Citations

Abstract Extracellular vesicles (EV) are phospholipid‐encapsulated nanoparticles secreted by cells into their surrounding environment. EVs can transfer a variety of biomolecules that mediate intercellular communication and play a key role in physiological and pathological processes. Therefore, EVs are emerging as new biomarkers for diseases, therapeutic targets, and drug delivery vehicles. The isolation and detection of EVs requires time‐consuming and labor‐intensive processes, first to extract EVs from biological and physiological fluids and then to detect EV‐associated molecules with high sensitivity. The methodologies and instruments commonly used for EV analysis are not widely accessible outside of dedicated research laboratories, creating practical barriers for the study of EV‐associated molecules in biology research and clinical applications. To bridge this gap, we developed a proof‐of‐concept digital microfluidic device that can automatedly extract EVs from 20 µL of culture and human plasma samples within 25 min and detect EV‐bound proteins (e.g PD‐L1) on‐chip using an electrochemical sensor. This work serves as a framework for the development of streamlined EV analysis in both research and diagnostics.

Abstract Background. Extracellular vesicles (EV) are emerging as new biomarkers for cancer diagnostics and therapeutic monitoring1. For example, in patients that receive PD1/PD-L1 immune checkpoint inhibitors (a key pillar of cancer immunotherapy), circulating EV-derived PD-L1 is gaining attention as a non-invasive biomarker for therapeutic efficacy. Standard methodologies to measure EV-derived PD-L1 requires ultracentrifugation to first separate EVs and then quantify those that express PD-L1 using nano flow cytometry. These are tedious processes that require trained technologists in centralized facilities, which is a key barrier to frequently monitoring EV-based biomarkers. Yet, frequent monitoring is crucial to quickly identify and stop an ineffective therapy while more fruitful options are still available. Method. To bridge the gap, we develop a proof-of-concept digital microfluidic (DMF) device that can separate EVs directly from biofluids and quantify PD-L1+ EVs automatedly. Briefly, DMF device supports automatedly droplet handling, including droplet transport, splitting and mixing, based on electrowetting principles2. Immunomagnetic beads were used to capture EVs from biofluids, and EVs were then detected by electrochemical sensors inserted into the device. These tips of the electrochemical sensors were modified with gold nanoparticle self-assembled layers to enhance target binding, and CD9 antibodies were immobilized on the tips to bind to EVs. We then used anti-PD-L1 as secondary antibodies for target detection. Differential Pulse Voltammetry (DPV)3 were performed to obtain the results. Results. We used the DMF device to extract 109- 1011 #/mL EVs secreted by a human breast cancer cell line (MDA-MB-231). Briefly, 10 mL of cell culture media was loaded into the DMF device, and the sample was mixed and incubated with a 10 mL droplet of immunomagnetic beads to capture EVs. After 5 min, EVs were eluted in 20 mL of elution buffer, and the beads were discarded. We estimated the number of EVs using Nanoparticle Tracking Analysis; the number of EVs extracted on-chip was comparable with those that were extracted using standard in-tube method. We also verified the purity of the EVs extracted on-chip using Western Blot. Our results showed that the electrochemical sensors can detect as low as 104 #/mL PD-L1+ EVs, with a linear range of 104 – 107 #/mL (R2=0.9701). The entire process can be completed within 1 hour. Conclusion. We integrated automated EV extraction and their surface marker detection in a single DMF device. Our next step is to extract and detect EV-based biomarkers from plasma samples. This platform holds promise for the regular monitoring of EV-based biomarkers that are indicators of therapeutic responses in patients that receive cancer immunotherapies. References1. F. Lucien, D. Gustafson, M. Lenassi et al, Journal of extracellular vesicles 12 (12), 12385 (2023). 2. Y. Zhang and Y. Liu, Sensors & Diagnostics (2022). 3. Y. Zhang, J. Liu, T.-W. Lo et al, Biosensors and Bioelectronics: X, 100490 (2024). Citation Format: Ting-Wen Lo, Yuqian Zhang, Jing Liu, Yohan Kim, Haidong Dong, Fabrice Lucien, Yuguang Liu. Rapid extraction and detection of extracellular vesicle-derived PD-L1 in a microfluidic platform [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A030.

The management of glioblastomas (GBMs) is challenged by the development of therapeutic resistance and early disease recurrence, despite multi-modal therapy. This may be attributed to the presence of glioma stem cells (GSCs) which are known to survive radio- and chemotherapy, by circumventing death signals and inducing cell re-population. Recent findings suggest GSCs may be enriched by certain treatment modality. These necessitate the development of novel therapeutics capable of targeting GBM cell plasticity and therapy-resistant GSCs. Here, aided by computer-assisted structure characterization and target identification, we predicted that a novel 5-(2′,4′-difluorophenyl)-salicylanilide derivative, LCC-09, could target dopamine receptors and oncogenic markers implicated in GBMs. Bioinformatics data have indicated that dopamine receptor (DRD) 2, DRD4, CD133 and Nestin were elevated in GBM clinical samples and correlated to TMZ (Temozolomide) resistance and increased ALDH (Aldehyde dehydrogenase) activity (3.5–8.9%) as well as enhanced (2.1–2.4-fold) neurosphere formation efficiency in U87MG and D54MG GBM cell lines. In addition, TMZ-resistant GSC phenotype was associated with up-regulated DRD4, Akt, mTOR, β-catenin, CDK6, NF-κB and Erk1/2 expression. LCC-09 alone, or combined with TMZ, suppressed the tumorigenic and stemness traits of TMZ-resistant GBM cells while concomitantly down-regulating DRD4, Akt, mTOR, β-catenin, Erk1/2, NF-κB, and CDK6 expression. Notably, LCC-09-mediated anti-GBM/GSC activities were associated with the re-expression of tumor suppressor miR-34a and reversal of TMZ-resistance, in vitro and in vivo. Collectively, these data lay the foundation for further exploration of the clinical feasibility of administering LCC-09 as single-agent or combinatorial therapy for patients with TMZ-resistant GBMs.

Consensus diagnostic recommendations to distinguish GORD from eosinophilic oesophagitis (EoE) by response to a trial of proton pump inhibitors (PPIs) unexpectedly uncovered an entity called ‘PPI-responsive oesophageal eosinophilia’ (PPI-REE). PPI-REE refers to patients with clinical and histological features of EoE that remit with PPI treatment. Recent and evolving evidence, mostly from adults, shows that patients with PPI-REE and patients with EoE at baseline are clinically, endoscopically and histologically indistinguishable and have a significant overlap in terms of features of Th2 immune-mediated inflammation and gene expression. Furthermore, PPI therapy restores oesophageal mucosal integrity, reduces Th2 inflammation and reverses the abnormal gene expression signature in patients with PPI-REE, similar to the effects of topical steroids in patients with EoE. Additionally, recent series have reported that patients with EoE responsive to diet/topical steroids may also achieve remission on PPI therapy. This mounting evidence supports the concept that PPI-REE represents a continuum of the same immunological mechanisms that underlie EoE. Accordingly, it seems counterintuitive to differentiate PPI-REE from EoE based on a differential response to PPI therapy when their phenotypic, molecular, mechanistic and therapeutic features cannot be reliably distinguished. For patients with symptoms and histological features of EoE, it is reasonable to consider PPI therapy not as a diagnostic test, but as a therapeutic agent. Due to its safety profile, ease of administration and high response rates (up to 50%), PPI can be considered a first-line treatment before diet and topical steroids. The reasons why some patients with EoE respond to PPI, while others do not, remain to be elucidated.