Yidong Chen

BACKGROUND: Hepatocellular carcinoma is a common and aggressive cancer that occurs mainly in men. We examined microRNA expression patterns, survival, and response to interferon alfa in both men and women with the disease. METHODS: We analyzed three independent cohorts that included a total of 455 patients with hepatocellular carcinoma who had undergone radical tumor resection between 1999 and 2003. MicroRNA-expression profiling was performed in a cohort of 241 patients with hepatocellular carcinoma to identify tumor-related microRNAs and determine their association with survival in men and women. In addition, to validate our findings, we used quantitative reverse-transcriptase-polymerase-chain-reaction assays to measure microRNAs and assess their association with survival and response to therapy with interferon alfa in 214 patients from two independent, prospective, randomized, controlled trials of adjuvant interferon therapy. RESULTS: In patients with hepatocellular carcinoma, the expression of miR-26a and miR-26b in nontumor liver tissue was higher in women than in men. Tumors had reduced levels of miR-26 expression, as compared with paired noncancerous tissues, which indicated that the level of miR-26 expression was also associated with hepatocellular carcinoma. Moreover, tumors with reduced miR-26 expression had a distinct transcriptomic pattern, and analyses of gene networks revealed that activation of signaling pathways between nuclear factor kappaB and interleukin-6 might play a role in tumor development. Patients whose tumors had low miR-26 expression had shorter overall survival but a better response to interferon therapy than did patients whose tumors had high expression of the microRNA. CONCLUSIONS: The expression patterns of microRNAs in liver tissue differ between men and women with hepatocellular carcinoma. The miR-26 expression status of such patients is associated with survival and response to adjuvant therapy with interferon alfa.

Accelerating cures for children with cancer remains an immediate challenge as a result of extensive oncogenic heterogeneity between and within histologies, distinct molecular mechanisms evolving between diagnosis and relapsed disease, and limited therapeutic options. To systematically prioritize and rationally test novel agents in preclinical murine models, researchers within the Pediatric Preclinical Testing Consortium are continuously developing patient-derived xenografts (PDXs)-many of which are refractory to current standard-of-care treatments-from high-risk childhood cancers. Here, we genomically characterize 261 PDX models from 37 unique pediatric cancers; demonstrate faithful recapitulation of histologies and subtypes; and refine our understanding of relapsed disease. In addition, we use expression signatures to classify tumors for TP53 and NF1 pathway inactivation. We anticipate that these data will serve as a resource for pediatric oncology drug development and will guide rational clinical trial design for children with cancer.

BACKGROUND: MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA levels. Computational prediction of miRNA targets is essential for elucidating the detailed functions of miRNA. However, the prediction specificity and sensitivity of the existing algorithms are still poor to generate meaningful, workable hypotheses for subsequent experimental testing. Constructing a richer and more reliable training data set and developing an algorithm that properly exploits this data set would be the key to improve the performance current prediction algorithms. RESULTS: A comprehensive training data set is constructed for mammalian miRNAs with its positive targets obtained from the most up-to-date miRNA target depository called miRecords and its negative targets derived from 20 microarray data. A new algorithm SVMicrO is developed, which assumes a 2-stage structure including a site support vector machine (SVM) followed by a UTR-SVM. SVMicrO makes prediction based on 21 optimal site features and 18 optimal UTR features, selected by training from a comprehensive collection of 113 site and 30 UTR features. Comprehensive evaluation of SVMicrO performance has been carried out on the training data, proteomics data, and immunoprecipitation (IP) pull-down data. Comparisons with some popular algorithms demonstrate consistent improvements in prediction specificity, sensitivity and precision in all tested cases. All the related materials including source code and genome-wide prediction of human targets are available at http://compgenomics.utsa.edu/svmicro.html. CONCLUSIONS: A 2-stage SVM based new miRNA target prediction algorithm called SVMicrO is developed. SVMicrO is shown to be able to achieve robust performance. It holds the promise to achieve continuing improvement whenever better training data that contain additional verified or high confidence positive targets and properly selected negative targets are available.

microRNA-449a (miR-449a) has been identified to function as a tumor suppressor in several types of cancers. However, the role of miR-449a in neuroblastoma has not been intensively investigated. We recently found that the overexpression of miR-449a significantly induces neuroblastoma cell differentiation, suggesting its potential tumor suppressor function in neuroblastoma. In this study, we further investigated the mechanisms underlying the tumor suppressive function of miR-449a in neuroblastoma. We observed that miR-449a inhibits neuroblastoma cell survival and growth through 2 mechanisms--inducing cell differentiation and cell cycle arrest. Our comprehensive investigations on the dissection of the target genes of miR-449a revealed that 3 novel targets- MFAP4, PKP4 and TSEN15 -play important roles in mediating its differentiation-inducing function. In addition, we further found that its function in inducing cell cycle arrest involves down-regulating its direct targets CDK6 and LEF1. To determine the clinical significance of the miR-449a-mediated tumor suppressive mechanism, we examined the correlation between the expression of these 5 target genes in neuroblastoma tumor specimens and the survival of neuroblastoma patients. Remarkably, we noted that high tumor expression levels of all the 3 miR-449a target genes involved in regulating cell differentiation, but not the target genes involved in regulating cell cycle, are significantly correlated with poor survival of neuroblastoma patients. These results suggest the critical role of the differentiation-inducing function of miR-449a in determining neuroblastoma progression. Overall, our study provides the first comprehensive characterization of the tumor-suppressive function of miR-449a in neuroblastoma, and reveals the potential clinical significance of the miR-449a-mediated tumor suppressive pathway in neuroblastoma prognosis.