Label-free electrochemical immunosensor based on gold nanoparticle/polyethyleneimine/reduced graphene oxide nanocomposites for the ultrasensitive detection of cancer biomarker matrix metalloproteinase-1.

Matrix metalloproteinase-1 (MMP-1) is associated with many types of cancers, including oral, colorectal, and brain cancers. This paper describes the fabrication of an MMP-1 immunosensor based on a gold nanoparticle/polyethyleneimine/reduced graphene oxide (AuNP/PEI/rGO)-modified disposable screen-printed electrode (SPE). A microwave-assisted single-step method was employed for the simultaneous reduction of gold and graphene oxide in a PEI environment to avoid AuNP agglomeration. The crystal structure, chemical composition, optical properties, and interior morphology of the materials were probed by X-ray diffraction, Raman spectroscopy, UV-visible spectrometry, and transmission electron microscopy techniques. To assemble a label-free MMP-1 immunosensor layer-by-layer, 3-mercaptopropionic acid was utilized due to its strong sulfur-gold bonding ability, and its tail end was attached to a carboxyl group, allowing the MMP-1 antibody (anti-MMP-1) to be subsequently cross-linked using the traditional N-(3-dimethylaminopropyl) and N' ethylcarbodiimide hydrochloride method. Differential pulse voltammetry analysis showed a linear relationship with MMP-1 concentration in the range of 1-50 ng ml-1 with an R2 value of ∼0.996 (n = 5, RSD < 5%). This immunosensor was successfully applied for MMP-1 detection in urine, saliva, bovine serum, and cell culture media (HSC-3 & C6) of oral and brain cancers showing results comparable to those of the credible ELISA method.

Establishment and validation of a novel risk model based on CD8T cell marker genes to predict prognosis in thyroid cancer by integrated analysis of single-cell and bulk RNA-sequencing.

Papillary thyroid cancer (PTC) is a histological type of thyroid cancer, and CD8T is important for the immune response. The single-cell RNA data were acquired from Gene Expression Omnibus. SingleR package was used for cluster identification, and CellChat was exploited to evaluate the interaction among several cell types. Bulk RNA data obtained from the cancer genome atlas were used for determination of prognosis using Kaplan-Meier and Receiver Operating Characteristic curve. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were applied for assessment of function enrichment. The drug sensitivity was calculated in Gene Set Cancer Analysis. The regulatory network was constructed by STRING and Cytoscape. We identified 23 cell clusters and 10 cell types. Cell communication results showed CD8T cell was vital among all immune cell types. Enrichment analysis found the marker genes of CD8T cell was enriched in some signal pathways related to tumor development. Overall, FAM107B and TUBA4A were considered as hub genes and used to construct a risk model. Most immune checkpoint expressions were upregulated in tumor group. Tumor mutation burden results indicated that prognosis of PTC was not related to the mutation of hub genes. Drug sensitivity analysis showed some drugs could be effectively used for the treatment of PTC, and regulatory network identified some targets for the immunotherapy. A 2-gene model of PTC was developed based on the single-cell RNA and bulk RNA data. Besides, we found CD8T was essential for the immune response in PTC.