NF-kappaB and AP-1 connection: mechanism of NF-kappaB-dependent regulation of AP-1 activity.

Nuclear factor kappaB (NF-kappaB) and activator protein 1 (AP-1) transcription factors regulate many important biological and pathological processes. Activation of NF-kappaB is regulated by the inducible phosphorylation of NF-kappaB inhibitor IkappaB by IkappaB kinase. In contrast, Fos, a key component of AP-1, is primarily transcriptionally regulated by serum responsive factors (SRFs) and ternary complex factors (TCFs). Despite these different regulatory mechanisms, there is an intriguing possibility that NF-kappaB and AP-1 may modulate each other, thus expanding the scope of these two rapidly inducible transcription factors. To determine whether NF-kappaB activity is involved in the regulation of fos expression in response to various stimuli, we analyzed activity of AP-1 and expression of fos, fosB, fra-1, fra-2, jun, junB, and junD, as well as AP-1 downstream target gene VEGF, using MDAPanc-28 and MDAPanc-28/IkappaBalphaM pancreatic tumor cells and wild-type, IKK1-/-, and IKK2-/- murine embryonic fibroblast cells. Our results show that elk-1, a member of TCFs, is one of the NF-kappaB downstream target genes. Inhibition of NF-kappaB activity greatly decreased expression of elk-1. Consequently, the reduced level of activated Elk-1 protein by extracellular signal-regulated kinase impeded constitutive, serum-, and superoxide-inducible c-fos expression. Thus, our study revealed a distinct and essential role of NF-kappaB in participating in the regulation of elk-1, c-fos, and VEGF expression.

Outcome-based adaptive randomization for binary data in clinical trials---Compare and contrast

Monte Carlo simulation has been conducted to investigate parameter estimation and hypothesis testing in some well known adaptive randomization procedures. The four urn models studied are Randomized Play-the-Winner (RPW), Randomized Pôlya Urn (RPU), Birth and Death Urn with Immigration (BDUI), and Drop-the-Loses Urn (DL). Two sequential estimation methods, the sequential maximum likelihood estimation (SMLE) and the doubly adaptive biased coin design (DABC), are simulated at three optimal allocation targets that minimize the expected number of failures under the assumption of constant variance of simple difference (RSIHR), relative risk (ORR), and odds ratio (OOR) respectively. Log likelihood ratio test and three Wald-type tests (simple difference, log of relative risk, log of odds ratio) are compared in different adaptive procedures. ^ Simulation results indicates that although RPW is slightly better in assigning more patients to the superior treatment, the DL method is considerably less variable and the test statistics have better normality. When compared with SMLE, DABC has slightly higher overall response rate with lower variance, but has larger bias and variance in parameter estimation. Additionally, the test statistics in SMLE have better normality and lower type I error rate, and the power of hypothesis testing is more comparable with the equal randomization. Usually, RSIHR has the highest power among the 3 optimal allocation ratios. However, the ORR allocation has better power and lower type I error rate when the log of relative risk is the test statistics. The number of expected failures in ORR is smaller than RSIHR. It is also shown that the simple difference of response rates has the worst normality among all 4 test statistics. The power of hypothesis test is always inflated when simple difference is used. On the other hand, the normality of the log likelihood ratio test statistics is robust against the change of adaptive randomization procedures. ^