Exon Array Analysis using re-defined probe sets results in reliable identification of alternatively spliced genes in non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>Treatment of non-small cell lung cancer with novel targeted therapies is a major unmet clinical need. Alternative splicing is a mechanism which generates diverse protein products and is of functional relevance in cancer.</p> <p>Results</p> <p>In this study, a genome-wide analysis of the alteration of splicing patterns between lung cancer and normal lung tissue was performed. We generated an exon array data set derived from matched pairs of lung cancer and normal lung tissue including both the adenocarcinoma and the squamous cell carcinoma subtypes. An enhanced workflow was developed to reliably detect differential splicing in an exon array data set. In total, 330 genes were found to be differentially spliced in non-small cell lung cancer compared to normal lung tissue. Microarray findings were validated with independent laboratory methods for <it>CLSTN1</it>, <it>FN1</it>, <it>KIAA1217</it>, <it>MYO18A</it>, <it>NCOR2</it>, <it>NUMB</it>, <it>SLK</it>, <it>SYNE2</it>, <it>TPM1</it>, (in total, 10 events) and <it>ADD3</it>, which was analysed in depth. We achieved a high validation rate of 69%. Evidence was found that the activity of FOX2, the splicing factor shown to cause cancer-specific splicing patterns in breast and ovarian cancer, is not altered at the transcript level in several cancer types including lung cancer.</p> <p>Conclusions</p> <p>This study demonstrates how alternatively spliced genes can reliably be identified in a cancer data set. Our findings underline that key processes of cancer progression in NSCLC are affected by alternative splicing, which can be exploited in the search for novel targeted therapies.</p

A genome-wide map of aberrantly expressed chromosomal islands in colorectal cancer

BACKGROUND: Cancer development is accompanied by genetic phenomena like deletion and amplification of chromosome parts or alterations of chromatin structure. It is expected that these mechanisms have a strong effect on regional gene expression. RESULTS: We investigated genome-wide gene expression in colorectal carcinoma (CRC) and normal epithelial tissues from 25 patients using oligonucleotide arrays. This allowed us to identify 81 distinct chromosomal islands with aberrant gene expression. Of these, 38 islands show a gain in expression and 43 a loss of expression. In total, 7.892 genes (25.3% of all human genes) are located in aberrantly expressed islands. Many chromosomal regions that are linked to hereditary colorectal cancer show deregulated expression. Also, many known tumor genes localize to chromosomal islands of misregulated expression in CRC. CONCLUSION: An extensive comparison with published CGH data suggests that chromosomal regions known for frequent deletions in colon cancer tend to show reduced expression. In contrast, regions that are often amplified in colorectal tumors exhibit heterogeneous expression patterns: even show a decrease of mRNA expression. Because for several islands of deregulated expression chromosomal aberrations have never been observed, we speculate that additional mechanisms (like abnormal states of regional chromatin) also have a substantial impact on the formation of co-expression islands in colorectal carcinoma

The relationship between differential gene expression and phenotypic changes in solid tumors like colorectal cancer

Das kolorektale Karzinom ist einer der häufigsten malignen Tumore weltweit mit einer weiterhin hohen Mortalitätsrate. Bei derzeit prognostisch nahezu ausgereizten chirurgischen Therapiestrategien stellen die Identifikation und Validierung a) neuer molekularer Angriffspunkte für die medikamentöse Tumortherapie (Targets), b) neuer Marker für die individuelle Vorhersage der Verträglichkeit und des Ansprechens der medikamentösen Tumortherapie und c) neuer individueller Prognosemarker, aktuelle Herausforderungen für die Tumorforschung dar. Ziel unserer Arbeiten war die Untersuchung des Zusammenhangs zwischen Veränderungen auf der Ebene der Genexpression und phänotypischen Merkmalen beim kolorektalen Karzinom durch die genomweite Microarray basierte Analyse der Transkription, dem sog. Gene Expression Profiling. In einem ersten Schritt konnten zahlreiche differentiell exprimierte Gene identifiziert werden, deren Validierung auf RNA- und Proteinebene eine Bewertung in Bezug auf funktionelle Einordnung in die Karzinogenese und eine Evaluierung in Bezug auf eine potentielle Rolle als Zielgen für die Tumortherapie ermöglichte. Wir konnten darüber hinaus einen Zusammenhang zwischen Tumorprogression und molekularen Veränderungen auf Genexpressionsebene darstellen und anhand einer 45-Gen-Signatur zeigen, dass sich hinter den phänotypischen Veränderungen und der Progression des kolorektalen Karzinoms von einem lokal begrenzten Tumorwachstum ohne Lymphknotenmetastasierung hin zu einer fortgeschrittenen Erkrankung uniforme Veränderungen auf Gen-expressionsebene abspielen. Interessant ist dieser Zusammenhang insbesondere vor dem Hintergrund der Heterogenität der Genexpression innerhalb der Tumoren, die wir im Rahmen der Analyse von Signalwegen belegen konnten. Durch unsere Ergebnisse im Bereich der prognostischen Signaturen konnten wir die Hypothese unterfüttern, dass die Transkripte des Primärtumors Informationen über die Prognose enthalten, die über die Genexpressionsanalyse gelesen werden können. Die große Liste der identifizierten Gene im Rahmen der Genexpressionsanalysen stellt eine Quelle für potenzielle Therapie-Targets dar, da die meisten der Gene in Schlüsselmechanismen der Tumorentstehung und Tumorprogression, von der Zellproliferation und Zelldifferenzierung bis hin zum Überleben der Zelle, involviert sind. Das systematische Verständnis der molekularen Basis einer jeden Tumorentität erfordert letztendlich drei Schritte. Eine umfassende Analyse charakteristischer genomischer Abberationen, die Interpretation der biologischen Rolle bei der Karzinogenese und die Evaluation der Einsetzbarkeit für die Entwicklung von Diagnostika, Prognoseparametern und Therapeutika. Daher ist eine umfassende Charakterisierung des Genoms und des Proteoms mithilfe neuer Technologien, wie GenChip Arrays, miRNA Arrays, Array-CGH und SNP Arrays notwendig, um neue Therapie-Targets zu identifizieren und die Möglichkeiten für die Behandlung des kolorektalen Karzinoms zu erweitern. Im Gegensatz zur Prognosevorhersage anhand der etablierten Tumor- Klassifikationen, die Gruppen über pathomorphologische Befunde und Fünfjahresüberlebensraten definiert, jedoch keine individuelle Prognoseabschätzung zulässt, sollte geprüft werden, ob anhand eines „molekularen Gesichts“ der Erkrankung eine individuelle Prognosevorhersage ergänzend oder unabhängig möglich wird. Inwieweit sich die Ergebnisse der Microarray-Technologie in Zukunft in die klinische Routine für Diagnostik, Prognostik und Therapie integrieren lassen, und somit einen Beitrag zur individualisierten Tumortherapie leisten, kann zum jetzigen Zeitpunkt nicht abschließend beurteilt werden und muss in weiteren Validierungsstudien analysiert werden.Colorectal cancer is among the most common malignant tumors worldwide with a continued high mortality rate. In view of the nearly exhausted surgical possibilities for prognostic improvement, tumor research faces the current challenge of identifying and validating a) new molecular targets for drug therapy, b) new markers for predicting individual drug tolerance and response, and c) new individual prognostic markers. The aim of our study was to examine the relationship between changes in gene expression patterns and phenotypic characteristics in colorectal cancer by genome-wide microarray-based transcriptional analysis (so-called gene expression profiling). The first step identified numerous differentially expressed genes whose validation at the RNA and protein level made it possible to assess their functional role in carcinogenesis and to evaluate them as potential targets for tumor therapy. In addition, we demonstrated a relationship between tumor progression and gene expression changes at the molecular level and, using a 45-gene signature, we showed that uniform gene expression changes underlie the phenotypic changes and the progression of colorectal cancer from localized tumor growth (without lymph node involvement) to advanced disease. This connection is particularly interesting in the context of intratumoral gene expression heterogeneity, which we were able to confirm by signaling pathway analysis. The results we obtained with prognostic signatures substantiated the hypothesis that transcripts in primary tumors contain prognostic information that can be “read” via gene expression profiling. The long list of genes identified by gene expression profiling is a source of potential treatment targets, since most of the genes are involved in key mechanisms of tumor development and progression, ranging from cell proliferation and differentiation to cell survival. A systematic understanding of the molecular basis of a given tumor entity ultimately requires three steps: a comprehensive analysis of characteristic genomic aberrations, an interpretation of the biological role in carcinogenesis, and an evaluation of applicability for the development of diagnostic agents, prognostic parameters and therapeutic agents. A comprehensive genomic and proteomic characterization should thus be achieved using new advanced technologies such as GeneChip arrays and miRNA arrays as well as Array-CGH and SNP arrays in order to identify new treatment targets and broaden the treatment options for colorectal cancer. Since established tumor staging systems stratify patients into prognostic groups according to pathomorphological factors and five-year survival rates but do not allow individual prognostic assessment, it seemed expedient to examine whether a “molecular face” of the disease can be used as a supplementary or independent tool to predict the prognosis of individual patients. It is still too early to draw final conclusions regarding the extent to which results in microarray technology can be integrated into the clinical routine for diagnostic, prognostic and therapeutic purposes and can thus contribute to individualized tumor therapy. Further validation studies are required