Tumor-derived exosomes possess significant clinical relevance due to their unique composition of genetic and protein material that is representative of the parent tumor. Specific isolation as well as identification of proportions of these clinically relevant exosomes (CREs) from biological samples could help to better understand their clinical significance as cancer biomarkers. Herein, we present a simple approach for quantification of the proportion of CREs within the bulk exosome population isolated from patient serum. This proportion of CREs can potentially inform on the disease stage and enable non-invasive monitoring of inter-individual variations in tumor-receptor expression levels. Our approach utilises a Surface Plasmon Resonance (SPR) platform to quantify the proportion of CREs in a two-step strategy that involves (i) initial isolation of bulk exosome population using tetraspanin biomarkers (i.e., CD9, CD63), and (ii) subsequent detection of CREs within the captured bulk exosomes using tumor-specific markers (e.g., human epidermal growth factor receptor 2 (HER2)). We demonstrate the isolation of bulk exosome population and detection of as low as 10% HER2(+) exosomes from samples containing designated proportions of HER2(+) BT474 and HER2(−) MDA-MB-231 cell derived exosomes. We also demonstrate the successful isolation of exosomes from a small cohort of breast cancer patient samples and identified that approximately 14–35% of their bulk population express HER2.

Cancer is a dynamic disease with heterogenic molecular signatures and constantly evolves during the course of the disease. Single cell proteomic analysis could offer a suitable pathway to monitor cancer cell heterogeneity and deliver critical information for the diagnosis, recurrence, and drug-resistant mechanisms in cancer. Current standard techniques for proteomic analysis such as ELISA, mass spectrometry, and Western blots are time-consuming, expensive, and often require fluorescence labeling that fails to provide accurate information about the multiple protein expression changes at the single cell level. Herein, we report a surface-enhanced Raman spectroscopy-based simple microfluidic device that enables the screening of single circulating tumor cells (CTC) in a dynamic state to precisely understand the heterogeneous expression of multiple protein biomarkers in response to therapy. It further enables identifying intercellular heterogeneous expression of CTC surface proteins which would be highly informative to identify the cancer cells surviving treatment and potentially responsible for drug resistance. Using a bead and cell line-based model system, we successfully detect single bead and single cell spectra when flowed through the device. Using SK-MEL-28 melanoma cells, we demonstrate that our system is capable of monitoring heterogeneous expressions of multiple surface protein markers (MCSP, MCAM, and LNGFR) before and during drug treatment. Integrating a label-free electrochemical system with the device, we also monitor the expression of an intracellular protein (here, BRAF V600E ) under drug treatment. Finally, we perform a longitudinal study with 15 samples from five different melanoma patients who underwent therapy. We find that the average expression of receptor proteins in a patient fails to determine the therapy response particularly when the disease progresses. However, single CTC analysis with our device shows a high level of intercellular heterogeneity in the receptor expression profiles of patient-derived CTCs and identifies heterogeneity within CTCs. More importantly, we find that a fraction of CTCs still shows a high expression of these receptor proteins during and after therapy, indicating the presence of resistant CTCs which may evolve after a certain time and progress the disease. We believe this automated assay will have high clinical importance in disease diagnosis and monitoring treatment and will significantly advance the understanding of cancer heterogeneity on the single cell level.

The use of circulating tumor nucleic acids (ctNA) in patient liquid biopsies for targeted genetic analysis is rapidly increasing in clinical oncology. Still, the call for an integrated methodology, which is both rapid and sensitive for analyzing trace ctNA amount in liquid biopsies, has unfortunately not been fully realized. Herein, we performed complex liquid biopsy sample-to-targeted genetic analysis on a biochip with a 50 copies-detection limit within 30 min. Our biochip uniquely integrated the following: (1) electrical lysis and release of cellular targets with minimal processing; (2) nanofluidic manipulation to accelerate molecular kinetics of solid-phase isothermal amplification; and (3) single-step capture and amplification of multiple NA targets prior to nanozyme-mediated electrochemical detection. Using prostate cancer liquid biopsies, we successfully demonstrated multifunctionality for cancer risk prediction; correlation of serum and urine analyses; and cancer relapse monitoring.

Cancer diagnosis and patient monitoring require sensitive and simultaneous measurement of multiple cancer biomarkers considering that single biomarker analysis present inadequate information on the underlying biological transformations. Thus, development of sensitive and selective assays for multiple biomarker detection might improve clinical diagnosis and expedite the treatment process. Herein, a microfluidic platform for the rapid, sensitive, and parallel detection of multiple cancer-specific protein biomarkers from complex biological samples is presented. This approach utilizes alternating current electrohydrodynamic-induced surface shear forces that provide exquisite control over fluid flow thereby enhancing target-sensor interactions and minimizing non-specific binding. Further, the use of surface-enhanced Raman scattering-based spectral encoding with individual barcodes for different targets enables specific and simultaneous detection of captured protein biomarkers. Using this approach, the specific and sensitive detection of clinically relevant biomarkers including human epidermal growth factor receptor 2 (HER2); Mucin 1, cell surface associated (MUC1); epidermal growth factor receptor; and Mucin 16, cell surface associated (MUC16) at concentrations as low as 10 fg mL in patient serum is demonstrated. Successful target detection from patient samples further demonstrates the potential of this current approach for the clinical diagnosis, which envisages a clinical translation for a rapid and sensitive appraisal of clinical samples in cancer diagnostics.

Simultaneous analysis of messenger RNA (mRNA), microRNA (miRNA), and long noncoding RNA (lncRNA)-multi-RNA-type profiling-is increasingly crucial in cancer diagnostics. Yet, rapid multi-RNA-type profiling is challenging due to enzymatic amplification reliance and RNA-type-dependent characteristics. Here, a nanodevice is reported to uniquely use alterable alternating current electrohydrodynamic (ac-EHD) forces to enhance probe-target hybridization prior to direct native RNA target detection, without target amplification or surface functionalization. To exemplify clinical applicability, noninvasive screening of next-generation prostate cancer (PCa) RNA biomarkers (of different types) in patient urine samples is performed. A strong correlation between multi-RNA-type expression and aggressive PCa is found, and the nanodevice performance is statistically evaluated. It is believed that this miniaturized system exhibits great potential for cancer risk stratification via multi-RNA-type profiling.