Tumor immunotherapy is a prominent area of research in oncology, particularly focusing on the blockade of programmed death 1 (PD-1) and programmed death-ligand 1 (PD-L1) for cancer treatment. While this approach has revolutionized clinical care and improved survival rates, challenges remain in accurately assessing patient response due to inconsistencies between PD-L1 levels and clinical outcomes. Existing methods for evaluating PD-L1 levels, such as immunohistochemistry and ELISA, lack the required wide detection range, high sensitivity, and high-resolution quantification necessary for precision medicine.
To address these limitations, a reliable and rapid detection method is needed to determine PD-L1 expression levels as a predictive biomarker for treatment outcomes. Lateral flow analysis (LFA) utilizing gold nanoparticles has been widely employed in point-of-care diagnostics but currently falls short in terms of sensitivity and specificity compared to enzyme-linked immunosorbent assay (ELISA) testing. Additionally, the hook effect, an interference phenomenon in immunoassays, restricts the detection range. Presently, gold strip-based assays are limited to qualitative analysis, lacking an LFA-based PD-L1 detection method.
To overcome these challenges, fluorescent nanoprobes, particularly upconversion nanoparticles (UCNPs), offer advantages in high-specificity biomarker identification and single-molecule tracking. UCNPs provide exceptional brightness, optical stability, uniformity, and an ultrahigh signal-to-noise ratio, enabling detection sensitivity at the single-molecule level. Their intense light emission enhances protein capture and specific labeling, countering non-specific binding issues faced by current lateral flow assays.
This work aims to develop an innovative PD-L1 assay with superior ultrasensitivity, wide detection range, and high-resolution quantification. By employing a proposed PD-L1 antigen retrieval method, false-negative patient stratification can be reduced, thereby guiding anti-PD-1/PD-L1 therapy effectively. The integration of UCNPs and LFA holds promising potential to address the limitations of existing PD-L1 detection methods, enabling accurate and rapid assessment of PD-L1 levels for improved treatment decision-making. This proposed research endeavors to advance PD-L1 detection techniques by combining the benefits of UCNPs and LFA, thereby enhancing precision medicine in anti-PD-1/PD-L1 therapy.