Although circulating cell-free DNA (cfDNA) is a promising biomarker for the diagnosis and prognosis of various tumors, clinical correlation of cfDNA with gastric cancer has not been fully understood. To address this, we developed a highly sensitive cfDNA capture system by integrating polydopamine (PDA) and silica. PDA-silica hybrids incorporated different molecular interactions to a single system, enhancing cfDNA capture by 1.34-fold compared to the conventional silica-based approach (p = 0.001), which was confirmed using cell culture supernatants. A clinical study using human plasma samples revealed that the diagnostic accuracy of the new system to be superior than the commercially available cfDNA kit, as well as other serum antigen tests. Among the cancer patients, plasma cfDNA levels exhibited a good correlation with the size of a tumor. cfDNA was also predicative of distant metastasis, as the median cfDNA levels of metastatic cancer patients were ~60-fold higher than those without metastasis (p = 0.008). Furthermore, high concordance between tissue biopsy and cfDNA genomic analysis was found, as HER2 expression in cfDNA demonstrated an area under ROC curve (AUC) of 0.976 (p <0.001) for detecting patients with HER2-positive tumors. The new system also revealed high prognostic capability of cfDNA, as the concentration of cfDNA was highly associated with the survival outcomes. Our novel technology demonstrates the potential to achieve efficient detection of cfDNA that may serve as a reliable biomarker for gastric tumor.

(1) Background: Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. Although various serum enzymes have been utilized for the diagnosis and prognosis of HCC, the currently available biomarkers lack the sensitivity needed to detect HCC at early stages and accurately predict treatment responses. (2) Methods: We utilized our highly sensitive cell-free DNA (cfDNA) detection system, in combination with a machine learning algorithm, to provide a platform for improved diagnosis and prognosis of HCC. (3) Results: cfDNA, specifically alpha-fetoprotein (AFP) expression in captured cfDNA, demonstrated the highest accuracy for diagnosing malignancies among the serum/plasma biomarkers used in this study, including AFP, aspartate aminotransferase, alanine aminotransferase, albumin, alkaline phosphatase, and bilirubin. The diagnostic/prognostic capability of cfDNA was further improved by establishing a cfDNA score (cfD_HCC), which integrated the total plasma cfDNA levels and cfAFP-DNA expression into a single score using machine learning algorithms. (4) Conclusion: The cfD_HCC score demonstrated significantly improved accuracy in determining the pathological features of HCC and predicting patients’ survival outcomes compared to the other biomarkers. The results presented herein reveal that our cfDNA capture/analysis platform is a promising approach to effectively utilize cfDNA as a biomarker for the diagnosis and prognosis of HCC.

Point-of-care (POC) use is one of the essential goals of biosensing platforms. Because the increasing demand for testing cannot be met by a centralized laboratory-based strategy, rapid and frequent testing at the right time and place will be key to increasing health and safety. To date, however, there are still difficulties in developing a simple and affordable, as well as sensitive and effective, platform that enables POC use. In terms of materials, hydrogels, a unique family of water-absorbing biocompatible polymers, have emerged as promising components for the development of biosensors. Combinations of hydrogels have various additional applications, such as in hydrophilic coatings, nanoscale filtration, stimuli-responsive materials, signal enhancement, and biodegradation. In this review, we highlight the recent efforts to develop hydrogel-assisted biosensing platforms for POC use, especially focusing on polysaccharide hydrogels like agarose, alginate, chitosan, and so on. We first discuss the pros and cons of polysaccharide hydrogels in practical applications and then introduce case studies that test different formats, such as paper-based analytical devices (PADs), microfluidic devices, and independent platforms. We believe the analysis in the present review provides essential information for the development of biosensing platforms for POC use in resource-limited settings.

Hepatocellular carcinoma (HCC) is a highly aggressive form of liver cancer with poor prognosis. The lack of reliable biomarkers for early detection and accurate diagnosis and prognosis poses a significant challenge to its effective clinical management. In this study, we investigated the diagnostic and prognostic potential of programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) expression in peripheral blood mononuclear cells (PBMCs) in HCC. PD-1 and CTLA-4 gene expression was analyzed comparatively using PBMCs collected from HCC patients and healthy individuals. The results revealed higher PD-1 gene expression levels in patients with multifocal tumors, lymphatic invasion, or distant metastasis than those in their control counterparts. However, conventional serum biomarkers of liver function do not exhibit similar correlations. In conclusion, PD-1 gene expression is associated with OS and PFS and CTLA-4 gene expression is associated with OS, whereas the serum biomarkers analyzed in this study show no significant correlation with survival in HCC. Hence, PD-1 and CTLA-4 expressed in PBMCs are considered potential prognostic biomarkers for patients with HCC that can facilitate prediction of malignancy, response to currently available HCC treatments, and overall survival.