Mogens Kruhøffer

MicroRNAs (miRNA) are a class of small noncoding RNAs with important posttranscriptional regulatory functions. Recent data suggest that miRNAs are aberrantly expressed in many human cancers and that they may play significant roles in carcinogenesis. Here, we used microarrays to profile the expression of 315 human miRNAs in 10 normal mucosa samples and 49 stage II colon cancers differing with regard to microsatellite status and recurrence of disease. Several miRNAs were differentially expressed between normal tissue and tumor microsatellite subtypes, with miR-145 showing the lowest expression in cancer relative to normal tissue. Microsatellite status for the majority of cancers could be correctly predicted based on miRNA expression profiles. Furthermore, a biomarker based on miRNA expression profiles could predict recurrence of disease with an overall performance accuracy of 81%, indicating a potential role of miRNAs in determining tumor aggressiveness. The expression levels of miR-320 and miR-498, both included in the predictive biomarker, correlated with the probability of recurrence-free survival by multivariate analysis. We successfully verified the expression of selected miRNAs using real-time reverse transcription-PCR assays for mature miRNAs, whereas in situ hybridization was used to detect the accumulation of miR-145 and miR-320 in normal epithelial cells and adenocarcinoma cells. Functional studies showed that miR-145 potently suppressed growth of three different colon carcinoma cell lines. In conclusion, our results suggest that perturbed expression of numerous miRNAs in colon cancer may have a functional effect on tumor cell behavior, and, furthermore, that some miRNAs with prognostic potential could be of clinical importance.

The presence of carcinoma in situ (CIS) lesions in the urinary bladder is associated with a high risk of disease progression to a muscle invasive stage. In this study, we used microarray expression profiling to examine the gene expression patterns in superficial transitional cell carcinoma (sTCC) with surrounding CIS (13 patients), without surrounding CIS lesions (15 patients), and in muscle invasive carcinomas (mTCC; 13 patients). Hierarchical cluster analysis separated the sTCC samples according to the presence or absence of CIS in the surrounding urothelium. We identified a few gene clusters that contained genes with similar expression levels in transitional cell carcinoma (TCC) with surrounding CIS and invasive TCC. However, no close relationship between TCC with adjacent CIS and invasive TCC was observed using hierarchical cluster analysis. Expression profiling of a series of biopsies from normal urothelium and urothelium with CIS lesions from the same urinary bladder revealed that the gene expression found in sTCC with surrounding CIS is found also in CIS biopsies as well as in histologically normal samples adjacent to the CIS lesions. Furthermore, we also identified similar gene expression changes in mTCC samples. We used a supervised learning approach to build a 16-gene molecular CIS classifier. The classifier was able to classify sTCC samples according to the presence or absence of surrounding CIS with a high accuracy. This study demonstrates that a CIS gene expression signature is present not only in CIS biopsies but also in sTCC, mTCC, and, remarkably, in histologically normal urothelium from bladders with CIS. Identification of this expression signature could provide guidance for the selection of therapy and follow-up regimen in patients with early stage bladder cancer.

PURPOSE: Colorectal cancer prognosis is currently predicted from pathologic staging, providing limited discrimination for Dukes stage B and C disease. Additional markers for outcome are required to help guide therapy selection for individual patients. EXPERIMENTAL DESIGN: A multisite single-platform microarray study was done on 553 colorectal cancers. Gene expression changes were identified between stage A and D tumors (three training sets) and assessed as a prognosis signature in stage B and C tumors (independent test and external validation sets). RESULTS: One hundred twenty-eight genes showed reproducible expression changes between three sets of stage A and D cancers. Using consistent genes, stage B and C cancers clustered into two groups resembling early-stage and metastatic tumors. A Prediction Analysis of Microarray algorithm was developed to classify individual intermediate-stage cancers into stage A-like/good prognosis or stage D-like/poor prognosis types. For stage B patients, the treatment adjusted hazard ratio for 6-year recurrence in individuals with stage D-like cancers was 10.3 (95% confidence interval, 1.3-80.0; P = 0.011). For stage C patients, the adjusted hazard ratio was 2.9 (95% confidence interval, 1.1-7.6; P = 0.016). Similar results were obtained for an external set of stage B and C patients. The prognosis signature was enriched for downregulated immune response genes and upregulated cell signaling and extracellular matrix genes. Accordingly, sparse tumor infiltration with mononuclear chronic inflammatory cells was associated with poor outcome in independent patients. CONCLUSIONS: Metastasis-associated gene expression changes can be used to refine traditional outcome prediction, providing a rational approach for tailoring treatments to subsets of patients. (Clin Cancer Res 2009;15(24):7642-51).

Formalin-fixed, paraffin-embedded (FFPE) tissues are an invaluable resource for clinical research. However, nucleic acids extracted from FFPE tissues are fragmented and chemically modified making them challenging to use in molecular studies. We analysed 23 fresh-frozen (FF), 35 FFPE and 38 paired FF/FFPE specimens, representing six different human tissue types (bladder, prostate and colon carcinoma; liver and colon normal tissue; reactive tonsil) in order to examine the potential use of FFPE samples in next-generation sequencing (NGS) based retrospective and prospective clinical studies. Two methods for DNA and three methods for RNA extraction from FFPE tissues were compared and were found to affect nucleic acid quantity and quality. DNA and RNA from selected FFPE and paired FF/FFPE specimens were used for exome and transcriptome analysis. Preparations of DNA Exome-Seq libraries was more challenging (29.5% success) than that of RNA-Seq libraries, presumably because of modifications to FFPE tissue-derived DNA. Libraries could still be prepared from RNA isolated from two-decade old FFPE tissues. Data were analysed using the CLC Bio Genomics Workbench and revealed systematic differences between FF and FFPE tissue-derived nucleic acid libraries. In spite of this, pairwise analysis of DNA Exome-Seq data showed concordance for 70-80% of variants in FF and FFPE samples stored for fewer than three years. RNA-Seq data showed high correlation of expression profiles in FF/FFPE pairs (Pearson Correlations of 0.90 +/- 0.05), irrespective of storage time (up to 244 months) and tissue type. A common set of 1,494 genes was identified with expression profiles that were significantly different between paired FF and FFPE samples irrespective of tissue type. Our results are promising and suggest that NGS can be used to study FFPE specimens in both prospective and retrospective archive-based studies in which FF specimens are not available.