New insights into the role of intra-tumor genetic heterogeneity in carcinogenesis: identification of complex single gene variance within tumors

Aim:Present cancer hypotheses are almost all based on the concept that accumulation of specific driver gene mutations cause carcinogenesis.The discovery of intra-tumor genetic heterogeneity(ITGH),has resulted in this hypothesis being modified by assuming that most of these ITGH mutations are in passenger genes.In addition,accumulating ITGH data on driver gene mutations have revealed considerable genotype/phenotype disconnects.This study proposes to investigate this disconnect by examining the nature and degree of ITGH in breast tumors.Methods:ITGH was examined in tumors using next generation sequencing of up to 68,000 reads and analysis tools that allowed for identification of distinct minority variants within single genes,i.e.,complex single gene variance(CSGV).Results:CSGV was identified in the androgen receptor genes in all breast tumors examined.Conclusion:Evidence of CSGV suggests that a selection-as opposed to a mutation-centric hypothesis could better explain carcinogenesis.Our hypothesis proposes that tumors develop by the selection of preexisting de novo mutations rather than just the accumulation of de novo mutations.Thus,the role of selection pressures,such as changes in tissue microenvironments will likely be critical to our understanding of tumor resistance as well as the development of more effective treatment protocols.

Molecular structure of imidazolate bridged binuclear zinc complex and its single crystal ESR spectra doped with bridged Cu—Zn complex

The X-ray crystal structure of [(dtma)ZnImZn(dtma)]ClO_4·2.5H_2O (Hdtma=4-Diethyl- enetriamineacetic acid) was determined.The crystal is of orthorhombic,space group Pbcn with a- 14.104(5),b=14.897(5),c=25.384(9),and Z=8.The least-square refinement of the structure leads to conventional R factor of 0.066.The magnetic properties of [(dtma)CulmZn(dtma)]CIO_4·2.5H_2O were investigated.From the single crystal ESR spectra of Zn—Im—Zn dimer doped with Cu—Im—Zn complex,the anisotropic g and A tensors and electronic spin-density of the Cu—Zn complex are obtained and the bonding nature of Cu is discussed.

Synthesis,crystal structures and complexing ability of difunctionalized copillar[5]arene Schiff bases

An efficient method for the synthesis of some difunctionalized copillar[5]arene Schiff bases from condensation of salicylaldehyde and its 5-chloro,5-bromo,3,5-di（t-butyl） substituted derivatives with corresponding diamino-functionalized copillar[5]arene,which were prepared by Gabriel reaction according to the reported method.Single-crystals of six copillar[5]arenes were determined by X-ray diffraction.An ORTEP of compounds showed that the two chains units of Schiff base exist in the outside of the cavity of pillar[5]arene.Furthermore,the complexing ability of these Schiff bases to transition metal ions were investigated by UV and fluorescence spectroscopy.

Genome-Wide Interaction-Based Association of Human Diseases—A Survey

Genome-Wide Association Studies（GWASs） aim to identify genetic variants that are associated with disease by assaying and analyzing hundreds of thousands of Single Nucleotide Polymorphisms（SNPs）. Although traditional single-locus statistical approaches have been standardized and led to many interesting findings, a substantial number of recent GWASs indicate that for most disorders, the individual SNPs explain only a small fraction of the genetic causes. Consequently, exploring multi-SNPs interactions in the hope of discovering more significant associations has attracted more attentions. Due to the huge search space for complicated multilocus interactions, many fast and effective methods have recently been proposed for detecting disease-associated epistatic interactions using GWAS data. In this paper, we provide a critical review and comparison of eight popular methods, i.e., BOOST, TEAM, epi Forest, EDCF, SNPHarvester, epi MODE, MECPM, and MIC, which are used for detecting gene-gene interactions among genetic loci. In views of the assumption model on the data and searching strategies, we divide the methods into seven categories. Moreover, the evaluation methodologies,including detecting powers, disease models for simulation, resources of real GWAS data, and the control of false discover rate, are elaborated as references for new approach developers. At the end of the paper, we summarize the methods and discuss the future directions in genome-wide association studies for detecting epistatic interactions.