Human Organotypic Lung Tumor Models: Suitable For Preclinical 18F-FDG PET-Imaging

Development of predictable in vitro tumor models is a challenging task due to the enormous complexity of tumors in vivo. The closer the resemblance of these models to human tumor characteristics, the more suitable they are for drug-development and –testing. In the present study, we generated a complex 3D lung tumor test system based on acellular rat lungs. A decellularization protocol was established preserving the architecture, important ECM components and the basement membrane of the lung. Human lung tumor cells cultured on the scaffold formed cluster and exhibited an up-regulation of the carcinoma-associated marker mucin1 as well as a reduced proliferation rate compared to respective 2D culture. Additionally, employing functional imaging with 2-deoxy-2-[¹⁸F]fluoro-D-glucose positron emission tomography (FDG-PET) these tumor cell cluster could be detected and tracked over time. This approach allowed monitoring of a targeted tyrosine kinase inhibitor treatment in the in vitro lung tumor model non-destructively. Surprisingly, FDG-PET assessment of single tumor cell cluster on the same scaffold exhibited differences in their response to therapy, indicating heterogeneity in the lung tumor model. In conclusion, our complex lung tumor test system features important characteristics of tumors and its microenvironment and allows monitoring of tumor growth and -metabolism in combination with functional imaging. In longitudinal studies, new therapeutic approaches and their long-term effects can be evaluated to adapt treatment regimes in future.

18F-fluoroethyl-L-tyrosine positron emission tomography for the differential diagnosis of tumefactive multiple sclerosis versus glioma: A case report

Large demyelinating inflammatory central nervous system (CNS) lesions may present with contrast enhancement on magnetic resonance imaging and may mimic CNS tumors such as glioma. In ambiguous cases, new diagnostic tools that may be helpful for distinguishing between demyelinating inflammatory and neoplastic CNS lesions are required. The current study presents the case of a patient with a large contrast-enhanced frontal brain lesion, who was initially diagnosed with tumefactive multiple sclerosis. Following the progression of the brain lesion, an ¹⁸F-fluoroethyl-L-tyrosine positron emission tomography (¹⁸F-FET PET) was performed, revealing markedly elevated static ¹⁸F-FET uptake parameters along with time activity-curves consistent with glioma. Subsequently, a biopsy was undertaken, which confirmed the presence of anaplastic oligoastrocytoma. This case illustrates that ¹⁸F-FET PET may provide useful diagnostic information in cases where distinction between neoplastic and demyelinating inflammatory CNS lesions is challenging. However, further systematic and prospective analyses are warranted to explore the value of this method in this setting.

Evaluation of the delivered activity of yttrium-90 resin microspheres using sterile water and 5 % glucose during administration

BACKGROUND

The purpose of this study is to evaluate the impact of switching from sterile water to 5 % glucose (G5W) for the administration of yttrium-90 ((90)Y)-resin microspheres on the total activity of (90)Y administered (expressed as a proportion of the prescribed/calculated activity), as well as the number of cases of stasis and the reported incidence of discomfort during the selective internal radiation therapy (SIRT) procedure.

METHODS

In December 2013, we switched from sterile water to G5W for the administration of SIRT using (90)Y resin microspheres in all patients. This retrospective observational single-center case series describes our experience in the months preceding and after the switch. Apart from the change in administration medium, the protocol for SIRT was otherwise identical.

RESULTS

One hundred and four SIRT procedures were performed on 78 patients (45 male, mean age: 63 years, range: 31-87 years) with either unresectable hepatocellular carcinoma, cholangiocarcinoma, or chemorefractory liver-dominant metastatic cancer. Compared with sterile water, the whole prescribed activity was administered in significantly more procedures with G5W: 85 vs. 22 %; p < 0.0001. A significantly higher proportion of the calculated activity was administered with G5W: 96.1 ± 11.0 % vs. 77.4 ± 24.3 % (p < 0.0001). G5W procedures were also associated with a significantly lower incidence of stasis (28 vs. 11 % procedures; p = 0.02) and mild-to-moderate upper abdominal pain during the procedure (1.8 vs. 44 % procedures; p < 0.0001).

CONCLUSIONS

Replacing sterile water with isotonic G5W during administration favorably impacts on the safety of SIRT, eliminates and/or minimizes flow reductions and stasis/reflux during administration of (90)Y resin microspheres, improves percentage activity delivered, and reduces peri-procedural pain.

Complete characterization of the edited transcriptome of the mitochondrion of Physarum polycephalum using deep sequencing of RNA

RNAs transcribed from the mitochondrial genome of Physarum polycephalum are heavily edited. The most prevalent editing event is the insertion of single Cs, with Us and dinucleotides also added at specific sites. The existence of insertional editing makes gene identification difficult and localization of editing sites has relied upon characterization of individual cDNAs. We have now determined the complete mitochondrial transcriptome of Physarum using Illumina deep sequencing of purified mitochondrial RNA. We report the first instances of A and G insertions and sites of partial and extragenic editing in Physarum mitochondrial RNAs, as well as an additional 772 C, U and dinucleotide insertions. The notable lack of antisense RNAs in our non-size selected, directional library argues strongly against an RNA-guided editing mechanism. Also of interest are our findings that sites of C to U changes are unedited at a significantly higher frequency than insertional editing sites and that substitutional editing of neighboring sites appears to be coupled. Finally, in addition to the characterization of RNAs from 17 predicted genes, our data identified nine new mitochondrial genes, four of which encode proteins that do not resemble other proteins in the database. Curiously, one of the latter mRNAs contains no editing sites.

A puzzle in DNA biophysics

In this issue, Lee et al. report the experimental temperature-dependence of the unzipping force for two natural DNA sequences. For both sequences, the curves show an anomaly at temperatures around 40 degrees C. In this brief contribution, we stress that the anomaly is not easily explained within the established theoretical models for the biophysics of DNA. As this puzzle questions our basic understanding of DNA, it must be resolved, most likely by a combination of additional experiments and new theoretical work.

Dynamics of intramolecular recognition: base-pairing in DNA/RNA near and far from equilibrium

The physics of the base-pairing interaction in DNA and RNA molecules plays a fundamental role in biology. Past experimental and theoretical research has led to a fairly complete and quantitative understanding of the equilibrium properties such as the different phases, the melting behavior, and the response to slow stretching. The non-equilibrium behavior is even richer than might be expected on the basis of thermodynamics. However, the non-equilibrium behavior is also far less understood. Here, we review different theoretical approaches to the study of base-pairing thermodynamics and kinetics, and illustrate the rich phenomenology with several examples that use these approaches.

A statistical analysis of RNA folding algorithms through thermodynamic parameter perturbation

Computational RNA secondary structure prediction is rather well established. However, such prediction algorithms always depend on a large number of experimentally measured parameters. Here, we study how sensitive structure prediction algorithms are to changes in these parameters. We found already that for changes corresponding to the actual experimental error to which these parameters have been determined, 30% of the structure are falsely predicted whereas the ground state structure is preserved under parameter perturbation in only 5% of all the cases. We establish that base-pairing probabilities calculated in a thermal ensemble are viable although not a perfect measure for the reliability of the prediction of individual structure elements. Here, a new measure of stability using parameter perturbation is proposed, and its limitations are discussed.

Computational prediction of RNA editing sites

MOTIVATION

Some organisms edit their messenger RNA resulting in differences between the genomic sequence for a gene and the corresponding messenger RNA sequence. This difference complicates experimental and computational attempts to find and study genes in organisms with RNA editing even if the full genomic sequence is known. Nevertheless, knowledge of these editing sites is crucial for understanding the editing machinery of these organisms.

RESULTS

We present a computational technique that predicts the position of editing sites in the genomic sequence. It uses a statistical approach drawing on the protein sequences of related genes and general features of editing sites of the organism. We apply the method to the mitochondrion of the slime mold Physarum polycephalum. It correctly predicts over 90% of the amino acids and over 70% of the editing sites.

Fluctuations and slow variables in genetic networks

Computer simulations of large genetic networks are often extremely time consuming because, in addition to the biologically interesting translation and transcription reactions, many less interesting reactions like DNA binding and dimerizations have to be simulated. It is desirable to use the fact that the latter occur on much faster timescales than the former to eliminate the fast and uninteresting reactions and to obtain effective models of the slow reactions only. We use three examples of self-regulatory networks to show that the usual reduction methods where one obtains a system of equations of the Hill type fail to capture the fluctuations that these networks exhibit due to the small number of molecules; moreover, they may even miss describing the behavior of the average number of proteins. We identify the inclusion of fast-varying variables in the effective description as the cause for the failure of the traditional schemes. We suggest a different effective description, which entails the introduction of an additional species, not present in the original networks, that is slowly varying. We show that this description allows for a very efficient simulation of the reduced system while retaining the correct fluctuations and behavior of the full system. This approach ought to be applicable to a wide range of genetic networks.

The role of dimerization in noise reduction of simple genetic networks

Fluctuations are an intrinsic property of genetic networks due to the small number of interacting molecules. We study the role of dimerization reactions in controlling these fluctuations in a simple genetic circuit with negative feedback. We compare two different pathways. In the dimeric pathway the proteins to be regulated form dimers in solution that afterward bind to an operator site and inhibit transcription. In the monomeric pathway monomers bind to the operator site and then recruit another monomer to form a dimer directly on the DNA. We find that while both pathways implement the same negative feedback mechanism, the protein number fluctuations in the dimeric pathway are drastically reduced compared to the monomeric pathway. This difference in the ability to reduce fluctuations may be of importance in the design of genetic networks.

Statistical mechanics of secondary structures formed by random RNA sequences

The formation of secondary structures by a random RNA sequence is studied as a model system for the sequence-structure problem omnipresent in biopolymers. Several toy energy models are introduced to allow detailed analytical and numerical studies. First, a two-replica calculation is performed. By mapping the two-replica problem to the denaturation of a single homogeneous RNA molecule in six-dimensional embedding space, we show that sequence disorder is perturbatively irrelevant, i.e., an RNA molecule with weak sequence disorder is in a molten phase where many secondary structures with comparable total energy coexist. A numerical study of various models at high temperature reproduces behaviors characteristic of the molten phase. On the other hand, a scaling argument based on the external statistics of rare regions can be constructed to show that the low-temperature phase is unstable to sequence disorder. We performed a detailed numerical study of the low-temperature phase using the droplet theory as a guide, and characterized the statistics of large-scale, low-energy excitations of the secondary structures from the ground state structure. We find the excitation energy to grow very slowly (i.e., logarithmically) with the length scale of the excitation, suggesting the existence of a marginal glass phase. The transition between the low-temperature glass phase and the high-temperature molten phase is also characterized numerically. It is revealed by a change in the coefficient of the logarithmic excitation energy, from being disorder dominated to being entropy dominated.

Asymmetric exclusion process and extremal statistics of random sequences

A mapping is established between sequence alignment, one of the most commonly used tools of computational biology, at a certain choice of scoring parameters and the asymmetric exclusion process, one of the few exactly solvable models of nonequilibrium physics. The statistical significance of sequence alignments is characterized through studying the total hopping current of the discrete time and space version of the asymmetric exclusion process.

Force-induced denaturation of RNA

We quantitatively describe an RNA molecule under the influence of an external force exerted at its two ends as in a typical single-molecule experiment. Our calculation incorporates the interactions between nucleotides by using the experimentally determined free energy rules for RNA secondary structure and models the polymeric properties of the exterior single-stranded regions explicitly as elastic freely jointed chains. We find that despite complicated secondary structures, force-extension curves are typically smooth in quasi-equilibrium. We identify and characterize two sequence/structure-dependent mechanisms that, in addition to the sequence-independent entropic elasticity of the exterior single-stranded regions, are responsible for the smoothness. These involve compensation between different structural elements on which the external force acts simultaneously and contribution of suboptimal structures, respectively. We estimate how many features a force-extension curve recorded in nonequilibrium, where the pulling proceeds faster than rearrangements in the secondary structure of the molecule, could show in principle. Our software is available to the public through an "RNA-pulling server."

The estimation of statistical parameters for local alignment score distributions

The distribution of optimal local alignment scores of random sequences plays a vital role in evaluating the statistical significance of sequence alignments. These scores can be well described by an extreme-value distribution. The distribution's parameters depend upon the scoring system employed and the random letter frequencies; in general they cannot be derived analytically, but must be estimated by curve fitting. For obtaining accurate parameter estimates, a form of the recently described 'island' method has several advantages. We describe this method in detail, and use it to investigate the functional dependence of these parameters on finite-length edge effects.

Rapid assessment of extremal statistics for gapped local alignment

The statistical significance of gapped local alignments is characterized by analyzing the extremal statistics of the scores obtained from the alignment of random amino acid sequences. By identifying a complete set of linked clusters, "islands," we devise a method which accurately predicts the extremal score statistics by using only one to a few pairwise alignments. The success of our method relies crucially on the link between the statistics of island scores and extremal score statistics. This link is motivated by heuristic arguments, and firmly established by extensive numerical simulations for a variety of scoring parameter settings and sequence lengths. Our approach is several orders of magnitude faster than the widely used shuffling method, since island counting is trivially incorporated into the basic Smith-Waterman alignment algorithm with minimal computational cost, and all islands are counted in a single alignment. The availability of a rapid and accurate significance estimation method gives one the flexibility to fine tune scoring parameters to detect weakly homologous sequences and obtain optimal alignment fidelity.