Cancers originating from epithelial cells are the most common malignancies. No common expression profile of solid tumors compared to normal tissues has been described so far. Therefore we were interested if genes differentially expressed in the majority of carcinomas could be identified using bioinformatic methods. Complete data sets were downloaded for carcinomas of the prostate, breast, lung, ovary, colon, pancreas, stomach, bladder, liver, and kidney, and were subjected to an expression analysis using SAM. In each experiment, a gene was scored as differentially expressed if the q value was below 25%. Probe identifiers were unified by comparing the respective probe sequences to the Unigene build 155 using BlastN. To obtain differentially expressed genes within the set of analyzed carcinomas, the number of experiments in which differential expression was observed was counted. Differential expression was assigned to genes if they were differentially expressed in at least eight experiments of tumors from different origin. The identified candidate genes ADRM1, EBNA1BP2, FDPS, FOXM1, H2AFX, HDAC3, IRAK1, and YY1 were subjected to further validation. Using this comparative approach, 100 genes were identified as upregulated and 21 genes as downregulated in the carcinomas.

In order to screen for differentially expressed genes that might be useful in diagnosis or therapy of prostate cancer we have used a custom made Affymetrix GeneChip containing 3950 cDNA fragments. Expression profiles were obtained from 42 matched pairs of mRNAs isolated from microdissected malignant and benign prostate tissues. Applying three different bioinformatic approaches to define differential gene expression, we found 277 differentially expressed genes, of which 98 were identified by all three methods. Fourteen per cent of these genes were not found in other expression studies, which were based on bulk tissue. Resultant candidate genes were further validated by quantitative RT-PCR, mRNA in situ hybridization and immunohistochemistry. AGR2 was over-expressed in 89% of prostate carcinomas, but did not have prognostic significance. Immunohistologically detected over-expression of MEMD and CD24 was identified in 86% and 38.5% of prostate carcinomas respectively, and both were predictive of PSA relapse. Combined marker analysis using MEMD and CD24 expression proved to be an independent prognostic factor (RR = 4.7, p = 0.006) in a Cox regression model, and was also superior to conventional markers. This combination of molecular markers thus appears to allow improved prediction of patient prognosis, but should be validated in larger studies.

Nicotinamide mononucleotide adenylyl transferase (NMNAT) is an essential enzyme in all organisms, because it catalyzes a key step of NAD synthesis. However, little is known about the structure and regulation of this enzyme. In this study we established the primary structure of human NMNAT. The human sequence represents the first report of the primary structure of this enzyme for an organism higher than yeast. The enzyme was purified from human placenta and internal peptide sequences determined. Analysis of human DNA sequence data then permitted the cloning of a cDNA encoding this enzyme. Recombinant NMNAT exhibited catalytic properties similar to the originally purified enzyme. Human NMNAT (molecular weight 31 932) consists of 279 amino acids and exhibits substantial structural differences to the enzymes from lower organisms. A putative nuclear localization signal was confirmed by immunofluorescence studies. NMNAT strongly inhibited recombinant human poly(ADP-ribose) polymerase 1, however, NMNAT was not modified by poly(ADP-ribose). NMNAT appears to be a substrate of nuclear kinases and contains at least three potential phosphorylation sites. Endogenous and recombinant NMNAT were phosphorylated in nuclear extracts in the presence of [Q Q-32 P]ATP. We propose that NMNAT's activity or interaction with nuclear proteins are likely to be modulated by phosphorylation. ß 2001 Federation of European Biochemical Societies. Published by Elsevier Science B.V. All rights reserved.

a b s t r a c tThe identification and annotation of protein-coding genes is one of the primary goals of whole-genome sequencing projects, and the accuracy of predicting the primary protein products of gene expression is vital to the interpretation of the available data and the design of downstream functional applications. Nevertheless, the comprehensive annotation of eukaryotic genomes remains a considerable challenge. Many genomes submitted to public databases, including those of major model organisms, contain significant numbers of wrong and incomplete gene predictions. We present a community-based reannotation of the Aspergillus nidulans genome with the primary goal of increasing the number and quality of protein functional assignments through the careful review of experts in the field of fungal biology.

A four-step procedure for the efficient and systematic mining of whole EST libraries for differentially expressed genes is presented. After eliminating redundant entries from the EST library under investigation (step 1), contigs of maximal length are built upon each remaining EST using about 4 000 000 public and proprietary ESTs (step 2). These putative genes are compared against a database comprising ESTs from 16 different tissues (both normal and tumour affected) to determine whether or not they are differentially expressed (step 3; electronic northern). Fisher's exact test is used to assess the significance of differential expression. In step 4, an attempt is made to characterise the contigs obtained in the assembly through database comparison. A case study of the CGAP library NCI_CGAP_Br1.1, a library made from three (well, moderately, and poorly differentiated) invasive ductal breast tumours (2126 ESTs in total) was carried out. Of the maximal contigs, 139 were found to be significantly (alpha = 0.05) over-expressed in breast tumour tissue, while 13 appeared to be down-regulated.