Ecogeographical variations of chromosomal polymorphism in Hawaiian populations of Drosophila immigrans

Reports were scanned in black and white at a resolution of 600 dots per inch and were converted to text using Adobe Paper Capture Plug-in.Eighteen samples from twelve populations of Drosophila immigrans in the islands of Kauai, Oahu and Hawaii in the Hawaiian archipelago were analyzed for inversion polymorphism in 1125 females and 206 males. Three kinds of second chromosome inversions, which appear to be identical with those previously reported by other workers, were present in all of our populations; two other new inversions of the same autosome were detected from the Hawaii collections, but their origin, whether natural or laboratory, could not be assured. The average proportion of inversion heterozygosity per individual of the populations from Kauai, Oahu and Hawaii was about 34%, 32% and 65% respectively. The frequencies of heterozygous inversions Here similar between different populations within islands (with one notable exception on Hawaii). In contrast, the frequencies were significantly heterogeneous from one island to the next. The results of gene arrangement frequency analysis consolidated the above findings. It is suggested that the inter-island differentiations are due to natural selection and probably maintained by the isolation by oceanic channels. Two near-by localities on Hawaii were inhabited with significantly heterogeneous populations. Such a microgeographic differentiation has been interpreted as being due to the presence of highly localized, differential selection forces in the two localities, and the difference seems to be maintained due to isolation by the lava flows. Our data suggest that the breeding units of Hawaiian populations of D. immigrans are not so small as to allow for genetic drift to significantly affect the populations. Inversion polymorphism was similar between females and males taken at the same time in the same localities

Convergence in international business ethics? A comparative study of ethical philosophies, thinking style, and ethical decision-making between US and Korean managers

This study investigates the relationship among ethical philosophy, thinking style, and managerial ethical decision-making. Based on the premise that business ethics is a function of culture and time, we attempt to explore two important questions as to whether the national differences in managerial ethical philosophies remain over time and whether the relationship between thinking style and ethical decision-making is consistent across different national contexts. We conducted a survey on Korean managers’ ethical decision-making and thinking style and made a cross-cultural, cross-temporal comparison with the results presented by previous studies that surveyed Korean and US managers with the same questionnaire at different points in time. Our analysis revealed that Korean managers have become more reliant on rule utilitarianism for ethical decision-making over the last two decades, which is dominantly used by US managers, corroborating our convergence hypothesis built on social contracts theory. However, as opposed to previous research, we found that managers with a balanced linear and nonlinear thinking style do not necessarily make more ethical decisions compared to those with a predominantly linear or nonlinear thinking style. This study contributes to international business ethics literature by presenting a theoretical framework that may explain the convergence of ethical philosophies employed by managers in different national contexts over time, and that the relationship between thinking style and managerial ethical decision-making may not be universal, but contingent on contextual factors

Origin of myofibroblasts in liver fibrosis

Most chronic liver diseases of all etiologies result in progressive liver fibrosis. Myofibroblasts produce the extracellular matrix, including type I collagen, which constitutes the fibrous scar in liver fibrosis. Normal liver has little type I collagen and no detectable myofibroblasts, but myofibroblasts appear early in experimental and clinical liver injury. The origin of the myofibroblast in liver fibrosis is still unresolved. The possibilities include activation of endogenous mesenchymal cells including fibroblasts and hepatic stellate cells, recruitment from the bone marrow, and transformation of epithelial or endothelial cells to myofibroblasts. In fact, the origin of myofibroblasts may be different for different types of chronic liver diseases, such as cholestatic liver disease or hepatotoxic liver disease. This review will examine our current understanding of the liver myofibroblast

Altered Expression of Insulin Receptor Isoforms in Breast Cancer

PURPOSE: Insulin-like growth factor (IGF) signaling through human insulin receptor isoform A (IR-A) contributes to tumorigenesis and intrinsic resistance to anti-IGF1R therapy. In the present study, we (a) developed quantitative TaqMan real time-PCR-based assays (qRT-PCR) to measure human insulin receptor isoforms with high specificity, (b) evaluated isoform expression levels in molecularly-defined breast cancer subtypes, and (c) identified the IR-A:IR-B mRNA ratio as a potential biomarker guiding patient stratification for anti-IGF therapies. EXPERIMENTAL DESIGN: mRNA expression levels of IR-A and IR-B were measured in 42 primary breast cancers and 19 matched adjacent normal tissues with TaqMan qRT-PCR assays. The results were further confirmed in 165 breast cancers. The tumor samples were profiled using whole genome microarrays and subsequently subtyped using the PAM50 breast cancer gene signature. The relationship between the IR-A:IR-B ratio and cancer subtype, as well as markers of proliferation were characterized. RESULTS: The mRNA expression levels of IR-A in the breast tumors were similar to those observed in the adjacent normal tissues, while the mRNA levels of IR-B were significantly decreased in tumors. The IR-A:IR-B ratio was significantly higher in luminal B breast cancer than in luminal A. Strong concordance between the IR-A:IR-B ratio and the composite Oncotype DX proliferation score was observed for stratifying the latter two breast cancer subtypes. CONCLUSIONS: The reduction in IR-B expression is the key to the altered IR-A:IR-B ratio observed in breast cancer. The IR-A:IR-B ratio may have biomarker utility in guiding a patient stratification strategy for an anti-IGF therapeutic

Potential prognostic value of heat-shock protein 90 in the presence of phosphatidylinositol-3-kinase overexpression or loss of PTEN, in invasive breast cancers

This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Abstract Introduction Evaluating the expression of signaling molecule proteins from the mitogen-activated protein kinase (MAPK) pathway and the phosphatidylinositol-3-kinase (PI3K) pathway in invasive breast cancers may identify prognostic marker(s) associated with early relapse. Methods Immunohistochemical analyses of phosphatase and tensin homologue deleted on chromosome 10 (PTEN), PI3K-p110α, phospho-AKT, phospho-p70S6 kinase, phospho-S6 ribosomal protein, phospho-RAF, phospho-p44/42 MAPK, and heat-shock protein 90 (HSP90) were performed on tumor samples from 212 patients with invasive breast cancer. Statistically significant relations between protein expression, clinicopathologic factors, and relapse-free survival (RFS) were analyzed. Results Expression of HSP90 was associated with 5-year RFS, as well as T stage, N stage, histologic grade, estrogen receptor (ER) expression, human epidermal growth factor receptor 2 (HER2) expression, and the Ki-67 proliferation index. On multivariate analysis, coexpression of HSP90 and PI3K-p110α or expression of HSP90 along with PTEN loss demonstrated significantly worse RFS. In subgroup analyses, both exhibited strong prognostic significance in HER2-positive cases, but not in HER2-negative cases. Conclusions The coexpression of HSP90 with PI3K-p110α or expression of HSP90 along with PTEN loss has a potential as a molecular prognostic marker to predict early relapse in patients with invasive breast cancers

Hybrid Models Identified a 12-Gene Signature for Lung Cancer Prognosis and Chemoresponse Prediction

Lung cancer remains the leading cause of cancer-related deaths worldwide. The recurrence rate ranges from 35-50% among early stage non-small cell lung cancer patients. To date, there is no fully-validated and clinically applied prognostic gene signature for personalized treatment.From genome-wide mRNA expression profiles generated on 256 lung adenocarcinoma patients, a 12-gene signature was identified using combinatorial gene selection methods, and a risk score algorithm was developed with Naïve Bayes. The 12-gene model generates significant patient stratification in the training cohort HLM & UM (n = 256; log-rank P = 6.96e-7) and two independent validation sets, MSK (n = 104; log-rank P = 9.88e-4) and DFCI (n = 82; log-rank P = 2.57e-4), using Kaplan-Meier analyses. This gene signature also stratifies stage I and IB lung adenocarcinoma patients into two distinct survival groups (log-rank P<0.04). The 12-gene risk score is more significant (hazard ratio = 4.19, 95% CI: [2.08, 8.46]) than other commonly used clinical factors except tumor stage (III vs. I) in multivariate Cox analyses. The 12-gene model is more accurate than previously published lung cancer gene signatures on the same datasets. Furthermore, this signature accurately predicts chemoresistance/chemosensitivity to Cisplatin, Carboplatin, Paclitaxel, Etoposide, Erlotinib, and Gefitinib in NCI-60 cancer cell lines (P<0.017). The identified 12 genes exhibit curated interactions with major lung cancer signaling hallmarks in functional pathway analysis. The expression patterns of the signature genes have been confirmed in RT-PCR analyses of independent tumor samples.The results demonstrate the clinical utility of the identified gene signature in prognostic categorization. With this 12-gene risk score algorithm, early stage patients at high risk for tumor recurrence could be identified for adjuvant chemotherapy; whereas stage I and II patients at low risk could be spared the toxic side effects of chemotherapeutic drugs

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

<p>Abstract</p> <p>Background</p> <p>In recent years, the completion of the Human Genome Project and other rapid advances in genomics have led to increasing anticipation of an era of genomic and personalized medicine, in which an individual's health is optimized through the use of all available patient data, including data on the individual's genome and its downstream products. Genomic and personalized medicine could transform healthcare systems and catalyze significant reductions in morbidity, mortality, and overall healthcare costs.</p> <p>Discussion</p> <p>Critical to the achievement of more efficient and effective healthcare enabled by genomics is the establishment of a robust, nationwide clinical decision support infrastructure that assists clinicians in their use of genomic assays to guide disease prevention, diagnosis, and therapy. Requisite components of this infrastructure include the standardized representation of genomic and non-genomic patient data across health information systems; centrally managed repositories of computer-processable medical knowledge; and standardized approaches for applying these knowledge resources against patient data to generate and deliver patient-specific care recommendations. Here, we provide recommendations for establishing a national decision support infrastructure for genomic and personalized medicine that fulfills these needs, leverages existing resources, and is aligned with the <it>Roadmap for National Action on Clinical Decision Support </it>commissioned by the U.S. Office of the National Coordinator for Health Information Technology. Critical to the establishment of this infrastructure will be strong leadership and substantial funding from the federal government.</p> <p>Summary</p> <p>A national clinical decision support infrastructure will be required for reaping the full benefits of genomic and personalized medicine. Essential components of this infrastructure include standards for data representation; centrally managed knowledge repositories; and standardized approaches for leveraging these knowledge repositories to generate patient-specific care recommendations at the point of care.</p

Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

Background Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and simultaneous activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step toward clinical application of patient-tailored treatment regimens. Results Toward this goal, we establish a library of 139 gynecologic tumors including epithelial ovarian cancers (EOCs), cervical, endometrial tumors, and uterine sarcomas that are genomically and/or pharmacologically annotated and explore dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discover lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identify TP53 mutation as a molecular determinant that elicits therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identify transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Conclusions Together, our results demonstrate the potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers