Aleksandra Karolak

Enhanced sampling simulations of DNA step parameters.

A novel approach for the selection of step parameters as reaction coordinates in enhanced sampling simulations of DNA is presented. The method uses three atoms per base and does not require coordinate overlays or idealized base pairs. This allowed for a highly efficient implementation of the calculation of all step parameters and their Cartesian derivatives in molecular dynamics simulations. Good correlation between the calculated and actual twist, roll, tilt, shift, and slide parameters is obtained, while the correlation with rise is modest. The method is illustrated by its application to the methylated and unmethylated 5′‐CATGTGACGTCACATG‐3′ double stranded DNA sequence. One‐dimensional umbrella simulations indicate that the flexibility of the central CG step is only marginally affected by methylation.

Importance of local interactions for the stability of inhibitory helix 1 in apo Ets-1.

Inhibitory helix 1 (HI-1) of the Ets-1 human transcription factor unfolds upon binding the target DNA sequence. To identify the interactions that stabilize HI-1 in the apo state, we performed replica exchange and molecular dynamics simulations of various apo Ets-1 constructs. The simulations indicate the importance of local interactions for the stability of HI-1. The HI-2 and H4 helices stabilize the helical state of HI-1 through specific residue-residue contacts and macrodipolar interactions. The amount of stabilization in small length HI-1+H2 and HI-1+H4 constructs was similar to that in the protein. The studies suggest that the partial unfolding of Ets-1 upon DNA binding can be achieved by the removal of just a few specific local contacts.

Towards personalized computational oncology: from spatial models of tumour spheroids, to organoids, to tissues

A main goal of mathematical and computational oncology is to develop quantitative tools to determine the most effective therapies for each individual patient. This involves predicting the right drug to be administered at the right time and at the right dose. Such an approach is known as precision medicine. Mathematical modelling can play an invaluable role in the development of such therapeutic strategies, since it allows for relatively fast, efficient and inexpensive simulations of a large number of treatment schedules in order to find the most effective. This review is a survey of mathematical models that explicitly take into account the spatial architecture of three-dimensional tumours and address tumour development, progression and response to treatments. In particular, we discuss models of epithelial acini, multicellular spheroids, normal and tumour spheroids and organoids, and multi-component tissues. Our intent is to showcase how these in silico models can be applied to patient-specific data to assess which therapeutic strategies will be the most efficient. We also present the concept of virtual clinical trials that integrate standard-of-care patient data, medical imaging, organ-on-chip experiments and computational models to determine personalized medical treatment strategies.

Mathematical Modeling of Tumor Organoids: Toward Personalized Medicine

Three-dimensional organoid and organoidal cell cultures can recreate certain aspects of in vivo tumors and tumor microenvironments, and thus can be used to test intratumoral interactions and tumor response to treatments. In silico organoid models, when based on biological or clinical data, are an invaluable tool for hypothesis testing, and provide an opportunity to explore experimental conditions beyond what is feasible experimentally. In this chapter, three different approaches to building in silico organoids are described together with methods for integration with experimental or clinical data. The first model will be used to determine the mechanisms of development of breast tumor acini, based on their in vitro morphology. The second model will be used to predict conditions for the most effective cellular uptake of therapies targeting pancreatic cancers that incorporate intravital microscopy data. The third model will provide a procedure for assessing patients’ response to chemotherapeutic treatments, based on the biopsy data. For each of the models, a protocol will be proposed indicating how it can be used to generate testable hypotheses or predictions. These models can help biologists in determining what experiments should be performed in the laboratory. They can also assist clinicians in assessing cancer patients’ response to a given therapy and their risk of tumor recurrence.

BII stability and base step flexibility of N6-adenine methylated GATC motifs

The effect of N6-adenine methylation on the flexibility and shape of palindromic GATC sequences has been investigated by molecular dynamics simulations. Variations in DNA backbone geometry were observed, which were dependent on the degree of methylation and the identity of the bases. While the effect was small, more frequent BI to BII conversions were observed in the GA step of hemimethylated DNA. The increased BII population of the hemimethylated system positively correlated with increased stacking interactions between methylated adenine and guanine, while stacking interactions decreased at the TC step for the fully methylated strand. The flexibility of the AT and TC steps was marginally affected by methylation, in a fashion that was correlated with stacking interactions. The facilitated BI to BII conversion in hemimethylated strands might be of importance for SeqA selectivity and binding.

Targeting Ligand Specificity Linked to Tumor Tissue Topological Heterogeneity via Single-Cell Micro-Pharmacological Modeling

Targeted therapy has held promise to be a successful anticancer treatment due to its specificity towards tumor cells that express the target receptors. However, not all targeting drugs used in the clinic are equally effective in tumor eradication. To examine which biochemical and biophysical properties of targeted agents are pivotal for their effective distribution inside the tumor and their efficient cellular uptake, we combine mathematical micro-pharmacological modeling with in vivo imaging of targeted human xenograft tumors in SCID mice. The mathematical model calibrated to experimental data was used to explore properties of the targeting ligand (diffusion and affinity) and ligand release schemes (rates and concentrations) with a goal to identify the properties of cells and ligands that enable high receptor saturation. By accounting for heterogeneities typical of in vivo tumors, our model was able to identify cell- and tissue-level barriers to efficient drug uptake. This work provides a base for utilizing experimentally measurable properties of a ligand-targeted agent and patient-specific attributes of the tumor tissue to support the development of novel targeted imaging agents and for improvement in their delivery to individual tumor cells.

Micropharmacology: An In Silico Approach for Assessing Drug Efficacy Within a Tumor Tissue

Systemic chemotherapy is one of the main anticancer treatments used for most kinds of clinically diagnosed tumors. However, the efficacy of these drugs can be hampered by the physical attributes of the tumor tissue, such as tortuous vasculature, dense and fibrous extracellular matrix, irregular cellular architecture, tumor metabolic gradients, and non-uniform expression of the cell membrane receptors. This can impede the transport of therapeutic agents to tumor cells in sufficient quantities. In addition, tumor microenvironments undergo dynamic spatio-temporal changes during tumor progression and treatment, which can also obstruct drug efficacy. To examine ways to improve drug delivery on a cell-to-tissue scale (single-cell pharmacology), we developed the microscale pharmacokinetics/pharmacodynamics (microPKPD) modeling framework. Our model is modular and can be adjusted to include only the mathematical equations that are crucial for a biological problem under consideration. This modularity makes the model applicable to a broad range of pharmacological cases. As an illustration, we present two specific applications of the microPKPD methodology that help to identify optimal drug properties. The hypoxia-activated drugs example uses continuous drug concentrations, diffusive–advective transport through the tumor interstitium, and passive transmembrane drug uptake. The targeted therapy example represents drug molecules as discrete particles that move by diffusion and actively bind to cell receptors. The proposed modeling approach takes into account the explicit tumor tissue morphology, its metabolic landscape and/or specific receptor distribution. All these tumor attributes can be assessed from patients’ diagnostic biopsies; thus, the proposed methodology can be developed into a tool suitable for personalized medicine, such as neoadjuvant chemotherapy.

Molecular Dynamics Simulations of 5-Hydroxycytosine Damaged DNA

Oxidation of cytosine is a leading cause of mutations and can lead to cancer. Here we report molecular dynamics simulations that characterized the structure and flexibility of 5-hydroxycytosine damaged DNA. A total of four systems were studied: undamaged DNA, damaged DNA base paired to a matching guanine, damaged DNA base paired to a mismatching adenine, and the corresponding undamaged mismatched strand. The simulations showed high spatial similarity between undamaged and damaged DNA; however, the matched damaged strand had greater overtwisting flexibility, and for both the matched and unmatched strands sugar puckering was much more flexible at the damaged site. The mismatch introduced larger changes, notably a loss in hydrogen bonding and a gain in stacking interactions, as well as effects on base pair and step geometry and solvation. Implications for damage recognition are discussed.

Abstract 4650: Quantitative assessment of the intracellular uptake of chlorotoxin in a U87 human glioma mouse model for the targeted drug delivery system

This study quantitatively evaluates the tumor cell-targeting capabilities and intracellular uptake pattern of chlorotoxin (CTX) when delivered intratumorally (IT) and intravenously (IV) using subcutaneous (SC) U87 human glioblastoma mouse model. CTX is a scorpion-derived polypeptide that selectively binds to tumor cells of neuroectodermal origin, such as glioma and a wide range of other tumor cells, but not normal cells. The quantification of CTX cellular uptake presented here will assist in the further development of our tumor-targeting drug delivery system (DDS) consisting of a chemotherapeutic encapsulated in nonionic surfactant vesicles embedded in a thermosensitive cross-linked chitosan hydrogel, which has affinity for MUC1 receptor overexpressed on many tumor cells, including low-differentiated glioma. CTX addition to the DDS will serve as a second tumor-targeting molecule. In this study, U87 human glioma cells were implanted SC in the flank of nude athymic/ncr/nus mice. When tumors reached approximately the volume of 0.25 cm3, mice were injected either IT or IV (tail vein) with 50 μl of 100 μg CTX or phosphate buffer saline (PBS) as a control. The tumors were harvested at 5 minutes post IT injection or 7 hours post IV injection, fixed, sectioned at 5 μm, and followed by either immunofluorescence or immunocytochemistry using anti-CTX primary antibody and AlexaFluor-594 conjugated secondary antibody or immunoperoxidase- AEC kit, and evaluated by confocal or scanning microscopy, respectively. CTX levels were compared between three different tumor regions (A, B, and C; A = injection site marked by methylene blue dye, C = most distant from injection site, B = equidistant between these two) after direct IT injection and compared to CTX levels in tumor tissues following IV injection. Quantitative evaluation of CTX levels was performed with ImageJ software, while further intracellular analysis of CTX presence utilized MATLAB system. CTX was found to be evenly distributed between cells within each region post IT injection, but decreased in intensity from the injection site (A) toward the tumor edge. With region A set at 100% CTX intensity, the levels decreased to 23.7% (in region B), and 2.1% (in region C), compared to 1.8% post IV injection. Our previous in vitro studies showed CTX localization near the nucleus in U87 glioma cells but not in normal human astrocytes. Current evaluation of tumor z-sections quantified levels of CTX inside U87 glioma cells in vivo. These results confirm the specificity of CTX uptake by U87 human glioma cells in vitro and in vivo with CTX tissue levels post IV injection, which is comparable to those post IT injection in the distant C tumor region. This proves CTX is an important second tumor-targeting molecule for our DDS system. Citation Format: Alan D. Roberts, Joseph O. Johnson, Aleksandra Karolak, Norma Alcantar, Katarzyna A. Rejniak, Marzenna Wiranowska. Quantitative assessment of the intracellular uptake of chlorotoxin in a U87 human glioma mouse model for the targeted drug delivery system [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4650.

Using Photoacoustic Calorimetry to Study the cis- to trans- Photoisomerization of the [Ru(II)(2,2’-bipyridine)2(H2O)2]2+ Complex in Aqueous Solution

Graphical Abstract The mechanism associated with the cis- to trans-photoisomerization of Ru(II)(2,2’-bipyridine)2(H2O)2 ([Ru(bpy)2(H2O)2]2+) complex in water has been examined using photoacoustic calorimetry (PAC) and density functional theory (DFT). Photolysis of the cis-[Ru(bpy)2(H2O)2]2+ complex results in a ΔH of -27 ±5 kcal mol–1 and ΔV of 0.1±2 mL mol–1. The DFT calculations give a ΔEcis-trans of +12 kcal mol–1, indicating that the observed ΔH contains significant contributions from changes in solvation. The DFT analysis of putative intermediates [Ru(bpy)2(H2O)]2+ and [Ru(bpy)2(H2O)3]2+ suggests the possibility of an associative mechanism for the isomerization process.