Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors

Physical status of multiple human papillomavirus genotypes in flow-sorted cervical cancer cells

Multiple human papilloma virus (HPV) infections have been detected in cervical cancer. To investigate the significance of multiple HPV infections, we studied their prevalence in cancer samples from a low-risk (Dutch) and a high-risk (Surinamese) population and the correlation of HPV infection with tumor cell aneuploidy. SPF 10 LiPA was used for HPV detection in formalin-fixed cervical carcinoma samples from 96 Dutch and 95 Surinamese patients. Samples with HPV type 16 or 18 infections were sorted by flow cytometry, and fluorescence in situ hybridization was performed on the diploid and aneuploid subpopulations to detect HPV 16 and 18 genotypes simultaneously. Multiple HPV infections were present in I I of 80 (13.8%) Dutch and 17 of 77 (22. 1%) Surinamese carcinomas. Three cases had an HPV 16 and HPV 18 coinfection: in two cases, integrated HPV copies of HPV 16 or 18 were detected in the aneuploid fraction, and in one case both HPV 16 and 18 were present solely as episomes. Based on our findings, multiple HPV infections are present in cervical cancer samples from both high- and low-risk populations. Furthermore, multiple HPV types can be present in an episomal state in both diploid and aneuploid tumor cells, but integrated HPV genomes are detectable only in the aneuploid tumor cell subpopulations. (c) 2007 Elsevier Inc. All rights reserved

A Novel Strategy for Human Papillomavirus Detection and Genotyping with SybrGreen and Molecular Beacon Polymerase Chain Reaction

Human papillomaviruses (HPVs) play an important role in the pathogenesis of cervical cancer. For identification of the large number of different HPV types found in (pre)malignant lesions, a robust methodology is needed that combines general HPV detection with HPV genotyping. We have developed for formaldehyde-fixed samples a strategy that, in a homogenous, real-time fluorescence polymerase chain reaction (PCR)-based assay, accomplishes general HPV detection by SybrGreen reporting of HPV-DNA amplicons, and genotyping of seven prevalent HPV types (HPV-6, -11, -16, -18, -31, -33, -45) by real-time molecular beacon PCR. The false-positive rate of the HPV SybrGreen-PCR was 4%, making it well suited as a prescreening, general HPV detection technology. The type specificity of the seven selected HPV molecular beacons was 100% and double infections were readily identified. The multiplexing capacity of the HPV molecular beacon PCR was analyzed and up to three differently labeled molecular beacons could be used in one PCR reaction without observing cross talk. The inherent quantitation capacities of real-time fluorescence PCR allowed the determination of average HPV copy number per cell. We conclude that the HPV SybrGreen-PCR in combination with the HPV molecular beacon PCR provides a robust, sensitive, and quantitative general HPV detection and genotyping methodology

High ALK mRNA expression has a negative prognostic significance in rhabdomyosarcoma

BACKGROUND: Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase aberrantly expressed in cancer, but its clinical and functional importance remain controversial. Mutation or amplification of ALK, as well as its expression levels assessed by conventional immunohistochemistry methods, has been linked to prognosis in cancer, although with potential bias because of the semi-quantitative approaches. Herein, we measured ALK mRNA expression in rhabdomyosarcoma (RMS) and determined its clinical impact on patients' stratification and outcome. METHODS: Specimens were obtained from RMS patients and cell lines, and ALK expression was analysed by quantitative RT–PCR, western blotting, IHC, and copy number analysis. RESULTS: High ALK mRNA expression was detected in the vast majority of PAX3/7-FOXO1-positive tumours, whereas PAX3/7-FOXO1-negative RMS displayed considerably lower amounts of both mRNA and protein. Notably, ALK mRNA distinguished unfavourable PAX3/7-FOXO1-positive tumours from PAX3/7-FOXO1-negative RMS (P<0.0001), and also correlated with larger tumour size (P<0.05) and advanced clinical stage (P<0.01), independently of fusion gene status. High ALK mRNA levels were of prognostic relevance by Cox univariate regression analysis and correlated with increased risk of relapse (P=0.001) and survival (P=0.01), whereas by multivariate analysis elevated ALK mRNA expression resulted a negative prognostic marker when clinical stage was not included. CONCLUSION: Quantitative assessment of ALK mRNA expression helps to improve risk stratification of RMS patients and identifies tumours with adverse biological characteristics and aggressive behaviour

Immunoglobulins as Radiopharmaceutical Vectors

With the introduction of the magic bullet concept by Ehrlich and the subsequent development of hybridoma technology by Kohler and Milstein, the world of target-specific protein-based drugs was opened. Since then, numerous immunoglobulins and a few dozen radioimmunoconjugates have been approved by the US Food and Drug Administration (US FDA) and the European Medicines Agency (EMA). In this chapter, we will discuss the array of natural and engineered immunoglobulins that are available as vectors for imaging and therapy as well as their in vivo modes of action. Several critical aspects of the accessibility and expression of targets related to the use of radioimmunoconjugates for imaging and therapy will be also discussed. These two introductory sections are followed by the core of the chapter in which we address the selection of appropriate radionuclide-immunoglobulin combinations, the possible applications of immunoPET and immunoSPECT, and how radiolabeled immunoglobulins can be evaluated