Rapid, Multianalyte Detection of Opioid Metabolites in Wastewater

By monitoring opioid metabolites, wastewater-based epidemiology (WBE) could be an excellent tool for real-time information on the consumption of illicit drugs. A key limitation of WBE is the reliance on costly laboratory-based techniques that require substantial infrastructure and trained personnel, resulting in long turnaround times. Here, we present an aptamer-based graphene field effect transistor (AptG-FET) platform for simultaneous detection of three different opioid metabolites. This platform provides a reliable, rapid, and inexpensive method for quantitative analysis of opioid metabolites in wastewater. The platform delivers a limit of detection 2-3 orders of magnitude lower than previous reports, but in line with the concentration range (pg/mL to ng/mL) of these opioid metabolites present in real samples. To enable multianalyte detection, we developed a facile, reproducible, and high-yield fabrication process producing 20 G-FETs with integrated side gate platinum (Pt) electrodes on a single chip. Our devices achieved the selective multianalyte detection of three different metabolites: noroxycodone (NX), 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), and norfentanyl (NF) in wastewater diluted 20× in buffer.

Transcutaneous Flexible Sensor for In Vivo Photonic Detection of pH and Lactate

Clinical research shows that frequent measurements of both pH and lactate can help guide therapy and improve patient outcome. However, current methods of sampling blood pH and lactate make it impractical to take readings frequently (due to the heightened risk of blood infection and anemia). As a solution, we have engineered a subcutaneous pH and lactate sensor (PALS) that can provide continuous, physiologically relevant measurements. To measure pH, a sheet containing a pH-sensitive fluorescent dye is placed over 400 and 465 nm light-emitting diodes (LEDs) and a filter-coated photodetector. The filter-coated photodetector collects an emitted signal from the dye for each LED excitation, and the ratio of the emitted signals is used to monitor pH. To measure lactate, two sensing sheets comprising an oxygen-sensitive phosphorescent dye are each mounted to a 625 nm LED. One sheet additionally comprises the enzyme lactate oxidase. The LEDs are sequentially modulated to excite the sensing sheets, and their phase shift at the LED drive frequency is used to monitor lactate. In vitro results indicate that PALS successfully records pH changes from 6.92 to 7.70, allowing for discrimination between acidosis and alkalosis, and can track lactate levels up to 9 mM. Both sensing strategies exhibit fast rise times (< 5 min) and stable measurements. Multianalyte in vitro models of physiological disorders show that the sensor measurements consistently quantify the expected pathophysiological trends without cross talk; in vivo rabbit testing further indicates usefulness in the clinical setting.

Organic Transistor Arrays Integrated with Finger-Powered Microfluidics for Multianalyte Saliva Testing

A compact multianalyte biosensing platform is reported, composed of an organic electrochemical transistor (OECT) microarray integrated with a pumpless "finger-powered" microfluidic, for quantitative screening of glucose, lactate, and cholesterol levels. A biofunctionalization method is designed, which provides selectivity towards specific metabolites as well as minimization of any background interference. In addition, a simple method is developed to facilitate multi-analyte sensing and avoid electrical crosstalk between the different transistors by electrically isolating the individual devices. The resulting biosensing platform, verified using human samples, offers the possibility to be used in easy-to-obtain biofluids with low abundance metabolites, such as saliva. Based on our proposed method, other types of enzymatic biosensors can be integrated into the array to achieve multiplexed, noninvasive, personalized point-of-care diagnostics.

A Delphic consensus assessment: imaging and biomarkers in gastroenteropancreatic neuroendocrine tumor disease management

The complexity of the clinical management of neuroendocrine neoplasia (NEN) is exacerbated by limitations in imaging modalities and a paucity of clinically useful biomarkers. Limitations in currently available imaging modalities reflect difficulties in measuring an intrinsically indolent disease, resolution inadequacies and inter-/intra-facility device variability and that RECIST (Response Evaluation Criteria in Solid Tumors) criteria are not optimal for NEN. Limitations of currently used biomarkers are that they are secretory biomarkers (chromogranin A, serotonin, neuron-specific enolase and pancreastatin); monoanalyte measurements; and lack sensitivity, specificity and predictive capacity. None of them meet the NIH metrics for clinical usage. A multinational, multidisciplinary Delphi consensus meeting of NEN experts (n = 33) assessed current imaging strategies and biomarkers in NEN management. Consensus (>75%) was achieved for 78% of the 142 questions. The panel concluded that morphological imaging has a diagnostic value. However, both imaging and current single-analyte biomarkers exhibit substantial limitations in measuring the disease status and predicting the therapeutic efficacy. RECIST remains suboptimal as a metric. A critical unmet need is the development of a clinico-biological tool to provide enhanced information regarding precise disease status and treatment response. The group considered that circulating RNA was better than current general NEN biomarkers and preliminary clinical data were considered promising. It was resolved that circulating multianalyte mRNA (NETest) had clinical utility in both diagnosis and monitoring disease status and therapeutic efficacy. Overall, it was concluded that a combination of tumor spatial and functional imaging with circulating transcripts (mRNA) would represent the future strategy for real-time monitoring of disease progress and therapeutic efficacy.

Neuroendocrine tumor biomarkers: From monoanalytes to transcripts and algorithms

The management of neuroendocrine neoplasia remains a perplexing problem because of the lack of knowledge of the biology of the disease, its late presentation, the relative insensitivity of imaging modalities and a paucity of predictably effective treatment options. A critical limitation is posed by the lack of accurate biomarkers to guide management, monitor the efficacy of therapy and provide a prognostic assessment of disease progress. Currently utilized monoanalyte biomarkers (e.g. chromogranin, serotonin, pancreastatin etc.) exhibit variable metrics, poor sensitivity, specificity, and predictive ability and are rarely used to guide clinical decision making. A National Cancer Institute Neuroendocrine Tumor summit conference held in 2007 noted biomarker limitations to be a crucial unmet need in the management of neuroendocrine tumors. Nevertheless little progress has been made in this field until recently with the consideration of blood transcript analysis, circulating tumor cells and miRNA measurement. Given the complexity and multidimensionality of the neoplastic process itself, the heterogeneity of neuroendocrine tumors (NET) as well as the interaction of the tumor microenvironment, it is not unexpected that no single (monoanalyte) biomarker has proven to be effective. This deduction reflects the growing recognition that use of a monoanalyte to define a multidimensional disease process has inherent flaws. Logic dictates that no single measured parameter can capture the pathobiological diversity of neoplasia and monoanalytes cannot define the multiple variables (proliferation, metabolic activity, invasive potential and metastatic propensity) that constitute tumor growth. Thus far, most biomarkers whether in tissue or blood/urine have been single analytes with varying degrees of sensitivity and specificity and in general have failed to exhibit robust metrics or lacked methodological rigor. Neuroendocrine (NE) disease represents an area of biomarker paucity since the individual biomarkers (gastrin, insulin etc) are not widely applicable to the diverse types of NE neoplasia (NEN). Broad spectrum markers such as CgA have limitations in sensitivity, specificity and reproducibility. This review serves to provide a general background of the evolution of NET biomarkers. It provides an assessment of their current and past usage and limitations in assessing their diagnostic, pathologic and prognostic aspects in respect of NET. It provides a view of the changing methodology of biomarker development and the application of biomathematical analyses to redefining detection and treatment. Finally, it presents a description and consensus on current advances in transcript analysis, miRNA measurement and circulating tumor cell identification.

A multianalyte PCR blood test outperforms single analyte ELISAs (chromogranin A, pancreastatin, neurokinin A) for neuroendocrine tumor detection

A critical requirement in neuroendocrine tumor (NET) management is a sensitive, specific and reproducible blood biomarker test. We evaluated a PCR-based 51 transcript signature (NETest) and compared it to chromogranin A (CgA), pancreastatin (PST) and neurokinin A (NKA). The multigene signature was evaluated in two groups: i) a validation set of 40 NETs and controls and ii) a prospectively collected group of NETs (n=41, 61% small intestinal, 50% metastatic, 44% currently treated and 41 age-sex matched controls). Samples were analyzed by a two-step PCR (51 marker genes) protocol and ELISAs for CgA, PST and NKA. Sensitivity comparisons included χ(2), non-parametric measurements, ROC curves and predictive feature importance (PFAI) analyses. NETest identified 38 of 41 NETs. Performance metrics were: sensitivity 92.8%, specificity 92.8%, positive predictive value 92.8% and negative predictive value 92.8%. Single analyte ELISA metrics were: CgA 76, 59, 65, and 71%; PST 63, 56, 59, and 61% and NKA 39, 93, 84, and 60%. The AUCs (ROC analysis) were: NETest: 0.96±0.025, CgA: 0.67±0.06, PST 0.56±0.06, NKA: 0.66±0.06. NETest significantly outperformed single analyte tests (area differences: 0.284-0.403, Z-statistic 4.85-5.9, P<0.0001). PFAI analysis determined NETest had most value (69%) in diagnosis (CgA (13%), PST (9%), and NKA (9%)). Test data were consistent with the validation set (NETest >95% sensitivity and specificity, AUC =0.98 vs single analytes: 59-67% sensitivity, AUCs: 0.58-0.63). The NETest is significantly more sensitive and efficient (>93%) than single analyte assays (CgA, PST or NKA) in NET diagnosis. Blood-based multigene analytic measurement will facilitate early detection of disease recurrence and can predict therapeutic efficacy.

Performance of a multianalyte test as an aid for the diagnosis of ovarian cancer in symptomatic women

BACKGROUND

Concomitant with the development of in vitro diagnostic multivariate index assays (IVDMIAs) to improve the diagnostic efficiency of ovarian cancer detection is the need to identify appropriate biostatistical approaches to assess improvements in risk predication. In this study, we assessed the utility of three different approaches for comparing diagnostic efficiency of an ovarian cancer multivariate assay in a retrospective case--control phase 2 biomarker trial. The control cohort included both disease-free women and women with benign gynecological conditions to more accurately reflect the target population of symptomatic women.

METHODS

The study cohort comprised plasma samples from 244 healthy controls, 223 women with benign gynecological conditions, 53 borderline ovarian cancer cases and 222 women with malignant epithelial ovarian cancer. A multivariate classification model was developed that incorporated plasma concentrations of CA125, C-reactive protein (CRP), serum amyloid-A (SAA), interleukin-6 (IL6) and interleukin-8 (IL8) that were measured using in vitro diagnostics assays on medical device approved clinical analysers. The posterior probability values derived from the implemented algorithm were used for comparisons of the diagnostic performance between the multianalyte panel and CA125 using multiple methods; area under the curve (AUC) of the receiver operating characteristics curve, integrated discrimination improvement (IDI) and net reclassification improvement (NRI).

RESULTS

Each of the biomarkers displayed significantly elevated plasma concentrations in malignant ovarian cancer patients compared with either benign or control subjects. For the discrimination of borderline and malignant ovarian cancer from control and benign subjects, the multivariate classification model showed a significantly greater AUC than that for CA125 alone (88.4% versus 84.3%, respectively, p < 0.001). At a posterior probability threshold of 0.5, the IVDMIA delivered a specificity of 92.3% and a sensitivity of 76.4%. When set at a specificity of 95%, the multimarker diagnostic delivered a sensitivity of 69.5% compared with 62.5% for CA125. Enhanced diagnostic performance of the IVDMIA over the use of CA125 alone was confirmed statistically by alternative comparisons using IDI and NRI.

CONCLUSIONS

This study confirms in an independent sample set that a blood-based multianalyte assay has significant advantages over CA125 for distinguishing symptomatic women with borderline and malignant ovarian cancer from controls or those with benign disease.

Multianalyte assay systems in the differential diagnosis of ovarian cancer

INTRODUCTION

The efficient triage of women diagnosed with a pelvic mass presents a current area of unmet need. Unnecessary surgical intervention performed on patients at a decreased risk of malignancy represents a significant source of preventable morbidity, anxiety and cost. Likewise, delayed or overlooked referral of patients harboring malignant tumors is strongly associated with diminished outcomes. Current tools including imaging modalities and the CA 125 blood test are of insufficient accuracy to overcome these challenges. The use of multianalyte assays systems which include additional biomarkers capable of complementing the performance of CA 125 may offer the best hope of improvement.

AREAS COVERED

Recent findings regarding the use of multianalyte biomarker panels for the differential diagnosis of a pelvic mass are reviewed and discussed. Particular attention is paid to to the FDA approved ROMA and OVA1 tests. The development, validation, recent evaluation and comparative performances of these two tests are reviewed in detail.

EXPERT OPINION

The performances achieved by the ROMA and OVA1 diagnostic tests represent significant milestones in the application of multianalyte assay systems into standard clinical practice. The overall impact and cost-effectiveness of widespread clinical use of these tools remains to be evaluated.

The effects of cholera toxin on cellular energy metabolism

Multianalyte microphysiometry, a real-time instrument for simultaneous measurement of metabolic analytes in a microfluidic environment, was used to explore the effects of cholera toxin (CTx). Upon exposure of CTx to PC-12 cells, anaerobic respiration was triggered, measured as increases in acid and lactate production and a decrease in the oxygen uptake. We believe the responses observed are due to a CTx-induced activation of adenylate cyclase, increasing cAMP production and resulting in a switch to anaerobic respiration. Inhibitors (H-89, brefeldin A) and stimulators (forskolin) of cAMP were employed to modulate the CTx-induced cAMP responses. The results of this study show the utility of multianalyte microphysiometry to quantitatively determine the dynamic metabolic effects of toxins and affected pathways.