The tumor suppressor protein DLC1 maintains protein kinase D activity and Golgi secretory function.

Many newly synthesized cellular proteins pass through the Golgi complex from where secretory transport carriers sort them to the plasma membrane and the extracellular environment. The formation of these secretory carriers at the trans-Golgi network is promoted by the protein kinase D (PKD) family of serine/threonine kinases. Here, using mathematical modeling and experimental validation of the PKD activation and substrate phosphorylation kinetics, we reveal that the expression level of the PKD substrate deleted in liver cancer 1 (DLC1), a Rho GTPase-activating protein that is inhibited by PKD-mediated phosphorylation, determines PKD activity at the Golgi membranes. RNAi-mediated depletion of DLC1 reduced PKD activity in a Rho-Rho-associated protein kinase (ROCK)-dependent manner, impaired the exocytosis of the cargo protein horseradish peroxidase, and was associated with the accumulation of the small GTPase RAB6 on Golgi membranes, indicating a protein-trafficking defect. In summary, our findings reveal that DLC1 maintains basal activation of PKD at the Golgi and Golgi secretory activity, in part by down-regulating Rho-ROCK signaling. We propose that PKD senses cytoskeletal changes downstream of DLC1 to coordinate Rho signaling with Golgi secretory function.

High-dose chemotherapy and autologous haematopoietic stem-cell transplantation in older, fit patients with primary diffuse large B-cell CNS lymphoma (MARTA): a single-arm, phase 2 trial.

BACKGROUND: Available treatments for older patients with primary diffuse large B-cell CNS lymphoma (PCNSL) offer progression-free survival of up to 16 months. We aimed to investigate an intensified treatment of high-dose chemotherapy and autologous haematopoietic stem-cell transplantation (HSCT) in older patients with PCNSL. METHODS: MARTA was a prospective, single-arm, phase 2 study done at 15 research hospitals in Germany. Patients aged 65 years or older with newly diagnosed, untreated PCNSL were enrolled if they had an Eastern Cooperative Oncology Group performance status of 0-2 and were fit for high-dose chemotherapy and autologous HSCT. Induction treatment consisted of two 21-day cycles of high-dose intravenous methotrexate 3·5 g/m2 (day 1), intravenous cytarabine 2 g/m2 twice daily (days 2 and 3), and intravenous rituximab 375 mg/m2 (days 0 and 4) followed by high-dose chemotherapy with intravenous rituximab 375 mg/m2 (day -8), intravenous busulfan 3·2 mg/kg (days -7 and -6), and intravenous thiotepa 5 mg/kg (days -5 and -4) plus autologous HSCT. The primary endpoint was progression-free survival at 12 months in all patients who met eligibility criteria and started treatment. The study was registered with the German clinical trial registry, DRKS00011932, and recruitment is complete. FINDINGS: Between Nov 28, 2017, and Sept 16, 2020, 54 patients started induction treatment and 51 were included in the full analysis set. Median age was 71 years (IQR 68-75); 27 (53%) patients were female and 24 (47%) were male. At a median follow-up of 23·0 months (IQR 16·8-37·4), 23 (45%) of 51 patients progressed, relapsed, or died. 12-month progression-free survival was 58·8% (80% CI 48·9-68·2; 95% CI 44·1-70·9). During induction treatment, the most common grade 3-5 toxicities were thrombocytopenia and leukopenia (each in 52 [96%] of 54 patients). During high-dose chemotherapy and autologous HSCT, the most common grade 3-5 toxicity was leukopenia (37 [100%] of 37 patients). Treatment-related deaths were reported in three (6%) of 54 patients, all due to infectious complications. INTERPRETATION: Although the primary efficacy threshold was not met, short induction followed by high-dose chemotherapy and autologous HSCT is active in selected older patients with PCNSL and could serve as a benchmark for comparative trials. FUNDING: Else Kröner-Fresenius Foundation, Riemser Pharma, and Medical Center-University of Freiburg.

ROSIE: RObust Sparse ensemble for outlIEr detection and gene selection in cancer omics data.

The extraction of novel information from omics data is a challenging task, in particular, since the number of features (e.g. genes) often far exceeds the number of samples. In such a setting, conventional parameter estimation leads to ill-posed optimization problems, and regularization may be required. In addition, outliers can largely impact classification accuracy.Here we introduce ROSIE, an ensemble classification approach, which combines three sparse and robust classification methods for outlier detection and feature selection and further performs a bootstrap-based validity check. Outliers of ROSIE are determined by the rank product test using outlier rankings of all three methods, and important features are selected as features commonly selected by all methods.We apply ROSIE to RNA-Seq data from The Cancer Genome Atlas (TCGA) to classify observations into Triple-Negative Breast Cancer (TNBC) and non-TNBC tissue samples. The pre-processed dataset consists of 16,600 genes and more than 1,000 samples. We demonstrate that ROSIE selects important features and outliers in a robust way. Identified outliers are concordant with the distribution of the commonly selected genes by the three methods, and results are in line with other independent studies. Furthermore, we discuss the association of some of the selected genes with the TNBC subtype in other investigations. In summary, ROSIE constitutes a robust and sparse procedure to identify outliers and important genes through binary classification. Our approach is ad hoc applicable to other datasets, fulfilling the overall goal of simultaneously identifying outliers and candidate disease biomarkers to the targeted in therapy research and personalized medicine frameworks.

Sampling-based Bayesian approaches reveal the importance of quasi-bistable behavior in cellular decision processes on the example of the MAPK signaling pathway in PC-12 cell lines.

BACKGROUND: Positive and negative feedback loops are ubiquitous motifs in biochemical signaling pathways. The mitogen-activated protein kinase (MAPK) pathway module is part of many distinct signaling networks and comprises several of these motifs, whose functioning depends on the cell line at hand and on the particular context. The maintainance of specificity of the response of the MAPK module to distinct stimuli has become a key paradigm especially in PC-12 cells, where the same module leads to different cell fates, depending on the stimulating growth factor. This cell fate is regulated by differences in the ERK (MAPK) activation profile, which shows a transient response upon stimulation with EGF, while the response is sustained in case of NGF. This behavior was explained by different effective network topologies. It is widely believed that this sustained response requires a bistable system. RESULTS: In this study we present a sampling-based Bayesian model analysis on a dataset, in which PC-12 cells have been stimulated with different growth factors. This is combined with novel analysis methods to investigate the role of feedback interconnections to shape ERK response. Results strongly suggest that, besides bistability, an additional effect called quasi-bistability can contribute to explain the observed responses of the system to different stimuli. Quasi-bistability is the ability of a monostable system to maintain two distinct states over a long time period upon a transient signal, which is also related to positive feedback, but cannot be detected by standard steady state analysis methods. CONCLUSIONS: Although applied on a specific example, our framework is generic enough to be also relevant for other regulatory network modeling studies that comprise positive feedback to explain cellular decision making processes. Overall, this study advices to focus not only on steady states, but also to take transient behavior into account in the analysis.