Patients (pts) with extensive-stage (ES) SCLC or extra-pulmonary grade 3 (G3) NEC rapidly develop progressive disease after 1st -line cytotoxic chemotherapy, and efficacious 2nd -line treatment options are needed. Lysine Specific Demethylase 1 (LSD1, aka KDM1A) is involved in repressing transcription by removing methyl groups from mono- and di-methylated lysine 4 of histone 3, epigenetic hallmarks commonly associated with actively transcribed genes. LSD1 over-expression is associated with tumor progression and worse prognosis, and its inhibition reduces cancer cell growth, migration, and invasion. The epigenetic drug iadademstat (aka ORY-1001 or iada) is a highly potent and selective LSD1 inhibitor (LSD1i) in phase 2 clinical development for malignant indications. Iada and other LSD1is are effective in in vitro and in vivo models of SCLC by preventing INSM1 recruitment of LSD1 which results in NOTCH signaling activation, reduced NE differentiation and tumor growth inhibition. Additionally, LSD1is have been implicated in reversing chemoresistance, synergizing with paclitaxel, and enhancing immunostimulatory responses by increasing MHC-Class I expression, IFN-Type I responses and T-cell infiltration and activity. NCT05420636 is a multi-center, non-randomized phase II study to treat up to 42 pts with iada (150 mg oral, 5d on-2d off every week) and paclitaxel (80 mg/m2 IV weekly) in 21 day cycles. Eligibility includes adult pts with metastatic/unresectable SCLC (cohort 1) or extra pulmonary G3 NEC or metastatic/unresectable prostate or bladder cancer with G3 NE or small cell component (cohort 2), who have received 1 to 3 prior lines of therapy and progressed on or after platinum-based chemotherapy. Pts must have measurable disease, normal organ, and marrow function, stable brain mets, ECOG status ≤1 and not have received prior taxanes for metastatic disease. The primary endpoint is ORR per RECIST 1.1; secondary endpoints include rate of ≥ grade 3 toxicities, PFS, OS and DoR. Exploratory endpoints include host inflammatory cytokine and immune profile, and epigenomic and genomic analysis of tumor and peripheral blood samples. NCT05420636. Fox Chase Cancer Center. Oryzon.

lead to misleading costeffectiveness estimates.

BACKGROUND:While the genetic basis of autosomal dominant polycystic kidney disease (ADPKD) has been clearly established, the pathogenesis of renal failure in ADPKD remains elusive. Cyst formation originates from proliferating renal tubular epithelial cells that de-differentiate. Fluid secretion with cyst expansion and reactive changes in the extracellular matrix composition combined with increased apoptosis and proliferation rates have been implicated in cystogenesis.METHODS:To identify genes that characterize pathogenical changes in ADPKD, we compared the expression profiles of 12 ADPKD kidneys, 13 kidneys with chronic transplant nephropathy and 16 normal kidneys using a 7 k cDNA microarray. RT-PCR and immunohistochemical techniques were used to confirm the microarray data.RESULTS:Hierarchical clustering revealed that the gene expression profiles of normal, ADPKD and rejected kidneys were clearly distinct. A total of 87 genes were specifically regulated in ADPKD; 26 of these 87 genes were typical for smooth muscle, suggesting epithelial-to-myofibroblast transition (EMT) as a pathogenetic factor in ADPKD. Immunohistology revealed that smooth muscle actin, a typical marker for myofibroblast transition, and caldesmon were mainly expressed in the interstitium of ADPKD kidneys. In contrast, up-regulated keratin 19 and fibulin-1 were confined to cystic epithelia.CONCLUSION:Our results show that the end stage of ADPKD is associated with increased markers of EMT, suggesting that EMT contributes to the progressive loss of renal function in ADPKD.

SummaryThe molecular aetiology of polycythaemia vera (PV) remains unknown and the differential diagnosis between PV and secondary erythrocytosis (SE) can be challenging. Gene expression profiling can identify candidates involved in the pathophysiology of PV and generate a molecular signature to aid in diagnosis. We thus performed cDNA microarray analysis on 40 PV and 12 SE patients. Two independent data sets were obtained: using a two‐step training/validation design, a set of 64 genes (class predictors) was determined, which correctly discriminated PV from SE patients. Separately 253 genes were identified to be upregulated and 391 downregulated more than 1·5‐fold in PV compared with healthy controls (P < 0·01). Of the genes overexpressed in PV, 27 contained Sp1 sites: we therefore propose that altered activity of Sp1‐like transcription factors may contribute to the molecular aetiology of PV. One Sp1 target, the transcription factor NF‐E2 [nuclear factor (erythroid‐derived 2)], is overexpressed 2‐ to 40‐fold in PV patients. In PV bone marrow, NF‐E2 is overexpressed in megakaryocytes, erythroid and granulocytic precursors. It has been shown that overexpression of NF‐E2 leads to the development of erythropoietin‐independent erythroid colonies and that ectopic NF‐E2 expression can reprogram monocytic cells towards erythroid and megakaryocytic differentiation. Transcription factor concentration may thus control lineage commitment. We therefore propose that elevated concentrations of NF‐E2 in PV patients lead to an overproduction of erythroid and, in some patients, megakaryocytic cells/platelets. In this model, the level of NF‐E2 overexpression determines both the severity of erythrocytosis and the concurrent presence or absence of thrombocytosis.

Data organization and data mining represents one of the main challenges for modern high throughput technologies in pharmaceutical chemistry and medical chemistry. The presented open source documentation and analysis system provides an integrated solution (tutorial, setup protocol, sources, executables) aimed at substituting the traditionally used lab-book. The data management solution provided incorporates detailed information about the processing of the gels and the experimental conditions used and includes basic data analysis facilities which can be easily extended. The sample database and User-Interface are available free of charge under the GNU license from http://webber.physik.uni-freiburg.de/~fallerd/tutorial.htm.

ChemInformVolume 35, Issue 17 Other Subjects An Open Source Protein Gel Documentation System for Proteome Analyses. Daniel Faller, Daniel Faller Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorThomas Reinheckel, Thomas Reinheckel Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorDaniel Wenzel, Daniel Wenzel Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorSascha Hagemann, Sascha Hagemann Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorKe Xiao, Ke Xiao Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorJosef Honerkamp, Josef Honerkamp Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorChristoph Peters, Christoph Peters Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorThomas Dandekar, Thomas Dandekar Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorJens Timmer, Jens Timmer Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this author Daniel Faller, Daniel Faller Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorThomas Reinheckel, Thomas Reinheckel Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorDaniel Wenzel, Daniel Wenzel Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorSascha Hagemann, Sascha Hagemann Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorKe Xiao, Ke Xiao Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorJosef Honerkamp, Josef Honerkamp Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorChristoph Peters, Christoph Peters Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorThomas Dandekar, Thomas Dandekar Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this authorJens Timmer, Jens Timmer Freiburger Zent. Datenanal. Modellbild., Albert-Ludwigs-Univ., D-79104 Freiburg, GermanySearch for more papers by this author First published: 05 April 2004 https://doi.org/10.1002/chin.200417225AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat No abstract is available for this article. References Daniel Faller, Thomas Reinheckel, Daniel Wenzel, Sascha Hagemann, Ke Xiao, Josef Honerkamp, Christoph Peters, Thomas Dandekar, Jens Timmer, An Open Source Protein Gel Documentation System for Proteome Analyses., J. Chem. Inf. Comput. Sci., 2004, 44, 168–169. 10.1021/ci034174m CASPubMedWeb of Science®Google Scholar Volume35, Issue17April 27, 2004 ReferencesRelatedInformation

Summary Cellular signalling pathways, mediating receptor activity to nuclear gene activation, are generally regarded as feed forward cascades. We analyse measured data of a partially observed signalling pathway and address the question of possible feed-back cycling of involved biochemical components between the nucleus and cytoplasm. First we address the question of cycling in general, starting from basic assumptions about the system. We reformulate the problem as a statistical test leading to likelihood ratio tests under non-standard conditions. We find that the modelling approach without cycling is rejected. Afterwards, to differentiate two different transport mechanisms within the nucleus, we derive the appropriate dynamical models which lead to two systems of ordinary differential equations. To compare both models we apply a statistical testing procedure that is based on bootstrap distributions. We find that one of both transport mechanisms leads to a dynamical model which is rejected whereas the other model is satisfactory.

BACKGROUND:Chronic transplant nephropathy remains a poorly defined inflammatory process that limits the survival rate of most renal transplants. We analyzed the gene profile of chronically rejected kidney transplants to identify candidate genes that characterize chronic transplant nephropathy.METHODS:To distinguish genes present in normal renal tissue or specific for end-stage renal failure, we compared the gene profiles of 13 chronically rejected kidney transplants with 16 normal kidneys and 12 end-stage polycystic kidneys using a 7K human cDNA microarray. After elimination of genes with signals close to background, 2190 genes were available for statistical analysis.RESULTS:More than 20% of the examined genes were significantly regulated when compared with the expression level of normal renal tissue (P<0.0003). Hierarchic clustering based on 571 genes differentiated normal and transplant tissue, and transplant and polycystic kidney tissue. Most of these genes encoded proteins involved in cellular metabolism, transport, signaling, transcriptional activation, adhesion, and the immune response. Notably, comprehensive gene profiling of chronically rejected kidneys revealed two distinct subsets of chronically rejected transplants. Neither clinical data nor histology could explain this genetic heterogeneity.CONCLUSIONS:Microarray analysis of rejected kidneys may help to define different entities of transplant nephropathy, reflecting the multifactorial cause of chronic rejection.

A master equation approach to the numerical solution of option pricing models is developed. The basic idea of the approach is to consider the Black–Scholes equation as the macroscopic equation of an underlying mesoscopic stochastic option price variable. The dynamics of the latter is constructed and formulated in terms of a master equation. The numerical efficiency of the approach is demonstrated by means of stochastic simulation of the mesoscopic process for both European and American options.

To obtain a systems-level understanding of a biological system, the authors conducted quantitative dynamic experiments from which the system structure and the parameters have to be deduced. Since biological systems have to cope with different environmental conditions, certain properties are often robust with respect to variations in some of the parameters. Hence, it is important to use optimal experimental design considerations in advance of the experiments to improve the information content of the measurements. Using the MAP-Kinase pathway as an example, the authors present a simulation study investigating the application of different optimality criteria. It is demonstrated that experimental design significantly improves the parameter estimation accuracy and also reveals difficulties in parameter estimation due to robustness.

High-throughput development of catalysts, initiators, and polymeric materials combines automated parallel catalyst synthesis and automated polymerization reactors. The reactors can be additionally equipped with on-line monitoring (ReactIR from Mettler) based on ATR-FT-IR technique. This powerful tool has proven to be a very valuable probe for high-throughput experiments. During copolymerizations of ethene and 1-hexene monomers, the ReactIR was used to monitor the 1-hexene conversion as well as polymer formation, polymer concentration, and polymer composition. This gives access to information on catalyst activity, activation and deactivation times of the catalyst, polymerization kinetics, copolymerization parameters, and the degree of homogeneity of the resulting copolymers. The technology is especially useful for solution copolymerization. The spectrometer can be applied in the lab as well as in pilot plants and production facilities where rapid on-line analyses are useful for product quality control.