FRET Assays for the Identification of C. albicans HSP90-Sba1 and Human HSP90α-p23 Binding Inhibitors.

Heat shock protein 90 (HSP90) is a critical target for anticancer and anti-fungal-infection therapies due to its central role as a molecular chaperone involved in protein folding and activation. In this study, we developed in vitro Förster Resonance Energy Transfer (FRET) assays to characterize the binding of C. albicans HSP90 to its co-chaperone Sba1, as well as that of the homologous human HSP90α to p23. The assay for human HSP90α binding to p23 enables selectivity assessment for compounds aimed to inhibit the binding of C. albicans HSP90 to Sba1 without affecting the physiological activity of human HSP90α. The combination of the two assays is important for antifungal drug development, while the assay for human HSP90α can potentially be used on its own for anticancer drug discovery. Since ATP binding of HSP90 is a prerequisite for HSP90-Sba1/p23 binding, ATP-competitive inhibitors can be identified with the assays. The specificity of binding of fusion protein constructs-HSP90-mNeonGreen (donor) and Sba1-mScarlet-I (acceptor)-to each other in our assay was confirmed via competitive inhibition by both non-labeled Sba1 and known ATP-competitive inhibitors. We utilized the developed assays to characterize the stability of both HSP90-Sba1 and HSP90α-p23 affinity complexes quantitatively. Kd values were determined and assessed for their precision and accuracy using the 95.5% confidence level. For HSP90-Sba1, the precision confidence interval (PCI) was found to be 70-120 (100 ± 20) nM while the accuracy confidence interval (ACI) was 100-130 nM. For HSP90α-p23, PCI was 180-260 (220 ± 40) nM and ACI was 200-270 nM. The developed assays were used to screen a nucleoside-mimetics library of 320 compounds for inhibitory activity against both C. albicans HSP90-Sba1 and human HSP90α-p23 binding. No novel active compounds were identified. Overall, the developed assays exhibited low data variability and robust signal separation, achieving Z factors > 0.5.

Nonsteady-State Electric Circuit in Electrophoresis on Paper: Thermal Consideration of Electrophoretic Lateral-Flow Assays.

Nonsteady-state behaviors are not expected in electric circuits that lack significant capacitance, inductivity, and/or active feedback. Here, we report that electrophoresis on paper─used, e.g., to electrophoretically driven lateral-flow immunoassays (LFIA)─can create a nonsteady-state electric circuit. We studied electrophoresis on 50 × 4 mm nitrocellulose membrane strips utilized in LFIA. The voltage was applied to strip termini immersed in reservoirs with a running buffer. If the electric power of this circuit exceeded approximately 0.5 W, neither the electric current nor the temperature map reached their steady states on a multiminute time scale. The current grew slowly to its maximum and then slowly decreased. The temperature map evolved slowly, with one or more hot spots appearing and disappearing gradually in different positions on the strip. The slow evolution of a temperature map led to the occurrence of a terminal hot spot in which the strip burned. No chaotic behavior was observed, i.e., time dependences of both the current and temperature map were reproducible. We analyzed major processes involved in paper-based electrophoresis and explained the nonsteady-state behavior. Unlike ordinary electric circuits with metal conductors, paper-based electrophoresis involves two slow processes: (i) intense buffer evaporation from hot spots and (ii) buffer supply from the reservoirs by an interplay of the capillary penetration and the electroosmotic flow. These processes affect heat generation and/or dissipation on the strip and, accordingly, the resistivity profile. The slow evolution of the resistivity profile is responsible for the nonsteady-state behavior. The results of our computer modeling support this explanation. The hot spots may have a destructive effect on electrophoretically driven LFIA. To avoid denaturation of immunoreagents, experimentalists should empirically confirm that spatiotemporal temperature maps are compatible with the developed assay.

Fundamental Determinants of the Accuracy of Equilibrium Constants for Affinity Complexes.

The equilibrium constant of a chemical reaction is arguably the key thermodynamic parameter in chemistry; we naturally expect that equilibrium constants are determined accurately. The majority of equilibrium constants determined today are those of binding reactions that form affinity complexes, such as protein-protein, protein-DNA, and protein-small molecule. There is growing awareness that the determination of equilibrium constants for highly stable affinity complexes may be very inaccurate. However, fundamental (i.e., method-independent) determinants of accuracy are poorly understood. Here, we present a study that explicitly shows what the accuracy of equilibrium constants of affinity complexes depends on. This study reveals the critical importance of the choice of concentration of interacting components and creates a theoretical foundation for improving the accuracy of the equilibrium constants. The predicted influence of concentrations on accuracy was confirmed experimentally. The results of this fundamental study provide instructive guidance for experimentalists independently on the method they use.

Automated identification and tracking of cells in Cytometry of Reaction Rate Constant (CRRC).

Cytometry of Reaction Rate Constant (CRRC) is a method for studying cell-population heterogeneity using time-lapse fluorescence microscopy, which allows one to follow reaction kinetics in individual cells. The current and only CRRC workflow utilizes a single fluorescence image to manually identify cell contours which are then used to determine fluorescence intensity of individual cells in the entire time-stack of images. This workflow is only reliable if cells maintain their positions during the time-lapse measurements. If the cells move, the original cell contours become unsuitable for evaluating intracellular fluorescence and the CRRC experiment will be inaccurate. The requirement of invariant cell positions during a prolonged imaging is impossible to satisfy for motile cells. Here we report a CRRC workflow developed to be applicable to motile cells. The new workflow combines fluorescence microscopy with transmitted-light microscopy and utilizes a new automated tool for cell identification and tracking. A transmitted-light image is taken right before every fluorescence image to determine cell contours, and cell contours are tracked through the time-stack of transmitted-light images to account for cell movement. Each unique contour is used to determine fluorescence intensity of cells in the associated fluorescence image. Next, time dependencies of the intracellular fluorescence intensities are used to determine each cell's rate constant and construct a kinetic histogram "number of cells vs rate constant." The new workflow's robustness to cell movement was confirmed experimentally by conducting a CRRC study of cross-membrane transport in motile cells. The new workflow makes CRRC applicable to a wide range of cell types and eliminates the influence of cell motility on the accuracy of results. Additionally, the workflow could potentially monitor kinetics of varying biological processes at the single-cell level for sizable cell populations. Although our workflow was designed ad hoc for CRRC, this cell-segmentation/cell-tracking strategy also represents an entry-level, user-friendly option for a variety of biological assays (i.e., migration, proliferation assays, etc.). Importantly, no prior knowledge of informatics (i.e., training a model for deep learning) is required.

The Sherpa hypothesis: Phenotype-Preserving Disordered Proteins stabilize the phenotypes of neurons and oligodendrocytes.

Intrinsically disordered proteins (IDPs), which can interact with many partner proteins, are central to many physiological functions and to various pathologies that include neurodegeneration. Here, we introduce the Sherpa hypothesis, according to which a subset of stable IDPs that we term Phenotype-Preserving Disordered Proteins (PPDP) play a central role in protecting cell phenotypes from perturbations. To illustrate and test this hypothesis, we computer-simulate some salient features of how cells evolve and differentiate in the presence of either a single PPDP or two incompatible PPDPs. We relate this virtual experiment to the pathological interactions between two PPDPs, α-synuclein and Tubulin Polymerization Promoting Protein/p25, in neurodegenerative disorders. Finally, we discuss the implications of the Sherpa hypothesis for aptamer-based therapies of such disorders.

Electrophoretic Assembly of Antibody-Antigen Complexes Facilitates 1000 Times Improvement in the Limit of Detection of Serological Paper-Based Assay.

Serological assays detect the presence of specific antibodies in blood. There are urgent and important applications for serological point-of-care (POC) assays. However, available detection methods are either insufficiently sensitive or too complex for POC settings. Here, we demonstrate that lateral flow immunoassay (LFIA), which is arguably the simplest universal molecular detection approach, can serve as a methodological platform for highly sensitive serological POC assays if combined with a simple, fast, and inexpensive electrophoretic step. In this work, we compared such electrophoretically driven LFIA (eLFIA) with conventional LFIA for the detection of immunoglobulins G against hepatitis B and C in serum. The limit of detection of eLFIA was proven to be 1000 times lower than that of conventional LFIA and sufficiently low to support clinical serological tests. eLFIA takes less than 10 min, requires only a minor accessory powered by a small 9 V battery, and can be performed by an untrained person in the POC environment using a 3 µL specimen of finger-prick capillary blood.

Streamlined Data Processing for Determination of Equilibrium Dissociation Constants with Accurate Constant via Transient Incomplete Separation (ACTIS).

The determination of accurate equilibrium dissociation constants, Kd, of protein-small molecule complexes is important but challenging as all established methods have inherent sources of inaccuracy. Accurate Constant via Transient Incomplete Separation (ACTIS) is a new method for Kd determination using transient incomplete separation of the complex from the unbound small molecule in a pressure-driven flow inside a capillary. ACTIS is accurate, and its accuracy is invariant to variations in geometries of both the fluidic system and the flow. Furthermore, ACTIS is implemented using a simple fluidic system supporting its accuracy and providing a simple-to-follow/copy template for instrumentation. Despite the simple and robust instrumentation/acquisition, the current data processing workflow is cumbersome, time consuming, and prone to hard-to-trace human errors therefore hindering ACTIS' ability to become a practical reference method for Kd determination. This technical note describes a streamlined workflow for processing ACTIS data; the workflow is implemented as a set of open-source software tools called prACTISed (https://github.com/prACTISedProgram/prACTISed). These tools allow all steps of data processing to be performed in a fast and straightforward fashion. These practical software tools complement the simple instrumentation serving both developers and users of ACTIS.

Electrophoresis-Assisted Multilayer Assembly of Nanoparticles for Sensitive Lateral Flow Immunoassay.

Lateral flow immunoassay (LFIA) is a rapid, simple, and inexpensive point-of-need method. A major limitation of LFIA is a high limit of detection (LOD), which impacts its diagnostic sensitivity. To overcome this limitation, we introduce a signal-enhancement procedure that is performed after completing LFIA and involves controllably moving biotin- and streptavidin-functionalized gold nanoparticles by electrophoresis. The nanoparticles link to immunocomplexes forming multilayer aggregates on the test strip, thus, enhancing the signal. Here, we demonstrate lowering the LOD of hepatitis B surface antigen from approximately 8 to 0.12 ng mL-1 , making it clinically acceptable. Testing 118 clinical samples for hepatitis B showed that signal enhancement increased the diagnostic sensitivity of LFIA from 73 % to 98 % while not affecting its 95 % specificity. Electrophoresis-driven enhancement of LFIA is universal (antigen-independent), takes two minutes, and can be performed by an untrained person.

Bulk Affinity Assays in Aptamer Selection: Challenges, Theory, and Workflow.

Selection of oligonucleotide aptamers involves consecutive rounds of affinity isolation of target-binding oligonucleotides from a random-sequence oligonucleotide library. Every next round produces an aptamer-enriched library with progressively higher fitness for tight binding to the target. The progress of enrichment can only be accurately assessed with bulk affinity assays in which a library is mixed with the target and one of two quantitative parameters, the fraction of the unbound library (R) or the equilibrium dissociation constant (Kd), is determined. These quantitative parameters are used to help researchers make a key decision of either continuing or stopping the selection. Despite the importance of this decision, the suitability of R and Kd for bulk affinity assays has never been studied theoretically, and researchers rely on intuition when choosing between them. Different approaches used for bulk affinity assays expectedly hinder comparative analyses of selections. Our current work has two goals: to give bulk affinity assays a thorough theoretical consideration and to propose a scientifically justified and practical bulk-affinity-assay approach. We postulate a formal criterion of suitability: a quantitative parameter must satisfy the principle of superposition. R satisfies this principle, while Kd does not, suggesting R as a theoretically preferable parameter. Further, we propose a solution for two limitations of R: its dependence on target concentration and narrow dynamic range. Finally, we demonstrate the use of this algorithm in both computer-simulated and experimental aptamer selection. This study sets a cornerstone in the theory of bulk affinity assays, and it provides researchers with a scientifically sound and instructive approach for conducting bulk affinity assays.

Transient Incomplete Separation of Species with Close Diffusivity to Study the Stability of Affinity Complexes.

Large molecules can be generically separated from small ones, though partially and temporarily, in a pressure-driven flow inside a capillary. This transient incomplete separation has been only applied to species with diffusion coefficients different by at least an order of magnitude. Here, we demonstrate, for the first time, the analytical utility of transient incomplete separation for species with close diffusion coefficients. First, we prove in silico that even a small difference in diffusivity can lead to detectable transient incomplete separation of species. Second, we use computer simulation to prove that such a separation can be used for the reliable determination of equilibrium dissociation constant (Kd) of complexes composed of similar-sized molecules. Finally, we demonstrate experimentally the use of this separation for the accurate determination of Kd value for a protein-aptamer complex. We conclude that "accurate constant via transient incomplete separation" (ACTIS) can serve as a reference method for affinity characterization of protein-aptamer binding in solution.

Circular Geometry in Molecular Stream Separation to Facilitate Nonorthogonal Field-to-Flow Orientation.

Molecular stream separation (MSS) is a promising complement for continuous-flow synthesis. MSS is driven by forces exerted on molecules by a field applied at an angle to the stream-carrying flow. MSS has only been performed with a 90° field-to-flow angle because of a rectangular geometry of canonic MSS; the second-order rotational symmetry of a rectangle prevents any other angle. Here, we propose a noncanonic circular geometry for MSS, which better aligns with the polar nature of MSS and allows changing the field-to-flow. We conducted in silico and experimental studies of circular geometry for continuous-flow electrophoresis (CFE, an MSS method). We proved two advantages of circular CFE over its rectangular counterpart. First, circular CFE can support better flow and electric-field uniformity than rectangular CFE. Second, the nonorthogonal field-to-flow orientation, achievable in circular CFE, can result in a higher stream resolution than the orthogonal one. Considering that circular CFE devices are not more complex in fabrication than rectangular ones, we foresee that circular CFE will serve as a new standard and a testbed for the investigation and creation of new CFE modalities.

Quantitative Characterization of Partitioning in Selection of DNA Aptamers for Protein Targets by Capillary Electrophoresis.

Partitioning of protein-DNA complexes from protein-unbound DNA is a key step in selection of DNA aptamers. Conceptually, the partitioning step is characterized by two parameters: transmittance for protein-bound DNA (binders) and transmittance for unbound DNA (nonbinders). Here, we present the first study to reveal how these transmittances depend on experimental conditions; such studies are pivotal to the effective planning and control of selection. Our focus was capillary electrophoresis (CE), which is a partitioning approach of high efficiency. By combining a theoretical model and experimental data, we evaluated the dependence of transmittances of binders and nonbinders on the molecular weight of the protein target in two modes of CE-based partitioning: nonequilibrium capillary electrophoresis of equilibrium mixtures (NECEEM) and ideal-filter capillary electrophoresis (IFCE). Our data suggest that as the molecular weight of the protein target decreases: (i) the transmittance for binders remains close to unity in NECEEM but decreases drastically in IFCE and (ii) the transmittance for nonbinders increases orders of magnitude in NECEEM but remains relatively stable at a very low level in IFCE. To determine the optimal CE conditions for a given size of protein target, a balance between transmittances of binders and nonbinders must be reached; such a balance would ensure the collection of binders of sufficient purity and quantity. We conclude that, as a rule of thumb, IFCE is preferable for large-size protein targets while NECEEM should be the method of choice for small-size protein targets.

Template Instrumentation for "Accurate Constant via Transient Incomplete Separation".

Accurate Constant via Transient Incomplete Separation (ACTIS) is a new method for finding the equilibrium dissociation constant Kd of a protein-small molecule complex based on transient incomplete separation of the complex from the unbound small molecule in a capillary. This separation is caused by differential transverse diffusion of the complex and the small molecule in a pressure-driven flow. The advection-diffusion processes underlying ACTIS can be described by a system of partial differential equations allowing for a virtual ACTIS instrument to be built and ACTIS to be studied in silico. The previous in silico studies show that large variations in the fluidic system geometry do not affect the accuracy of Kd determination, thus, proving that ACTIS is conceptually accurate. The conceptual accuracy does not preclude, however, instrumental inaccuracy caused by run-to-run signal drifts. Here we report on assembling a physical ACTIS instrument with a fluidic system that mimics the virtual one and proving the absence of signal drifts. Furthermore, we confirmed method ruggedness by assembling a second ACTIS instrument and comparing the results of experiments performed with both instruments in parallel. Despite some unintentional differences between the instruments (caused by tolerances in sizes, positions, etc.) and noticeable differences in their respective separagrams, we found that the Kd values determined for identical samples with these instruments were equal. Conclusively, the fluidic system presented here can serve as a template for reliable ACTIS instrumentation.

Multi-drug-resistance efflux in cisplatin-naive and cisplatin-exposed A2780 ovarian cancer cells responds differently to cell culture dimensionality.

A primary reason for chemotherapy failure is chemoresistance, which is driven by various mechanisms. Multi-drug resistance (MDR) is one such mechanism that is responsible for drug extrusion from the intracellular space. MDR can be intrinsic and thus, may pre-exist the first application of chemotherapy. However, MDR may also be acquired during tumor exposure to chemotherapeutic agents. To understand whether cell clustering can influence intrinsic and acquired MDR, the present study assessed cultured monolayers (representing individual cells) and spheroids (representing clusters) formed by cisplatin-naïve (intrinsic MDR) and cisplatin-exposed (acquired MDR) lines of ovarian cancer A2780 cells by determining the cytometry of reaction rate constant (CRRC). MDR efflux was characterized using accurate and robust cell number vs. MDR efflux rate constant (k MDR) histograms. Both cisplatin-naïve and cisplatin-exposed monolayer cells presented unimodal histograms; the histogram of cisplatin-exposed cells was shifted towards a higher k MDR value suggesting greater MDR activity. Spheroids of cisplatin-naïve cells presented a bimodal histogram indicating the presence of two subpopulations with different MDR activity. In contrast, spheroids of cisplatin-exposed cells presented a unimodal histogram qualitatively similar to that of the monolayers of cisplatin-exposed cells but with a moderate shift towards greater MDR activity. A flow-cytometry assessment of multidrug resistance-associated protein 1 transporter levels in monolayers and dissociated spheroids revealed distributions similar to those of k MDR, thus, suggesting a plausible molecular mechanism for the observed differences in MDR activity. The observed greater effect of cell clustering on intrinsic rather than in acquired MDR can help guide the development of new therapeutic strategies targeting clusters of circulating tumor cells.

Topino: A Graphical Tool for Quantitative Assessment of Molecular Stream Separations.

In molecular-stream separation (MSS), a stream of a multicomponent mixture is separated into multiple streams of individual components. Quantitative evaluation of MSS data has been a bottleneck in MSS for decades as there was no conventional way to present the data in a reproducible and uniform fashion. The roots of the problem were in the multidimensional nature of MSS data; even in the ideal case of steady-state separation, the data is three-dimensional: intensity and two spatial coordinates. We recently found a way to reduce the dimensionality via presenting the MSS data in a polar coordinate system and convoluting the data via integration of intensity along the radius axis. The result of this convolution is an angulagram, a simple 2D plot presenting integrated intensity vs angle. Not only does an angulagram simplify the visual assessment, but it also allows the determination of three quantitative parameters characterizing the quality of MSS: stream width, stream linearity, and stream deflection. Reliably converting an MSS image into an angulagram and accurately determining the stream parameters requires an advanced and user-friendly software tool. In this technical note, we introduce such a tool: the open-source software Topino available at https://github.com/Schallaven/topino. Topino is a stand-alone program with a modern graphical user interface that allows processing an MSS image in a fast (<2 min) and straightforward way. The robustness and ruggedness of Topino were confirmed by comparing the results obtained by three users. Topino removes the analytical bottleneck in MSS and will be an indispensable tool for MSS users with varying levels of experience.

How to Develop and Prove High-Efficiency Selection of Ligands from Oligonucleotide Libraries: A Universal Framework for Aptamers and DNA-Encoded Small-Molecule Ligands.

Screening molecular libraries for ligands capable of binding proteins is widely used for hit identification in the early drug discovery process. Oligonucleotide libraries provide a very high diversity of compounds, while the combination of the polymerase chain reaction and DNA sequencing allow the identification of ligands in low copy numbers selected from such libraries. Ligand selection from oligonucleotide libraries requires mixing the library with the target followed by the physical separation of the ligand-target complexes from the unbound library. Cumulatively, the low abundance of ligands in the library and the low efficiency of available separation methods necessitate multiple consecutive rounds of partitioning. Multiple rounds of inefficient partitioning make the selection process ineffective and prone to failures. There are continuing efforts to develop a separation method capable of reliably generating a pure pool of ligands in a single round of partitioning; however, none of the proposed methods for single-round selection have been universally adopted. Our analysis revealed that the developers' efforts are disconnected from each other and hindered by the lack of quantitative criteria of selection quality assessment. Here, we present a formalism that describes single-round selection mathematically and provides parameters for quantitative characterization of selection quality. We use this formalism to define a universal strategy for development and validation of single-round selection methods. Finally, we analyze the existing partitioning methods, the published single-round selection reports, and some pertinent practical considerations through the prism of this formalism. This formalism is not an experimental protocol but a framework for correct development of experimental protocols. While single-round selection is not a goal by itself and may not always suffice selection of good-quality ligands, our work will help developers of highly efficient selection approaches to consolidate their efforts under an umbrella of universal quantitative criteria of method development and assessment.

Necessity and Challenges of Sample Preconcentration in Analysis of Multiple MicroRNAs by Capillary Electrophoresis.

Thousands of putative microRNA (miRNA)-based cancer biomarkers have been reported, but none has been validated for approval by the Food and Drug Administration. One of the reasons for this alarming discrepancy is the lack of a method that is sufficiently robust for carrying out validation studies, which may require analysis of samples from hundreds of patients across multiple institutions and pooling the results together. The capillary electrophoresis (CE)-based hybridization assay proved to be more robust than reversed transcription polymerase chain reaction (the current standard), but its limit of quantification (LOQ) exceeds 10 pM while miRNA concentrations in cell lysates are below 1 pM. Thus, CE-based separation must be preceded by on-column sample preconcentration. Here, we explain the challenges of sample preconcentration for CE-based miRNA analyses and introduce a preconcentration method that can suit CE-based miRNA analysis utilizing peptide nucleic acid (PNA) hybridization probes. The method combines field-amplified sample stacking (FASS) with isotachophoresis (ITP). We proved that FASS-ITP could retain and concentrate both near-neutral PNA with highly negatively charged PNA-miRNA hybrids. We demonstrated that preconcentration by FASS-ITP could be combined with the CE-based separation of the unreacted PNA probes from the PNA-miRNA hybrids and facilitate improvement in LOQ by a factor of 140, down to 0.1 pM. Finally, we applied FASS-ITP-CE for the simultaneous detection of two miRNAs in crude cell lysates and proved that the method was robust when used in complex biological matrices. The 140-fold improvement in LOQ and the robustness to biological matrices will significantly expand the applicability of CE-based miRNA analysis, bringing it closer to becoming a practical tool for validation of miRNA biomarkers.

Assessing Accuracy of an Analytical Method In Silico: Application to "Accurate Constant via Transient Incomplete Separation" (ACTIS).

Analytical methods may not have reference standards required for testing their accuracy. We postulate that the accuracy of an analytical method can be assessed in the absence of reference standards in silico if the method is built upon deterministic processes. A deterministic process can be precisely computer-simulated, thus allowing virtual experiments with virtual reference standards. Here, we apply this in silico approach to study "Accurate Constant via Transient Incomplete Separation" (ACTIS), a method for finding the equilibrium dissociation constant (Kd) of protein-small-molecule complexes. ACTIS is based on a deterministic process: molecular diffusion of the interacting protein-small-molecule pair in a laminar pipe flow. We used COMSOL software to construct a virtual ACTIS setup with a fluidic system mimicking that of a physical ACTIS instrument. Virtual ACTIS experiments performed with virtual samples-mixtures of a protein and a small molecule with defined rate constants and, thus, Kd of their interaction-allowed us to assess ACTIS accuracy by comparing the determined Kd value to the input Kd value. Further, the influence of multiple system parameters on ACTIS accuracy was investigated. Within multifold ranges of parameter values, the values of Kd did not deviate from the input Kd values by more than a factor of 1.25, strongly suggesting that ACTIS is intrinsically accurate and that its accuracy is robust. Accordingly, further development of ACTIS can focus on achieving high reproducibility and precision. We foresee that in silico accuracy assessment, demonstrated here with ACTIS, will be applicable to other analytical methods built upon deterministic processes.

Analytical Challenges in Development of Chemoresistance Predictors for Precision Oncology.

Chemoresistance, i.e., tumor insensitivity to chemotherapy, shortens life expectancy of cancer patients. Despite the availability of new treatment options, initial systemic regimens for solid tumors are dominated by a set of standard chemotherapy drugs, and alternative therapies are used only when a patient has demonstrated chemoresistance clinically. Chemoresistance predictors use laboratory parameters measured on tissue samples to predict the patient's response to chemotherapy and help to avoid application of chemotherapy to chemoresistant patients. Despite thousands of publications on putative chemoresistance predictors, there are only about a dozen predictors that are sufficiently accurate for precision oncology. One of the major reasons for inaccuracy of predictors is inaccuracy of analytical methods utilized to measure their laboratory parameters: an inaccurate method leads to an inaccurate predictor. The goal of this study was to identify analytical challenges in chemoresistance-predictor development and suggest ways to overcome them. Here we describe principles of chemoresistance predictor development via correlating a clinical parameter, which manifests disease state, with a laboratory parameter. We further classify predictors based on the nature of laboratory parameters and analyze advantages and limitations of different predictors using the reliability of analytical methods utilized for measuring laboratory parameters as a criterion. Our eventual focus is on predictors with known mechanisms of reactions involved in drug resistance (drug extrusion, drug degradation, and DNA damage repair) and using rate constants of these reactions to establish accurate and robust laboratory parameters. Many aspects and conclusions of our analysis are applicable to all types of disease biomarkers built upon the correlation of clinical and laboratory parameters.