Use of H19 Gene Regulatory Sequences in DNA-Based Therapy for Pancreatic Cancer

Pancreatic cancer is the eighth most common cause of death from cancer in the world, for which palliative treatments are not effective and frequently accompanied by severe side effects. We propose a DNA-based therapy for pancreatic cancer using a nonviral vector, expressing the diphtheria toxin A chain under the control of the H19 gene regulatory sequences. The H19 gene is an oncofetal RNA expressed during embryo development and in several types of cancer. We tested the expression of H19 gene in patients, and found that 65% of human pancreatic tumors analyzed showed moderated to strong expression of the gene. In vitro experiments showed that the vector was effective in reducing Luciferase protein activity on pancreatic carcinoma cell lines. In vivo experiment results revealed tumor growth arrest in different animal models for pancreatic cancer. Differences in tumor size between control and treated groups reached a 75% in the heterotopic model (P = .037) and 50% in the orthotopic model (P = .007). In addition, no visible metastases were found in the treated group of the orthotopic model. These results indicate that the treatment with the vector DTA-H19 might be a viable new therapeutic option for patients with unresectable pancreatic cancer

Integrating software architectures for distributed simulations and simulation analysis communities.

The one-year Software Architecture LDRD (No.79819) was a cross-site effort between Sandia California and Sandia New Mexico. The purpose of this research was to further develop and demonstrate integrating software architecture frameworks for distributed simulation and distributed collaboration in the homeland security domain. The integrated frameworks were initially developed through the Weapons of Mass Destruction Decision Analysis Center (WMD-DAC), sited at SNL/CA, and the National Infrastructure Simulation & Analysis Center (NISAC), sited at SNL/NM. The primary deliverable was a demonstration of both a federation of distributed simulations and a federation of distributed collaborative simulation analysis communities in the context of the same integrated scenario, which was the release of smallpox in San Diego, California. To our knowledge this was the first time such a combination of federations under a single scenario has ever been demonstrated. A secondary deliverable was the creation of the standalone GroupMeld{trademark} collaboration client, which uses the GroupMeld{trademark} synchronous collaboration framework. In addition, a small pilot experiment that used both integrating frameworks allowed a greater range of crisis management options to be performed and evaluated than would have been possible without the use of the frameworks

Myelin-associated glycoprotein gene mutation causes Pelizaeus-Merzbacher disease-like disorder

Pelizaeus-Merzbacher disease is an X-linked hypomyelinating leukodystrophy. Lossos et al. describe a family with an early-onset Pelizaeus-Merzbacher disease-like phenotype that slowly evolves into complicated hereditary spastic paraplegia, affecting both the CNS and PNS. Exome sequencing reveals a causative homozygous missense mutation in MAG, which encodes myelin associated glycoprotei

The non-coding transcriptome as a dynamic regulator of cancer metastasis.

Since the discovery of microRNAs, non-coding RNAs (NC-RNAs) have increasingly attracted the attention of cancer investigators. Two classes of NC-RNAs are emerging as putative metastasis-related genes: long non-coding RNAs (lncRNAs) and small nucleolar RNAs (snoRNAs). LncRNAs orchestrate metastatic progression through several mechanisms, including the interaction with epigenetic effectors, splicing control and generation of microRNA-like molecules. In contrast, snoRNAs have been long considered "housekeeping" genes with no relevant function in cancer. However, recent evidence challenges this assumption, indicating that some snoRNAs are deregulated in cancer cells and may play a specific role in metastasis. Interestingly, snoRNAs and lncRNAs share several mechanisms of action, and might synergize with protein-coding genes to generate a specific cellular phenotype. This evidence suggests that the current paradigm of metastatic progression is incomplete. We propose that NC-RNAs are organized in complex interactive networks which orchestrate cellular phenotypic plasticity. Since plasticity is critical for cancer cell metastasis, we suggest that a molecular interactome composed by both NC-RNAs and proteins orchestrates cancer metastasis. Interestingly, expression of lncRNAs and snoRNAs can be detected in biological fluids, making them potentially useful biomarkers. NC-RNA expression profiles in human neoplasms have been associated with patients' prognosis. SnoRNA and lncRNA silencing in pre-clinical models leads to cancer cell death and/or metastasis prevention, suggesting they can be investigated as novel therapeutic targets. Based on the literature to date, we critically discuss how the NC-RNA interactome can be explored and manipulated to generate more effective diagnostic, prognostic, and therapeutic strategies for metastatic neoplasms