LY2109761, a novel transforming growth factor beta receptor type I and type II dual inhibitor, as a therapeutic approach to suppressing pancreatic cancer metastasis.

Most pancreatic cancer patients present with inoperable disease or develop metastases after surgery. Conventional therapies are usually ineffective in treating metastatic disease. It is evident that novel therapies remain to be developed. Transforming growth factor beta (TGF-beta) plays a key role in cancer metastasis, signaling through the TGF-beta type I/II receptors (TbetaRI/II). We hypothesized that targeting TbetaRI/II kinase activity with the novel inhibitor LY2109761 would suppress pancreatic cancer metastatic processes. The effect of LY2109761 has been evaluated on soft agar growth, migration, invasion using a fibroblast coculture model, and detachment-induced apoptosis (anoikis) by Annexin V flow cytometric analysis. The efficacy of LY2109761 on tumor growth, survival, and reduction of spontaneous metastasis have been evaluated in an orthotopic murine model of metastatic pancreatic cancer expressing both luciferase and green fluorescence proteins (L3.6pl/GLT). To determine whether pancreatic cancer cells or the cells in the liver microenvironment were involved in LY2109761-mediated reduction of liver metastasis, we used a model of experimental liver metastasis. LY2109761 significantly inhibited the L3.6pl/GLT soft agar growth, suppressed both basal and TGF-beta1-induced cell migration and invasion, and induced anoikis. In vivo, LY2109761, in combination with gemcitabine, significantly reduced the tumor burden, prolonged survival, and reduced spontaneous abdominal metastases. Results from the experimental liver metastasis models indicate an important role for targeting TbetaRI/II kinase activity on tumor and liver microenvironment cells in suppressing liver metastasis. Targeting TbetaRI/II kinase activity on pancreatic cancer cells or the cells of the liver microenvironment represents a novel therapeutic approach to prevent pancreatic cancer metastasis.

Long-term survival after multidisciplinary management of resected pancreatic adenocarcinoma.

INTRODUCTION: Actual 5-year survival rates of 10-18% have been reported for patients with resected pancreatic adenocarcinoma (PC), but the use of multimodality therapy was uncommon in these series. We evaluated long-term survival and patterns of recurrence in patients treated for PC with contemporary staging and multimodality therapy. METHODS: We analyzed 329 consecutive patients with PC evaluated between 1990 and 2002 who underwent resection. Each received a multidisciplinary evaluation and a standard operative approach. Pre- or postoperative chemotherapy and/or chemoradiation were routine. Surgical specimens of 5-year survivors were re-reviewed. A multivariate model of factors associated with long-term survival was constructed. RESULTS: Patients underwent pancreaticoduodenectomy (n = 302; 92%), distal (n = 20; 6%), or total pancreatectomy (n = 7; 2%). A total of 108 patients (33%) underwent vascular reconstruction, 301 patients (91%) received neoadjuvant or adjuvant therapy, 157 specimens (48%) were node positive, and margins were microscopically positive in 52 patients (16%). Median overall survival and disease-specific survival was 23.9 and 26.5 months. Eighty-eight patients (27%) survived a minimum of 5 years and had a median overall survival of 11 years. Of these, 21 (24%) experienced recurrence, 7 (8%) after 5 years. Late recurrences occurred most frequently in the lungs, the latest at 6.7 years. Multivariate analysis identified disease-negative lymph nodes (P = .02) and no prior attempt at resection (P = 0.01) as associated with 5-year survival. CONCLUSIONS: Our 27% actual 5-year survival rate for patients with resected PC is superior to that previously reported, and it is influenced by our emphasis on detailed staging and patient selection, a standardized operative approach, and routine use of multimodality therapy.

Bayesian doubly optimal group sequential designs for randomized clinical trials

When conducting a randomized comparative clinical trial, ethical, scientific or economic considerations often motivate the use of interim decision rules after successive groups of patients have been treated. These decisions may pertain to the comparative efficacy or safety of the treatments under study, cost considerations, the desire to accelerate the drug evaluation process, or the likelihood of therapeutic benefit for future patients. At the time of each interim decision, an important question is whether patient enrollment should continue or be terminated; either due to a high probability that one treatment is superior to the other, or a low probability that the experimental treatment will ultimately prove to be superior. The use of frequentist group sequential decision rules has become routine in the conduct of phase III clinical trials. In this dissertation, we will present a new Bayesian decision-theoretic approach to the problem of designing a randomized group sequential clinical trial, focusing on two-arm trials with time-to-failure outcomes. Forward simulation is used to obtain optimal decision boundaries for each of a set of possible models. At each interim analysis, we use Bayesian model selection to adaptively choose the model having the largest posterior probability of being correct, and we then make the interim decision based on the boundaries that are optimal under the chosen model. We provide a simulation study to compare this method, which we call Bayesian Doubly Optimal Group Sequential (BDOGS), to corresponding frequentist designs using either O'Brien-Fleming (OF) or Pocock boundaries, as obtained from EaSt 2000. Our simulation results show that, over a wide variety of different cases, BDOGS either performs at least as well as both OF and Pocock, or on average provides a much smaller trial. ^

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. ^

Three Years in a Mad-House: The Story of my Life at the Asylum, my Escape, and the Strange Adventures which Followed

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