A Minimal Model of Signaling Network Elucidates Cell-to-Cell Stochastic Variability in Apoptosis

Signaling networks are designed to sense an environmental stimulus and adapt to it. We propose and study a minimal model of signaling network that can sense and respond to external stimuli of varying strength in an adaptive manner. The structure of this minimal network is derived based on some simple assumptions on its differential response to external stimuli. We employ stochastic differential equations and probability distributions obtained from stochastic simulations to characterize differential signaling response in our minimal network model. We show that the proposed minimal signaling network displays two distinct types of response as the strength of the stimulus is decreased. The signaling network has a deterministic part that undergoes rapid activation by a strong stimulus in which case cell-to-cell fluctuations can be ignored. As the strength of the stimulus decreases, the stochastic part of the network begins dominating the signaling response where slow activation is observed with characteristic large cell-to-cell stochastic variability. Interestingly, this proposed stochastic signaling network can capture some of the essential signaling behaviors of a complex apoptotic cell death signaling network that has been studied through experiments and large-scale computer simulations. Thus we claim that the proposed signaling network is an appropriate minimal model of apoptosis signaling. Elucidating the fundamental design principles of complex cellular signaling pathways such as apoptosis signaling remains a challenging task. We demonstrate how our proposed minimal model can help elucidate the effect of a specific apoptotic inhibitor Bcl-2 on apoptotic signaling in a cell-type independent manner. We also discuss the implications of our study in elucidating the adaptive strategy of cell death signaling pathways.Comment: 9 pages, 6 figure

Increased expression of Ki-67 in mantle cell lymphoma is associated with de-regulation of several cell cycle regulatory components, as identified by global gene expression analysis

Background and Objectives. Mantle cell lymphoma (MCL) is an aggressive disease. Patients with this malignancy have a median survival of 3 years. To better understand disease progression, which is characterized by increased proliferation, we analyzed the gene expression of MCL with different proliferative indices, as determined by immunohistochemical staining for Ki-67. Furthermore, primary and relapsed tumors were compared to identify the possible growth advantages possessed by cells which persist after therapy and which might evolve into a tumor relapse. Design and Methods. Twenty-one samples of MCL were analyzed, using the Affymetrix U95Av2 chip, containing probes for approximately 12,000 transcripts. Samples with a high versus low fraction of Ki-67(+) cells were compared as were relapsed versus primary tumors. Immunohistochemistry was used to confirm the expression of some gene products. Results. A distinct genetic signature, consisting of 32 genes, was found when comparing Ki-67(high) with Ki-67(low) MCL. The signature consisted of genes involved in cellular processes, such as mitotic spindle formation, gene transcription and cell cycle regulation, e.g. components of the p53 and retinoblastoma protein (pRb) pathways. Of note, cyclin D1, the hallmark of MCL, as well as Ki-67 were up-regulated in the samples with a high proliferative index. Comparing primary vs. relapsed tumors, 26 individual genes were found, several involved in cell adhesion. Furthermore, increased expression of transferrin receptor was found in the relapsed tumors. Interpretation and Conclusions. A genetic signature distinguishing Ki-67(high) MCL from Ki-67(low) was established. The generated signature was used to assign new MCL samples to the high proliferative group, validating the association between these genes and proliferation in MCL

Biological markers may add to prediction of outcome achieved by the international prognostic score in Hodgkin's disease

Background The International Prognostic Score (IPS) identifies seven independent factors predicting progression-free and overall survival in advanced stage Hodgkin's disease (HD). The IPS is also applicable in limited disease. However, the IPS does not identify patients with a very poor prognosis. The aim of this study was to define biological markers which may add to the IPS in predicting outcome. Patients and methods One hundred forty-five patients (>15 years) with HD of all stages and histopathology sub groups were included. In addition to factors included in the IPS, serum levels of CRP, sCD4, sCD8, sCD25, sCD30, sCD54, interleukin (IL)-10, β2-microglobulin and thymidine kinase were analysed. Results The strongest predictors of a poor cause-specific survival (CSS) in univariate analyses were: increased serum levels of IL-10, sCD30 and CRP, anaemia, low levels of albumin (P < 0.001); stage IV (P = 0.003), age ≥ 45 years (P = 0.006), increased serum levels of sCD25 (P = 0.010), low lymphocyte counts (P = 0.020). Serum IL-10 added prognostic information to that achieved by the IPS: patients with a high score and increased serum IL-10 had a very poor outcome with a five-year CSS of 38%. Patients with increased serum levels of sCD30 and a high score also had a poor outcome with a five-year CSS of 54%. Conclusion Serum levels of IL-10 and sCD30 may add to IPS in prediction of outcome in HD, and should be validated in large, prospective studies

A population-based cohort study on early-stage Hodgkin lymphoma treated with radiotherapy alone: with special reference to older patients

Background: Combined modality treatment has reduced the risk of relapse among younger early-stage Hodgkin lymphoma (HL) patients. Older HL patients may not tolerate chemotherapy and their prognosis is less favorable. We conducted a population-based study to evaluate long-term follow-up outcome in older early-stage HL patients initially treated with radiotherapy (RT) alone. Patients and methods: We included 308 consecutive patients (22% were ≥60 years) diagnosed 1972–1999 (median follow-up 20 years; range 1–28). Using Cox regression models we defined risk of relapse and survival in relation to clinical factors. Results: 272/308 (88%) patients obtained complete remission following first-line RT alone. Among these, 42% relapsed within a median of 21 months. The relapse rate was independent of gender and age at diagnosis (median age 32 years, range 14–85); however, lymphocyte-predominant HL was associated with borderline (P = 0.049) 56% decreased risk of relapse. Among patients <60 years and ≥60 years, we observed 29 (median latency 10 years, range 2–25) and 11 (median latency 3 years, range 1–10) second tumors, respectively. Conclusions: Older age (≥60 years) was not associated with an increased risk of relapse following RT alone. Given the risks of iatrogenic morbidity/mortality of chemotherapy in older patients, RT alone could be an alternative first-line therapy in early-stage older HL patients