Bidirectional linkage of DNA barcodes for the multiplexed mapping of higher-order protein interactions in cells.

Capturing the full complexity of the diverse hierarchical interactions in the protein interactome is challenging. Here we report a DNA-barcoding method for the multiplexed mapping of pairwise and higher-order protein interactions and their dynamics within cells. The method leverages antibodies conjugated with barcoded DNA strands that can bidirectionally hybridize and covalently link to linearize closely spaced interactions within individual 3D protein complexes, encoding and decoding the protein constituents and the interactions among them. By mapping protein interactions in cancer cells and normal cells, we found that tumour cells exhibit a larger diversity and abundance of protein complexes with higher-order interactions. In biopsies of human breast-cancer tissue, the method accurately identified the cancer subtype and revealed that higher-order protein interactions are associated with cancer aggressiveness.

Outcome-based analytical performance specifications: current status and future challenges.

Analytical performance specifications (APS) based on outcomes refer to how 'good' the analytical performance of a test needs to be to do more good than harm to the patient. Analytical performance of a measurand affects its clinical performance. Without first setting clinical performance requirements, it is difficult to define how good analytically the test needs to be to meet medical needs. As testing is indirectly linked to health outcomes through clinical decisions on patient management, often simulation-based studies are used to assess the impact of analytical performance on the probability of clinical outcomes which is then translated to Model 1b APS according to the Milan consensus. This paper discusses the related key definitions, concepts and considerations that should assist in finding the most appropriate methods for deriving Model 1b APS. We review the advantages and limitations of published methods and discuss the criteria for transferability of Model 1b APS to different settings. We consider that the definition of the clinically acceptable misclassification rate is central to Model 1b APS. We provide some examples and guidance on a more systematic approach for first defining the clinical performance requirements for tests and we also highlight a few ideas to tackle the future challenges associated with providing outcome-based APS for laboratory testing.

Next-Generation Patient-Based Real-Time Quality Control Models.

Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBRTQC algorithms have advanced in parallel with developments in computer science and the increased availability of more powerful computers. The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. However, until this review, there has been no critical comparison of these. The PBRTQC algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted. As Artificial Intelligence tools become more available to laboratories, user-friendly and computationally efficient, the major disadvantages, such as complexity and the need for high computing resources, are reduced and become attractive to implement in PBRTQC applications.

Applying the Milan models to setting analytical performance specifications - considering all the information.

Analytical performance specifications (APS) are used for decisions about the required analytical quality of pathology tests to meet clinical needs. The Milan models, based on clinical outcome, biological variation, or state of the art, were developed to provide a framework for setting APS. An approach has been proposed to assign each measurand to one of the models based on a defined clinical use, physiological control, or an absence of quality information about these factors. In this paper we propose that in addition to such assignment, available information from all models should be considered using a risk-based approach that considers the purpose and role of the actual test in a clinical pathway and its impact on medical decisions and clinical outcomes in addition to biological variation and the state-of-the-art. Consideration of APS already in use and the use of results in calculations may also need to be considered to determine the most appropriate APS for use in a specific setting.

Biological Variation Estimates for Plasma Copeptin and Clinical Implications.

BACKGROUND: Plasma copeptin measurement is useful for the differential diagnoses of polyuria-polydipsia syndrome. It has also been proposed as a prognostic marker for cardiovascular diseases. However, limited information is available about the within- (CVI) and between-subject (CVG) biological variation (BV). This study presents BV estimates for copeptin in healthy individuals. METHODS: Samples were collected weekly from 41 healthy subjects over 5 weeks and analyzed using the BRAHMS Copeptin proAVP KRYPTOR assay after at least 8 h of food and fluid abstinence. Outlier detection, variance homogeneity, and trend analysis were performed followed by CV-ANOVA for BV and analytical variation (CVA) estimation with 95% confidence intervals. Reference change values (RCVs), index of individuality (II), and analytical performance specification (APS) were also calculated. RESULTS: The analysis included 178 results from 20 males and 202 values from 21 females. Copeptin concentrations were significantly higher in males than in females (mean 8.5 vs 5.2 pmol/L, P < 0.0001). CVI estimates were 18.0% (95% CI, 15.4%-21.6%) and 19.0% (95% CI, 16.4%-22.6%), for males and females, respectively; RCVs were -35% (decreasing value) and 54% (increasing value). There was marked individuality for copeptin. No result exceeded the diagnostic threshold (>21.4 pmol/L) for arginine vasopressin resistance. CONCLUSIONS: The availability of BV data allows for refined APS and associated II, and RCVs applicable as aids in the serial monitoring of patients with specific diseases such as heart failure. The BV estimates are only applicable in subjects who abstained from oral intake due to the rapid and marked effects of fluids on copeptin physiology.

The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures.

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers, and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.

High-density lipoprotein cholesterol subfraction HDL2 is associated with improved endothelial function in systemic lupus erythematosus.

OBJECTIVE: Patients with systemic lupus erythematosus (SLE) have increased risk of premature atherosclerosis but the exact mechanisms remains unclear. Flow-mediated dilatation (FMD) is an established non-invasive assessment of vascular endothelial function. Lipoprotein subfractions may be better predictors of FMD than conventional cholesterol measurements. We tested the hypothesis that lipoprotein subfractions are independently associated with FMD. METHODS: Forty-one consecutive adult patients with SLE without known cardiovascular risk factors or disease were recruited in this cross-sectional study. Endothelial function and early atherosclerosis were assessed by brachial FMD and common carotid artery (CCA) intima-media thickness (IMT). High-density lipoprotein (HDL)/low-density lipoprotein (LDL) subfractions were measured. Machine learning models were also constructed to predict FMD and CCA IMT. RESULTS: Median FMD was 4.48% (IQR 5.00%) while median IMT was 0.54 mm (IQR 0.12 mm). Univariate analysis showed lower LDL1 (r=-0.313, p<0.05) and higher HDL2 subfractions (r=0.313, p<0.05) were significantly associated with higher log-transformed FMD. In a multiple linear regression model, HDL2 (ß=0.024, SE=0.012, p<0.05) remained an independent predictor of higher FMD after adjusting for age, body mass index, LDL1 and systolic blood pressure. The machine learning model included parameters such as HDL2 (positive association), prednisolone dose, LDL cholesterol and LDL1 for prediction of FMD (r=0.433, p<0.01). Age, LDL cholesterol and systolic blood pressure were independently associated with higher CCA IMT after adjusting for body mass index and HDL2. CONCLUSIONS: HDL 2, a large HDL particle, was independently associated with greater FMD and may be a biomarker of vascular health in SLE.

Ensuring quality in 17OHP mass spectrometry measurement: an international study assessing isomeric steroid interference.

OBJECTIVES: Interference from isomeric steroids is a potential cause of disparity between mass spectrometry-based 17-hydroxyprogesterone (17OHP) results. We aimed to assess the proficiency of mass spectrometry laboratories to report 17OHP in the presence of known isomeric steroids. METHODS: A series of five samples were prepared using a previously demonstrated commutable approach. These samples included a control (spiked to 15.0 nmol/L 17OHP) and four challenge samples further enriched with equimolar concentrations of 17OHP isomers (11α-hydroxyprogesterone, 11ß-hydroxyprogesterone, 16α-hydroxyprogesterone or 21-hydroxyprogesterone). These samples were distributed to 38 participating laboratories that reported serum 17OHP results using mass spectrometry in two external quality assurance programs. The result for each challenge sample was compared to the control sample submitted by each participant. RESULTS: Twenty-six laboratories (68 % of distribution) across three continents returned results. Twenty-five laboratories used liquid chromatography-tandem mass spectrometry (LC-MS/MS), and one used gas chromatography-tandem mass spectrometry to measure 17OHP. The all-method median of the control sample was 14.3 nmol/L, ranging from 12.4 to 17.6 nmol/L. One laboratory had results that approached the lower limit of tolerance (minus 17.7 % of the control sample), suggesting the isomeric steroid caused an irregular result. CONCLUSIONS: Most participating laboratories demonstrated their ability to reliably measure 17OHP in the presence of the four clinically relevant isomeric steroids. The performance of the 12 (32 %) laboratories that did not engage in this activity remains unclear. We recommend that all laboratories offering LC-MS/MS analysis of 17OHP in serum, plasma, or dried bloodspots determine that the isomeric steroids are appropriately separated.

A review of clinical guidelines, laboratory recommendations and external quality assurance programs for monoclonal gammopathy testing.

Monoclonal gammopathy (MG) is a spectrum of diseases ranging from the benign asymptomatic monoclonal gammopathy of undetermined significance to the malignant multiple myeloma. Clinical guidelines and laboratory recommendations have been developed to inform best practices in the diagnosis, monitoring, and management of MG. In this review, the pathophysiology, relevant laboratory testing recommended in clinical practice guidelines and laboratory recommendations related to MG testing and reporting are examined. The clinical guidelines recommend serum protein electrophoresis, serum immunofixation and serum free light chain measurement as initial screening. The laboratory recommendations omit serum immunofixation as it offers limited additional diagnostic value. The laboratory recommendations offer guidance on reporting findings beyond monoclonal protein, which was not required by the clinical guidelines. The clinical guidelines suggested monitoring total IgA concentration by turbidimetry or nephelometry method if the monoclonal protein migrates in the non-gamma region, whereas the laboratory recommendations make allowance for involved IgM and IgG. Additionally, several external quality assurance programs for MG protein electrophoresis and free light chain testing are also appraised. The external quality assurance programs show varied assessment criteria for protein electrophoresis reporting and unit of measurement. There is also significant disparity in reported monoclonal protein concentrations with wide inter-method analytical variation noted for both monoclonal protein quantification and serum free light chain measurement, however this variation appears smaller when the same method was used. Greater harmonization among laboratory recommendations and reporting format may improve clinical interpretation of MG testing.

The LEAP checklist for laboratory evaluation and analytical performance characteristics reporting of clinical measurement procedures.

Reporting a measurement procedure and its analytical performance following method evaluation in a peer-reviewed journal is an important means for clinical laboratory practitioners to share their findings. It also represents an important source of evidence base to help others make informed decisions about their practice. At present, there are significant variations in the information reported in laboratory medicine journal publications describing the analytical performance of measurement procedures. These variations also challenge authors, readers, reviewers and editors in deciding the quality of a submitted manuscript. The International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Method Evaluation Protocols (IFCC WG-MEP) developed a checklist and recommends its adoption to enable a consistent approach to reporting method evaluation and analytical performance characteristics of measurement procedures in laboratory medicine journals. It is envisioned that the LEAP checklist will improve the standardisation of journal publications describing method evaluation and analytical performance characteristics, improving the quality of the evidence base that is relied upon by practitioners.

Impact of analytical imprecision and bias on patient classification.

OBJECTIVES: An increase in analytical imprecision and/or the introduction of bias can affect the interpretation of quantitative laboratory results. In this study, we explore the impact of varying assay imprecision and bias introduction on the classification of patients based on fixed thresholds. METHODS: Simple spreadsheets (Microsoft Excel) were constructed to simulate conditions of assay deterioration, expressed as coefficient of variation and bias (in percentages). The impact on patient classification was explored based on fixed interpretative limits. A combined matrix of imprecision and bias of 0%, 2%, 4%, 6%, 8%, and 10% (tool 1) as well as 0%, 2%, 5%, 10%, 15%, and 20% (tool 2) was simulated, respectively. The percentage of patients who were reclassified following the addition of simulated imprecision and bias was summarized and presented in tables and graphs. RESULTS: The percentage of patients who were reclassified increased with increasing/decreasing magnitude of imprecision and bias. The impact of imprecision lessens with increasing bias such that at high biases, the bias becomes the dominant cause for reclassification. CONCLUSIONS: The spreadsheet tools, available as Supplemental Material, allow laboratories to visualize the impact of additional analytical imprecision and bias on the classification of their patients when applied to locally extracted historical results.

Dynamic altruistic cooperation within breast tumors.

BACKGROUND: Social behaviors such as altruism, where one self-sacrifices for collective benefits, critically influence an organism's survival and responses to the environment. Such behaviors are widely exemplified in nature but have been underexplored in cancer cells which are conventionally seen as selfish competitive players. This multidisciplinary study explores altruism and its mechanism in breast cancer cells and its contribution to chemoresistance. METHODS: MicroRNA profiling was performed on circulating tumor cells collected from the blood of treated breast cancer patients. Cancer cell lines ectopically expressing candidate miRNA were used in co-culture experiments and treated with docetaxel. Ecological parameters like relative survival and relative fitness were assessed using flow cytometry. Functional studies and characterization performed in vitro and in vivo include proliferation, iTRAQ-mass spectrometry, RNA sequencing, inhibition by small molecules and antibodies, siRNA knockdown, CRISPR/dCas9 inhibition and fluorescence imaging of promoter reporter-expressing cells. Mathematical modeling based on evolutionary game theory was performed to simulate spatial organization of cancer cells. RESULTS: Opposing cancer processes underlie altruism: an oncogenic process involving secretion of IGFBP2 and CCL28 by the altruists to induce survival benefits in neighboring cells under taxane exposure, and a self-sacrificial tumor suppressive process impeding proliferation of altruists via cell cycle arrest. Both processes are regulated concurrently in the altruists by miR-125b, via differential NF-κB signaling specifically through IKKß. Altruistic cells persist in the tumor despite their self-sacrifice, as they can regenerate epigenetically from non-altruists via a KLF2/PCAF-mediated mechanism. The altruists maintain a sparse spatial organization by inhibiting surrounding cells from adopting the altruistic fate via a lateral inhibition mechanism involving a GAB1-PI3K-AKT-miR-125b signaling circuit. CONCLUSIONS: Our data reveal molecular mechanisms underlying manifestation, persistence and spatial spread of cancer cell altruism. A minor population behave altruistically at a cost to itself producing a collective benefit for the tumor, suggesting tumors to be dynamic social systems governed by the same rules of cooperation in social organisms. Understanding cancer cell altruism may lead to more holistic models of tumor evolution and drug response, as well as therapeutic paradigms that account for social interactions. Cancer cells constitute tractable experimental models for fields beyond oncology, like evolutionary ecology and game theory.