No abstract

Tumor-derived extracellular vesicles (EVs) present in bodily fluids are emerging liquid biopsy markers for non-invasive cancer diagnosis and treatment monitoring. Because the majority of EVs in circulation are not of tumor origin, it is critical to develop new platforms capable of enriching tumor-derived EVs from the blood. Herein, we introduce a biostructure-inspired NanoVilli Chip, capable of highly efficient and reproducible immunoaffinity capture of tumor-derived EVs from blood plasma samples. Anti-EpCAM-grafted silicon nanowire arrays were engineered to mimic the distinctive structures of intestinal microvilli, dramatically increasing surface area and enhancing tumor-derived EV capture. RNA in the captured EVs can be recovered for downstream molecular analyses by reverse transcription Droplet Digital PCR. We demonstrate that this assay can be applied to monitor the dynamic changes of ROS1 rearrangements and epidermal growth factor receptor T790M mutations that predict treatment responses and disease progression in non-small cell lung cancer patients.

Well-preserved mRNA in circulating tumor cells (CTCs) offers an ideal material for conducting molecular profiling of tumors, thereby providing a noninvasive diagnostic solution for guiding treatment intervention and monitoring disease progression. However, it is technically challenging to purify CTCs while retaining high-quality mRNA.Here, we demonstrate a covalent chemistry–based nanostructured silicon substrate (“Click Chip”) for CTC purification that leverages bioorthogonal ligation–mediated CTC capture and disulfide cleavage–driven CTC release. This platform is ideal for CTC mRNA assays because of its efficient, specific, and rapid purification of pooled CTCs, enabling downstream molecular quantification using reverse transcription Droplet Digital polymerase chain reaction. Rearrangements of ALK/ROS1 were quantified using CTC mRNA and matched with those identified in biopsy specimens from 12 patients with late-stage non–small cell lung cancer. Moreover, CTC counts and copy numbers of ALK/ROS1 rearrangements could be used together for evaluating treatment responses and disease progression.

Purpose: To introduce and describe the feasibility of a novel method for abdominal fat segmentation on both water-saturated and non-water-saturated MR images with improved absolute fat tissue quantification. Materials and Methods:A general fat distribution model which fits both water-saturated (WS) and nonwater-saturated (NWS) MR images based on image gray-level histogram is first proposed. Next, a novel fuzzy c-means clustering step followed by a simple thresholding is proposed to achieve automated and accurate abdominal quantification taking into consideration the partial-volume effects (PVE) in abdominal MR images. Eleven subjects were scanned at central abdomen levels with both WS and NWS MRI techniques. Synthesized ''noisy'' NWS (nNWS) images were also generated to study the impact of reduced SNR on fat quantification using the novel approach. The visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) amounts of the WS MR images were quantified with a traditional intensity thresholding method as a reference to evaluate the performance of the novel method on WS, NWS, and nNWS MR images. Results:The novel approach resulted in consistent SAT and VAT amounts for WS, NWS, and nNWS images. Automatic segmentation and incorporation of spatial information during segmentation improved speed and accuracy. These results were in good agreement with those from the WS images quantified with a traditional intensity thresholding method and accounted for PVE contributions. Conclusion:The proposed method using a novel fuzzy cmeans clustering method followed by thresholding can achieve consistent quantitative results on both WS and NWS abdominal MR images while accounting for PVE contributing inaccuracies. THE ASSOCIATION OF human abdominal fat and its body distribution with multiple metabolic syndrome abnormalities has fueled interest in accurate, fast and automatic methods of adipose tissue quantification (1-4). Of the current imaging methods that can be applied, computed tomography (CT) and MRI are the most promising tools (5,6). Compared with CT, MRI can generate high quality cross-sectional images without ionizing radiation. Therefore, MRI is the preferable imaging modality particularly for longitudinal studies and studies that involve young subjects. Despite its straightforward appearance on MR images, abdominal fat tissue quantification has been challenging. Chief among these challenges are the disseminated distribution of fatty tissue and its inherent partial volume effects (PVE) in the visceral compartments of the abdomen and pelvis. Moreover, inherent visceral motion from peristalsis, vascular flow, pulsation, and breathing further contribute to limited accurate quantification.Due to the highly complicated abdominal compartments and the disseminated nature of visceral fat, the ratio of the number of partial-volume (PV) voxels to full-volume (FV) voxels may be large (7). Its impact on VAT quantification may also vary significantly depending on body size, habitus, and adiposity. A recent study has shown th...