Prostate cancer relapsing from antiandrogen therapies can exhibit variant histology with altered lineage marker expression, suggesting that lineage plasticity facilitates therapeutic resistance. The mechanisms underlying prostate cancer lineage plasticity are incompletely understood. Studying mouse models, we demonstrate that Rb1 loss facilitates lineage plasticity and metastasis of prostate adenocarcinoma initiated by Pten mutation. Additional loss of Trp53 causes resistance to antiandrogen therapy. Gene expression profiling indicates that mouse tumors resemble human prostate cancer neuroendocrine variants; both mouse and human tumors exhibit increased expression of epigenetic reprogramming factors such as Ezh2 and Sox2. Clinically relevant Ezh2 inhibitors restore androgen receptor expression and sensitivity to antiandrogen therapy. These findings uncover genetic mutations that enable prostate cancer progression; identify mouse models for studying prostate cancer lineage plasticity; and suggest an epigenetic approach for extending clinical responses to antiandrogen therapy.

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Histone methylation is a dynamic process that participates in a diverse array of cellular processes and has been found to associate with cancer. Recently, several histone demethylases have been identified that catalyze the removal of methylation from histone H3 lysine residues. Through bioinformatic and biochemical analysis, we identified JARID1B as a H3K4 demethylase. Overexpression of JARID1B resulted in loss of tri-, di-, and monomethyl H3K4 but did not affect other histone lysine methylations. In vitro biochemical experiments demonstrated that JARID1B directly catalyzes the demethylation. The enzymatic activity requires the JmjC domain and uses Fe(II) and ␣-ketoglutarate as cofactors. Furthermore, we found that JARID1B is up-regulated in prostate cancer tissues, compared with benign prostate samples. We also demonstrated that JARID1B associates with androgen receptor and regulates its transcriptional activity. Thus, we identified JARID1B as a demethylase capable of removing three methyl groups from histone H3 lysine 4 and up-regulated in prostate cancer. Histone methylation plays an important role in regulating chromatin dynamics and transcription (1). Methylation can occur on either arginine or lysine residues (2). Each lysine can undergo three distinct stages of methylation, having either one (mono), two (di), or three (tri) methyl groups covalently bonded to the amine group of the lysine side chain, and arginine can be mono-or dimethylated (3). Depending on specific residues, methylation can either activate or repress transcription. In general, lysine methylation at H3K9, H3K27, and H4K20 is associated with transcriptional repression, whereas methylation at H3K4, H3K36, and H3K79 is associated with transcriptional activation. However, recent findings have blurred this generality. For example, methylation at H3K9 can result in transcriptional activation, and methylation at H3K36 can repress transcription (4, 5).Methylation had long been considered a stable modification, but recent studies have proved otherwise (6-16). The first histone demethylase identified is LSD1, which can remove di-and monomethylation from H3K4 by using an amine oxidase reaction (8). Subsequently, a JmjC domain-containing protein was identified to possess histone demethylase activity, and the JmjC domain was shown as a demethylase signature motif (9). This class of enzymes catalyzes the removal of methylation by using a hydroxylation reaction and required iron and ␣-ketoglutarate as cofactors. Based on this demethylase signature motif, several proteins were identified to be histone lysine demethylases (6,7,(10)(11)(12)(13)(14)(15)(16).Prostate cancer is the most common nonskin cancer and the second leading cause of cancer in America. Histone methylation has been suggested to be associated with prostate cancer. For example, it was demonstrated that histone methylations and acetylations can be used to predict the risk of prostate cancer recurrence (17). In addition, EZH2, a H3K27 methyltransferase, is shown to be involved in progression...

A dynamic model of glucose overflow metabolism in batch and fed-batch cultivations of Escherichia coli W3110 under fully aerobic conditions is presented. Simulation based on the model describes cell growth, respiration, and acetate formation as well as acetate reconsumption during batch cultures, the transition of batch to fed-batch culture, and fed-batch cultures. E. coli excreted acetate only when specific glucose uptake exceeded a critical rate corresponding to a maximum respiration rate. In batch cultures where the glucose uptake was unlimited, the overflow acetate made up to 9. 0 +/- 1.0% carbon/carbon of the glucose consumed. The applicability of the model to dynamic situations was tested by challenging the model with glucose and acetate pulses added during the fed-batch part of the cultures. In the presence of a glucose feed, E. coli utilized acetate 3 times faster than in the absence of glucose. The cells showed no significant difference in maximum specific uptake rate of endogenous acetate produced by glucose overflow and exogenous acetate added to the culture, the value being 0.12-0.18 g g-1 h-1 during the entire fed-batch culture period. Acetate inhibited the specific growth rate according to a noncompetitive model, with the inhibition constant (ki) being 9 g of acetate/L. This was due to the reduced rate of glucose uptake rather than the reduced yield of biomass.

Industrial 20-m3-scale and laboratory-scale aerobic fed-batch processes with Escherichia coli were compared. In the large-scale process the observed overall biomass yield was reduced by 12% at a cell density of 33 g/l and formate accumulated to 50 mg/l during the later constant-feeding stage of the process. Though the dissolved oxygen signal did not show any oxygen limitation, it is proposed that the lowered yield and the formate accumulation are caused by mixed-acid fermentation in local zones where a high glucose concentration induced oxygen limitation. The hypothesis was further investigated in a scale-down reactor with a controlled oxygen-limitation compartment. In this scaledown reactor similar results were obtained: i.e. an observed yield lowered by 12% and formate accumulation to 238 mg/l. The dynamics of glucose uptake and mixed-acid product formation (acetate, formate, D-lactate, succinate and ethanol) were investigated within the 54 s of passage time through the oxygen-limited compartment. Of these, all except succinate and ethanol were formed; however, the products were re-assimilated in the oxygen-sufficient reactor compartment. Formate was less readily assimilated, which accounts for its accumulation. The total volume of the induced-oxygen-limited zones was estimated to be 10% of the whole liquid volume in the large bioreactor. It is also suggested that repeated excretion and re-assimilation of mixed-acid products contribute to the reduced yield during scale-up and that formate analysis is useful for detecting local oxygen deficiency in large-scale E. coli processes.

Cervical cancer is caused by high-risk human papillomaviruses (HPV), in more than half of the worldwide cases by HPV16. Viral DNA integration into the host genome is a frequent mutation in cervical carcinogenesis. Because integration occurs into different genomic locations, it creates unique viral-cellular DNA junctions in every single case. This singularity complicates the precise identification of HPV integration sites enormously. We report here the development of a novel multiplex strategy for sequence determination of HPV16 DNA integration sites. It includes DNA fragmentation and adapter tagging, PCR enrichment of the HPV16 early region, Illumina next-generation sequencing, data processing, and validation of candidate integration sites by junction-PCR. This strategy was performed with 51 cervical cancer samples (47 primary tumors and 4 cell lines). Altogether 75 HPV16 integration sites (3′-junctions) were identified and assigned to the individual samples. By comparing the DNA junctions with the presence of viral oncogene fusion transcripts, 44 tumors could be classified into four groups: Tumors with one transcriptionally active HPV16 integrate (n = 12), tumors with transcribed and silent DNA junctions (n = 8), tumors carrying episomal HPV16 DNA (n = 10), and tumors with one to six DNA junctions, but without fusion transcripts (n = 14). The 3′-breakpoints of integrated HPV16 DNA show a statistically significant (p<0.05) preferential distribution within the early region segment upstream of the major splice acceptor underscoring the importance of deregulated viral oncogene expression for carcinogenesis. Half of the mapped HPV16 integration sites target cellular genes pointing to a direct influence of HPV integration on host genes (insertional mutagenesis). In summary, the multiplex strategy for HPV16 integration site determination worked very efficiently. It will open new avenues for comprehensive mapping of HPV integration sites and for the possible use of HPV integration sites as individualized biomarkers after cancer treatment of patients for the early diagnosis of residual and recurrent disease.

A simple pulse-based method for the determination of the maximum uptake capacities for glucose and oxygen in glucose limited cultivations of E. coli is presented. The method does not depend on the time-consuming analysis of glucose or acetate, and therefore can be used to control the feed rate in glucose limited cultivations, such as fed-batch processes. The application of this method in fed-batch processes of E. coli showed that the uptake capacity for neither glucose nor oxygen is a constant parameter, as often is assumed in fed-batch models. The glucose uptake capacity decreased significantly when the specific growth rate decreased below 0.15 h(-1) and fell to about 0.6 mmol g(-1) h(-1) (mmol per g cell dry weight and hour) at the end of fed-batch fermentations, where specific growth rate was approximately 0.02 h(-1). The oxygen uptake capacity started to decrease somewhat earlier when specific growth rate declined below 0.25 h(-1) and was 5 mmol g(-1) h(-1) at the end of the fermentations. The behavior of both uptake systems is integrated in a dynamic model which allows a better fitting of experimental values for glucose in fed-batch processes in comparison to generally used unstructured kinetic models.

Limited tumor permeability of therapeutic agents is a great challenge faced by current cancer therapy methods. Herein, a kind of near infrared light (NIR)‐driven nanomotor with autonomous movement, targeted ability, hierarchical porous structure, multi‐drugs for cancer chemo/photothermal therapy is designed, prepared and characterized. Further, we establish a method to study the interaction between nanomotors and cells, along with their tumor permeability mechanism, including 2D cellular models, 3D multicellular tumor spheroids and in vivo models. In vivo tumor elimination results verify that the movement behaviour of the nanomotors can greatly facilitate them to eliminate tumor through multiple therapeutic methods. This work tries to establish systematic research and evaluation models, providing strategies to understand the relationship between motion behaviour and tumor permeation efficiency of nanomotors in depth.