Annotation and functional characterization of long noncoding RNAs deregulated in pancreatic adenocarcinoma.

PURPOSE: Transcriptome analysis of pancreatic ductal adenocarcinoma (PDAC) has been useful to identify gene expression changes that sustain malignant phenotypes. Yet, most studies examined only tumor tissues and focused on protein-coding genes, leaving long non-coding RNAs (lncRNAs) largely underexplored. METHODS: We generated total RNA-Seq data from patient-matched tumor and nonmalignant pancreatic tissues and implemented a computational pipeline to survey known and novel lncRNAs. siRNA-mediated knockdown in tumor cell lines was performed to assess the contribution of PDAC-associated lncRNAs to malignant phenotypes. Gene co-expression network and functional enrichment analyses were used to assign deregulated lncRNAs to biological processes and molecular pathways. RESULTS: We detected 9,032 GENCODE lncRNAs as well as 523 unannotated lncRNAs, including transcripts significantly associated with patient outcome. Aberrant expression of a subset of novel and known lncRNAs was confirmed in patient samples and cell lines. siRNA-mediated knockdown of a subset of these lncRNAs (LINC01559, LINC01133, CCAT1, LINC00920 and UCA1) reduced cell proliferation, migration and invasion. Gene co-expression network analysis associated PDAC-deregulated lncRNAs with diverse biological processes, such as cell adhesion, protein glycosylation and DNA repair. Furthermore, UCA1 knockdown was shown to specifically deregulate co-expressed genes involved in DNA repair and to negatively impact DNA repair following damage induced by ionizing radiation. CONCLUSIONS: Our study expands the repertoire of lncRNAs deregulated in PDAC, thereby revealing novel candidate biomarkers for patient risk stratification. It also provides a roadmap for functional assays aimed to characterize novel mechanisms of action of lncRNAs in pancreatic cancer, which could be explored for therapeutic development.

Transcriptional signatures underlying dynamic phenotypic switching and novel disease biomarkers in a linear cellular model of melanoma progression.

Despite advances in therapeutics, the progression of melanoma to metastasis still confers a poor outcome to patients. Nevertheless, there is a scarcity of biological models to understand cellular and molecular changes taking place along disease progression. Here, we characterized the transcriptome profiles of a multi-stage murine model of melanoma progression comprising a nontumorigenic melanocyte lineage (melan-a), premalignant melanocytes (4C), nonmetastatic (4C11-) and metastasis-prone (4C11+) melanoma cells. Clustering analyses have grouped the 4 cell lines according to their differentiated (melan-a and 4C11+) or undifferentiated/"mesenchymal-like" (4C and 4C11-) morphologies, suggesting dynamic gene expression patterns associated with the transition between these phenotypes. The cell plasticity observed in the murine melanoma progression model was corroborated by molecular markers described during stepwise human melanoma differentiation, as the differentiated cell lines in our model exhibit upregulation of transitory and melanocytic markers, whereas "mesenchymal-like" cells show increased expression of undifferentiated and neural crest-like markers. Sets of differentially expressed genes (DEGs) were detected at each transition step of tumor progression, and transcriptional signatures related to malignancy, metastasis and epithelial-to-mesenchymal transition were identified. Finally, DEGs were mapped to their human orthologs and evaluated in uni- and multivariate survival analyses using gene expression and clinical data of 703 drug-naïve primary melanoma patients, revealing several independent candidate prognostic markers. Altogether, these results provide novel insights into the molecular mechanisms underlying the phenotypic switch taking place during melanoma progression, reveal potential drug targets and prognostic biomarkers, and corroborate the translational relevance of this unique sequential model of melanoma progression.