Is there a governance failure in corporatised Australian Government Business Enterprises? Evidence from their Chief Executive Officers’ compensation.

Over the last three decades, governments have commercialised and corporatised many of their government business enterprises (GBEs) without privatising them under New Public Management (NPM) policy, which requires them to act as a corporate sector entity. These GBEs have independent boards that are responsible for the corporate governance of these entities, including the hiring of chief executive officers (CEOs) and determining their compensation. We examine the association between pay and performance for CEOs of GBEs and find that the levels and changes in CEO compensation are not associated with GBE performance despite being the explicit intent of NPM and regulatory policy. We suggest that this corporate governance failure could be due to the composition of the GBE boards. Our evidence shows that only 11.29% of directors appointed have public listed company experience with the balance of director appointments, being either senior public servants or political appointments who may lack the motivation or have any incentive to closely monitor CEO compensation. Accordingly, we suggest some possible policy changes to both the determination of CEO compensation and the composition of GBE boards

BCL10 is rarely mutated in human prostate carcinoma, small-cell lung cancer, head and neck tumours, renal carcinoma and sarcomas

We have used single-strand conformation polymorphism (SSCP) analysis to screen for mutations in the BCL 10 gene in 81 primary prostate carcinomas, 20 squamous cell cancers of the head and neck, 15 small-cell lung cancer cell lines, 24 renal carcinoma cell lines and 13 sarcoma cell lines. We failed to find evidence of somatically acquired mutations of the BCL10 gene suggesting that BCL 10 does not play a major role in the development of these malignancies

Genomic profiling using array comparative genomic hybridization define distinct subtypes of diffuse large b-cell lymphoma: a review of the literature

Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin Lymphoma comprising of greater than 30% of adult non-Hodgkin Lymphomas. DLBCL represents a diverse set of lymphomas, defined as diffuse proliferation of large B lymphoid cells. Numerous cytogenetic studies including karyotypes and fluorescent in situ hybridization (FISH), as well as morphological, biological, clinical, microarray and sequencing technologies have attempted to categorize DLBCL into morphological variants, molecular and immunophenotypic subgroups, as well as distinct disease entities. Despite such efforts, most lymphoma remains undistinguishable and falls into DLBCL, not otherwise specified (DLBCL-NOS). The advent of microarray-based studies (chromosome, RNA, gene expression, etc) has provided a plethora of high-resolution data that could potentially facilitate the finer classification of DLBCL. This review covers the microarray data currently published for DLBCL. We will focus on these types of data; 1) array based CGH; 2) classical CGH; and 3) gene expression profiling studies. The aims of this review were three-fold: (1) to catalog chromosome loci that are present in at least 20% or more of distinct DLBCL subtypes; a detailed list of gains and losses for different subtypes was generated in a table form to illustrate specific chromosome loci affected in selected subtypes; (2) to determine common and distinct copy number alterations among the different subtypes and based on this information, characteristic and similar chromosome loci for the different subtypes were depicted in two separate chromosome ideograms; and, (3) to list re-classified subtypes and those that remained indistinguishable after review of the microarray data. To the best of our knowledge, this is the first effort to compile and review available literatures on microarray analysis data and their practical utility in classifying DLBCL subtypes. Although conventional cytogenetic methods such as Karyotypes and FISH have played a major role in classification schemes of lymphomas, better classification models are clearly needed to further understanding the biology, disease outcome and therapeutic management of DLBCL. In summary, microarray data reviewed here can provide better subtype specific classifications models for DLBCL