Minicircles for a two-step blood biomarker and PET imaging early cancer detection strategy

Targeting and monitoring ovarian cancer invasion with an RNAi and peptide delivery system

RNA interference (RNAi) therapeutics are an emerging class of medicines that selectively target mRNA transcripts to silence protein production and combat disease. Despite the recent progress, a generalizable approach for monitoring the efficacy of RNAi therapeutics without invasive biopsy remains a challenge. Here, we describe the development of a self-reporting, theranostic nanoparticle that delivers siRNA to silence a protein that drives cancer progression while also monitoring the functional activity of its downstream targets. Our therapeutic target is the transcription factor SMARCE1, which was previously identified as a key driver of invasion in early-stage breast cancer. Using a doxycycline-inducible shRNA knockdown in OVCAR8 ovarian cancer cells both in vitro and in vivo, we demonstrate that SMARCE1 is a master regulator of genes encoding proinvasive proteases in a model of human ovarian cancer. We additionally map the peptide cleavage profiles of SMARCE1-regulated proteases so as to design a readout for downstream enzymatic activity. To demonstrate the therapeutic and diagnostic potential of our approach, we engineered self-assembled layer-by-layer nanoparticles that can encapsulate nucleic acid cargo and be decorated with peptide substrates that release a urinary reporter upon exposure to SMARCE1-related proteases. In an orthotopic ovarian cancer xenograft model, theranostic nanoparticles were able to knockdown SMARCE1 which was in turn reported through a reduction in protease-activated urinary reporters. These LBL nanoparticles both silence gene products by delivering siRNA and noninvasively report on downstream target activity by delivering synthetic biomarkers to sites of disease, enabling dose-finding studies as well as longitudinal assessments of efficacy.

Ultrasensitive Surface Plasmon Resonance Sensor with a Feature of Dynamically Tunable Sensitivity and High Figure of Merit for Cancer Detection

Cancer is one of the leading causes of death worldwide, and it is well known that an early detection of cancer in a human body will provide an opportunity to cure the cancer. Early detection of cancer depends on the sensitivity of the measuring device and method, where the lowest detectable concentration of the cancerous cell in a test sample becomes a matter of high importance. Recently, Surface Plasmon Resonance (SPR) has proven to be a promising method to detect cancerous cells. The SPR method is based on the detection of changes in refractive indices of samples under testing and the sensitivity of such a SPR based sensor is related to the smallest detectable change in the refractive index of the sample. There exist many techniques where different combinations of metals, metal alloys and different configurations have been shown to lead to high sensitivities of the SPR sensors. Based on the difference in the refractive index between a normal healthy cell and a cancerous cell, recently, SPR method has been shown to be applicable to detect different types of cancers. In this work, we propose a new sensor surface configuration that comprises of gold-silver-graphene-black phosphorus to detect different cancerous cells based on the SPR method. Additionally, recently we proposed that the application of electric field across gold-graphene layers that form the SPR sensor surface can provide enhanced sensitivity than that is possible without the application of electrical bias. We utilized the same concept and numerically studied the impact of electrical bias across the gold-graphene layers combined with silver and black Phosphorus layers which forms the SPR sensor surface. Our numerical results have shown that electrical bias across the sensor surface in this new heterostructure can provide enhanced sensitivity compared to the original unbiased sensor surface. Not only that, our results have shown that as the electrical bias increases, the sensitivity increases up to a certain value and stabilizes at a still improved sensitivity value. Such dependence of sensitivity on the applied bias provides a dynamic tunability of the sensitivity and figure-of-merit (FOM) of the sensor to detect different types of cancer. In this work, we used the proposed heterostructure to detect six different types of cancers: Basal, Hela, Jurkat, PC12, MDA-MB-231, and MCF-7. Comparing our results to work published recently, we were able to achieve an enhanced sensitivity ranging from 97.2 to 1851.4 (deg/RIU) and FOM values ranging from 62.13 to 89.81 far above the values presented recently by other researchers.

The Need to Pair Molecular Monitoring Devices with Molecular Imaging to Personalize Health

By enabling the non-invasive monitoring and quantification of biomolecular processes, molecular imaging has dramatically improved our understanding of disease. In recent years, non-invasive access to the molecular drivers of health versus disease has emboldened the goal of precision health, which draws on concepts borrowed from process monitoring in engineering, wherein hundreds of sensors can be employed to develop a model which can be used to preventatively detect and diagnose problems. In translating this monitoring regime from inanimate machines to human beings, precision health posits that continual and on-the-spot monitoring are the next frontiers in molecular medicine. Early biomarker detection and clinical intervention improves individual outcomes and reduces the societal cost of treating chronic and late-stage diseases. However, in current clinical settings, methods of disease diagnoses and monitoring are typically intermittent, based on imprecise risk factors, or self-administered, making optimization of individual patient outcomes an ongoing challenge. Low-cost molecular monitoring devices capable of on-the-spot biomarker analysis at high frequencies, and even continuously, could alter this paradigm of therapy and disease prevention. When these devices are coupled with molecular imaging, they could work together to enable a complete picture of pathogenesis. To meet this need, an active area of research is the development of sensors capable of point-of-care diagnostic monitoring with an emphasis on clinical utility. However, a myriad of challenges must be met, foremost, an integration of the highly specialized molecular tools developed to understand and monitor the molecular causes of disease with clinically accessible techniques. Functioning on the principle of probe-analyte interactions yielding a transducible signal, probes enabling sensing and imaging significantly overlap in design considerations and targeting moieties, however differing in signal interpretation and readout. Integrating molecular sensors with molecular imaging can provide improved data on the personal biomarkers governing disease progression, furthering our understanding of pathogenesis, and providing a positive feedback loop toward identifying additional biomarkers and therapeutics. Coupling molecular imaging with molecular monitoring devices into the clinical paradigm is a key step toward achieving precision health.

BRET Sensors for Imaging Membrane Integrity of Microfluidically Generated Extracellular Vesicles

Extracellular vesicles (EVs) derived from various cell lines have been extensively used as natural nanodelivery vehicles for drug, protein, and nucleic acid deliveries in therapeutic applications for cancer. Recently, we developed a microfluidic-based reconstruction strategy as a novel method to generate microRNA-loaded membrane vesicles for cancer therapy in vivo. We used EVs and cell membranes isolated from different source of cells for this reconstruction process. The microfluidic system produced reconstructed vesicles of uniform sizes with high microRNA loading efficiency independent of input membrane sources (EVs or cell membranes). To address the functional integrity of the membrane structure and of proteins in the reconstructed EVs, we introduce a membrane-insertable bioluminescence resonance energy transfer (BRET) sensor system. This sensor, with its membrane-insertable palmitoylation signal peptide sequence derived from a growth-associated protein 43 (GAP43), helps in trafficking the fusion protein to the cell membrane upon its expression in cells and allows for imaging reconstructed membrane vesicles using optical imaging. In this chapter, we detail the stepwise methods used for the engineering of cells using this sensor, isolation of EVs from the engineered cells, preparation of reconstructed EVs by microfluidic processing, and BRET imaging of reconstructed EVs for membrane integrity evaluation.

A dual-signal fluorometric-colorimetric sensing platform and visual detection with a smartphone for the determination of β-galactosidase activity based on fluorescence silicon nanoparticles

As one of primary biomarkers of ovarian cancer in early stages, β-galactosidase (β-Gal) is significant in the discovery and diagnosis of the disease. In this work, we constructed a multi-signal sensing platform based on silicon nanoparticles (Si NPs) for β-Gal activity determination. When β-Gal was introduced to the sensing system, 2-Nitrophenyl β-D-galactopyranoside (ONPG) could be converted to o-Nitrophenol (o-NP), which had a characteristic absorption peak at 416 nm and the colorless solution turned yellow. The fluorescence emission of Si NPs at 450 nm can be greatly quenched by o-NP as a consequence of inner filter effect (IFE). This dual-signal fluorometric and colorimetric determination approach could be utilized to detect β-Gal in the range of 2-120 U/L and 6-120 U/L. The limits of detection were 1.36 U/L and 1.07 U/L, respectively. This sensing platform could be successfully utilized to detect β-Gal in real samples. Additionally, a visual detection method was designed to achieve quantitative analysis of β-Gal with the assistance of the smartphone.