Categories
Delta Opioid Receptors

Finally, femto luminol chemiluminescence reagent was delivered to detection compartment and chemiluminescence signal was captured using a CCD camera for 15s

Finally, femto luminol chemiluminescence reagent was delivered to detection compartment and chemiluminescence signal was captured using a CCD camera for 15s. into the HNSCC culture medium. Beta-tubulin (-Tub) was used as a loading control to estimate the number of cells in analyzed samples. Limits of detection (LOD) were 0.10 fg/mL for DSG3, and 0.20 fg/mL for VEGF-A, VEGF-C and -Tub. Three orders of magnitude semilogarithmic dynamic ranges were achieved. VEGF-A showed high in-cell expression, but VEGF-C had low levels inside cells. The very low LODs enabled quantifying these proteins released from single cells. Strong correlation between results from on-chip cell lysis, conventional off-line lysis and ELISA confirmed accuracy. strong class=”kwd-title” Keywords: Chemiluminescence, Microfluidics, HNSCC, Metastatic Cancer Biomarkers, Single cell, 3D Printing Graphical Abstract A 3D printed microfluidic array with on-line cell lysis was developed for single cell assays to detect metastatic cancer biomarker proteins at sub-fg/mL levels INTRODUCTION Ninety percent of all cancer deaths are caused by metastasis of initial tumors (Spano et al., 2012), and early detection leads to improved survival of cancer (Kalinich and Haber, 2018) and cancer metastasis patients (Gerges et al., 2010). While the approach reported here is applicable to any cancer and virtually any type of cells, the main goal of this work is to ML-098 demonstrate the ability to quantify ultralow concentration of desmoglein 3 (DSG3) as a membrane-bound diagnostic biomarker for lymph node metastasis in oral cancer, or head and neck squamous cell carcinoma (HNSCC) (Siriwardena et al., 2018; Apu, et al., 2018). Membrane protein DSG3 is usually a biomarker for occult lymph node metastasis of HNSCC (Patel et al., 2013). It is highly expressed in metastatic ML-098 oral malignancy cells in neck lymph nodes, but not found in non-invaded lymph nodes (Patel et al., 2008). Oral cancer has an unusually high tendency to metastasize due to an extensive nearby neck lymphatic network (Leemans et al., 1994; Forastiere et al., 2001; Marur and Forastiere, 2016; De Zinis et al., 2006). ML-098 Incidence of Mouse monoclonal to GATA1 occult lymph node metastasis ranges between 10 C 50% (Shah et al., 1990; Kuriakose and Trivedi, 2009; Mcke et al., 2014; Read ML-098 on NIH website on head and neck malignancy, 2020; ML-098 Read online on Genetics Home Reference, 2020; Koloutsos et al. 2014; Dogan et al., 2014). Thus, rapid and sensitive diagnosis of lymph node metastasis is essential for HNSCC prognosis and key for clinical staging and treatment decisions (Kuriakose and Trivedi, 2009; Snow et al., 1982). The histopathological hematoxylin-eosin (H&E)-immunohistochemistry (IHC) assay (de Bondt et al., 2007; Alkureishi et al., 2009; Don et al., 1995) can detect metastatic lesions ~0.2 mm in lymph nodes, but requires days to deliver the report and cannot be used for in-operative staging. Modern imaging tools (Di Gioia et al., 2015; de Bree et al., 2014; Chaturvedi et al., 2015), and assays of circulating cancer cells (Gerges et al., 2010) are not yet sensitive enough to detect very early metastasis. Real time (RT)-PCR, single-cell RNA sequencing and other next generation sequencing techniques can detect metastasis at single cell level coupled with strong cell sorting techniques such as fluorescence-activated cell sorting (FACS), but are relatively expensive, require long assay time and technical skills, and are mostly available in the research setting to date (Ferris et al., 2011; Ellsworth et al., 2017). H&E- IHC of sentinel lymph nodes remains the preferred option, despite false negatives due to failure to detect lesions 0.2 mm (Ferris et al., 2011; Kim et al., 2013). Thus, there is urgent need for fast, accurate, and ultrasensitive in-operative detection of metastatic oral and other cancers. Microfluidics can be used to design fast, reliable platforms for ultrasensitive automated multi-protein assays (Rusling, 2013). Microfluidic tools possess inherent qualification for low-cost production, ease of complex fluid handling, miniaturization and automation (Whitesides, 2006). With high surface area to volume ratio, microfluidics allowed ultrasensitive detection of analytes from small volumes due to improved conversation kinetics between targets and surface biorecognition elements. This interaction allows development of assays with much shorter assay time and lower cost compared to other protein quantification techniques (Sackmann et al, 2014; Sia et al, 2008; Henares et al, 2008). We previously exhibited the use of an amperometric microfluidic immunosensor to detect low concentrations of DSG3 as a reliable oral malignancy biomarker for lymph node metastasis (Patel et al., 2013). Several microfluidic immunosensors using electrochemical, fluorescent, electrochemiluminescent (ECL), and chemiluminescent (CL) detection have been developed to measure multiple protein and peptide biomarkers for cancer diagnostics (Malhotra et.