Endre Anderssen

Regression of a data matrix on descriptors of both its rows and of its columns via latent variables: L-PLSR

Abstract A new approach is described, for extracting and visualising structures in a data matrix Y in light of additional information BOTH about the ROWS in Y, given in matrix X, AND about the COLUMNS in Y, given in matrix Z. The three matrices Z–Y–X may be envisioned as an “L-shape”; X(I×K) and Z(J×L) share no matrix size dimension, but are connected via Y(I×J). A few linear combinations (components) are extracted from X and from Z, and their interactions are used for bi-linear modelling of Y, as well as for bi-linear modelling of X and Z themselves. The components are defined by singular value decomposition (SVD) of X′YZ. Two versions of the L-PLSR are described—using one single SVD for all components, or component-wise SVDs after deflation. The method is applied to the analysis of consumer liking data Y of six products assessed by 125 persons, in light of 10 other product descriptors X and 15 other person descriptors Z. Its performance is also checked on artificial data.

Exposure and effects of persistent organic pollutants in european shag (Phalacrocorax aristotelis) hatchlings from the coast of Norway

Although the coast of Norway is relatively clean regarding contaminants compared to areas of Europe with higher density of both people and industry, levels of persistent organic pollutants (POPs) exist in the marine ecosystem that may cause chronic exposure effects in wildlife. In this study, polychlorinated biphenyls (PCBs), some organochlorinated pesticides (OCPs), polybrominated diphenyl ethers (PBDEs), and hexabromocyclododecane (HBCD) were analyzed in yolk sac of European shag (Phalacrocorax aristotelis) hatchlings from an island situated on the coast of Mid-Norway. In addition, levels of retinol (vitamin A), retinyl palmitate, and alpha-tocopherol (vitamin E) were measured in plasma and liver. The shag hatchlings seemed to be relatively highly contaminated by PBDEs and HBCD on a European scale. A negative relationship between PBDE-28 and liver tocopherol levels was revealed, and plasma retinol levels correlated negatively to levels of several PCB congeners, the summed PCB concentrations (sigmaPCBs), and some OCPs. More studies should be done to reveal the effects of POPs, and especially PBDEs, on vitamin status in wild birds.

Spatial trends and associated biological responses of organochlorines and brominated flame retardants in hatchlings of North Atlantic kittiwakes (Rissa tridactyla)

Persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs), some organochlorinated pesticides (OCPs), polybrominated diphenyl ethers (PBDEs), and hexabromocyclododecane (HBCD), were analyzed in yolk sacs of kittiwake (Rissa tridactyla) hatchlings from Kongsfjorden at Svalbard (Norwegian Arctic; 79 degrees N) and from Runde, an island on the coast of Norway (62 degrees N). Retinol (vitamin A), retinyl palmitate, and alpha-tocopherol (vitamin E) were measured in plasma and liver of the hatchlings to examine whether these vitamins were associated with the POPs. Higher levels of PCBs and OCPs were found in hatchlings from Kongsfjorden than in hatchlings from Runde. However, HBCD levels were significantly lower in hatchlings from Kongsfjorden compared to those in hatchlings from Runde. No differences between the two populations of kittiwake hatchlings were found regarding levels of PBDEs. In comparison with seabirds from other European waters and the Canadian Arctic, the kittiwakes seemed to have relatively high levels of PBDEs and HBCD. No effects on morphological variables or vitamin levels by the POPs were revealed, but multivariate regression indicated that liver tocopherol levels may be influenced by POPs.

Genome-Wide Profile of Pleural Mesothelioma versus Parietal and Visceral Pleura: The Emerging Gene Portrait of the Mesothelioma Phenotype

Background Malignant pleural mesothelioma is considered an almost incurable tumour with increasing incidence worldwide. It usually develops in the parietal pleura, from mesothelial lining or submesothelial cells, subsequently invading the visceral pleura. Chromosomal and genomic aberrations of mesothelioma are diverse and heterogenous. Genome-wide profiling of mesothelioma versus parietal and visceral normal pleural tissue could thus reveal novel genes and pathways explaining its aggressive phenotype. Methodology and Principal Findings Well-characterised tissue from five mesothelioma patients and normal parietal and visceral pleural samples from six non-cancer patients were profiled by Affymetrix oligoarray of 38 500 genes. The lists of differentially expressed genes tested for overrepresentation in KEGG PATHWAYS (Kyoto Encyclopedia of Genes and Genomes) and GO (gene ontology) terms revealed large differences of expression between visceral and parietal pleura, and both tissues differed from mesothelioma. Cell growth and intrinsic resistance in tumour versus parietal pleura was reflected in highly overexpressed cell cycle, mitosis, replication, DNA repair and anti-apoptosis genes. Several genes of the “salvage pathway” that recycle nucleobases were overexpressed, among them TYMS, encoding thymidylate synthase, the main target of the antifolate drug pemetrexed that is active in mesothelioma. Circadian rhythm genes were expressed in favour of tumour growth. The local invasive, non-metastatic phenotype of mesothelioma, could partly be due to overexpression of the known metastasis suppressors NME1 and NME2. Down-regulation of several tumour suppressor genes could contribute to mesothelioma progression. Genes involved in cell communication were down-regulated, indicating that mesothelioma may shield itself from the immune system. Similarly, in non-cancer parietal versus visceral pleura signal transduction, soluble transporter and adhesion genes were down-regulated. This could represent a genetical platform of the parietal pleura propensity to develop mesothelioma. Conclusions Genome-wide microarray approach using complex human tissue samples revealed novel expression patterns, reflecting some important features of mesothelioma biology that should be further explored.

Malignant pleural mesothelioma: Genome-wide expression patterns reflecting general resistance mechanisms and a proposal of novel targets

Malignant pleural mesothelioma is an asbestos-related multi-resistant tumour with increasing incidence worldwide. Well-characterized snap-frozen normal parietal, visceral pleura and mesothelioma samples were analysed with Affymetrix Human Genome U133 Plus 2.0 GeneChip oligoarray of 38500 genes. We discovered a close relation between gene profile and resistance towards topoisomerase poisons, alkylating agents, antitubulines, antifolates, platinum compounds and radiation therapy. Target genes of chemo- (e.g. TOP2A, BIRC5/Survivin and proteasome) and radiotherapy (e.g. BRCA2, FANCA, FANCD2, CCNB1 and RAD50) were significantly overexpressed. The Fanconi anemia/BRCA2 pathway, responsible for homologous recombination DNA repair appears as a key pathway in both chemo- and radio-resistance of mesothelioma. Leukocyte trans-endothelial migration gene down-regulation could partly explain resistance against immunological therapies. Gene expression features found in other resistant cancer types related to DNA repair and replication are shared by mesothelioma and could represent general features of tumour resistance. Targeted suppression of some of those key genes and pathways combined with chemotherapy or radiation could improve the outcome of mesothelioma therapy. We propose CHEK1, RAD21, FANCD2 and RAN as new co-targets for mesothelioma treatment. The pro-angiogenic AGGF1 mRNA and protein was highly overexpressed in all tumours and may serve as a target for anti-angiogenic treatment. Overexpression of NQO1 may render mesothelioma sensitive to the novel compound beta-Lapachone.

Lung cancer and DNA repair genes: multilevel association analysis from the International Lung Cancer Consortium

Lung cancer (LC) is the leading cause of cancer-related death worldwide and tobacco smoking is the major associated risk factor. DNA repair is an important process, maintaining genome integrity and polymorphisms in DNA repair genes may contribute to susceptibility to LC. To explore the role of DNA repair genes in LC, we conducted a multilevel association study with 1655 single nucleotide polymorphisms (SNPs) in 211 DNA repair genes using 6911 individuals pooled from four genome-wide case-control studies. Single SNP association corroborates previous reports of association with rs3131379, located on the gene MSH5 (P = 3.57 × 10-5) and returns a similar risk estimate. The effect of this SNP is modulated by histological subtype. On the log-additive scale, the odds ratio per allele is 1.04 (0.84-1.30) for adenocarcinomas, 1.52 (1.28-1.80) for squamous cell carcinomas and 1.31 (1.09-1.57) for other histologies (heterogeneity test: P = 9.1 × 10(-)(3)). Gene-based association analysis identifies three repair genes associated with LC (P < 0.01): UBE2N, structural maintenance of chromosomes 1L2 and POLB. Two additional genes (RAD52 and POLN) are borderline significant. Pathway-based association analysis identifies five repair pathways associated with LC (P < 0.01): chromatin structure, DNA polymerases, homologous recombination, genes involved in human diseases with sensitivity to DNA-damaging agents and Rad6 pathway and ubiquitination. This first international pooled analysis of a large dataset unravels the role of specific DNA repair pathways in LC and highlights the importance of accounting for gene and pathway effects when studying LC.

Homology-Based Modelling of Targets for Rational Drug Design

The current status in rational drug design using homology-based models is discussed, with focus on template selection, model building, model verification and strategies for drug design based on model structures. A novel approach for identification of unique binding site features from homology-based models, Protein Alpha Shape Similarity Analysis (PASSA) is described.

A framework for significance analysis of gene expression data using dimension reduction methods.

BackgroundThe most popular methods for significance analysis on microarray data are well suited to find genes differentially expressed across predefined categories. However, identification of features that correlate with continuous dependent variables is more difficult using these methods, and long lists of significant genes returned are not easily probed for co-regulations and dependencies. Dimension reduction methods are much used in the microarray literature for classification or for obtaining low-dimensional representations of data sets. These methods have an additional interpretation strength that is often not fully exploited when expression data are analysed. In addition, significance analysis may be performed directly on the model parameters to find genes that are important for any number of categorical or continuous responses. We introduce a general scheme for analysis of expression data that combines significance testing with the interpretative advantages of the dimension reduction methods. This approach is applicable both for explorative analysis and for classification and regression problems.ResultsThree public data sets are analysed. One is used for classification, one contains spiked-in transcripts of known concentrations, and one represents a regression problem with several measured responses. Model-based significance analysis is performed using a modified version of Hotellings T2-test, and a false discovery rate significance level is estimated by resampling. Our results show that underlying biological phenomena and unknown relationships in the data can be detected by a simple visual interpretation of the model parameters. It is also found that measured phenotypic responses may model the expression data more accurately than if the design-parameters are used as input. For the classification data, our method finds much the same genes as the standard methods, in addition to some extra which are shown to be biologically relevant. The list of spiked-in genes is also reproduced with high accuracy.ConclusionThe dimension reduction methods are versatile tools that may also be used for significance testing. Visual inspection of model components is useful for interpretation, and the methodology is the same whether the goal is classification, prediction of responses, feature selection or exploration of a data set. The presented framework is conceptually and algorithmically simple, and a Matlab toolbox (Mathworks Inc, USA) is supplemented.

Transcription profiling during the cell cycle shows that a subset of Polycomb-targeted genes is upregulated during DNA replication

Genome-wide gene expression analyses of the human somatic cell cycle have indicated that the set of cycling genes differ between primary and cancer cells. By identifying genes that have cell cycle dependent expression in HaCaT human keratinocytes and comparing these with previously identified cell cycle genes, we have identified three distinct groups of cell cycle genes. First, housekeeping genes enriched for known cell cycle functions; second, cell type-specific genes enriched for HaCaT-specific functions; and third, Polycomb-regulated genes. These Polycomb-regulated genes are specifically upregulated during DNA replication, and consistent with being epigenetically silenced in other cell cycle phases, these genes have lower expression than other cell cycle genes. We also find similar patterns in foreskin fibroblasts, indicating that replication-dependent expression of Polycomb-silenced genes is a prevalent but unrecognized regulatory mechanism.

Quantum chemical descriptors in the formulation of pectin pellets produced by extrusion/spheronisation

The objective of this study was to employ quantitative structure-activity relationships (QSAR) to relate calculated molecular descriptors of granulation liquid additives to improvements in the size of pectin pellets produced by extrusion/spheronisation. Quantum chemical descriptors were calculated for a large number of candidate additives. Based on a principal component analysis (PCA) of descriptors of the candidates, a few substances were selected. The most suitable concentration for each additive was found, and pellets were prepared by an extrusion/spheronisation process. Three pectin grades of different methoxy and amide substitution were tested and the quality of the pellets was evaluated based on size. PLS models were constructed to identify the molecular properties that were most important in producing short, nearly spherical pellets. The results show that quantum chemical descriptors can be a useful tool in the formulation of pectin pellets. Acceptable models relating additive properties and pellet size were achieved. Independent of the pectin grade, the two most important factors favouring formation of small spherical pellets were a small molecular size and a strong hydrogen bond forming ability of the additive molecules.