New aspects of estrogen action in the endometrium: Reciprocal interplay with retinoic acid pathway and a novel estrogen-regulated gene

The uterine endometrium is a major target for the estrogen. However, the molecular basis of estrogen action in the endometrium is largely unknown. I have used two approaches to study the effects of estrogen on the endometrium. One approach involved the study of the interaction between estrogen and retinoic acid (RA) pathways in the endometrium. I have demonstrated that estrogen administration to rodents and estrogen replacement therapy (ERT) in postmenopausal women selectively induced the endometrial expression of retinaldehyde dehydrogenase II (RALDH2), a critical enzyme of RA biosynthesis. RALDH2 was expressed exclusively in the stromal cells, especially in the stroma adjacent to the luminal and glandular epithelia. The induction of RALDH2 by estrogen required estrogen receptor and occurred via a direct increase in RALDH2 transcription. Among the three RA receptors, estrogen selectively induced the expression of RARα. In parallel, estrogen also increased the utilization of all-trans retinol (the substrate for RA biosynthesis) and the expression of two RA-regulated marker genes, cellular retinoic acid binding protein II (CRABP2) and tissue transglutaminase (tTG) in the endometrium. Thus estrogen coordinately upregulated both the production and signaling of RA in both the rodent and human endometrium. This coordinate upregulation of RA system appeared to play a role in counterbalancing the stimulatory effects of estrogen on the endometrium, since the depletion of endogenous RA in mice led to an increase in estrogen-stimulated stromal proliferation and endometrial Akt phosphorylation. In addition, I have also used a systematic approach (DNA microarray) to categorize genes and pathways affected by the ERT in the endometrium of postmenopausal women and identified a novel estrogen-regulated gene EIG121. EIG121 was exclusively expressed in the glandular epithelial cells of the endometrium and induced by estrogen in vivo and in cultured cell lines. Compared with the normal endometrium, EIG121 was highly overexpressed in type 1 endometrial cancer, but profoundly suppressed in type 2 endometrial tumors. Taken together, these studies suggested that estrogen regulates the expression of many genes of both the pro-proliferative and anti-proliferative pathways and the abnormality of these pathways may increase the risks for estrogen-dependent endometrial hyperplasia and endometrial cancer. ^

Extension of k-ratio methods to rank-based analyses

An extension of k-ratio multiple comparison methods to rank-based analyses is described. The new method is analogous to the Duncan-Godbold approximate k-ratio procedure for unequal sample sizes or correlated means. The close parallel of the new methods to the Duncan-Godbold approach is shown by demonstrating that they are based upon different parameterizations as starting points.^ A semi-parametric basis for the new methods is shown by starting from the Cox proportional hazards model, using Wald statistics. From there the log-rank and Gehan-Breslow-Wilcoxon methods may be seen as score statistic based methods.^ Simulations and analysis of a published data set are used to show the performance of the new methods. ^

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. ^

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^