Change in lung tumor volume as a biomarker of treatment response: a critical review of the evidence.

SPECIFIC AIM: To review the evidence indicating that volumetric image analysis of computed tomography scans meets specifications for qualification as a biomarker in clinical trials or the management of individual patients with lung cancer. METHODS: Claims of value were broken down into questions about technical feasibility, accuracy, the precision of measurement, sensitivity, the correlations with health outcomes, and the risks of producing misleading information. For each claim, the pertinent literature was reviewed. RESULTS: Technical feasibility has now been shown, but only in limited contexts. Accuracy has been demonstrated, but only for tumors with favorable anatomical features. Measurement error still makes the assessment of change in small nodules precarious in diagnostic settings unless rigorous image acquisition and analysis procedures are followed. Precision is sufficient in some larger masses to make volumetrics a sensitive biomarker. In a few trials, correlations with clinical outcomes have been higher for volumetric-based measures than for unidimensional or bidimensional diameters. Value in clinical practice settings and clinical trials has been suggested, but not proven. CONCLUSION: The weight of the evidence indicates there are circumstances in which volumetric image analysis adds value to clinical trial science and the practice of medicine.

An indirect method to measure trimerization constants using surface plasmon resonance.

The ability of surface plasmon resonance to precisely measure kinetic binding constants was exploited here to indirectly evaluate the thermodynamic dissociation trimerization constant (K(d)) of a designed chimeric protein, IZN-23, derived from an isoleucine zipper and a portion of the N-terminal helix residues of HIV-1 gp41. The method uses two monoclonal antibodies (mAbs) that display different off-rates when binding the monomeric or trimeric IZN-23. A detailed description of the data analysis strategy employed to unravel the K(d) trimerization constant from the observed off-rate kinetic values is presented, and the potential exploitation of this technique in different fields is highlighted.

Quantifying the phosphorylation timescales of receptor-ligand complexes: a Markovian matrix-analytic approach.

Cells interact with the extracellular environment by means of receptor molecules on their surface. Receptors can bind different ligands, leading to the formation of receptor-ligand complexes. For a subset of receptors, called receptor tyrosine kinases, binding to ligand enables sequential phosphorylation of intra-cellular residues, which initiates a signalling cascade that regulates cellular function and fate. Most mathematical modelling approaches employed to analyse receptor signalling are deterministic, especially when studying scenarios of high ligand concentration or large receptor numbers. There exist, however, biological scenarios where low copy numbers of ligands and/or receptors need to be considered, or where signalling by a few bound receptor-ligand complexes is enough to initiate a cellular response. Under these conditions stochastic approaches are appropriate, and in fact, different attempts have been made in the literature to measure the timescales of receptor signalling initiation in receptor-ligand systems. However, these approaches have made use of numerical simulations or approximations, such as moment-closure techniques. In this paper, we study, from an analytical perspective, the stochastic times to reach a given signalling threshold for two receptor-ligand models. We identify this time as an extinction time for a conveniently defined auxiliary absorbing continuous time Markov process, since receptor-ligand association/dissociation events can be analysed in terms of quasi-birth-and-death processes. We implement algorithmic techniques to compute the different order moments of this time, as well as the steady-state probability distribution of the system. A novel feature of the approach introduced here is that it allows one to quantify the role played by each kinetic rate in the timescales of signal initiation, and in the steady-state probability distribution of the system. Finally, we illustrate our approach by carrying out numerical studies for the vascular endothelial growth factor and one of its receptors, the vascular endothelial growth factor receptor of human endothelial cells.

Automated rodent in situ muscle contraction assay and myofiber organization analysis in sarcopenia animal models.

Age-related sarcopenia results in frailty and decreased mobility, which are associated with increased falls and long-term disability in the elderly. Given the global increase in lifespan, sarcopenia is a growing, unmet medical need. This report aims to systematically characterize muscle aging in preclinical models, which may facilitate the development of sarcopenia therapies. Naïve rats and mice were subjected to noninvasive micro X-ray computed tomography (micro-CT) imaging, terminal in situ muscle function characterizations, and ATPase-based myofiber analysis. We developed a Definiens (Parsippany, NJ)-based algorithm to automate micro-CT image analysis, which facilitates longitudinal in vivo muscle mass analysis. We report development and characterization of translational in situ skeletal muscle performance assay systems in rat and mouse. The systems incorporate a custom-designed animal assay stage, resulting in enhanced force measurement precision, and LabVIEW (National Instruments, Austin, TX)-based algorithms to support automated data acquisition and data analysis. We used ATPase-staining techniques for myofibers to characterize fiber subtypes and distribution. Major parameters contributing to muscle performance were identified using data mining and integration, enabled by Labmatrix (BioFortis, Columbia, MD). These technologies enabled the systemic and accurate monitoring of muscle aging from a large number of animals. The data indicated that longitudinal muscle cross-sectional area measurement effectively monitors change of muscle mass and function during aging. Furthermore, the data showed that muscle performance during aging is also modulated by myofiber remodeling factors, such as changes in myofiber distribution patterns and changes in fiber shape, which affect myofiber interaction. This in vivo muscle assay platform has been applied to support identification and validation of novel targets for the treatment of sarcopenia.

X-ray computed tomography: semiautomated volumetric analysis of late-stage lung tumors as a basis for response assessments.

Background. This study presents a semiautomated approach for volumetric analysis of lung tumors and evaluates the feasibility of using volumes as an alternative to line lengths as a basis for response evaluation criteria in solid tumors (RECIST). The overall goal for the implementation was to accurately, precisely, and efficiently enable the analyses of lesions in the lung under the guidance of an operator. Methods. An anthropomorphic phantom with embedded model masses and 71 time points in 10 clinical cases with advanced lung cancer was analyzed using a semi-automated workflow. The implementation was done using the Cognition Network Technology. Results. Analysis of the phantom showed an average accuracy of 97%. The analyses of the clinical cases showed both intra- and interreader variabilities of approximately 5% on average with an upper 95% confidence interval of 14% and 19%, respectively. Compared to line lengths, the use of volumes clearly shows enhanced sensitivity with respect to determining response to therapy. Conclusions. It is feasible to perform volumetric analysis efficiently with high accuracy and low variability, even in patients with late-stage cancer who have complex lesions.