Machine learning to detect the SINEs of cancer.

We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a machine learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to 7615 samples from 5178 individuals, 2073 with solid cancer and the remainder without cancer. Samples from patients with cancer and controls were prespecified into four cohorts used for model training, analyte integration, and threshold determination, validation, and reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the validation cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and eight common protein biomarkers detected 51% of the cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature-the global reduction of AluS subfamily elements in the circulating DNA of patients with solid cancer. We confirmed this reduction through the analysis of another independent dataset obtained with a different approach (whole-genome sequencing). The evaluation of Alu elements may therefore have the potential to enhance the performance of several methods designed for the earlier detection of cancer.

Interrogation of Electrochemical Aptamer-Based Sensors via Peak-to-Peak Separation in Cyclic Voltammetry Improves the Temporal Stability and Batch-to-Batch Variability in Biological Fluids.

Electrochemical, aptamer-based (E-AB) sensors support continuous, real-time measurements of specific molecular targets in complex fluids such as undiluted serum. They achieve these measurements by using redox-reporter-modified, electrode-attached aptamers that undergo target binding-induced conformational changes which, in turn, change electron transfer between the reporter and the sensor surface. Traditionally, E-AB sensors are interrogated via pulse voltammetry to monitor binding-induced changes in transfer kinetics. While these pulse techniques are sensitive to changes in electron transfer, they also respond to progressive changes in the sensor surface driven by biofouling or monolayer desorption and, consequently, present a significant drift. Moreover, we have empirically observed that differential voltage pulsing can accelerate monolayer desorption from the sensor surface, presumably via field-induced actuation of aptamers. Here, in contrast, we demonstrate the potential advantages of employing cyclic voltammetry to measure electron-transfer changes directly. In our approach, the target concentration is reported via changes in the peak-to-peak separation, ΔEP, of cyclic voltammograms. Because the magnitude of ΔEP is insensitive to variations in the number of aptamer probes on the electrode, ΔEP-interrogated E-AB sensors are resistant to drift and show decreased batch-to-batch and day-to-day variability in sensor performance. Moreover, ΔEP-based measurements can also be performed in a few hundred milliseconds and are, thus, competitive with other subsecond interrogation strategies such as chronoamperometry but with the added benefit of retaining sensor capacitance information that can report on monolayer stability over time.

Alkanethiol Monolayer End Groups Affect the Long-Term Operational Stability and Signaling of Electrochemical, Aptamer-Based Sensors in Biological Fluids.

Electrochemical aptamer-based (E-AB) sensors achieve highly precise measurements of specific molecular targets in untreated biological fluids. This unique ability, together with their measurement frequency of seconds or faster, has enabled the real-time monitoring of drug pharmacokinetics in live animals with unprecedented temporal resolution. However, one important weakness of E-AB sensors is that their bioelectronic interface degrades upon continuous electrochemical interrogation-a process typically seen as a drop in faradaic and an increase in charging currents over time. This progressive degradation limits their in vivo operational life to 12 h at best, a period that is much shorter than the elimination half-life of the vast majority of drugs in humans. Thus, there is a critical need to develop novel E-AB interfaces that resist continuous electrochemical interrogation in biological fluids for prolonged periods. In response, our group is pursuing the development of better packed, more stable self-assembled monolayers (SAMs) to improve the signaling and extend the operational life of in vivo E-AB sensors from hours to days. By invoking hydrophobicity arguments, we have created SAMs that do not desorb from the electrode surface in aqueous physiological solutions and biological fluids. These SAMs, formed from 1-hexanethiol solutions, decrease the voltammetric charging currents of E-AB sensors by 3-fold relative to standard monolayers of 6-mercapto-1-hexanol, increase the total faradaic current, and alter the electron transfer kinetics of the platform. Moreover, the stability of our new SAMs enables uninterrupted, continuous E-AB interrogation for several days in biological fluids, like undiluted serum, at a physiological temperature of 37 °C.

Open Source Software for the Real-Time Control, Processing, and Visualization of High-Volume Electrochemical Data.

Electrochemical sensors are major players in the race for improved molecular diagnostics due to their convenience, temporal resolution, manufacturing scalability, and their ability to support real-time measurements. This is evident in the ever-increasing number of health-related electrochemical sensing platforms, ranging from single-measurement point-of-care devices to wearable devices supporting immediate and continuous monitoring. In support of the need for such systems to rapidly process large data volumes, we describe here an open-source, easily customizable, multiplatform compatible program for the real-time control, processing, and visualization of electrochemical data. The software's architecture is modular and fully documented, allowing the easy customization of the code to support the processing of voltammetric (e.g., square-wave and cyclic) and chronoamperometric data. The program, which we have called Software for the Analysis and Continuous Monitoring of Electrochemical Systems (SACMES), also includes a graphical interface allowing the user to easily change analysis parameters (e.g., signal/noise processing, baseline correction) in real-time. To demonstrate the versatility of SACMES we use it here to analyze the real-time data output by (1) the electrochemical, aptamer-based measurement of a specific small-molecule target, (2) a monoclonal antibody-detecting DNA-scaffold sensor, and (3) the determination of the folding thermodynamics of an electrode-attached, redox-reporter-modified protein.