Diverse Biomarkers Research Articles

Does allostatic load predict incidental coronary events differently among sexes?

BackgroundOne measure to quantify the degree of dysregulation is allostatic load (AL). Typically, AL incorporates information on diverse biomarkers and is associated with health outcomes such as cardiovascular diseases or the incidence of coronary events (C-E). AimsThis study investigates the predictive performance of different AL scoring methods on the incidence of coronary events (C-E). This study also elaborates sex differences in the baseline risks of C-E and the AL associated risks of C-E. DesignLongitudinal data analysis of the Heinz Nixdorf Recall Study (Risk Factors, Evaluation of Coronary Calcification, and Lifestyle) of 4327 participants free of C-E at study baseline aged 45–75. The data contains over 13 biomarkers measuring AL. MethodsAfter conducting multiple imputations on missing values on AL for 826 participants, the analysis sample consisted of N = 4327 participants. We applied the two most commonly used methods of AL scoring AL (count-based and Z-score) and a recently developed logistic regression weighting method (LRM) approach. Cox regression was used to predict the incidence of C-E for each AL score. Results were estimated without (M0) and with (M1) covariate adjustment, and in a final model (M2), with an interaction between AL and sex. ResultsWe found no violation of the proportional hazard assumption and significant differences in the survival curves between the sexes for C-E (Log-rank test: prob. > Chi2 = 0.000). In M0, all AL-scoring methods predicted C-E significantly, with the LRM based AL-score having the best performance (hazard ratio = 3.133; CI: [2.630, 3.732]; Somer's D = 0.717). After covariate inclusion, differences between the scoring methods levelled, though the count-based method and LRM performed better than the Z-scoring method. The interaction analysis in M2 showed a significant multiplicative interaction for the count-based method (1.254; [1.066, 1.475]) and for the LRM (1.746; [1.132, 2.692]). The additive relative excess risk due to interaction (RERI) measure was negative for the count-based method (RERI = −1.967; [-3.778; −0.156]) and the LRM (RERI = −1.909 [-3.910; 0.091]), indicating subadditivity. ConclusionAL scores are suitable for predicting C-E. Differences between the AL-scoring algorithms were only present after including interactions. We value the count-based method as suitable for clinical practice since its calculation is relatively simple, and performance was among the best. Interaction analysis revealed that despite strong sex differences in baseline C-E, the effect of AL is more pronounced for females at high levels of AL; thus, females could benefit more from a potential intervention on AL. We suggest further investigation of sex differences concerning the mediation by physiological and psychological intermediates.

On Deep Landscape Exploration of COVID-19 Patients Cells and Severity Markers.

COVID-19 is a disease with a spectrum of clinical responses ranging from moderate to critical. To study and control its effects, a large number of researchers are focused on two substantial aims. On the one hand, the discovery of diverse biomarkers to classify and potentially anticipate the disease severity of patients. These biomarkers could serve as a medical criterion to prioritize attention to those patients with higher prone to severe responses. On the other hand, understanding how the immune system orchestrates its responses in this spectrum of disease severities is a fundamental issue required to design new and optimized therapeutic strategies. In this work, using single-cell RNAseq of bronchoalveolar lavage fluid of nine patients with COVID-19 and three healthy controls, we contribute to both aspects. First, we presented computational supervised machine-learning models with high accuracy in classifying the disease severity (moderate and severe) in patients with COVID-19 starting from single-cell data from bronchoalveolar lavage fluid. Second, we identified regulatory mechanisms from the heterogeneous cell populations in the lungs microenvironment that correlated with different clinical responses. Given the results, patients with moderate COVID-19 symptoms showed an activation/inactivation profile for their analyzed cells leading to a sequential and innocuous immune response. In comparison, severe patients might be promoting cytotoxic and pro-inflammatory responses in a systemic fashion involving epithelial and immune cells without the possibility to develop viral clearance and immune memory. Consequently, we present an in-depth landscape analysis of how transcriptional factors and pathways from these heterogeneous populations can regulate their expression to promote or restrain an effective immune response directly linked to the patients prognosis.

Functional Nucleic Acids for Pathogenic Bacteria Detection.

Pathogens have long presented a significant threat to human lives, and hence the rapid detection of infectious pathogens is vital for improving human health. Current detection methods lack the means to detect infectious pathogens in a simple, rapid, and reliable manner at the time and point of need. Functional nucleic acids (FNAs) have the potential to overcome these limitations by acting as key components for point-of-care (POC) biosensors due to their distinctive advantages that include high binding affinities and specificities, excellent chemical stability, ease of synthesis and modification, and compatibility with a variety of signal-amplification and signal-transduction mechanisms.This Account summarizes the work completed in our groups toward developing FNA-based biosensors for detecting bacteria. In vitro selection has led to the isolation of many RNA-cleaving fluorogenic DNAzymes (RFDs) and DNA aptamers that can recognize infectious pathogens, including Escherichia coli, Clostridium difficile, Helicobacter pylori, and Legionella pneumophila. In most cases, a "many-against-many" approach was employed using a DNA library against a crude cellular mixture of an infectious pathogen containing diverse biomarkers as the target to isolate RFDs, with combined counter and positive selections ensuring high specificity toward the desired target. This procedure allows for the isolation of pathogen-specific FNAs without first identifying a suitable biomarker. Multiple target-specific DNA aptamers, including anti-glutamate dehydrogenase (GDH) circular aptamers, anti-degraded toxin B aptamers, and anti-RNase HII aptamers, have also been isolated for the detection of bacteria such as Clostridium difficile. The isolated FNAs have been integrated into fluorescent, colorimetric, and electrochemical biosensors using various signal transduction mechanisms. Both simple-to-use paper-based analytical devices and hand-held electrical devices with integrated FNAs have been developed for POC applications. In addition, signal-amplification strategies, including DNA catenane enabled rolling circle amplification (RCA), DNAzyme feedback RCA, and an all-DNA amplification system using a four-way junction and catalytic hairpin assembly (CHA), have been designed and applied to these systems to further increase their detection sensitivity. The use of these FNA-based biosensors to detect pathogens directly in clinical samples, such as urine, blood, and stool, has now been demonstrated with an outstanding sensitivity of as low as 10 cells per milliliter, highlighting the tremendous potential of using FNA-based sensors in clinical applications. We further describe strategies to overcome the challenges of using FNA-based biosensors in clinical applications, including strategies to improve the stability of FNAs in biological samples and prevent their nonspecific degradation from nucleases and strategies to deal with issues such as signal loss caused by nonspecific binding and biofouling. Finally, the remaining roadblocks for employing FNA-based biosensors in clinical applications are discussed.

Near-Infrared Light-Initiated Photoelectrochemical Biosensor Based on Upconversion Nanorods for Immobilization-Free miRNA Detection with Double Signal Amplification.

Photoelectrochemical (PEC) sensors are relatively new sensing platforms with high detection sensitivity and low cost. However, the current PEC biosensors dependent on ultraviolet or visible light as the exciting resource cause injuries to biological samples and systems, which restrains the applications in complicated matrixes. Herein, a near-infrared light (NIR)-initiated PEC biosensor based on NaYF4:Yb,Tm@NaYF4@TiO2@CdS (csUCNRs@TiO2@CdS) was constructed for sensitive detection of acute myocardial infarction (AMI)-related miRNA-133a in an immobilization-free format coupled with a hybridization chain reaction and a redox circle signal amplification strategy. A low-energy 980 nm NIR incident laser was converted to 300-480 nm light to excite the adjacent TiO2@CdS photosensitive shell to generate photocurrent by NaYF4:Yb,Tm@NaYF4 upconversion nanorods. Also, magnetic beads were employed for the homogeneous determination of target miRNA-133a to reduce the recognition steric hindrance and improve the detection sensitivity. The photocurrent response was positively correlated with the level of ascorbic acid as the energy donor to consume photoacoustic holes produced on the surface of csUCNRs@TiO2@CdS, which was generated by alkaline phosphatase catalyzation and regenerated by tris(2-carboxyethyl) phosphine reduction upon the appearance of miRNA-133a. Exerting a NIR-light-driven and immobilization-free strategy, the as-constructed biosensor displayed linearly sensitive and selective determination of miRNA-133a with a detection limit of 36.12 aM. More significantly, the assay method provided a new concept of the PEC sensing strategy driven by NIR light to detect diverse biomarkers with pronounced sensitivity, light stability, and low photodamage.

CRISPR-/Cas12a-Mediated Liposome-Amplified Strategy for the Surface-Enhanced Raman Scattering and Naked-Eye Detection of Nucleic Acid and Application to Food Authenticity Screening

Surface-enhanced Raman scattering (SERS) has been recognized as a powerful tool for biosensors due to the ultrahigh sensitivity and unique fingerprint information. However, there are some limitations in trace target nucleic acid detection for the restricted signal-transducing and amplification strategies. Inspired by CRISPR/Cas12a with specific target DNA-activated collateral single-strand DNA (ssDNA) cleavage activity and liposome with signal molecule-loading properties, we first proposed a sensitive SERS-based on-site nucleic acid detection strategy mediated by CRISPR/Cas12a with trans-cleavage activity on ssDNA linkers utilized to capture liposomes. Liposomes loading two kinds of signal molecules, 4-nitrothiophenol (4-NTP) and cysteine, could achieve the dual-mode detection of target DNA with SERS and naked eye, respectively. The promptly amplified signals were initiated by the triggered breakdown of signal molecule-loaded liposomes. Emancipated 4-NTP, a biological-silent Raman reporter, would achieve highly selective and sensitive SERS measurement. Released cysteine induced the aggregation of plasmonic gold nanoparticles, leading to an obvious red to blue colorimetric shift to realize portable naked-eye detection. With this strategy, target nucleic acid concentration was dexterously converted into SERS and visualization signals and could be detected as low as 100 aM and 10 pM, respectively. The approach was also successfully applied to determine meat adulteration, achieving the detection of a low adulteration ratio in the complicated food matrix. We anticipate that this strategy will not only be regarded as a universal platform for the on-site detection of food authenticity but also broaden SERS application for the accurate determination of diverse biomarkers.

The clinical use of blood-test factors for Alzheimer\u2019s disease: improving the prediction of cerebral amyloid deposition by the QPLEXTMAlz plus assay kit

Alzheimer’s disease (AD) is the leading cause of dementia, and many studies have focused on finding effective blood biomarkers for the accurate diagnosis of this disease. Predicting cerebral amyloid deposition is considered the key for AD diagnosis because a cerebral amyloid deposition is the hallmark of AD pathogenesis. Previously, blood biomarkers were discovered to predict cerebral amyloid deposition, and further efforts have been made to increase their sensitivity and specificity. In this study, we analyzed blood-test factors (BTFs) that can be commonly measured in medical health check-ups from 149 participants with cognitively normal, 87 patients with mild cognitive impairment, and 64 patients with clinically diagnosed AD dementia with brain amyloid imaging data available. We demonstrated that four factors among regular health check-up blood tests, cortisol, triglyceride/high-density lipoprotein cholesterol ratio, alanine aminotransferase, and free triiodothyronine, showed either a significant difference by or correlation with cerebral amyloid deposition. Furthermore, we made a prediction model for Pittsburgh compound B-positron emission tomography positivity, using BTFs and the previously discovered blood biomarkers, the QPLEXTMAlz plus assay kit biomarker panel, and the area under the curve was significantly increased up to 0.845% with 69.4% sensitivity and 90.6% specificity. These results show that BTFs could be used as co-biomarkers and that a highly advanced prediction model for amyloid plaque deposition could be achieved by the combinational use of diverse biomarkers.

Enriched transcriptome analysis of laser capture microdissected populations of single cells to investigate intracellular heterogeneity in immunostained FFPE sections

To investigate intracellular heterogeneity, cell capture of particular cell populations followed by transcriptome analysis has been highly effective in freshly isolated tissues. However, this approach has been quite challenging in immunostained formalin-fixed paraffin-embedded (FFPE) sections. This study aimed at combining the standard pathology techniques, immunostaining and laser capture microdissection, with whole RNA-sequencing and bioinformatics analysis to characterize FFPE breast cancer cell populations with heterogeneous expression of progesterone receptor (PR). Immunocytochemical analysis revealed that 60% of MCF-7 cells admixture highly express PR. Immunocytochemistry-based targeted RNA-seq (ICC-RNAseq) and in silico functional analysis revealed that the PR-high cell population is associated with upregulation in transcripts implicated in immunomodulatory and inflammatory pathways (e.g. NF-κB and interferon signaling). In contrast, the PR-low cell population is associated with upregulation of genes involved in metabolism and mitochondrial processes as well as EGFR and MAPK signaling. These findings were cross-validated and confirmed in FACS-sorted PR high and PR-low MCF-7 cells and in MDA-MB-231 cells ectopically overexpressing PR. Significantly, ICC-RNAseq could be extended to analyze samples captured at specific spatio-temporal states to investigate gene expression profiles using diverse biomarkers. This would also facilitate our understanding of cell population-specific molecular events driving cancer and potentially other diseases.

Direct Kinetic Fingerprinting for High-Accuracy Single-Molecule Counting of Diverse Disease Biomarkers.

Methods for detecting and quantifying disease biomarkers in biofluids with high specificity and sensitivity play a pivotal role in enabling clinical diagnostics, including point-of-care tests. The most widely used molecular biomarkers include proteins, nucleic acids, hormones, metabolites, and other small molecules. While numerous methods have been developed for analyzing biomarkers, most techniques are challenging to implement for clinical use due to insufficient analytical performance, high cost, and/or other practical shortcomings. For instance, the detection of cell-free nucleic acid (cfNA) biomarkers by digital PCR and next-generation sequencing (NGS) requires time-consuming nucleic acid extraction steps, often introduces enzymatic amplification bias, and can be costly when high specificity is required. While several amplification-free methods for detecting cfNAs have been reported, these techniques generally suffer from low specificity and sensitivity. Meanwhile, the quantification of protein biomarkers is generally performed using immunoassays such as enzyme-linked immunosorbent assay (ELISA); the analytical performance of these methods is often limited by the availability of antibodies with high affinity and specificity as well as the significant nonspecific binding of antibodies to assay surfaces. To address the drawbacks of existing biomarker detection methods and establish a universal diagnostics platform capable of detecting different types of analytes, we have developed an amplification-free approach, named single-molecule recognition through equilibrium Poisson sampling (SiMREPS), for the detection of diverse biomarkers with arbitrarily high specificity and single-molecule sensitivity. SiMREPS utilizes the transient, reversible binding of fluorescent detection probes to immobilized target molecules to generate kinetic fingerprints that are detected by single-molecule fluorescence microscopy. The analysis of these kinetic fingerprints enables nearly perfect discrimination between specific binding to target molecules and any nonspecific binding. Early proof-of-concept studies demonstrated the in vitro detection of miRNAs with a limit of detection (LOD) of approximately 1 fM and >500-fold selectivity for single-nucleotide polymorphisms. The SiMREPS approach was subsequently expanded to the detection of rare mutant DNA alleles from biofluids at mutant allele fractions of as low as 1 in 1 million, corresponding to a specificity of >99.99999%. Recently, SiMREPS was generalized to protein quantification using dynamically binding antibody probes, permitting LODs in the low-femtomolar to attomolar range. Finally, SiMREPS has been demonstrated to be suitable for the in situ detection of miRNAs in cultured cells, the quantification of small-molecule toxins and drugs, and the monitoring of telomerase activity at the single-molecule level. In this Account, we discuss the principles of SiMREPS for the highly specific and sensitive detection of molecular analytes, including considerations for assay design. We discuss the generality of SiMREPS for the detection of very disparate analytes and provide an overview of data processing methods, including the expansion of the dynamic range using super-resolution analysis and the improvement of performance using deep learning algorithms. Finally, we describe current challenges, opportunities, and future directions for the SiMREPS approach.

Hydra vulgaris assay as environmental assessment tool for ecotoxicology in freshwaters: a review

Freshwaters are vulnerable ecosystems owing to several anthropogenic impacts, including chemical pollution. Among existing model organisms, the cnidarian Hydra vulgaris is widely used for toxicological tests, with the aim of detecting either toxicity or teratogenicity of different dissolved chemicals. Given the widespread range of applications and developed assays, the aim of this review was to show and discuss the actual use of this model for ecotoxicological assessments in freshwaters as an ‘early warning system’. To achieve this goal, a thorough review was conducted by consulting several search engines for peer-reviewed international articles. Among all resulting articles from literature search, those focusing on H. vulgaris assay applied to environmental pollution were first selected (n=19). Then, only articles that specifically tested freshwater samples collected directly in the field were considered (n=4). The literature search highlighted that Hydra assays are suitable monitoring tools for freshwater ecotoxicity assessment. In addition, H. vulgaris allows testing diverse biomarkers (e.g. molecular, histological, morphological and behavioural) and exploring innovative research fields. So as to be able to assess the impact of emerging contaminants on both habitat and human health, the Hydra assays are demonstrating that they have an increasing potential that must be exploited.

Challenges Associated With the Design and Deployment of Food Intake Urine Biomarker Technology for Assessment of Habitual Diet in Free-Living Individuals and Populations-A Perspective.

Improvement of diet at the population level is a cornerstone of national and international strategies for reducing chronic disease burden. A critical challenge in generating robust data on habitual dietary intake is accurate exposure assessment. Self-reporting instruments (e.g., food frequency questionnaires, dietary recall) are subject to reporting bias and serving size perceptions, while weighed dietary assessments are unfeasible in large-scale studies. However, secondary metabolites derived from individual foods/food groups and present in urine provide an opportunity to develop potential biomarkers of food intake (BFIs). Habitual dietary intake assessment in population surveys using biomarkers presents several challenges, including the need to develop affordable biofluid collection methods, acceptable to participants that allow collection of informative samples. Monitoring diet comprehensively using biomarkers requires analytical methods to quantify the structurally diverse mixture of target biomarkers, at a range of concentrations within urine. The present article provides a perspective on the challenges associated with the development of urine biomarker technology for monitoring diet exposure in free-living individuals with a view to its future deployment in “real world” situations. An observational study (n = 95), as part of a national survey on eating habits, provided an opportunity to explore biomarker measurement in a free-living population. In a second food intervention study (n = 15), individuals consumed a wide range of foods as a series of menus designed specifically to achieve exposure reflecting a diversity of foods commonly consumed in the UK, emulating normal eating patterns. First Morning Void urines were shown to be suitable samples for biomarker measurement. Triple quadrupole mass spectrometry, coupled with liquid chromatography, was used to assess simultaneously the behavior of a panel of 54 potential BFIs. This panel of chemically diverse biomarkers, reporting intake of a wide range of commonly-consumed foods, can be extended successfully as new biomarker leads are discovered. Towards validation, we demonstrate excellent discrimination of eating patterns and quantitative relationships between biomarker concentrations in urine and the intake of several foods. In conclusion, we believe that the integration of information from BFI technology and dietary self-reporting tools will expedite research on the complex interactions between dietary choices and health.

Cytokines and neuron-specific proteins in pediatric viral encephalitis and convulsive syndrome. I. Viral encephalitis

Convulsive syndrome in children is manifested in the three forms: febrile convulsions in acute infections, symptomatic convulsions during acute neuroinfection, as well as onset of epilepsy requiring careful differentiation to prescribe adequate therapy. A threat of convulsive syndrome spreads beyond complications related to ongoing infection, because its development is associated with the risk of emerging symptomatic epilepsy in the future. Postencephalitic epilepsy developing in children within the first years after viral encephalitis has been specifically highlighted. A necessity to identify groups at risk of developing epilepsy gave a momentum to seek out for biomarkers of epileptogenesis reflecting the features of systemic and local inflammatory process in the central nervous system during the immune response to infection. Cytokines mainly mediating inflammation are currently examined being studied as candidate biomarkers of the risk of epilepsy. On the other hand, neuron-specific proteins known as inflammation biomarkers identified in various diseases of the central nervous system are being investigated to reveal brain cell injury in neuroinfections and epilepsy. Here we review publications assessing a potential to use inflammation biomarkers (cytokines and neuron-specific proteins) to diagnose and monitor pediatric neurological diseases associated with convulsive syndrome. The first part of the review describes the results of determining the inflammation biomarkers in the blood and cerebrospinal fluid during acute viral encephalitis/encephalopathy associated with various neurotropic viruses (herpes viruses, flaviviruses, enteroviruses). A significance of diverse biomarkers in predicting an outcome and long-term disease consequences are discussed.

Reviewing the value of leukocytes cell population data (CPD) in the management of sepsis

Sepsis is a medical emergency that describes the body’s systemic immune response to an infection and can lead to end-stage organic dysfunction and death. Despite the advances in understanding the pathophysiology of this syndrome and therapies, sepsis remains one of the leading causes of morbidity and mortality in critically ill patients. Early diagnosis and rapid intervention are essential to improve outcomes, which inspired the concept “golden hour,” during which the correction of shock and organic dysfunction can improve the patients’ outcomes. But the initial presentation of sepsis is often nonspecific and its severity is difficult to assess. Anomalies in temperature, heart and respiratory rates and leukocyte counts are manifestations of systemic inflammatory response syndrome (SIRS). Diagnosis, management and follow-up of patients with sepsis remains a challenge, and diverse biomarkers have been proposed for the timely diagnosis and prognosis of septic patients: lactic acid, procalcitonin (PCT), C-reactive protein, immature granulocytes. The host’s initial response to infection is a humoral, cellular and neuroendocrine reaction to infection, and leukocytes interact with endothelial cells. The new generation of hematological analyzers incorporates technological innovations allowing to expand the information derived from the complete blood count: new leukocyte derived parameters are emerging as potentially useful markers in different clinical situations. Additional research parameters cell population data (CPD), characterizing different leukocyte populations have become available, and preliminary observations suggest their utility in the diagnosis of sepsis. This review emphasizes the value of CPD, reported by modern cellular counters for early recognition of sepsis, and therefore the potential improvement in patient outcomes.

Predictors of Sexual Desire and Sexual Function in Sedentary Middle-Aged Adults: The Role of Lean Mass Index and S-Klotho Plasma Levels. The FIT-AGEING Study

BackgroundUnhealthy lifestyle and aging negatively impact sexuality; consequently, the prevalence of sexual problems increases sharply in middle-aged adults, but the determinants of low sexual desire and sexual dysfunction are not fully elucidated. AimsTo investigate the association of cardiometabolic profile, free testosterone plasma levels, body composition, physical fitness, and S-Klotho plasma levels with sexual desire and sexual function in middle-aged sedentary adults. MethodsSeventy-four (39 women) sedentary middle-aged adults (45–65 years old) were recruited for the present cross-sectional study. OutcomesThe blood samples were collected in the morning (12 h of fasting) to determine cardiometabolic biomarkers and free testosterone and S-Klotho plasma levels. The cardiometabolic risk score was calculated based on the International Diabetes Federation's clinical criteria, quantitative insulin sensitivity check index, and homeostatic model assessment of insulin resistance index. A dual-energy X-ray absorptiometry scanner was used to determine the lean mass index (LMI) and the fat mass index. Maximal oxygen uptake was determined by a maximum treadmill test using indirect calorimetry. Muscular strength was measured with knee extensor isokinetic dynamometry (60° s−1). Sexual desire was assessed with the Sexual Desire Inventory 2. Sexual function was assessed with the Massachusetts General Hospital-Sexual Functioning Questionnaire. ResultsAfter age adjustment, free testosterone plasma levels were associated with solitary sexual desire in women (R2 = 0.193, β = 0.342, P = .044). The LMI was associated with solitary sexual desire in men (R2 = 0.258, β = 0.445, P = .024) and sexual function in women (R2 = 0.470, β = −0.607, P < .001). S-Klotho plasma levels were associated with solitary sexual desire and sexual function in men (R2 = 0.412, β = 0.817, P = .001; R2 = 0.193, β = −0.659, P = .021, respectively) and with dyadic sexual desire and sexual function in women (R2 = 0.270, β = 0.508, P = .020; R2 = 0.467, β = −0.676, P < .001, respectively). Clinical ImplicationsS-Klotho plasma levels may represent a potential new biomarker for sexual desire and sexual function. Lean body mass development may benefit sexual desire and sexual function. Strengths and LimitationsStrengths include the analysis of novel and diverse biomarkers of health for sexual desire and sexual function. Limitations include the cross-sectional design and a relatively small sample size; thus, results should be interpreted cautiously and in the study population context. ConclusionS-Klotho plasma levels were strongly associated with dyadic sexual desire, solitary sexual desire, and sexual function in sedentary middle-aged adults. The LMI was also positively associated with solitary sexual desire and sexual function in men and women, respectively.Dote-Montero M, De-la-O A, Castillo MJ, et al. Predictors of Sexual Desire and Sexual Function in Sedentary Middle-Aged Adults: The Role of Lean Mass Index and S-Klotho Plasma Levels. The FIT-AGEING Study. J Sex Med 2020;17:665–677.

Cancer cell-targeted nanoprobe for multilayer imaging of diverse biomarkers and precise photodynamic therapy.

A novel multifunctional nanoprobe was designed for cancer cell targeted multilayer imaging of two cancer biomarkers. Based on the proposed method, in situ imaging of membrane MUC1 mucin and cytoplasmic microRNA miR-21 coupled with precise photodynamic therapy was achieved.

PEGylated Bilirubin-coated Iron Oxide Nanoparticles as a Biosensor for Magnetic Relaxation Switching-based ROS Detection in Whole Blood.

Rationale: Magnetic relaxation switching (MRSw) induced by target-triggered aggregation or dissociation of superparamagnetic iron oxide nanoparticles (SPIONs) have been utilized for detection of diverse biomarkers. However, an MRSw-based biosensor for reactive oxygen species (ROS) has never been documented.Methods: To this end, we constructed a biosensor for ROS detection based on PEGylated bilirubin (PEG-BR)-coated SPIONs (PEG-BR@SPIONs) that were prepared by simple sonication via ligand exchange. In addition, near infra-red (NIR) fluorescent dye was loaded onto PEG-BR@SPIONs as a secondary option for fluorescence-based ROS detection.Results: PEG-BR@SPIONs showed high colloidal stability under physiological conditions, but upon exposure to the model ROS, NaOCl, in vitro, they aggregated, causing a decrease in signal intensity in T2-weighted MR images. Furthermore, ROS-responsive PEG-BR@SPIONs were taken up by lipopolysaccharide (LPS)-activated macrophages to a much greater extent than ROS-unresponsive control nanoparticles (PEG-DSPE@SPIONs). In a sepsis-mimetic clinical setting, PEG-BR@SPIONs were able to directly detect the concentrations of ROS in whole blood samples through a clear change in T2 MR signals and a 'turn-on' signal of fluorescence.Conclusions: These findings suggest that PEG-BR@SPIONs have the potential as a new type of dual mode (MRSw-based and fluorescence-based) biosensors for ROS detection and could be used to diagnose many diseases associated with ROS overproduction.

The Utility and Experience with Disease Biomarkers in Juvenile Onset Arthritis vs. Adult Onset Arthritis.

Juvenile idiopathic arthritis (JIA) is the most common but extremely heterogeneous group of rheumatic diseases of childhood. There are no reliable, well-researched and published biomarkers for diagnosis or monitoring in juvenile idiopathic arthritis as there are for rheumatoid arthritis (RA) in adults. Biomarkers are not utilized in classifying JIA as they are in adult RA, making the JIA classifications less clinically effective and informative. The situation presents a lost opportunity for early aggressive therapy in JIA patients. Various researchers have used diverse biomarkers anecdotally in JIA and more systematically in RA patients and have drawn inferences on their utility from their experiences. The experience with biomarkers from RA patients cannot necessarily be extrapolated for JIA patients because they are dissimilar diseases. This article reconnoiters the comparative utility of various arthritis biomarkers in adult as well as in JIA patients. In contrast to RA, JIA is in itself a diverse group of arthritis with clinically overlapping subgroups with diverse etiology. The difference in the etiopathogenesis of arthritis subgroups demands identifying subgroup-specific biomarkers for diagnosis/monitoring and subgroup-specific therapies for management. The diagnostic/prognostic value of the individual biomarker could be different in different types of arthritis and in different types of hosts. Understanding the utility of individual biomarkers and careful selection of the assay are important to achieve the best disease outcomes.

Chimeric DNA-Functionalized Titanium Carbide MXenes for Simultaneous Mapping of Dual Cancer Biomarkers in Living Cells.

Acquiring multilayer information on diverse biomarkers with different spatial distributions at the cellular level is crucial for monitoring the progression of cancers. Herein, a dual-signal-tagged chimeric DNA-functionalized titanium carbide MXenes nanoprobe (dcDNA-Ti3C2) that responds to biomarkers with different cellular locations from plasma membrane to cytoplasm was designed toward this end. In the presence of cancer biomarkers, including transmembrane glycoprotein mucin 1 (MUC1) and cytoplasmic microRNA-21 (miR-21), the recognition between MUC1 and its aptamer in the dcDNA-Ti3C2 probe induces the separation of TAMRA-MUC1 aptamer from Ti3C2 MXenes, thereby resulting in an increase in red fluorescence; and the hybridization of miR-21 with the hairpin probe triggers the increase of green fluorescence. As a result, dual analysis of MUC1 and miR-21 at low-nanomolar concentrations in vitro, as well as in situ simultaneous imaging of the biomarkers within MCF-7 breast cancer cells, was achieved. The feasibility of the nanoprobe was further demonstrated by monitoring the expression changes of both the biomarkers in cancer cells under different inhibitor combinations. Therefore, this strategy allows us to acquire the expression levels and spatial distributions of different biomarkers in living cells, providing a helpful tool for reliable diagnosis of cancers and basic understanding their progression.

Detection of Various Biomarkers and Enzymes via a Nanocluster-Based Fluorescence Turn-on Sensing Platform.

The profiling of disease-related biomarkers is an essential procedure for the accurate diagnosis and intervention of metabolic disorders. Therefore, the development of ultrasensitive and highly selective fluorogenic biosensors for diverse biomarkers is extremely desirable. There is still a considerable challenge to prepare nanocluster-based fluorescence turn-on probes capable of recognizing multiple biomolecules. We herein provide a novel nanocluster-based chemical information processing system (CIPS) for the programmable detection of various metabolites and enzymes. This CIPS consists of biocatalytic reactions between substrates and their respective oxidases to generate H2O2, which was then employed to synthesize bright fluorescent silver nanoclusters (Ag NCs). Utilizing this system, we are able to accurately probe a series of substrates/corresponding oxidases with high sensitivity and specificity, including glucose/glucose oxidase, uric acid/uric acid oxidase, sarcosine/sarcosine oxidase, choline/choline oxidase, xanthine/xanthine oxidase, and lactic acid/lactic acid oxidase. Furthermore, this metabolite profiling CIPS can be integrated with binary logic operations, which create an intelligent tool for the high-throughput screening of various diseases in vitro (e.g., diabetes, gout, prostate cancer, cardiovascular disease, and lactic acidosis).

Addressing Cancer Chemotherapeutic Toxicity, Resistance, and Heterogeneity: Novel Theranostic Use of DNA‐Encoded Small Molecule Libraries

Major problems in cancer chemotherapy are toxicity, resistance, and cancer heterogeneity. A new theranostic paradigm has been proposed by the authors. Many million small molecules (SM) are bound to the proteins extracted from a patient's cancer. SM that also bind proteins extracted from normal human tissues are subtracted from the cancer protein bound SM leaving a large array of SM targeting many sites on each of the cancer biomarkers. Targeting many more than the conventional 1 - 4 cancer biomarkers will reduce development of tumor resistance. After several cycles of selection and counter selection, DNA codes appended to the SM will be PCR amplified to provide templates for restricted libraries of the SM to improve selectivity and sensitivity. The large array of selected and counter selected SM assures that many of the compounds in the array will penetrate the cell membrane and bind to intracellular targets, low tumor resistance, low background for imaging, low therapeutic toxicity, and targeting of the diverse biomarkers present in the heterogeneous mixture of cells in primary and metastatic cancer. Theranostic use of radiolabeled SM binding many sites on many, not necessarily critical, biomarkers provides high cancer cell killing. Experiments to provide proof of principle of this novel concept suggested by the authors.

Abstract 4757: A clinically validated comprehensive companion diagnostic platform for care of patients with advanced cancer

Abstract Introduction: Increase in targeted therapies has resulted in the need for a single assay capable of detecting diverse biomarkers indicated for these agents. Comprehensive genomic profiling (CGP) provides such a solution, but due to the complexity and number of assays available today, standardization of validation has become critically important. We present FoundationOne CDx, the first NGS-based comprehensive companion diagnostics (CDx) platform developed and performed in compliance with FDA 21 CFR part 820. The assay interrogates 324 genes, and has CDx indications in five tumor types associated with 17 targeted therapies (Table 1). The versatile assay design will facilitate streamlined development of future CDx indications. Methods: DNA extracted from FFPE tumor tissue underwent whole-genome shotgun library construction and hybridization-based capture, followed by sequencing using Illumina HiSeq 4000. Sequence data were processed using a proprietary analysis pipeline designed to detect base substitutions, indels, copy number alterations, rearrangements, microsatellite instability (MSI), and tumor mutational burden (TMB). Results: Clinical validity was established such that the concordance between CGP and approved CDx were statistically non-inferior to that of two runs of approved CDx. For analytical validity, limit of detection (LoD) was at allele frequency 4% for known substitutions and indels. LoD was 16% tumor content for copy number amplifications, 30% for homozygous deletions, 11% for rearrangements, 12% for MSI, and 20% for TMB. Concordance with an orthogonal NGS platform was 94.6% for substitutions and indels. Within-assay reproducibility had PPA 99.4%. Conclusion: Rapid expansion of targeted therapies and CDx has necessitated a new approach and urgency to defining performance standards. We developed a comprehensive CDx assay and demonstrated clinical and analytical validity to support and accelerate using CGP for routine clinical care. Table 1. Companion Diagnostic IndicationsIndicationBiomarkerTherapyNon-small cell lung cancer (NSCLC)EGFR exon 19 deletions and EGFR exon 21 L858R alterationsafatinib, gefitinib, or erlotinibEGFR exon 20 T790M alterationsosimertinibALK rearrangementsalectinib, crizotinib, or ceritinibBRAF V600Edabrafenib in combination with trametinibMelanomaBRAF V600Edabrafenib, vemurafenibBRAF V600E and V600Ktrametinib, cobimetinib, in combination with vemurafenibBreast cancerERBB2 (HER2) amplificationtrastuzumab, ado-trastuzumab-emtansine, or pertuzumabColorectal cancerKRAS wild-type (absence of mutations in codons 12 and 13)cetuximabKRAS and NRAS wild-type (absence of mutations in exons 2, 3, and 4)panitumumabOvarian cancerBRCA1/2 alterationsrucaparib Citation Format: James X. Sun, Yali Li, Coren Milbury, Joel Skoletsky, Christine Burns, Wai-ki Yip, Jun Luo, Ninad Dewal, Adrienne Johnson, Kyle Gowen, Jing Tong, Yuting He, Jie He, Pei Ma, Jared White, Steve Roels, John Truesdell, Eric Peters, Houston Gilbert, Charlie Wu, Erica Schleifman, Johannes Noe, Carl Barrett, Kenneth Thress, Suzanne Jenkins, Julia Elvin, Geoff Otto, Doron Lipson, Jeffrey Ross, Vincent Miller, Philip Stephens, Michael Doherty, Christine Vietz. A clinically validated comprehensive companion diagnostic platform for care of patients with advanced cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4757.