Gene-expression profiles predict survival of patients with lung adenocarcinoma

In order to elucidate the biological variance between normal ovarian surface epithelial (NOSE) and epithelial ovarian cancer (EOC) cells, and to build a molecular classifier to discover new markers distinguishing these cells, we analysed gene expression patterns of 65 primary cultures of these tissues by oligonucleotide microarray. Unsupervised clustering highlights three subgroups of tumours: low malignant potential tumours, invasive solid tumours and tumour cells derived from ascites. We selected 18 genes with expression profiles that enable the distinction of NOSE from these three groups of EOC with 92% accuracy. Validation using an independent published data set derived from tissues or primary cultures confirmed a high accuracy (87 -96%). The distinctive expression pattern of a subset of genes was validated by quantitative reverse transcription -PCR. An ovarian-specific tissue array representing tissues from NOSE and EOC samples of various subtypes and grades was used to further assess the protein expression patterns of two differentially expressed genes (Msln and BMP-2) by immunohistochemistry. This study highlights the relevance of using primary cultures of epithelial ovarian cells as a model system for gene profiling studies and demonstrates that the statistical analysis of gene expression profiling is a useful approach for selecting novel molecular tumour markers.

Global gene expression profiling of hepatocellular carcinoma (HCC) is a promising new technology that has already refined the diagnosis and prognostic predictions of HCC patients. This has been accomplished by identifying genes whose expression pattern is associated with clinicopathological features of HCC tumors. Molecular characterization of HCC from gene expression profiling studies will undoubtedly improve the prediction of treatment responses, selection of treatments for specific molecular subtypes of HCC and ultimately the clinical outcome of HCC patients. The research focus is now shifting toward the identification of genetic determinants that are components of the specific regulatory pathways altered in cancers, and that may constitute novel therapeutic targets. Here we review the recent advances in gene expression profiling of HCC and discuss the future strategies for analysing large and complicated data sets from microarray studies and how to integrate these with diverse genomic data.

Krü ppel-like factor 6 (KLF6) has been reported to act as a tumor suppressor gene involved in the regulation of the cell cycle by activating p21 in a p53-independent manner. Many studies suggest that KLF6 is inactivated by allelic loss and somatic mutation. However, there is a high variability in the reported frequency of mutations (from 1 to 55%). TP53 also regulates the cell cycle through the activation of p21. In prostate cancer, the reported frequency of TP53 mutations ranges from 3 to 42%. In all these reports, there is a considerable degree of methodological heterogeneity. Our aim was to determine the frequency of KLF6 and TP53 mutations in a welldefined group of prostate tumors with different stages and Gleason grades. The four exons of KLF6 and exons 4-9 of TP53 were studied in 103 cases, including 90 formalin-fixed, paraffin-embedded (FFPE) and 13 frozen samples. All tumors were analyzed through PCR and direct sequencing. All changes found were confirmed by a second independent PCR and sequencing reaction. For KLF6, mutation (E227G) was only detected in one tumor (1%) and for TP53, three different mutations (L130H, H214R, and Y234C) were detected in five tumors (5%). This low mutation index is in keeping with recent papers on the subject. Our study strongly supports the notion that KLF6 and TP53 mutations are not frequent events in prostate cancer. When using FFPE tissues, it is mandatory to perform at least two independent rounds of PCR and sequencing to confirm mutations and exclude Taq polymerase-induced artifacts. Two of these genes are Krü ppel-like factor 6 (KLF6) and TP53.KLF6 is a transcription factor that interacts with DNA through three zinc-fingers in its COOHterminal domain. KLF6 belongs to the KLF family, a family that is broadly involved in cell differentiation, development, growth-related signal transduction, cell proliferation, apoptosis, and angiogenesis. 5 It has been suggested that KLF6 could be involved in the regulation of the cell cycle by activating p21 in a p53-independent manner. 6 This has been proven in several in vitro 5 and in vivo assays. 7 KLF6 is believed to regulate cancer development and progression through the downregulation of the c-Jun oncoprotein 8 and the activation of E-cadherin. 9 The reported frequency of KLF6 mutations in different types of human cancer varies in the different published studies. [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29] In prostate cancer, four studies have analyzed the frequency of KLF6 mutations. 6,[30][31][32] In the first published study, Narla et al 6 showed a very high frequency, 55%, whereas in the following study, Chen et al 30 obtained a lower frequency, around 15%. The results of two recent reports provided frequencies of 0 and 1%. 31,32 It should be noted that there were considerable