Diagnosing the RGS11 Lung Cancer Biomarker: The Integration of Competitive Immunoassay and Isothermal Nucleic Acid Exponential Amplification Reaction.

Abstract

Lung cancer is the primary cause of cancer-associated mortality worldwide, which makes the identification of reliable lung cancer biomarkers a pressing need for early diagnosis and prognosis. RGS11, which is a regulator of G-protein signaling and also a lung cancer biomarker, plays an important role in cancer-related metastasis. However, trace levels of RGS11 (in the range of pg/mL) in serum samples make it difficult to quantify using currently available enzyme-linked immunosorbent assay (ELISA) kits and, therefore, this hinders progress in the discovery of new approaches for treating lung cancer. The aim of this study is to develop a rapid, sensitive, and reliable platform for the detection of RGS11 lung cancer biomarker based on a suspension immunoassay coupled with an isothermal exponential amplification strategy. Our study was initiated by the functionalization of magnetic beads with anti-RGS11 antibodies (Ab-MB) by EDC (1-ethyl-3-(3-(dimethylamino)propyl)-carbodiimide)/NHS ( N-hydroxysulfosuccinimide) activation. Ab-MB served as a sensing probe for the competitive immunorecognitions between known concentrations of His-tag RGS11 and unknown concentrations of target RGS11 in serum. The reporter anti-His antibodies, which were modified with primers that induced an isothermal exponential amplification reaction, were subsequently introduced to the reaction mixture that resulted in the formation of immunosandwich complexes. The exponentially amplified DNA duplex that was intercalated with SYBR Green was designated as a signal reporter for the assessment of RGS11 in an inversely proportional relationship. The sensing platform was excellent for the determination of RGS11 with an exceptional detection limit of 148 fg/mL and a linear dynamic range of 0.1-10 pg/mL using a minimal sample volume (20 μL) and with a reaction time of 1.5 h. In addition, we challenged the sensing platform with RGS11-spiked samples (in 2× diluted serum), and an acceptable recovery rate (>90%) was observed. Finally, 24 clinical samples acquired from patients with advanced lung cancer (C), inflammation (I), and heart failure (H) were analyzed by this newly developed sensing platform and a commercial ELISA kit for validation. This sensing platform has potential in biomedical applications for clinically diagnosing liquid biopsy samples for patients with lung cancer. Moreover, the universal design of our proposed system is easily adapted to detect any other protein if a His-tag recombinant protein is available.