BCL6 degradation caused by the interaction with the C-terminus of pro-HB-EGF induces cyclin D2 expression in gastric cancers

BCL6 is a transcriptional repressor that has important functions in lymphocyte differentiation and lymphomagenesis, but there have been no reports of BCL6 expression in gastric cancers. In the present study, we investigated the BCL6 function in gastric cancers. Treatment with TPA resulted in BCL6 degradation and cyclin D2 upregulation. This phenomenon was inhibited by the suppression of the nuclear translocation of HB-EGF-CTF (C-terminal fragment of pro-HB-EGF). The HB-EGF-CTF nuclear translocation leads to the interaction of BCL6 with HB-EGF-CTF and the nuclear export of BCL6, and after that BCL6 degradation was mediated by ubiquitin/proteasome pathway. Real-time RT–PCR and siRNA targeting BCL6 revealed that BCL6 suppresses cyclin D2 expression. Our data indicate that BCL6 interacts with nuclear-translocated HB-EGF-CTF and that the nuclear export and degradation of BCL6 induces cyclin D2 upregulation. We performed immunohistochemical analyses of BCL6, HB-EGF and cyclin D2 in human gastric cancers. The inverse correlation between BCL6 and cyclin D2 was also found in HB-EGF-positive human gastric cancers. BCL6 degradation caused by the HB-EGF-CTF also might induce cyclin D2 expression in human gastric cancers. Inhibition of HB-EGF-CTF nuclear translocation and maintenance of BCL6 function are important for the regulation of gastric cancer progression

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases

Observational study of lenalidomide in patients with mantle cell lymphoma who relapsed/progressed after or were refractory/intolerant to ibrutinib (MCL-004).

BACKGROUND: The observational MCL-004 study evaluated outcomes in patients with relapsed/refractory mantle cell lymphoma who received lenalidomide-based therapy after ibrutinib failure or intolerance. METHODS: The primary endpoint was investigator-assessed overall response rate based on the 2007 International Working Group criteria. RESULTS: Of 58 enrolled patients (median age, 71 years; range, 50-89), 13 received lenalidomide monotherapy, 11 lenalidomide plus rituximab, and 34 lenalidomide plus other treatment. Most patients (88%) had received ≥ 3 prior therapies (median 4; range, 1-13). Median time from last dose of ibrutinib to the start of lenalidomide was 1.3 weeks (range, 0.1-21.7); 45% of patients had partial responses or better to prior ibrutinib. Primary reasons for ibrutinib discontinuation were lack of efficacy (88%) and ibrutinib toxicity (9%). After a median of two cycles (range, 0-11) of lenalidomide-based treatment, 17 patients responded (8 complete responses, 9 partial responses), for a 29% overall response rate (95% confidence interval, 18-43%) and a median duration of response of 20 weeks (95% confidence interval, 2.9 to not available). Overall response rate to lenalidomide-based therapy was similar for patients with relapsed/progressive disease after previous response to ibrutinib (i.e., ≥PR) versus ibrutinib-refractory (i.e., ≤SD) patients (30 versus 32%, respectively). The most common all-grade treatment-emergent adverse events after lenalidomide-containing therapy (n = 58) were fatigue (38%) and cough, dizziness, dyspnea, nausea, and peripheral edema (19% each). At data cutoff, 28 patients have died, primarily due to mantle cell lymphoma. CONCLUSION: Lenalidomide-based treatment showed clinical activity, with no unexpected toxicities, in patients with relapsed/refractory mantle cell lymphoma who previously failed ibrutinib therapy. TRIAL REGISTRATION: Clinicaltrials.gov identifier NCT02341781 . Date of registration: January 14, 2015

Enhanced Monocyte Response and Decreased Central Memory T Cells in Children with Invasive Staphylococcus aureus Infections

Staphylococcus aureus has emerged as a significant pathogen causing severe invasive disease in otherwise healthy people. Despite considerable advances in understanding the epidemiology, resistance mechanisms, and virulence factors produced by the bacteria, there is limited knowledge of the in vivo host immune response to acute, invasive S. aureus infections. Herein, we report that peripheral blood mononuclear cells from patients with severe S. aureus infections demonstrate a distinctive and robust gene expression profile which is validated in a distinct group of patients and on a different microarray platform. Application of a systems-wide modular analysis framework reveals significant over-expression of innate immunity genes and under-expression of genes related to adaptive immunity. Simultaneous flow cytometry analyses demonstrated marked alterations in immune cell numbers, with decreased central memory CD4 and CD8 T cells and increased numbers of monocytes. CD14+ monocyte numbers significantly correlated with the gene expression levels of genes related to the innate immune response. These results demonstrate the value of applying a systems biology approach that reveals the significant alterations in the components of circulating blood lymphocytes and monocytes in invasive S. aureus infections

Identification and Characterization of Peripheral T-Cell Lymphoma-Associated SEREX Antigens

Peripheral T-cell lymphomas (PTCL) are generally less common and pursue a more aggressive clinical course than B-cell lymphomas, with the T-cell phenotype itself being a poor prognostic factor in adult non-Hodgkin lymphoma (NHL). With notable exceptions such as ALK+ anaplastic large cell lymphoma (ALCL, ALK+), the molecular abnormalities in PTCL remain poorly characterised. We had previously identified circulating antibodies to ALK in patients with ALCL, ALK+. Thus, as a strategy to identify potential antigens associated with the pathogenesis of PTCL, not otherwise specified (PTCL, NOS), we screened a testis cDNA library with sera from four PTCL, NOS patients using the SEREX (serological analysis of recombinant cDNA expression libraries) technique. We identified nine PTCL, NOS-associated antigens whose immunological reactivity was further investigated using sera from 52 B- and T-cell lymphoma patients and 17 normal controls. The centrosomal protein CEP250 was specifically recognised by patients sera and showed increased protein expression in cell lines derived from T-cell versus B-cell malignancies. TCEB3, BECN1, and two previously uncharacterised proteins, c14orf93 and ZBTB44, were preferentially recognised by patients' sera. Transcripts for all nine genes were identified in 39 cancer cell lines and the five genes encoding preferentially lymphoma-recognised antigens were widely expressed in normal tissues and mononuclear cell subsets. In summary, this study identifies novel molecules that are immunologically recognised in vivo by patients with PTCL, NOS. Future studies are needed to determine whether these tumor antigens play a role in the pathogenesis of PTCL

Antibody Vh Repertoire Differences between Resolving and Chronically Evolving Hepatitis C Virus Infections

Despite the production of neutralizing antibodies to hepatitis C virus (HCV), many patients fail to clear the virus and instead develop chronic infection and long-term complications. To understand how HCV infection perturbs the antibody repertoire and to identify molecular features of antibody genes associated with either viral clearance or chronic infection, we sequenced the V(D)J region of naïve and memory B cells of 6 persons who spontaneously resolved an HCV infection (SR), 9 patients with a newly diagnosed chronically evolving infection (CE), and 7 healthy donors. In both naïve and memory B cells, the frequency of use of particular antibody gene subfamilies and segments varied among the three clinical groups, especially between SR and CE. Compared to CE, SR antibody genes used fewer VH, D and JH gene segments in naïve B cells and fewer VH segments in memory B cells. SR and CE groups significantly differed in the frequency of use of 7 gene segments in naïve B cell clones and 3 gene segments in memory clones. The nucleotide mutation rates were similar among groups, but the pattern of replacement and silent mutations in memory B cell clones indicated greater antigen selection in SR than CE. Greater clonal evolution of SR than CE memory B cells was revealed by analysis of phylogenetic trees and CDR3 lengths. Pauciclonality of the peripheral memory B cell population is a distinguishing feature of persons who spontaneously resolved an HCV infection. This finding, previously considered characteristic only of patients with HCV-associated lymphoproliferative disorders, suggests that the B cell clones potentially involved in clearance of the virus may also be those susceptible to abnormal expansion

A cyclin-D1 interaction with BAX underlies its oncogenic role and potential as a therapeutic target in mantle cell lymphoma

The chromosomal translocation t(11;14)(q13;q32) leading to cyclin-D1 overexpression plays an essential role in the development of mantle cell lymphoma (MCL), an aggressive tumor that remains incurable with current treatment strategies. Cyclin-D1 has been postulated as an effective therapeutic target, but the evaluation of this target has been hampered by our incomplete understanding of its oncogenic functions and by the lack of valid MCL murine models. To address these issues, we generated a cyclin-D1-driven mouse model in which cyclin-D1 expression can be regulated externally. These mice developed cyclin-D1-expressing lymphomas capable of recapitulating features of human MCL. We found that cyclin-D1 inactivation was not sufficient to induce lymphoma regression in vivo; however, using a combination of in vitro and in vivo assays, we identified a novel prosurvival cyclin-D1 function in MCL cells. Specifically, we found that cyclin-D1, besides increasing cell proliferation through deregulation of the cell cycle at the G(1)-S transition, sequestrates the proapoptotic protein BAX in the cytoplasm, thereby favoring BCL2's antiapoptotic function. Accordingly, cyclin-D1 inhibition sensitized the lymphoma cells to apoptosis through BAX release. Thus, genetic or pharmacologic targeting of cyclin-D1 combined with a proapoptotic BH3 mimetic synergistically killed the cyclin-D1-expressing murine lymphomas, human MCL cell lines, and primary lymphoma cells. Our study identifies a role of cyclin-D1 in deregulating apoptosis in MCL cells, and highlights the potential benefit of simultaneously targeting cyclin-D1 and survival pathways in patients with MCL. This effective combination therapy also might be exploited in other cyclin-D1-expressing tumors

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice