Identification of Pharmacodynamic Transcript Biomarkers in Response to FGFR Inhibition by AZD4547

The challenge of developing effective pharmacodynamic biomarkers for preclinical and clinical testing of FGFR signaling inhibition is significant. Assays that rely on the measurement of phospho-protein epitopes can be limited by the availability of effective antibody detection reagents. Transcript profiling enables accurate quantification of many biomarkers and provides a broader representation of pathway modulation. To identify dynamic transcript biomarkers of FGFR signaling inhibition by AZD4547, a potent inhibitor of FGF receptors 1, 2, and 3, a gene expression profiling study was performed in FGFR2-amplified, drug-sensitive tumor cell lines. Consistent with known signaling pathways activated by FGFR, we identified transcript biomarkers downstream of the RAS-MAPK and PI3K/AKT pathways. Using different tumor cell lines in vitro and xenografts in vivo, we confirmed that some of these transcript biomarkers (DUSP6, ETV5, YPEL2) were modulated downstream of oncogenic FGFR1, 2, 3, whereas others showed selective modulation only by FGFR2 signaling (EGR1). These transcripts showed consistent time-dependent modulation, corresponding to the plasma exposure of AZD4547 and inhibition of phosphorylation of the downstream signaling molecules FRS2 or ERK. Combination of FGFR and AKT inhibition in an FGFR2-mutated endometrial cancer xenograft model enhanced modulation of transcript biomarkers from the PI3K/AKT pathway and tumor growth inhibition. These biomarkers were detected on the clinically validated nanoString platform. Taken together, these data identified novel dynamic transcript biomarkers of FGFR inhibition that were validated in a number of in vivo models, and which are more robustly modulated by FGFR inhibition than some conventional downstream signaling protein biomarkers

Reproducibility of the NanoString 22-gene molecular subgroup assay for improved prognostic prediction of medulloblastoma

Medulloblastoma is the most frequent malignant brain tumor in children. Four medulloblastoma molecular subgroups, MBSHH , MBWNT , MBGRP3 and MBGRP4 , have been identified by integrated high-throughput platforms. Recently, a 22-gene panel NanoString-based assay was developed for medulloblastoma molecular subgrouping, but the robustness of this assay has not been widely evaluated. Mutations in the gene for human telomerase reverse transcriptase (hTERT) have been found in medulloblastomas and are associated with distinct molecular subtypes. This study aimed to implement the 22-gene panel in a Brazilian context, and to associate the molecular profile with patients' clinical-pathological features. Formalin-fixed, paraffin-embedded (FFPE) medulloblastoma samples (n = 104) from three Brazilian centers were evaluated. Expression profiling of the 22-gene panel was performed by NanoString and a Canadian series (n = 240) was applied for training phase. hTERT mutations were analyzed by PCR followed by direct Sanger sequencing and the molecular profile was associated with patients' clinicopathological features. Overall, 65% of the patients were male, average age at diagnosis was 18 years and 7% of the patients presented metastasis at diagnosis. The molecular classification was attained in 100% of the cases, with the following frequencies: MBSHH (n = 51), MBWNT (n = 19), MBGRP4 (n = 19) and MBGRP3 (n = 15). The MBSHH and MBGRP3 subgroups were associated with older and younger patients, respectively. The MBGRP4 subgroup exhibited the lowest 5-year cancer-specific overall survival (OS), yet in the multivariate analysis, only metastasis at diagnosis and surgical resection were associated with OS. hTERT mutations were detected in 29% of the cases and were associated with older patients, increased hTERT expression and MBSHH subgroup. The 22-gene panel provides a reproducible assay for molecular subgrouping of medulloblastoma FFPE samples in a routine setting and is well-suited for future clinical trials.We thank Barretos Cancer Hospital and FINEP (MCTI/ FINEP/MS/SCTIE/DECIT - BioPlat 1302/13) for partially funding the present study. LFL is supported by Public Ministry of Labor Campinas (Research, Prevention and Education of Occupational Cancer) in Campinas, Brazil. RMR is sponsored by National Council for Scientific and Technological Development (CNPq, Brazil).info:eu-repo/semantics/publishedVersio

Nucleic acid extraction from formalin-fixed paraffin-embedded cancer cell line samples: a trade off between quantity and quality?

Background: Advanced genomic techniques such as Next-Generation-Sequencing (NGS) and gene expression profiling, including NanoString, are vital for the development of personalised medicines, as they enable molecular disease classification. This has become increasingly important in the treatment of cancer, aiding patient selection. However, it requires efficient nucleic acid extraction often from formalin-fixed paraffin-embedded tissue (FFPE). Methods: Here we provide a comparison of several commercially available manual and automated methods for DNA and/or RNA extraction from FFPE cancer cell line samples from Qiagen, life Technologies and Promega. Differing extraction geometric mean yields were evaluated across each of the kits tested, assessing dual DNA/RNA extraction vs. specialised single extraction, manual silica column based extraction techniques vs. automated magnetic bead based methods along with a comparison of subsequent nucleic acid purity methods, providing a full evaluation of nucleic acids isolated. Results: Out of the four RNA extraction kits evaluated the RNeasy FFPE kit, from Qiagen, gave superior geometric mean yields, whilst the Maxwell 16 automated method, from Promega, yielded the highest quality RNA by quantitative real time RT-PCR. Of the DNA extraction kits evaluated the PicoPure DNA kit, from Life Technologies, isolated 2–14× more DNA. A miniaturised qPCR assay was developed for DNA quantification and quality assessment. Conclusions: Careful consideration of an extraction kit is necessary dependent on quality or quantity of material required. Here we provide a flow diagram on the factors to consider when choosing an extraction kit as well as how to accurately quantify and QC the extracted material

Development of Rapid Detection and Genetic Characterization of Salmonella in Poultry Breeder Feeds

Salmonella is a leading cause of foodborne illness in the United States, with poultry and poultry products being a primary source of infection to humans. Poultry may carry some Salmonella serovars without any signs or symptoms of disease and without causing any adverse effects to the health of the bird. Salmonella may be introduced to a flock by multiple environmental sources, but poultry feed is suspected to be a leading source. Detecting Salmonella in feed can be challenging because low levels of the bacteria may not be recovered using traditional culturing techniques. Numerous detection methodologies have been examined over the years for quantifying Salmonella in feeds and many have proven to be effective for Salmonella isolation and detection in a variety of feeds. However, given the potential need for increased detection sensitivity, molecular detection technologies may the best candidate for developing rapid sensitive methods for identifying small numbers of Salmonella in the background of large volumes of feed. Several studies have been done using polymerase chain reaction (PCR) assays and commercial kits to detect Salmonella spp. in a wide variety of feed sources. In addition, DNA array technology has recently been utilized to track the dissemination of a specific Salmonella serotype in feed mills. This review will discuss the processing of feeds and potential points in the process that may introduce Salmonella contamination to the feed. Detection methods currently used and the need for advances in these methods also will be discussed. Finally, implementation of rapid detection for optimizing control methods to prevent and remove any Salmonella contamination of feeds will be considered

C6-ceramide synergistically potentiates the anti-tumor effects of histone deacetylase inhibitors via AKT dephosphorylation and α-tubulin hyperacetylation both in vitro and in vivo

Histone deacetylase inhibitors (HDACIs) have shown promising anti-tumor effects for a variety of malignancies, however, many tumors are reportedly resistant to them. In this study, we made a novel discovery that co-administration of HDACIs (Trichostatin A (TSA) and others) and exogenous cell-permeable short-chain ceramide (C6) results in striking increase in cancer cell death and apoptosis in multiple cancer cells. These events are associated with perturbations in diverse cell signaling pathways, including inactivation of Akt/mTOR and increase in α-tubulin acetylation (both in vivo and in vitro). TSA interacts in a highly synergistic manner with C6-ceramide to disrupt HDAC6/protein phosphatase 1 (PP1)/tubulin complex, to induce α-tubulin hyperacetylation, and to release and activate PP1, which then leads to AKT dephosphorylation and eventually causes cancer cell death. Interestingly, TSA itself results in short-term ceramide accumulation, which as a result of metabolic (glycosylation) removal, does not result in evident increase of cancer cell death. However, adding C6-ceramide led to a very pronounced increase in ceramide level and marked increase in cell death. Importantly, the effective synergistic anti-tumor activity of TSA plus C6-ceramide is also seen in in vivo mice xenograft pancreatic and ovarian cancer models, indicating that this regimen (HDACI plus C6-ceramide) may represent a more effective form of therapy against pancreatic and ovarian carcinoma

Factors That Affect Large Subunit Ribosomal DNA Amplicon Sequencing Studies of Fungal Communities: Classification Method, Primer Choice, and Error

Nuclear large subunit ribosomal DNA is widely used in fungal phylogenetics and to an increasing extent also amplicon-based environmental sequencing. The relatively short reads produced by next-generation sequencing, however, makes primer choice and sequence error important variables for obtaining accurate taxonomic classifications. In this simulation study we tested the performance of three classification methods: 1) a similarity-based method (BLAST + Metagenomic Analyzer, MEGAN); 2) a composition-based method (Ribosomal Database Project naïve Bayesian classifier, NBC); and, 3) a phylogeny-based method (Statistical Assignment Package, SAP). We also tested the effects of sequence length, primer choice, and sequence error on classification accuracy and perceived community composition. Using a leave-one-out cross validation approach, results for classifications to the genus rank were as follows: BLAST + MEGAN had the lowest error rate and was particularly robust to sequence error; SAP accuracy was highest when long LSU query sequences were classified; and, NBC runs significantly faster than the other tested methods. All methods performed poorly with the shortest 50–100 bp sequences. Increasing simulated sequence error reduced classification accuracy. Community shifts were detected due to sequence error and primer selection even though there was no change in the underlying community composition. Short read datasets from individual primers, as well as pooled datasets, appear to only approximate the true community composition. We hope this work informs investigators of some of the factors that affect the quality and interpretation of their environmental gene surveys

Antimicrobial Resistance in Escherichia coli

Multidrug resistance in Escherichia coli has become a worrying issue that is increasingly observed in human but also in veterinary medicine worldwide. E. coli is intrinsically susceptible to almost all clinically relevant antimicrobial agents, but this bacterial species has a great capacity to accumulate resistance genes, mostly through horizontal gene transfer. The most problematic mechanisms in E. coli correspond to the acquisition of genes coding for extended-spectrum β-lactamases (conferring resistance to broad-spectrum cephalosporins), carbapenemases (conferring resistance to carbapenems), 16S rRNA methylases (conferring pan-resistance to aminoglycosides), plasmid-mediated quinolone resistance (PMQR) genes (conferring resistance to [fluoro]quinolones), and mcr genes (conferring resistance to polymyxins). Although the spread of carbapenemase genes has been mainly recognized in the human sector but poorly recognized in animals, colistin resistance in E. coli seems rather to be related to the use of colistin in veterinary medicine on a global scale. For the other resistance traits, their cross-transfer between the human and animal sectors still remains controversial even though genomic investigations indicate that extended- spectrum β-lactamase producers encountered in animals are distinct from those affecting humans. In addition, E. coli of animal origin often also show resistances to other—mostly older—antimicrobial agents, including tetracyclines, phenicols, sulfonamides, trimethoprim, and fosfomycin. Plasmids, especially multiresistance plasmids, but also other mobile genetic elements, such as transposons and gene cassettes in class 1 and class 2 integrons, seem to play a major role in the dissemination of resistance genes. Of note, coselection and persistence of resistances to critically important antimicrobial agents in human medicine also occurs through the massive use of antimicrobial agents in veterinary medicine, such as tetracyclines or sulfonamides, as long as all those determinants are located on the same genetic elements

A quantitative systems pharmacology consortium approach to managing immunogenicity of therapeutic proteins

Immunogenicity is a major challenge in drug development and patient care. Currently, most efforts are dedicated to the elimination of the unwanted immune responses through T‐cell epitope prediction and protein engineering. However, because it is unlikely that this approach will lead to complete eradication of immunogenicity, we propose that quantitative systems pharmacology models should be developed to predict and manage immunogenicity. The potential impact of such a mechanistic model‐based approach is precedented by applications of physiologically‐based pharmacokinetics

The desmosome and pemphigus

Desmosomes are patch-like intercellular adhering junctions (“maculae adherentes”), which, in concert with the related adherens junctions, provide the mechanical strength to intercellular adhesion. Therefore, it is not surprising that desmosomes are abundant in tissues subjected to significant mechanical stress such as stratified epithelia and myocardium. Desmosomal adhesion is based on the Ca2+-dependent, homo- and heterophilic transinteraction of cadherin-type adhesion molecules. Desmosomal cadherins are anchored to the intermediate filament cytoskeleton by adaptor proteins of the armadillo and plakin families. Desmosomes are dynamic structures subjected to regulation and are therefore targets of signalling pathways, which control their molecular composition and adhesive properties. Moreover, evidence is emerging that desmosomal components themselves take part in outside-in signalling under physiologic and pathologic conditions. Disturbed desmosomal adhesion contributes to the pathogenesis of a number of diseases such as pemphigus, which is caused by autoantibodies against desmosomal cadherins. Beside pemphigus, desmosome-associated diseases are caused by other mechanisms such as genetic defects or bacterial toxins. Because most of these diseases affect the skin, desmosomes are interesting not only for cell biologists who are inspired by their complex structure and molecular composition, but also for clinical physicians who are confronted with patients suffering from severe blistering skin diseases such as pemphigus. To develop disease-specific therapeutic approaches, more insights into the molecular composition and regulation of desmosomes are required

A Review of SHV Extended-Spectrum β-Lactamases: Neglected Yet Ubiquitous

Microbial Biotechnolog