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Objectives: Minichromosome maintenance (MCM) proteins play important roles in DNA replication by interacting with other factors which participate in the regulation of DNA synthesis. Abnormal over-expression of MCMs was observed in numerous malignancies, such as colorectal cancer. However, the expression of MCMs in pancreatic cancer (PC) was less investigated so far. This study was designed to analyze the expression and prognostic roles of MCM1-10 in PC based on the data provided by The Cancer Genome Atlas (TCGA)., Methods: Pearson χ2 test was applied to evaluate the association of MCMs expression with clinicopathologic indicators, and biomarkers for tumor biological behaviors. Kaplan-Meier plots and log-rank tests were used to assess survival analysis, and univariate and multivariate Cox proportional hazard regression models were used to recognize independent prognostic factors., Results: MCM1-10 were generally expressed in PC samples. The levels of some molecules were markedly correlated with that of biomarkers for S phase, proliferation, gemcitabine resistance. And part of these molecules over-expression was significantly associated with indicators of disease progression, such as depth of tumor invasion and lymph node metastasis. Furthermore, MCM2, 4, 6, 8, and 10 over-expression was remarkably associated with shorter disease free survival time, and MCM2, 4,8, and 10 over-expression was associated with shorter overall survival time. Further multivariate analysis suggested that MCM8 was an independent prognostic factor for PC., Conclusion: MCMs abnormal over-expression was significantly associated with PC progression and prognosis. These molecules could be regarded as prognostic and therapeutic biomarkers for PC. The roles of MCMs may be vitally important and the underlying mechanisms need to be furtherinvestigated., Competing Interests: The authors have declared that no competing interests exist.

Neuroblastoma is one of the most genomically heterogeneous childhood malignances studied to date, and the molecular events that occur during the course of the disease are not fully understood. Genomic studies in neuroblastoma have showed only a few recurrent mutations and a low somatic mutation burden. However, none of these studies has examined the mutations arising during the course of disease, nor have they systemically examined the expression of mutant genes. Here we performed genomic analyses on tumors taken during a 3.5 years disease course from a neuroblastoma patient (bone marrow biopsy at diagnosis, adrenal primary tumor taken at surgical resection, and a liver metastasis at autopsy). Whole genome sequencing of the index liver metastasis identified 44 non-synonymous somatic mutations in 42 genes (0.85 mutation/MB) and a large hemizygous deletion in the ATRX gene which has been recently reported in neuroblastoma. Of these 45 somatic alterations, 15 were also detected in the primary tumor and bone marrow biopsy, while the other 30 were unique to the index tumor, indicating accumulation of de novo mutations during therapy. Furthermore, transcriptome sequencing on the 3 tumors demonstrated only 3 out of the 15 commonly mutated genes (LPAR1, GATA2, and NUFIP1) had high level of expression of the mutant alleles, suggesting potential oncogenic driver roles of these mutated genes. Among them, the druggable G-protein coupled receptor LPAR1 was highly expressed in all tumors. Cells expressing the LPAR1 R163W mutant demonstrated a significantly increased motility through elevated Rho signaling, but had no effect on growth. Therefore, this study highlights the need for multiple biopsies and sequencing during progression of a cancer and combinatorial DNA and RNA sequencing approach for systematic identification of expressed driver mutations.

Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma. Despite advances in modern therapy, patients with relapsed or metastatic disease have a very poor clinical prognosis. Fibroblast Growth Factor Receptor 4 (FGFR4) is a cell surface tyrosine kinase receptor that is involved in normal myogenesis and muscle regeneration, but not commonly expressed in differentiated muscle tissues. Amplification and mutational activation of FGFR4 has been reported in RMS and promotes tumor progression. Therefore, FGFR4 is a tractable therapeutic target for patients with RMS. In this study, we used a chimeric Ba/F3 TEL-FGFR4 construct to test five tyrosine kinase inhibitors reported to specifically inhibit FGFRs in the nanomolar range. We found ponatinib (AP24534) to be the most potent FGFR4 inhibitor with an IC50 in the nanomolar range. Ponatinib inhibited the growth of RMS cells expressing wild-type or mutated FGFR4 through increased apoptosis. Phosphorylation of wild-type and mutated FGFR4 as well as its downstream target STAT3 was also suppressed by ponatinib. Finally, ponatinib treatment inhibited tumor growth in a RMS mouse model expressing mutated FGFR4. Therefore, our data suggests that ponatinib is a potentially effective therapeutic agent for RMS tumors that are driven by a dysregulated FGFR4 signaling pathway.

Peptide nucleic acids (PNAs) have gained much interest as molecular recognition tools in biology, medicine and chemistry. This is due to high hybridization efficiency to complimentary oligonucleotides and stability of the duplexes with RNA or DNA. We have synthesized 15/16-mer PNA probes to detect the HER2 mRNA. The performance of these probes to detect the HER2 target was evaluated by fluorescence imaging and fluorescence bead assays. The PNA probes have sufficiently discriminated between the wild type HER2 target and the mutant target with single base mismatches. Furthermore, the probes exhibited excellent linear concentration dependence between 0.4 to 400 fmol for the target gene. The results demonstrate potential application of PNAs as diagnostic probes with high specificity for quantitative measurements of amplifications or over-expressions of oncogenes.

Identification of somatic mutations in cancer is a major goal for understanding and monitoring the events related to cancer initiation and progression. High resolution melting (HRM) curve analysis represents a fast, post-PCR high-throughput method for scanning somatic sequence alterations in target genes. The aim of this study was to assess the sensitivity and specificity of HRM analysis for tumor mutation screening in a range of tumor samples, which included 216 frozen pediatric small rounded blue-cell tumors as well as 180 paraffin-embedded tumors from breast, endometrial and ovarian cancers (60 of each). HRM analysis was performed in exons of the following candidate genes known to harbor established commonly observed mutations: PIK3CA, ERBB2, KRAS, TP53, EGFR, BRAF, GATA3, and FGFR3. Bi-directional sequencing analysis was used to determine the accuracy of the HRM analysis. For the 39 mutations observed in frozen samples, the sensitivity and specificity of HRM analysis were 97% and 87%, respectively. There were 67 mutation/variants in the paraffin-embedded samples, and the sensitivity and specificity for the HRM analysis were 88% and 80%, respectively. Paraffin-embedded samples require higher quantity of purified DNA for high performance. In summary, HRM analysis is a promising moderate-throughput screening test for mutations among known candidate genomic regions. Although the overall accuracy appears to be better in frozen specimens, somatic alterations were detected in DNA extracted from paraffin-embedded samples.