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The possible impact of hydrophobic lectin nanoparticles on the prognosis and progression of Alzheimer's disease (AD) and cancers was investigated by Visual Molecular Dynamics (VMD) computer modeling programs available from the Beckmann Advanced Research Institute at the University of Illinois at Urbana. Our results indicate the possibility of impeding pathological aggregation of certain proteins such as modified tau-or beta-amyloid that are currently being considered as possible causes of Alzheimer's disease. VMD programs serve as useful tools for investigation hydrophobic protein aggregation that may play a role in aging of human populations.
The possible impact of hydrophobic lectin nanoparticles on the prognosis and progression of Alzheimer's disease (AD) and cancers was investigated by Visual Molecular Dynamics (VMD) computer modeling programs available from the Beckmann Advanced Research Institute at the University of Illinois at Urbana. Our results indicate the possibility of impeding pathological aggregation of certain proteins such as modified tau-or beta-amyloid that are currently being considered as possible causes of Alzheimer's disease. VMD programs serve as useful tools for investigation hydrophobic protein aggregation that may play a role in aging of human populations.
A critical overview of recent clinical trials in cancer is presently focused on signaling pathway blockers or inhibitors with a view to developing successful clinical trials employing personalized cancer therapies. Rational, pharmacogenomic strategies in cancer trials should be adopted that include specific molecular targeting based on adequate data for, and detailed modeling of, cancer cell genomes, modifications of cancer signaling pathways and epigenetic mechanisms. Novel translational oncogenomics research is rapidly expanding through the application of highly sensitive and specific advanced technology, research findings and computational tools and complex models to both pharmaceutical and clinical problems. Multiple sample analyses from several recent clinical studies have shown that gene expression data for cancer cells can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies or, in general, 'personalized medicine' that will have to be validated through optimally designed clinical trials in cancer. A Human Cancer Genomes and Epigenetics Project is proposed that can provide the essential data required for the optimal design of clinical trials with the goal of achieving significant improvements of the survival rates of cancer patients participating in clinical trials for advanced cancer stages. The results of such a six-year Human Cancer Genomes and Epigenetics Project should also greatly aid with the accelerated, rational development of effective anti-cancer medicines and the chemoprevention of cancers. Jo u r n a l o f Clini c a l T r ia ls
To optimize the survival of patients in cancer clinical trials requires that rational, pharmacogenomic strategies in cancer clinical trials be adopted which include specific molecular targeting cancer cells that are resistant to existing cancer therapies. Such novel strategies must be based on adequate cancer genomics data [1] and on a detailed understanding/modeling of cancer cell genomes, the modifications of cancer signaling pathways and the epigenetic mechanisms involved in cancer. It can be said in general that "all cancers arise as a result of changes that have occurred in the DNA sequence of the genomes of cancer cells" [1]. Cancer research and clinical trials are now moving into a completely new phase in which it has become feasible to obtain the complete DNA sequences for large numbers of cancer genomes that would provide essential information on how individual cancers have developed in specific patients. Novel translational oncogenomics research [2] is thus rapidly expanding through the application of highly sensitive and specific advanced technology, novel research findings, computational tools and complex models utilized to solve to both pharmaceutical and clinical problems. Multiple sample analyses from several recent clinical studies have shown that gene expression data for cancer cells can be employed to distinguish between tumor types as well as to predict outcomes. Potentially important applications of such results are individualized human cancer therapies [2][3][4] or, in general, 'personalized medicine' that will have to be validated through optimally designed clinical trials in cancer [4]. Such treatments based on personalized medicines form the subject of the new field of Pharmacogenomics.Carcinogenesis is a very complex process that involves dynamically inter-connected biomolecules in the intercellular, membrane, cytosolic, nuclear and nucleolar compartments that form numerous interrelated pathways referred to as networks [2][3][4][5][6]. One such family of signaling pathways contains the cell cyclins. Cyclins are often over-expressed in cancerous cells [6]. This provides a basis for the development of novel rational chemotherapies and chemoprevention of cancers. Cyclins are proteins that link several critical pro-apoptotic and other cell cycling/division components, including the tumor suppressor gene TP53 and its product, the Thomsen-Friedenreich antigen (T-F antigen), Rb, mdm2, cMyc, p21, p27, Bax,, which all play major roles in carcinogenesis of many cancers. Cyclindependent kinases (CDK), their respective cyclins, and inhibitors of CDKs (CKIs) were identified as instrumental components of the cell cycle-regulating machinery. CDKs are enzymes that phosphorylate several cellular proteins thus 'fueling' the sequential transitions through the cell division cycle. The
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