Molecular evolution of primate immunodeficiency viruses and hepatitis delta virus

Primate immunodeficiency viruses, or lentiviruses (HIV-1, HIV-2, and SIV), and hepatitis delta virus (HDV) are RNA viruses characterized by rapid evolution. Infection by primate immunodeficiency viruses usually results in the development of acquired immunodeficiency syndrome (AIDS) in humans and AIDS-like illnesses in Asian macaques. Similarly, hepatitis delta virus infection causes hepatitis and liver cancer in humans. These viruses are heterogeneous within an infected patient and among individuals. Substitution rates in the virus genomes are high and vary in different lineages and among sites. Methods of phylogenetic analysis were applied to study the evolution of primate lentiviruses and the hepatitis delta virus. The following results have been obtained: (1) The substitution rate varies among sites of primate lentivirus genes according to the two parameter gamma distribution, with the shape parameter $\alpha$ being close to 1. (2) Primate immunodeficiency viruses fall into species-specific lineages. Therefore, viral transmissions across primate species are not as frequent as suggested by previous authors. (3) Primate lentiviruses have acquired or lost their pathogenicity several times in the course of evolution. (4) Evidence was provided for multiple infections of a North American patient by distinct HIV-1 strains of the B subtype. (5) Computer simulations indicate that the probability of committing an error in testing HIV transmission depends on the number of virus sequences and their length, the divergence times among sequences, and the model of nucleotide substitution. (6) For future investigations of HIV-1 transmissions, using longer virus sequences and avoiding the use of distant outgroups is recommended. (7) Hepatitis delta virus strains are usually related according to the geographic region of isolation. (8) Evolution of HDV is characterized by the rate of synonymous substitution being lower than the nonsynonymous substitution rate and the rate of evolution of the noncoding region. (9) There is a strong preference for G and C nucleotides at the third codon positions of the HDV coding region. ^

Intrinsic oxidative stress in cancer cells: A biochemical basis for therapeutic selectivity using ROS -generating agents

A major goal of chemotherapy is to selectively kill cancer cells while minimizing toxicity to normal cells. Identifying biological differences between cancer and normal cells is essential in designing new strategies to improve therapeutic selectivity. Superoxide dismutases (SOD) are crucial antioxidant enzymes required for the elimination of superoxide (O2·− ), a free radical produced during normal cellular metabolism. Previous studies in our laboratory demonstrated that 2-methoxyestradiol (2-ME), an estradiol derivative, inhibits the function of SOD and selectively kills human leukemia cells without exhibiting significant cytotoxicity in normal lymphocytes. The present work was initiated to examine the biochemical basis for the selective anticancer activity of 2-ME. Investigations using two-parameter flow cytometric analyses and ROS scavengers established that O2·− is a primary and essential mediator of 2-ME-induced apoptosis in cancer cells. In addition, experiments using SOD overexpression vectors and SOD knockout cells found that SOD is a critical target of 2-ME. Importantly, the administration of 2-ME resulted in the selective accumulation of O 2·− and apoptosis in leukemia and ovarian cancer cells. The preferential activity of 2-ME was found to be due to increased intrinsic oxidative stress in these cancer cells versus their normal counterparts. This intrinsic oxidative stress was associated with the upregulation of the antioxidant enzymes SOD and catalase as a mechanism to cope with the increase in ROS. Furthermore, oxygen consumption experiments revealed that normal lymphocytes decrease their respiration rate in response to 2-ME-induced oxidative stress, while human leukemia cells seem to lack this regulatory mechanism. This leads to an uncontrolled production of O2·−, severe accumulation of ROS, and ultimately ROS-mediated apoptosis in leukemia cells treated with 2-ME. The biochemical differences between cancer and normal cells identified here provide a basis for the development of drug combination strategies using 2-ME with other ROS-generating agents to enhance anticancer activity. The effectiveness of such a combination strategy in killing cancer cells was demonstrated by the use of 2-ME with agents/modalities such as ionizing radiation and doxorubicin. Collectively, the data presented here strongly suggests that 2-ME may have important clinical implications for the selective killing of cancer cells. ^

Evaluation of the accuracy of multilevel analysis parameter estimates for intra-cluster correlation in correlated binary data

Many studies in biostatistics deal with binary data. Some of these studies involve correlated observations, which can complicate the analysis of the resulting data. Studies of this kind typically arise when a high degree of commonality exists between test subjects. If there exists a natural hierarchy in the data, multilevel analysis is an appropriate tool for the analysis. Two examples are the measurements on identical twins, or the study of symmetrical organs or appendages such as in the case of ophthalmic studies. Although this type of matching appears ideal for the purposes of comparison, analysis of the resulting data while ignoring the effect of intra-cluster correlation has been shown to produce biased results.^ This paper will explore the use of multilevel modeling of simulated binary data with predetermined levels of correlation. Data will be generated using the Beta-Binomial method with varying degrees of correlation between the lower level observations. The data will be analyzed using the multilevel software package MlwiN (Woodhouse, et al, 1995). Comparisons between the specified intra-cluster correlation of these data and the estimated correlations, using multilevel analysis, will be used to examine the accuracy of this technique in analyzing this type of data. ^

A SIMULATION STUDY OF THE SIZE AND POWER OF SOME TWO-SAMPLE TESTS FOR UNEQUALLY CENSORED SURVIVAL DATA (RANK TESTS, LOGRANK, PROPORTIONAL HAZARDS, WILCOXON TESTS, EXPONENTIAL DISTRIBUTION)

Sizes and power of selected two-sample tests of the equality of survival distributions are compared by simulation for small samples from unequally, randomly-censored exponential distributions. The tests investigated include parametric tests (F, Score, Likelihood, Asymptotic), logrank tests (Mantel, Peto-Peto), and Wilcoxon-Type tests (Gehan, Prentice). Equal sized samples, n = 18, 16, 32 with 1000 (size) and 500 (power) simulation trials, are compared for 16 combinations of the censoring proportions 0%, 20%, 40%, and 60%. For n = 8 and 16, the Asymptotic, Peto-Peto, and Wilcoxon tests perform at nominal 5% size expectations, but the F, Score and Mantel tests exceeded 5% size confidence limits for 1/3 of the censoring combinations. For n = 32, all tests showed proper size, with the Peto-Peto test most conservative in the presence of unequal censoring. Powers of all tests are compared for exponential hazard ratios of 1.4 and 2.0. There is little difference in power characteristics of the tests within the classes of tests considered. The Mantel test showed 90% to 95% power efficiency relative to parametric tests. Wilcoxon-type tests have the lowest relative power but are robust to differential censoring patterns. A modified Peto-Peto test shows power comparable to the Mantel test. For n = 32, a specific Weibull-exponential comparison of crossing survival curves suggests that the relative powers of logrank and Wilcoxon-type tests are dependent on the scale parameter of the Weibull distribution. Wilcoxon-type tests appear more powerful than logrank tests in the case of late-crossing and less powerful for early-crossing survival curves. Guidelines for the appropriate selection of two-sample tests are given. ^