Morten Krogh

Recurrent gross mutations of the PTEN tumor suppressor gene in breast cancers with deficient DSB repair

Basal-like breast cancer (BBC) is a subtype of breast cancer with poor prognosis. Inherited mutations of BRCA1, a cancer susceptibility gene involved in double-strand DNA break (DSB) repair, lead to breast cancers that are nearly always of the BBC subtype; however, the precise molecular lesions and oncogenic consequences of BRCA1 dysfunction are poorly understood. Here we show that heterozygous inactivation of the tumor suppressor gene Pten leads to the formation of basal-like mammary tumors in mice, and that loss of PTEN expression is significantly associated with the BBC subtype in human sporadic and BRCA1-associated hereditary breast cancers. In addition, we identify frequent gross PTEN mutations, involving intragenic chromosome breaks, inversions, deletions and micro copy number aberrations, specifically in BRCA1-deficient tumors. These data provide an example of a specific and recurrent oncogenic consequence of BRCA1-dependent dysfunction in DNA repair and provide insight into the pathogenesis of BBC with therapeutic implications. These findings also argue that obtaining an accurate census of genes mutated in cancer will require a systematic examination for gross gene rearrangements, particularly in tumors with deficient DSB repair.

Basal-like phenotype is not associated with patient survival in estrogen-receptor-negative breast cancers

IntroductionBasal-phenotype or basal-like breast cancers are characterized by basal epithelium cytokeratin (CK5/14/17) expression, negative estrogen receptor (ER) status and distinct gene expression signature. We studied the clinical and biological features of the basal-phenotype tumors determined by immunohistochemistry (IHC) and cDNA microarrays especially within the ER-negative subgroup.MethodsIHC was used to evaluate the CK5/14 status of 445 stage II breast cancers. The gene expression signature of the CK5/14 immunopositive tumors was investigated within a subset (100) of the breast tumors (including 50 ER-negative tumors) with a cDNA microarray. Survival for basal-phenotype tumors as determined by CK5/14 IHC and gene expression signature was assessed.ResultsFrom the 375 analyzable tumor specimens, 48 (13%) were immunohistochemically positive for CK5/14. We found adverse distant disease-free survival for the CK5/14-positive tumors during the first years (3 years hazard ratio (HR) 2.23, 95% confidence interval (CI) 1.17 to 4.24, p = 0.01; 5 years HR 1.80, 95% CI 1.02 to 3.15, p = 0.04) but the significance was lost at the end of the follow-up period (10 years HR 1.43, 95% CI 0.84 to 2.43, p = 0.19). Gene expression profiles of immunohistochemically determined CK5/14-positive tumors within the ER-negative tumor group implicated 1,713 differently expressed genes (p < 0.05). Hierarchical clustering analysis with the top 500 of these genes formed one basal-like and a non-basal-like cluster also within the ER-negative tumor entity. A highly concordant classification could be constructed with a published gene set (Sorlies intrinsic gene set, concordance 90%). Both gene sets identified a basal-like cluster that included most of the CK5/14-positive tumors, but also immunohistochemically CK5/14-negative tumors. Within the ER-negative tumor entity there was no survival difference between the non-basal and basal-like tumors as identified by immunohistochemical or gene-expression-based classification.ConclusionBasal cytokeratin-positive tumors have a biologically distinct gene expression signature from other ER-negative tumors. Even if basal cytokeratin expression predicts early relapse among non-selected tumors, the clinical outcome of basal tumors is similar to non-basal ER-negative tumors. Immunohistochemically basal cytokeratin-positive tumors almost always belong to the basal-like gene expression profile, but this cluster also includes few basal cytokeratin-negative tumors.

Detection of pancreatic cancer using antibody microarray-based serum protein profiling

The driving force behind oncoproteomics is to identify protein signatures that are associated with a particular malignancy. Here, we have used a recombinant scFv antibody microarray in an attempt to classify sera derived from pancreatic adenocarcinoma patients versus healthy subjects. Based on analysis of nonfractionated, directly labeled, whole human serum proteomes we have identified a protein signature based on 19 nonredundant analytes, that discriminates between cancer patients and healthy subjects. Furthermore, a potential protein signature, consisting of 21 protein analytes, could be defined that was shown to be associated with cancer patients having a life expectancy of <12 months. Taken together, the data suggest that antibody microarray analysis of complex proteomes will be a useful tool to define disease associated protein signatures.

Folding Free Energies of 5′-UTRs Impact Post-Transcriptional Regulation on a Genomic Scale in Yeast

Using high-throughput technologies, abundances and other features of genes and proteins have been measured on a genome-wide scale in Saccharomyces cerevisiae. In contrast, secondary structure in 5′–untranslated regions (UTRs) of mRNA has only been investigated for a limited number of genes. Here, the aim is to study genome-wide regulatory effects of mRNA 5′-UTR folding free energies. We performed computations of secondary structures in 5′-UTRs and their folding free energies for all verified genes in S. cerevisiae. We found significant correlations between folding free energies of 5′-UTRs and various transcript features measured in genome-wide studies of yeast. In particular, mRNAs with weakly folded 5′-UTRs have higher translation rates, higher abundances of the corresponding proteins, longer half-lives, and higher numbers of transcripts, and are upregulated after heat shock. Furthermore, 5′-UTRs have significantly higher folding free energies than other genomic regions and randomized sequences. We also found a positive correlation between transcript half-life and ribosome occupancy that is more pronounced for short-lived transcripts, which supports a picture of competition between translation and degradation. Among the genes with strongly folded 5′-UTRs, there is a huge overrepresentation of uncharacterized open reading frames. Based on our analysis, we conclude that (i) there is a widespread bias for 5′-UTRs to be weakly folded, (ii) folding free energies of 5′-UTRs are correlated with mRNA translation and turnover on a genomic scale, and (iii) transcripts with strongly folded 5′-UTRs are often rare and hard to find experimentally.

The Antiproliferative Effect of Dietary Fiber Phenolic Compounds Ferulic Acid and p-Coumaric Acid on the Cell Cycle of Caco-2 Cells.

Epidemiological and animal studies have shown that dietary fiber is protective against the development of colon cancer. Dietary fiber is a rich source of the hydroxycinnamic acids ferulic acid (FA) and p-coumaric acid (p-CA), which both may contribute to the protective effect. We have investigated the effects of FA and p-CA treatment on global gene expression in Caco-2 colon cancer cells. The Caco-2 cells were treated with 150 μM FA or p-CA for 24 h, and gene expression was analyzed with cDNA microarray technique. A total of 517 genes were significantly affected by FA and 901 by p-CA. As we previously have found that FA or p-CA treatment delayed cell cycle progression, we focused on genes involved in proliferation and cell cycle regulation. The expressions of a number of genes involved in centrosome assembly, such as RABGAP1 and CEP2, were upregulated by FA treatment as well as the gene for the S phase checkpoint protein SMC1L1. p-CA treatment upregulated CDKN1A expression and downregulated CCNA2, CCNB1, MYC, and ODC1. Some proteins corresponding to the affected genes were also studied. Taken together, the changes found can partly explain the effects of FA or p-CA treatment on cell cycle progression, specifically in the S phase by FA and G2/M phase by p-CA treatment.

Comprehensive regional and temporal gene expression profiling of the rat brain during the first 24 h after experimental stroke identifies dynamic ischemia-induced gene expression patterns, and reveals a biphasic activation of genes in surviving tissue.

In order to identify biological processes relevant for cell death and survival in the brain following stroke, the postischemic brain transcriptome was studied by a large‐scale cDNA array analysis of three peri‐infarct brain regions at eight time points during the first 24 h of reperfusion following middle cerebral artery occlusion in the rat. K‐means cluster analysis revealed two distinct biphasic gene expression patterns that contained 44 genes (including 18 immediate early genes), involved in cell signaling and plasticity (i.e. MAP2K7, Sprouty2, Irs‐2, Homer1, GPRC5B, Grasp). The first gene induction phase occurred at 0–3 h of reperfusion, and the second at 9–15 h, and was validated by in situ hybridization. Four gene clusters displayed a progressive increase in expression over time and included 50 genes linked to cell motility, lipid synthesis and trafficking (i.e. ApoD, NPC1, G3P‐dehydrogenase1, and Choline kinase) or cell death‐regulating genes such as mitochondrial CLIC. We conclude that a biphasic transcriptional up‐regulation of the brain‐derived neurotrophic factor (BDNF)–G‐protein coupled receptor (GPCR)–mitogen‐activated protein (MAP) kinase signaling pathways occurs in surviving tissue, concomitant with a progressive and persistent activation of cell proliferation signifying tissue regeneration, which provide the means for cell survival and postischemic brain plasticity.

Comparing functional annotation analyses with Catmap

BackgroundRanked gene lists from microarray experiments are usually analysed by assigning significance to predefined gene categories, e.g., based on functional annotations. Tools performing such analyses are often restricted to a category score based on a cutoff in the ranked list and a significance calculation based on random gene permutations as null hypothesis.ResultsWe analysed three publicly available data sets, in each of which samples were divided in two classes and genes ranked according to their correlation to class labels. We developed a program, Catmap (available for download at http://bioinfo.thep.lu.se/Catmap), to compare different scores and null hypotheses in gene category analysis, using Gene Ontology annotations for category definition. When a cutoff-based score was used, results depended strongly on the choice of cutoff, introducing an arbitrariness in the analysis. Comparing results using random gene permutations and random sample permutations, respectively, we found that the assigned significance of a category depended strongly on the choice of null hypothesis. Compared to sample label permutations, gene permutations gave much smaller p-values for large categories with many coexpressed genes.ConclusionsIn gene category analyses of ranked gene lists, a cutoff independent score is preferable. The choice of null hypothesis is very important; random gene permutations does not work well as an approximation to sample label permutations.

Gene expression profiling in primary breast cancer distinguishes patients developing local recurrence after breast-conservation surgery, with or without postoperative radiotherapy

IntroductionSome patients with breast cancer develop local recurrence after breast-conservation surgery despite postoperative radiotherapy, whereas others remain free of local recurrence even in the absence of radiotherapy. As clinical parameters are insufficient for identifying these two groups of patients, we investigated whether gene expression profiling would add further information.MethodsWe performed gene expression analysis (oligonucleotide arrays, 26,824 reporters) on 143 patients with lymph node-negative disease and tumor-free margins. A support vector machine was employed to build classifiers using leave-one-out cross-validation.ResultsWithin the estrogen receptor-positive (ER+) subgroup, the gene expression profile clearly distinguished patients with local recurrence after radiotherapy (n = 20) from those without local recurrence (n = 80 with or without radiotherapy). The receiver operating characteristic (ROC) area was 0.91, and 5,237 of 26,824 reporters had a P value of less than 0.001 (false discovery rate = 0.005). This gene expression profile provides substantially added value to conventional clinical markers (for example, age, histological grade, and tumor size) in predicting local recurrence despite radiotherapy. Within the ER- subgroup, a weaker, but still significant, signal was found (ROC area = 0.74). The ROC area for distinguishing patients who develop local recurrence from those who remain local recurrence-free in the absence of radiotherapy was 0.66 (combined ER+/ER-).ConclusionA highly distinct gene expression profile for patients developing local recurrence after breast-conservation surgery despite radiotherapy has been identified. If verified in further studies, this profile might be a most important tool in the decision making for surgery and adjuvant therapy.

Signal transduction pathway profiling of individual tumor samples

BackgroundSignal transduction pathways convey information from the outside of the cell to transcription factors, which in turn regulate gene expression. Our objective is to analyze tumor gene expression data from microarrays in the context of such pathways.ResultsWe use pathways compiled from the TRANSPATH/TRANSFAC databases and the literature, and three publicly available cancer microarray data sets. Variation in pathway activity, across the samples, is gauged by the degree of correlation between downstream targets of a pathway. Two correlation scores are applied; one considers all pairs of downstream targets, and the other considers only pairs without common transcription factors. Several pathways are found to be differentially active in the data sets using these scores. Moreover, we devise a score for pathway activity in individual samples, based on the average expression value of the downstream targets. Statistical significance is assigned to the scores using permutation of genes as null model. Hence, for individual samples, the status of a pathway is given as a sign, + or -, and a p-value. This approach defines a projection of high-dimensional gene expression data onto low-dimensional pathway activity scores. For each dataset and many pathways we find a much larger number of significant samples than expected by chance. Finally, we find that several sample-wise pathway activities are significantly associated with clinical classifications of the samples.ConclusionThis study shows that it is feasible to infer signal transduction pathway activity, in individual samples, from gene expression data. Furthermore, these pathway activities are biologically relevant in the three cancer data sets.

Proteomic analysis of striatal proteins in the rat model of L-DOPA-induced dyskinesia.

l‐DOPA‐induced dyskinesia (LID) is among the motor complications that arise in Parkinson’s disease (PD) patients after a prolonged treatment with l‐DOPA. To this day, transcriptome analysis has been performed in a rat model of LID [Neurobiol. Dis., 17 (2004), 219] but information regarding the proteome is still lacking. In the present study, we investigated the changes occurring at the protein level in striatal samples obtained from the unilaterally 6‐hydroxydopamine‐lesion rat model of PD treated with saline, l‐DOPA or bromocriptine using two‐dimensional difference gel electrophoresis and mass spectrometry (MS). Rats treated with l‐DOPA were allocated to two groups based on the presence or absence of LID. Among the 2000 spots compared for statistical difference, 67 spots were significantly changed in abundance and identified using matrix‐assisted laser desorption/ionization time‐of‐flight MS, atmospheric pressure matrix‐assisted laser desorption/ionization and HPLC coupled tandem MS (LC/MS/MS). Out of these 67 proteins, LID significantly changed the expression level of five proteins: αβ‐crystalin, gamma‐enolase, guanidoacetate methyltransferase, vinculin, and proteasome α‐2 subunit. Complementary techniques such as western immunoblotting and immunohistochemistry were performed to investigate the validity of the data obtained using the proteomic approach. In conclusion, this study provides new insights into the protein changes occurring in LID.