Impact of preanalytical variables on the analysis of biological fluids in proteomic studies

Although proteomic technologies have been enthusiastically embraced in the field of biomarker discovery and particularly with biological fluids, it is increasingly being recognized that pre‐analytical effects, i.e. those occurring prior to the point of actual sample analysis and including factors such as sample processing and storage, can exert marked influences on the results obtained. Such effects have been recognized already for specific analytes in clinical chemistry, but with the increasing sensitivity and resolution of the newer technologies, such effects are potentially even more marked. The challenge of translating initial findings into clinical application requires such issues to be addressed at a very early stage in study design and this paper reviews the current knowledge of the potential impact of pre‐analytical factors on proteomic studies of biological fluids

Bifunctional Rhodamine Probes of Myosin Regulatory Light Chain Orientation in Relaxed Skeletal Muscle Fibers

The orientation of the regulatory light chain (RLC) region of the myosin heads in relaxed skinned fibers from rabbit psoas muscle was investigated by polarized fluorescence from bifunctional rhodamine (BR) probes cross-linking pairs of cysteine residues introduced into the RLC. Pure 1:1 BR-RLC complexes were exchanged into single muscle fibers in EDTA rigor solution for 30 min at 30°C; ∼60% of the native RLC was removed and stoichiometrically replaced by BR-RLC, and >85% of the BR-RLC was located in the sarcomeric A-bands. The second- and fourth-rank order parameters of the orientation distributions of BR dipoles linking RLC cysteine pairs 100-108, 100-113, 108-113, and 104-115 were calculated from polarized fluorescence intensities, and used to determine the smoothest RLC orientation distribution—the maximum entropy distribution—consistent with the polarized fluorescence data. Maximum entropy distributions in relaxed muscle were relatively broad. At the peak of the distribution, the “lever” axis, linking Cys(707) and Lys(843) of the myosin heavy chain, was at 70–80° to the fiber axis, and the “hook” helix (Pro(830)–Lys(843)) was almost coplanar with the fiber and lever axes. The temperature and ionic strength of the relaxing solution had small but reproducible effects on the orientation of the RLC region

Orientation of the Essential Light Chain Region of Myosin in Relaxed, Active, and Rigor Muscle

The orientation of the ELC region of myosin in skeletal muscle was determined by polarized fluorescence from ELC mutants in which pairs of introduced cysteines were cross-linked by BSR. The purified ELC-BSRs were exchanged for native ELC in demembranated fibers from rabbit psoas muscle using a trifluoperazine-based protocol that preserved fiber function. In the absence of MgATP (in rigor) the ELC orientation distribution was narrow; in terms of crystallographic structures of the myosin head, the LCD long axis linking heavy-chain residues 707 and 843 makes an angle (β) of 120–125° with the filament axis. This is ∼30° larger than the broader distribution determined previously from RLC probes, suggesting that, relative to crystallographic structures, the LCD is bent between its ELC and RLC regions in rigor muscle. The ELC orientation distribution in relaxed muscle had two broad peaks with β ∼70° and ∼110°, which may correspond to the two head regions of each myosin molecule, in contrast with the single broad distribution of the RLC region in relaxed muscle. During isometric contraction the ELC orientation distribution peaked at β ∼105°, similar to that determined previously for the RLC region

UK Multicenter Prospective Evaluation of the Leibovich Score in Localized Renal Cell Carcinoma: Performance has Altered Over Time.

OBJECTIVE: To examine changes in outcome by the Leibovich score using contemporary and historic cohorts of patients presenting with renal cell carcinoma (RCC) PATIENTS AND METHODS: Prospective observational multicenter cohort study, recruiting patients with suspected newly diagnosed RCC. A historical cohort of patients was examined for comparison. Metastasis-free survival (MFS) formed the primary outcome measure. Model discrimination and calibration were evaluated using Cox proportional hazard regression and the Kaplan-Meier method. Overall performance of the Leibovich model was assessed by estimating explained variation. RESULTS: Seven hundred and six patients were recruited between 2011 and 2014 and RCC confirmed in 608 (86%) patients. Application of the Leibovich score to patients with localized clear cell RCC in this contemporary cohort demonstrated good model discrimination (c-index = 0.77) but suboptimal calibration, with improved MFS for intermediate- and high-risk patients (5-year MFS 85% and 50%, respectively) compared to the original Leibovich cohort (74% and 31%) and a historic (1998-2006) UK cohort (76% and 37%). The proportion of variation in outcome explained by the model is low and has declined over time (28% historic vs 22% contemporary UK cohort). CONCLUSION: Prognostic models are widely employed in patients with localized RCC to guide surveillance intensity and clinical trial selection. However, the majority of the variation in outcome remains unexplained by the Leibovich model and, over time, MFS rates among intermediate- and high-risk classified patients have altered. These findings are likely to have implications for all such models used in this setting