. They have been especially useful for assigning genes to chromosomes and isolating DNA markers from specific regions of the human genome.^ By employing a combination of somatic cell genetic, recombinant DNA, and cytogenetic techniques, human DNA excision repair gene ERCC4 was mapped regionally to human 16p13.13-13.2, even though the gene has not been cloned. Human x Chinese hamster ovary (CHO) cell hybrids selected for human ERCC4 activity and containing 16p13.1-p13.3 as the only human genetic material were identified. These hybrids were used to order DNA markers located in 16p13.1-p13.3. New DNA markers physically close to ERCC4 were isolated from such hybrids. Using amplified human DNA from the hybrids as probe in fluorescent in situ hybridization, the short arm breakpoint in the chromosome 16 inversion associated with acute myelomonocytic leukemia (AMML) was found to be physically close to the ERCC4 gene. The physical mapping and eventually, the cloning of the ERCC4 gene, will benefit the understanding of the DNA repair system and the study of other important biomedical problems such as tumorigenesis.^ To facilitate the cloning of ERCC4 gene and, in general, the cloning of genes from any defined regions of the human genome, a method was developed for the direct isolation of human transcribed genes ffom somatic cell hybrids. cDNA was prepared from human x rodent hybrid by using consensus 5$\sp\prime$ splice site sequences as primers. These primers were designed to select immature, unspliced messenger RNA (still retaining species specific repeat sequences) as templates. Screening of a derived cDNA library for human repeat sequences resulted in the isolation of human clones at the anticipated frequency with characteristics expected of exons of transcribed human genes. The usefulness of the splice site specific primers was analyzed and the cDNA synthesis conditions with these primers were optimized. The procedure was shown to be sensitive enough to clone weakly expressed genes. Studying the expression of the represented genes with the isolated clones was shown to be feasible. Such regional specific human gene fragments will be very valuable for many human genetic studies such as the search of inherited disease genes and the construction of a cDNA map of the human genome. ^

Selection bias and the cross-validation of regression models for prediction

Strategies are compared for the development of a linear regression model with stochastic (multivariate normal) regressor variables and the subsequent assessment of its predictive ability. Bias and mean squared error of four estimators of predictive performance are evaluated in simulated samples of 32 population correlation matrices. Models including all of the available predictors are compared with those obtained using selected subsets. The subset selection procedures investigated include two stopping rules, C$\sb{\rm p}$ and S$\sb{\rm p}$, each combined with an 'all possible subsets' or 'forward selection' of variables. The estimators of performance utilized include parametric (MSEP$\sb{\rm m}$) and non-parametric (PRESS) assessments in the entire sample, and two data splitting estimates restricted to a random or balanced (Snee's DUPLEX) 'validation' half sample. The simulations were performed as a designed experiment, with population correlation matrices representing a broad range of data structures.^ The techniques examined for subset selection do not generally result in improved predictions relative to the full model. Approaches using 'forward selection' result in slightly smaller prediction errors and less biased estimators of predictive accuracy than 'all possible subsets' approaches but no differences are detected between the performances of C$\sb{\rm p}$ and S$\sb{\rm p}$. In every case, prediction errors of models obtained by subset selection in either of the half splits exceed those obtained using all predictors and the entire sample.^ Only the random split estimator is conditionally (on $\\beta$) unbiased, however MSEP$\sb{\rm m}$ is unbiased on average and PRESS is nearly so in unselected (fixed form) models. When subset selection techniques are used, MSEP$\sb{\rm m}$ and PRESS always underestimate prediction errors, by as much as 27 percent (on average) in small samples. Despite their bias, the mean squared errors (MSE) of these estimators are at least 30 percent less than that of the unbiased random split estimator. The DUPLEX split estimator suffers from large MSE as well as bias, and seems of little value within the context of stochastic regressor variables.^ To maximize predictive accuracy while retaining a reliable estimate of that accuracy, it is recommended that the entire sample be used for model development, and a leave-one-out statistic (e.g. PRESS) be used for assessment. ^

Developing a Framework for Child Welfare Supervision

The roles of the child welfare supervisor in guiding practice and in retaining child welfare workers are well established in the literature. In this article, we discuss a framework for child welfare supervision that was developed and implemented in the state of Iowa with support from the Children’s Bureau through a five-year grant to improve recruitment and retention in public child welfare. The framework supports family centered practice through a parallel process of supervision reflecting these guiding principles: strength-based, competency-based, culturally competent, reflective, individualized to workers’ learning styles and stages of development, and aimed at enhancing worker skill, autonomy, teamwork, and commitment to the organization. We present key elements of the framework, an overview of implementation, and evaluation results regarding knowledge gain, use of skills, and rates of worker retention.

Heregulin -beta 1 directly associates with RhoA via the immunoglobulin -like domain thereby modulating breast cancer metastasis-related properties

Heregulins constitute a family of growth factors belonging to the epidermal growth factor (EGF) family. Breast cancers that overexpress specific members of the EGF receptor family (EGFR, ErbB2, ErbB3, ErbB4) have increased metastatic potential, and Heregulin-β1 (HRGβ1), a ligand for ErbB3 and ErbB4, has also been shown to induce metastasis-related properties in breast cancer cells in vitro. The secreted form of the HRGβ1 is composed of five distinct structural domains, including the N-terminal domain, an immunoglobulin-like domain (IgG-like), a glycosylation domain, an EGF-like domain, and a β1-specific domain. Of these, the EGF-like domain is well characterized for its function in metastasis-related properties as well as its structure. However, the contributions of the other HRGβ1 domains in breast cancer metastasis remains unclear. ^ To investigate this, HRGβ1 proteins with targeted domain deletions were purified and subjected to assays for metastasis-related properties, including aggregation, invasion, activation of EGFR family members, and motility of breast cancer cells. These assays showed that retaining the EGF-like domain of HRGβ1 is important for activation of EGFRs. Interestingly, the HRGβ1 protein lacking the IgG-like domain (NGEB) led to a decrease in breast cancer cell motility, indicating the IgG-like domain modulates cell motility, an important step in cancer metastasis. ^ To understand the underlying mechanisms, I performed protein sequence and structural analysis of HRGβ1 and identified that the IgG-like domain of HRGβ1 shares sequence homology and three-dimensional structural similarity with the IgG-like domain of TRIO. TRIO is a cytoplasmic protein that directly associates with RhoA, a GTPase involved in cell reorganization and cell motility. Therefore, I hypothesized that HRGβ1 may translocate inside the breast cancer cells through receptor mediated endocytosis and bind to RhoA via its IgG-like domain. I show wild type HRGβ1 but not NGEB binds RhoA in vitro and in vivo, leading to RhoA activation. Inhibition of HRG-β1 internalization via endocytosis disrupted HRGβ1 binding to RhoA. Additionally, breast cancer cell motility induced by HRG-β1 is reduced after treatment with inhibitors to both endocytosis and RhoA function, similar to levels seen with NGEB treatment. ^ Thus, in addition to the well-known role of HRGβ1 as an extracellular stimulator of the EGFR family members, HRGβ1 also functions within the cell as a binding partner and activator of RhoA to modulate cancer cell motility. ^