Bayesian joint modeling of longitudinal and survival data

The joint modeling of longitudinal and survival data is a new approach to many applications such as HIV, cancer vaccine trials and quality of life studies. There are recent developments of the methodologies with respect to each of the components of the joint model as well as statistical processes that link them together. Among these, second order polynomial random effect models and linear mixed effects models are the most commonly used for the longitudinal trajectory function. In this study, we first relax the parametric constraints for polynomial random effect models by using Dirichlet process priors, then three longitudinal markers rather than only one marker are considered in one joint model. Second, we use a linear mixed effect model for the longitudinal process in a joint model analyzing the three markers. In this research these methods were applied to the Primary Biliary Cirrhosis sequential data, which were collected from a clinical trial of primary biliary cirrhosis (PBC) of the liver. This trial was conducted between 1974 and 1984 at the Mayo Clinic. The effects of three longitudinal markers (1) Total Serum Bilirubin, (2) Serum Albumin and (3) Serum Glutamic-Oxaloacetic transaminase (SGOT) on patients' survival were investigated. Proportion of treatment effect will also be studied using the proposed joint modeling approaches. ^ Based on the results, we conclude that the proposed modeling approaches yield better fit to the data and give less biased parameter estimates for these trajectory functions than previous methods. Model fit is also improved after considering three longitudinal markers instead of one marker only. The results from analysis of proportion of treatment effects from these joint models indicate same conclusion as that from the final model of Fleming and Harrington (1991), which is Bilirubin and Albumin together has stronger impact in predicting patients' survival and as a surrogate endpoints for treatment. ^

Preclinical modeling of multi-drug cancer therapies

Anticancer drugs typically are administered in the clinic in the form of mixtures, sometimes called combinations. Only in rare cases, however, are mixtures approved as drugs. Rather, research on mixtures tends to occur after single drugs have been approved. The goal of this research project was to develop modeling approaches that would encourage rational preclinical mixture design. To this end, a series of models were developed. First, several QSAR classification models were constructed to predict the cytotoxicity, oral clearance, and acute systemic toxicity of drugs. The QSAR models were applied to a set of over 115,000 natural compounds in order to identify promising ones for testing in mixtures. Second, an improved method was developed to assess synergistic, antagonistic, and additive effects between drugs in a mixture. This method, dubbed the MixLow method, is similar to the Median-Effect method, the de facto standard for assessing drug interactions. The primary difference between the two is that the MixLow method uses a nonlinear mixed-effects model to estimate parameters of concentration-effect curves, rather than an ordinary least squares procedure. Parameter estimators produced by the MixLow method were more precise than those produced by the Median-Effect Method, and coverage of Loewe index confidence intervals was superior. Third, a model was developed to predict drug interactions based on scores obtained from virtual docking experiments. This represents a novel approach for modeling drug mixtures and was more useful for the data modeled here than competing approaches. The model was applied to cytotoxicity data for 45 mixtures, each composed of up to 10 selected drugs. One drug, doxorubicin, was a standard chemotherapy agent and the others were well-known natural compounds including curcumin, EGCG, quercetin, and rhein. Predictions of synergism/antagonism were made for all possible fixed-ratio mixtures, cytotoxicities of the 10 best-scoring mixtures were tested, and drug interactions were assessed. Predicted and observed responses were highly correlated (r2 = 0.83). Results suggested that some mixtures allowed up to an 11-fold reduction of doxorubicin concentrations without sacrificing efficacy. Taken together, the models developed in this project present a general approach to rational design of mixtures during preclinical drug development. ^

Transcriptional regulation of lung tumor suppressor GPRC5A in malignant and normal cells

Chronic exposure of the airways to cigarette smoke induces inflammatory response and genomic instability that play important roles in lung cancer development. Nuclear factor kappa B (NF-κB), the major intracellular mediator of inflammatory signals, is frequently activated in preneoplastic and malignant lung lesions. ^ Previously, we had shown that a lung tumor suppressor GPRC5A is frequently repressed in human non-small cell lung cancers (NSCLC) cells and lung tumor specimens. Recently, other groups have shown that human GPRC5A transcript levels are higher in bronchial samples of former than of current smokers. These results suggested that smoking represses GPRC5A expression and thus promotes the occurrence of lung cancer. We hypothesized that cigarette smoking or associated inflammatory response repressed GPRC5A expression through NF-κB signaling. ^ To determine the effect of inflammation, we examined GPRC5A protein expression in several lung cell lines following by TNF-α treatment. TNF-α significantly suppressed GPRC5A expression in normal small airway epithelial cells (SAEC) as well as in Calu-1 cells. Real-time PCR analysis indicated that TNF-α inhibits GPRC5A expression at the transcriptional level. NF-κB, the major downstream effectors of TNF-α signaling, mediates TNF-α-induced repression of GPRC5A because over-expression of NF-κB suppressed GPRC5A. To determine the region in the GPRC5A promoter through which NF-κB acts, we examined the ability of TNF-α to inhibit a series of reporter constructs with different deletions of GPRC5A promoter. The luciferase assay showed that the potential NF-κB binding sites containing region are irresponsible for TNF-α-induced suppression. Further analysis using constructs with different deletions in p65 revealed that NF-κB-mediated repression of GPRC5A is transcription-independent. Co-immunoprecipitation assays revealed that NF-κB could form a complex with RAR/RXR heterodimer. Moreover, the inhibitory effect of NF-κB has been found to be proportional to NF-κB/RAR ratio in luciferase assay. Finally, Chromatin IP demonstrated that NF-κB/p65 bound to GPRC5A promoter as well as RAR/RXR and suppressed transcription. Taken together, we propose that inflammation-induced NF-κB activation disrupts the RA signaling and suppresses GPRC5A expression and thus contributes to the oncogenesis of lung cancer. Our studies shed new light on the pathogenesis of lung cancer and potentially provide novel interventions for preventing and treating this disease. ^

Survival analysis of circulating tumor cells in triple-negative breast cancer

Background. Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer death among females, accounting for 23% (1.38 million) of the total new cancer cases and 14% (458,400) of the total cancer deaths in 2008. [1] Triple-negative breast cancer (TNBC) is an aggressive phenotype comprising 10–20% of all breast cancers (BCs). [2-4] TNBCs show absence of estrogen, progesterone and HER2/neu receptors on the tumor cells. Because of the absence of these receptors, TNBCs are not candidates for targeted therapies. Circulating tumor cells (CTCs) are observed in blood of breast cancer patients even at early stages (Stage I & II) of the disease. Immunological and molecular analysis can be used to detect the presence of tumor cells in the blood (Circulating tumor cells; CTCs) of many breast cancer patients. These cells may explain relapses in early stage breast cancer patients even after adequate local control. CTC detection may be useful in identifying patients at risk for disease progression, and therapies targeting CTCs may improve outcome in patients harboring them. Methods . In this study we evaluated 80 patients with TNBC who are enrolled in a larger prospective study conducted at M D Anderson Cancer Center in order to determine whether the presence of circulating tumor cells is a significant prognostic factor in relapse free and overall survival . Patients with metastatic disease at the time of presentation were excluded from the study. CTCs were assessed using CellSearch System™ (Veridex, Raritan, NJ). CTCs were defined as nucleated cells lacking the presence of CD45 but expressing cytokeratins 8, 18 or 19. The distribution of patient and tumor characteristics was analyzed using chi square test and Fisher's exact test. Log rank test and Cox regression analysis was applied to establish the association of circulating tumor cells with relapse free and overall survival. Results. The median age of the study participants was 53years. The median duration of follow-up was 40 months. Eighty-eight percent (88%) of patients were newly diagnosed (without a previous history of breast cancer), and (60%) of patients were chemo naïve (had not received chemotherapy at the time of their blood draw for CTC analysis). Tumor characteristics such as stage (P=0.40), tumor size (P=69), sentinel nodal involvement (P=0.87), axillary lymph node involvement (P=0.13), adjuvant therapy (P=0.83), and high histological grade of tumor (P=0.26) did not predict the presence of CTCs. However, CTCs predicted worse relapse free survival (1 or more CTCs log rank P value = 0.04, at 2 or more CTCs P = 0.02 and at 3 or more CTCs P < 0.0001) and overall survival (at 1 or more CTCs log rank P value = 0.08, at 2 or more CTCs P = 0.01 and at 3 or more CTCs P = 0.0001. Conclusions. The number of circulating tumor cells predicted worse relapse free survival and overall survival in TNBC patients.^

A Novel Mechanism of Skin Tumor Promotion Involving Interferon-gamma (IFNγ)/Signal Transducer and Activator of Transcription-1 (Stat1) Signaling in Epidermis

The JAK-STAT pathway is a major signaling pathway involved in many biological processes including proliferation, apoptosis, and differentiation. Aberrant expression of STATs has been reported in multiple human cancers and murine mouse models of tumorigenesis. Previous studies from our lab and others have established a critical role for Stat3 in epithelial tumorigenesis, but the role of Stat1 is largely unknown. The current study was designed to explore the role of Stat1 during multistage skin carcinogenesis. Topical treatment with both TPA and the anthrone derivative chrysarobin (CHRY) led to rapid phosphorylation of Stat1 on both tyrosine (Tyr701) and serine (Ser727) residues in epidermis. CHRY treatment also led to upregulation of unphosphorylated Stat1 (uStat1) at later time points. In addition, CHRY treatment also led to upregulation of IRF-1 mRNA and protein which was dependent on Stat1. Further analyses demonstrated that topical treatment with CHRY but not TPA upregulated interferon-gamma (IFNg) mRNA in the epidermis and that the induction of both IRF-1 and uStat1 was dependent on IFNg signaling. Stat1 deficient (Stat1-/-) mice were highly resistant to skin tumor promotion by CHRY. In contrast, the tumor response (in terms of both papillomas and squamous cell carcinomas) was similar in Stat1-/- mice and wild-type littermates with TPA as the promoter. Histological evaluation of the proliferative response confirmed the data obtained from the tumor study for both TPA and CHRY. In addition, maximal induction of both cyclooxygenase-2 and inducible nitric oxide synthase in epidermis following treatment with CHRY was also dependent on the presence of functional Stat1. Following CHRY treatment, Stat1-/- mice exhibited reduced macrophage infiltration and reduced production of many immune cell derived chemokines/cytokines. These studies define a novel mechanism associated with skin tumor promotion by the anthrone class of tumor promoters involving upregulation of IFNg signaling in the epidermis and downstream signaling through activated (phosphorylated) Stat1 and subsequent upregulation of IRF-1 and uStat1.

Analysis of the mechanism of replication inhibition of the tumor suppressor gene p53

p53 plays a role in cell cycle arrest and apoptosis. p53 has also been shown to be involved in DNA replication. To study the effect of p53 on DNA replication, we utilized a SV40 based shuttle vector system. The pZ402 shuttle vector, was constructed with a mutated T-antigen unable to interact with p53 but able to support replication of the shuttle vector. When a transcriptional activation domain p53 mutant was tested for its ability to inhibit DNA replication no inhibition was observed. Competition assays with the DNA binding domain of p53 was also able to block the inhibition of DNA replication by p53 suggesting that p53 can inhibit DNA replication through the transcriptional activation of a target gene. One likely target gene, p21$\sp{\rm cip/waf}$ was tested to determine whether p53 inhibited DNA replication by transcriptionally activating p21$\sp{\rm cip/waf}$. Two independent approaches utilizing p21$\sp{\rm cip/waf}$ null cells or the expression of an anti-sense p21$\sp{\rm cip/waf}$ expression vector were utilized. p53 was able to inhibit pZ402 replication independently of p21$\sp{\rm cip/waf}$. p53 was also able to inhibit DNA replication independent of the p53 target genes Gadd45 and the replication processivity factor PCNA. The inhibition of DNA replication by p53 was also independent of direct DNA binding to a consensus site on the replicating plasmid. p53 mutants can be classified into two categories: conformational and DNA contact mutants. The two types of p53 mutants were tested for their effects on DNA replication. While all conformational mutants were unable to inhibit DNA replication three out of three DNA contact mutants tested were able to inhibit DNA replication. The work here studies the effect wild-type and mutant p53 has on DNA replication and demonstrated a possible mechanism by which wild-type p53 could inhibit DNA replication through the transcriptional activation of a target gene. ^

A distinct element involved in the lipopolysaccharide activation of the tumor necrosis factor -alpha promoter in a promonocytic cell line, THP-1

TNF-α is a pleiotropic cytokine involved in normal homeostasis and plays a key role in defending the host from infection and malignancy. However when deregulated, TNF-α can lead to various disease states. Therefore, understanding the mechanisms by which TNF-α is regulated may aid in its control. In spite of the knowledge gained regarding the transcriptional regulation of TNF-α further characterization of specific TNF-α promoter elements remains to be elucidated. In particular, the T&barbelow;NF-α A&barbelow;P-1/C&barbelow;RE-like (TAC) element of the TNF-α promoter has been shown to be important in the regulation of TNF-α in lymphocytes. Activating transcription factor-2 (ATF-2) and c-Jun were shown to bind to and transactivate the TAC element However, the role of TAC and transcription factors ATF-2 and c-Jun in the regulation of TNF-α in monocytes is not as well characterized. Lipopolysaccharide (LPS), a potent activator of TNF-α in monocytes, provides a good model to study the involvement of TAC in TNF-α regulation. On the other hand, all-tram retinoic acid (ATRA), a physiological monocyte-differentiation agent, is unable to induce TNF-α protein release. ^ To delineate the functional role of TAC, we transfected the wildtype or the TAC deleted TNF-α promoter-CAT construct into THP-1 promonocytic cells before stimulating them with LPS. CAT activity was induced 17-fold with the wildtype TNF-α promoter, whereas the CAT activity was uninducible when the TAC deletion mutant was used. This daft suggests that TAC is vital for LPS to activate the TNF-α promoter. Electrophoretic mobility shift assays using the TAC element as a probe showed a unique pattern for LPS-activated cells: the disappearance of the upper band of a doublet seen in untreated and ATRA treated cells. Supershift analysis identified c-Jun and ATF-2 as components of the LPS-stimulated binding complex. Transient transfection studies using dominant negative mutants of JNK, c-Jun, or ATF-2 suggest that these proteins we important for LPS to activate the TNF-α promoter. Furthermore, an increase in phosphorylated or activated c-Jun was bound to the TAC element in LPS-stimulated cells. Increased c-Jun activation was correlated with increased activity of Jun N-terminal kinase (JNK), a known upstream stimulator of c-Jun and ATF-2, in LPS-stimulated monocytes. On the other hand, ATRA did not induce TNF-α protein release nor changes in the phosphorylation of c-Jun or JNK activity, suggesting that pathways leading to ATRA differentiation of monocytic cells are independent of TNF-α activation. Together, the induction of TNF-α gene expression seems to require JNK activation, and activated c-Jun binding to the TAC element of the TNF-α promoter in THP-1 promonocytic cells. ^

Numerical modeling of marine radiocarbon reservoir ages during the last deglaciation

A critical problem in radiocarbon dating is the spatial and temporal variability of marine reservoir ages (MRAs). We assessed the MRA evolution during the last deglaciation by numerical modeling, applying a self-consistent iteration scheme in which an existing radiocarbon chronology (derived by Hughen et al., Quat. Sci. Rev., 25, pp. 3216-3227, 2006) was readjusted by transient, 3-D simulations of marine and atmospheric Delta14C. To estimate the uncertainties regarding the ocean ventilation during the last deglaciation, we considered various ocean overturning scenarios which are based on different climatic background states (PD: modern climate, GS: LGM climate conditions). Minimum and maximum MRAs are included in file 'MRAminmax_21-14kaBP.nc'. Three further files include MRAs according to equilibrium simulations of the preindustrial ocean (file 'C14age_preindustrial.nc'; this is an update of our results published in 2005) and of the glacial ocean (files 'C14age_spinupLGM_GS.nc' and 'C14age_spinupLGM_PD.nc').

Collisional Formation and Modeling of Asteroid Families

In the last decade, thanks to the development of sophisticated numerical codes, major breakthroughs have been achieved in our understanding of the formation of asteroid families by catastrophic disruption of large parent bodies. In this review, we describe numerical simulations of asteroid collisions that reproduced the main properties of families, accounting for both the fragmentation of an asteroid at the time of impact and the subsequent gravitational interactions of the generated fragments. The simulations demonstrate that the catastrophic disruption of bodies larger than a few hundred meters in diameter leads to the formation of large aggregates due to gravitational reaccumulation of smaller fragments, which helps explain the presence of large members within asteroid families. Thus, for the first time, numerical simulations successfully reproduced the sizes and ejection velocities of members of representative families. Moreover, the simulations provide constraints on the family dynamical histories and on the possible internal structure of family members and their parent bodies.