Use of computed tomography to assess subcutaneous drug dispersion with recombinant human hyaluronidase PH20 in a swine model.

INTRODUCTION: Subcutaneous (SC) formulations of therapeutics with recombinant human hyaluronidase PH20 (rHuPH20) are currently approved across various disease indications. The rHuPH20-mediated enzymatic degradation of SC hyaluronan (HA) facilitates bulk fluid flow and dispersion of co-administered therapeutics. However, current methods of quantifying dispersion in the SC space are limited. Here, a novel method is outlined to quantify and follow rapid SC volumetric dispersion of a representative therapeutic fluid in the presence of rHuPH20 using computed tomography (CT). METHODS: Ten Yucatan miniature swine were randomized to three groups. Animals received simultaneous infusions of contrast agent (CA) alone (left side of the animal) or in combination with rHuPH20 (right side) at infusion rates of 2.5, 5, or 10 mL/min. Spiral CT scans (1.5 mm thickness) were conducted before and after the infusion and at regular time intervals throughout. Scans were used to create three-dimensional (3D) reconstructions of the fluid pockets and analyze surface area, volume, and sphericity. RESULTS: 3D reconstruction showed increased dispersion of CA with rHuPH20 compared with CA alone, with fenestration and increased dispersion in the craniocaudal and lateromedial directions. The CA with rHuPH20 fluid pockets showed an average increase of 46% in surface area (p = 0.001), a 35% increase in volume (p = 0.001) and a 17% decrease in sphericity post-infusion compared with CA alone at 30 min post-infusion. DISCUSSION: This exploratory study confirms the value of CT imaging as a non-invasive method of assessing real-time spatial and temporal behavior of SC-administered fluids. This technique could help to assess the dispersion pattern of novel rHuPH20 SC co-formulations.

Parallel Accumulation of Tumor Hyaluronan, Collagen, and Other Drivers of Tumor Progression.

Purpose: The tumor microenvironment (TME) evolves to support tumor progression. One marker of more aggressive malignancy is hyaluronan (HA) accumulation. Here, we characterize biological and physical changes associated with HA-accumulating (HA-high) tumors.Experimental Design: We used immunohistochemistry, in vivo imaging of tumor pH, and microdialysis to characterize the TME of HA-high tumors, including tumor vascular structure, hypoxia, tumor perfusion by doxorubicin, pH, content of collagen. and smooth muscle actin (α-SMA). A novel method was developed to measure real-time tumor-associated soluble cytokines and growth factors. We also evaluated biopsies of murine and pancreatic cancer patients to investigate HA and collagen content, important contributors to drug resistance.Results: In immunodeficient and immunocompetent mice, increasing tumor HA content is accompanied by increasing collagen content, vascular collapse, hypoxia, and increased metastatic potential, as reflected by increased α-SMA. In vivo treatment of HA-high tumors with PEGylated recombinant human hyaluronidase (PEGPH20) dramatically reversed these changes and depleted stores of VEGF-A165, suggesting that PEGPH20 may also diminish the angiogenic potential of the TME. Finally, we observed in xenografts and in pancreatic cancer patients a coordinated increase in HA and collagen tumor content.Conclusions: The accumulation of HA in tumors is associated with high tIP, vascular collapse, hypoxia, and drug resistance. These findings may partially explain why more aggressive malignancy is observed in the HA-high phenotype. We have shown that degradation of HA by PEGPH20 partially reverses this phenotype and leads to depletion of tumor-associated VEGF-A165. These results encourage further clinical investigation of PEGPH20. Clin Cancer Res; 24(19); 4798-807. ©2018 AACR.

Technological issues and experimental design of gene association studies.

Genome-wide association studies (GWAS), in which thousands of single-nucleotide polymorphisms (SNPs) spanning the genome are genotyped in individuals who are phenotypically well characterized, -currently represent the most popular strategy for identifying gene regions associated with common -diseases and related quantitative traits. Improvements in technology and throughput capability, development of powerful statistical tools, and more widespread acceptance of pooling-based genotyping approaches have led to greater utilization of GWAS in human genetics research. However, important considerations for optimal experimental design, including selection of the most appropriate genotyping platform, can enhance the utility of the approach even further. This chapter reviews experimental and technological issues that may affect the success of GWAS findings and proposes strategies for developing the most comprehensive, logical, and cost-effective approaches for genotyping given the population of interest.

Why are proteins so robust to site mutations?

There have been repeated observations that proteins are surprisingly robust to site mutations, enduring significant numbers of substitutions with little change in structure, stability, or function. These results are almost paradoxical in light of what is known about random heteropolymers and the sensitivity of their properties to seemingly trivial mutations. To address this discrepancy, the preservation of biological protein properties in the presence of mutation has been interpreted as indicating the independence of selective pressure on such properties. Such results also lead to the prediction that de novo protein design should be relatively easy, in contrast to what is observed. Here, we use a computational model with lattice proteins to demonstrate how this robustness can result from population dynamics during the evolutionary process. As a result, sequence plasticity may be a characteristic of evolutionarily derived proteins and not necessarily a property of designed proteins. This suggests that this robustness must be re-interpreted in evolutionary terms, and has consequences for our understanding of both in vivo and in vitro protein evolution.

Why are proteins marginally stable?

Most globular proteins are marginally stable regardless of size or activity. The most common interpretation is that proteins must be marginally stable in order to function, and so marginal stability represents the results of positive selection. We consider the issue of marginal stability directly using model proteins and the dynamical aspects of protein evolution in populations. We find that the marginal stability of proteins is an inherent property of proteins due to the high dimensionality of the sequence space, without regard to protein function. In this way, marginal stability can result from neutral, non-adaptive evolution. By allowing evolving protein sub-populations with different stability requirements for functionality to complete, we find that marginally stable populations of proteins tend to dominate. Our results show that functionalities consistent with marginal stability have a strong evolutionary advantage, and might arise because of the natural tendency of proteins towards marginal stability.