The effects of proteasome inhibition on angiogenesis and autophagy in human prostate cancer cells

The proteasome degrades approximately 80% of intracellular proteins to maintain homeostasis. Proteasome inhibition is a validated therapeutic strategy, and currently, proteasome inhibitor bortezomib is FDA approved for the treatment of MM and MCL. Specific pathways affected by proteasome inhibition have been identified, but mechanisms of the anti-tumor effects of proteasome inhibition are not fully characterized and cancer cells display marked heterogeneity in terms of their sensitivity to proteasome inhibitor induced cell death. ^ The antitumor effects of proteasome inhibition involve suppression of tumor angiogenesis and vascular endothelial growth factor (VEGF) expression, but the mechanisms involved have not been clarified. In this dissertation I investigated the mechanisms underlying the effects of two proteasome inhibitors, bortezomib and NPI-0052, on VEGF expression in human prostate cancer cells. I found that proteasome inhibitors selectively downregulated hypoxia inducible factor 1alpha (HIF-1α) protein and its transcriptional activity to inhibit VEGF expression. Mechanistic studies demonstrated that proteasome inhibitors mediate the induction of the unfolded protein response (UPR) and that downregulation of HIF-1α is caused by eukaryotic translation initiation factor 2α (eIF2α) phosphorylation and translation repression. Importantly, I showed that proteasome inhibitors activated the UPR in some cells but not in others. My observation may have implications for the design of combination regimens that are based on exploiting proteasome inhibitor-induced ER stress.^ Although proteasome inhibitors have shown modest activity on prostate cancer, there is general consensus that no single agent is likely to have significant activity in prostate cancer. In the second part of this dissertation I attempted to exploit the effects of proteasome inhibition on the UPR to design a combination therapy that would enhance cancer cell death. Autophagy is a lysosome dependent degradation pathway that functions to eliminate long-lived protein and subcellular structures. Targeting autophagy has been shown to inhibit tumors in preclinical studies. I found that inhibition of autophagy with chloroquine or 3-methyladenine enhanced proteasome inhibitor induced cell death and the effects were associated with increased intracellular stress as marked by aggresome formation. Multiple cancers appear to be resistant to proteasome inhibition treatment alone. The implications of synergy for the combined inhibition of autophagy and the proteasome would likely apply to other cancers aside from prostate cancer. ^

The role of reactive astrocytes in the resistance of melanoma brain metastasis to chemotherapy

Brain metastasis is resistant to chemotherapy while the leaky blood-brain-barrier in brain metastasis can not be the underlying reason. Metastatic tumor cells (“seed”) exploit the host microenvironment (“soil”) for survival advantages. Astrocytes which maintain the homeostasis of the brain microenvironment become reactive subsequent to brain damages and protect neurons from various injuries. We observed reactive astrocytes surrounding and infiltrating into brain metastasis in both clinical specimen and experimental animal model, thus raising a possibility that reactive astrocytes may protect tumor cells from cytotoxic chemotherapeutic drugs. ^ To test this hypothesis, we first generated an immortalized astrocyte cell line from H-2Kb-tsA58 mice. The immortal mouse astrocytes expressed specific markers including GFAP. Scanning electron microscopy demonstrated that astrocytes formed direct physical contact with tumor cells. Moreover, the expression of GFAP by astrocytes was up-regulated subsequent to co-culture with tumor cells, indicating that the co-culture of astrocytes and tumor cells may serve as a model to recapitulate the pathophysiological situation of brain metastasis. ^ In co-culture, astrocytes dramatically reduced apoptosis of tumor cells produced by various chemotherapeutic drugs. This protection effect was not because of culturing cells from different species since mouse fibroblasts did not protect tumor cells from chemotherapy. Furthermore, the protection by astrocytes was completely dependent on a physical contact. ^ Gap junctional communication (GJC) served as this physical contact. Tumor cells and astrocytes both expressed the major component of gap junctional channel—connexin 43 and formed functional GJC as evidenced by the “dye transfer” assay. The blockage of GJC between tumor cells and astrocytes by either specific chemical blocker carbenoxolone (CBX) or by genetically knocking down connexin 43 on astrocytes reversed the chemo-protection. ^ Calcium was the signal molecule transmitted through GJC that rescued tumor cells from chemotherapy. Accumulation of cytoplasmic calcium preceded the progress of apoptosis in tumor cells treated with chemotherapeutic drugs. Furthermore, chelation of accumulated cytoplasmic calcium inhibited the apoptosis of tumor cells treated with chemotherapeutic drugs. Most importantly, astrocytes could “shunt” the accumulated cytoplasmic calcium from tumor cells (treated with chemotherapeutic drug) through GJC. We also used gene expression micro-array to investigate global molecular consequence of tumor cells forming GJC with astrocytes. The data demonstrated that astrocytes (but not fibroblasts), through GJC, up-regulated the expressions of several well known survival genes in tumor cells. ^ In summary, this dissertation provides a novel mechanism underlying the resistance of brain metastasis to chemotherapy, which is due to protection by astrocytes through GJC. Interference with the GJC between astrocytes and tumor cells holds great promise in sensitizing brain metastasis to chemotherapy and improving the prognosis for patients with brain metastasis. ^

Modeling Techniques for the High-Resolution Interpretation of Cryo-Electron Microscopy Reconstructions

Essential biological processes are governed by organized, dynamic interactions between multiple biomolecular systems. Complexes are thus formed to enable the biological function and get dissembled as the process is completed. Examples of such processes include the translation of the messenger RNA into protein by the ribosome, the folding of proteins by chaperonins or the entry of viruses in host cells. Understanding these fundamental processes by characterizing the molecular mechanisms that enable then, would allow the (better) design of therapies and drugs. Such molecular mechanisms may be revealed trough the structural elucidation of the biomolecular assemblies at the core of these processes. Various experimental techniques may be applied to investigate the molecular architecture of biomolecular assemblies. High-resolution techniques, such as X-ray crystallography, may solve the atomic structure of the system, but are typically constrained to biomolecules of reduced flexibility and dimensions. In particular, X-ray crystallography requires the sample to form a three dimensional (3D) crystal lattice which is technically di‑cult, if not impossible, to obtain, especially for large, dynamic systems. Often these techniques solve the structure of the different constituent components within the assembly, but encounter difficulties when investigating the entire system. On the other hand, imaging techniques, such as cryo-electron microscopy (cryo-EM), are able to depict large systems in near-native environment, without requiring the formation of crystals. The structures solved by cryo-EM cover a wide range of resolutions, from very low level of detail where only the overall shape of the system is visible, to high-resolution that approach, but not yet reach, atomic level of detail. In this dissertation, several modeling methods are introduced to either integrate cryo-EM datasets with structural data from X-ray crystallography, or to directly interpret the cryo-EM reconstruction. Such computational techniques were developed with the goal of creating an atomic model for the cryo-EM data. The low-resolution reconstructions lack the level of detail to permit a direct atomic interpretation, i.e. one cannot reliably locate the atoms or amino-acid residues within the structure obtained by cryo-EM. Thereby one needs to consider additional information, for example, structural data from other sources such as X-ray crystallography, in order to enable such a high-resolution interpretation. Modeling techniques are thus developed to integrate the structural data from the different biophysical sources, examples including the work described in the manuscript I and II of this dissertation. At intermediate and high-resolution, cryo-EM reconstructions depict consistent 3D folds such as tubular features which in general correspond to alpha-helices. Such features can be annotated and later on used to build the atomic model of the system, see manuscript III as alternative. Three manuscripts are presented as part of the PhD dissertation, each introducing a computational technique that facilitates the interpretation of cryo-EM reconstructions. The first manuscript is an application paper that describes a heuristics to generate the atomic model for the protein envelope of the Rift Valley fever virus. The second manuscript introduces the evolutionary tabu search strategies to enable the integration of multiple component atomic structures with the cryo-EM map of their assembly. Finally, the third manuscript develops further the latter technique and apply it to annotate consistent 3D patterns in intermediate-resolution cryo-EM reconstructions. The first manuscript, titled An assembly model for Rift Valley fever virus, was submitted for publication in the Journal of Molecular Biology. The cryo-EM structure of the Rift Valley fever virus was previously solved at 27Å-resolution by Dr. Freiberg and collaborators. Such reconstruction shows the overall shape of the virus envelope, yet the reduced level of detail prevents the direct atomic interpretation. High-resolution structures are not yet available for the entire virus nor for the two different component glycoproteins that form its envelope. However, homology models may be generated for these glycoproteins based on similar structures that are available at atomic resolutions. The manuscript presents the steps required to identify an atomic model of the entire virus envelope, based on the low-resolution cryo-EM map of the envelope and the homology models of the two glycoproteins. Starting with the results of the exhaustive search to place the two glycoproteins, the model is built iterative by running multiple multi-body refinements to hierarchically generate models for the different regions of the envelope. The generated atomic model is supported by prior knowledge regarding virus biology and contains valuable information about the molecular architecture of the system. It provides the basis for further investigations seeking to reveal different processes in which the virus is involved such as assembly or fusion. The second manuscript was recently published in the of Journal of Structural Biology (doi:10.1016/j.jsb.2009.12.028) under the title Evolutionary tabu search strategies for the simultaneous registration of multiple atomic structures in cryo-EM reconstructions. This manuscript introduces the evolutionary tabu search strategies applied to enable a multi-body registration. This technique is a hybrid approach that combines a genetic algorithm with a tabu search strategy to promote the proper exploration of the high-dimensional search space. Similar to the Rift Valley fever virus, it is common that the structure of a large multi-component assembly is available at low-resolution from cryo-EM, while high-resolution structures are solved for the different components but lack for the entire system. Evolutionary tabu search strategies enable the building of an atomic model for the entire system by considering simultaneously the different components. Such registration indirectly introduces spatial constrains as all components need to be placed within the assembly, enabling the proper docked in the low-resolution map of the entire assembly. Along with the method description, the manuscript covers the validation, presenting the benefit of the technique in both synthetic and experimental test cases. Such approach successfully docked multiple components up to resolutions of 40Å. The third manuscript is entitled Evolutionary Bidirectional Expansion for the Annotation of Alpha Helices in Electron Cryo-Microscopy Reconstructions and was submitted for publication in the Journal of Structural Biology. The modeling approach described in this manuscript applies the evolutionary tabu search strategies in combination with the bidirectional expansion to annotate secondary structure elements in intermediate resolution cryo-EM reconstructions. In particular, secondary structure elements such as alpha helices show consistent patterns in cryo-EM data, and are visible as rod-like patterns of high density. The evolutionary tabu search strategy is applied to identify the placement of the different alpha helices, while the bidirectional expansion characterizes their length and curvature. The manuscript presents the validation of the approach at resolutions ranging between 6 and 14Å, a level of detail where alpha helices are visible. Up to resolution of 12 Å, the method measures sensitivities between 70-100% as estimated in experimental test cases, i.e. 70-100% of the alpha-helices were correctly predicted in an automatic manner in the experimental data. The three manuscripts presented in this PhD dissertation cover different computation methods for the integration and interpretation of cryo-EM reconstructions. The methods were developed in the molecular modeling software Sculptor (http://sculptor.biomachina.org) and are available for the scientific community interested in the multi-resolution modeling of cryo-EM data. The work spans a wide range of resolution covering multi-body refinement and registration at low-resolution along with annotation of consistent patterns at high-resolution. Such methods are essential for the modeling of cryo-EM data, and may be applied in other fields where similar spatial problems are encountered, such as medical imaging.