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Small noncoding microRNAs (miRNA) regulate the expression of target mRNAs by repressing their translation or orchestrating their sequence-specific degradation. In this study, we investigated miRNA and miRNA target gene expression patterns in melanoma to identify candidate biomarkers for early and progressive disease. Because data presently available on miRNA expression in melanoma are inconsistent thus far, we applied several different miRNA detection and profiling techniques on a panel of 10 cell lines and 20 patient samples representing nevi and primary or metastatic melanoma. Expression of selected miRNAs was inconsistent when comparing cell line–derived and patient-derived data. Moreover, as expected, some discrepancies were also detected when miRNA microarray data were correlated with qPCR-measured expression levels. Nevertheless, we identified miRNA-200c to be consistently downregulated in melanocytes, melanoma cell lines, and patient samples, whereas miRNA-205 and miRNA-23b were markedly reduced only in patient samples. In contrast, miR-146a and miR-155 were upregulated in all analyzed patients but none of the cell lines. Whole-genome microarrays were performed for analysis of selected melanoma cell lines to identify potential transcriptionally regulated miRNA target genes. Using Ingenuity pathway analysis, we identified a deregulated gene network centered around microphthalmia-associated transcription factor, a transcription factor known to play a key role in melanoma development. Our findings define miRNAs and miRNA target genes that offer candidate biomarkers in human melanoma. Cancer Res; 70(10); 4163–73. ©2010 AACR.

Although lung cancer is one of the major causes of cancer death in men and women worldwide, the molecular pathogenesis of this disease remains elusive. The contribution of alternative splicing (AS) to cancer pathogenesis and progression is emerging as an area of considerable interest. Cancer-specific splice variants seem to play a key role in disease mechanism and etiology. In this study, we analyzed 20 matched pairs of tumor specimens of Adenocarcinomas (AC), Squamous Cell Carcinomas (SCC) and adjacent normal tissue using Affymetrix GeneChip Exon microarrays. With this technology, it is possible to profile simultaneously gene expression and alternative splicing patterns for the entire genome using a single array. At the exon level, multiple probes for each exon enable the discrimination among different isoforms of a gene. Total RNA from tumors or normal tissue samples were amplified using the Ambion whole transcript expression kit and were hybridized onto GeneChip Human Exon 1.0 ST Array®. Data generated were normalized using RMA and were subjected to several layers of filtering (DABG filter, Multiple mRNAs filter). The delta splice index (ΔSI) was calculated, and alternative splicing events were detected using MIDAS and Rank Product method. Probesets were ranked based on their SI p-values. By comparing tumor samples to the corresponding normal subgroups, we generated a list of 1689 splice variant candidates for SCC and 1010 for AC showing significant differential expression between normal and tumor tissues. Top candidates in each tumor subtype were selected based on their ΔSI for manual inspection and further bioinformatics analysis. Study of alternatively spliced candidates revealed that approximately 30 % of the genes were detected in both types of cancer. Gene function analysis combining text mining and knowledge-based approaches indicated that the largest subset (70 %) of these genes was related to cancer. Within this group, 30% of genes were related to lung cancers. Interestingly the major part (85%) of variant candidates was not previously associated with AS events in cancer. We focused our attention on this latter group and, through validation by RT/PCR, confirmed the existence of new specific alternative splicing events occurring in each cancer type. In addition, we identified biological pathways and gene networks that are specifically altered in AC or SCC. The cancer-specific AS variants and pathways identified in our study are promising biomarkers and targets for diagnostic or therapeutic purposes. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3905. doi:10.1158/1538-7445.AM2011-3905