A fluorescence-electrochemiluminescence dual-mode sensor based on a "switch" system for highly selective and sensitive K-ras gene detection.

Herein, an fluorescence (FL)-electrochemiluminescence (ECL) dual-mode biosensor is constructed based on the dual-signal "turn-on" strategy of functionalized metal-organic frameworks nanosheets (RuMOFNSs)-tetraferrocene for K-ras gene detection, and the mechanism of bursting through front-line orbital theory is explained for the first time. Amino-functionalized tetraferrocene-labeled probe DNA molecules are linked to RuMOFNSs by covalent amide bonds, acting as FL and ECL intensity switches. The target DNA, complementary to the probe DNA, triggers cyclic amplification of the target by nucleic acid exonuclease III (Exo III), repelling tetraferrocene reporter groups away from RuMOFNSs and inhibiting the electron transfer process and photoinduced electron transfer (PET) effect. These phenomena induce a double turn-on of FL and ECL signals with a high signal-to-noise ratio. The developed FL-ECL dual-mode sensing platform provides sensitive detection of the K-ras gene with detection limits of 0.01 fM (the detection range is 1 fM to 1 nM) and 0.003 fM (the detection range is 0.01 fM to 10 pM), respectively. In addition, the proposed dual-mode sensor can be easily extended to detect other disease-related biomarkers by changing the specific target and probe base sequences, depicting potential applications in bioanalysis and early disease diagnosis.

A self-powered and reagent-less electrochemical aptasensor based on a DNA walker and tetraferrocene for the detection of aflatoxin B1.

We constructed a self-powered and reagent-less electrochemical aptamer sensor for sensitive detection of aflatoxin B1 (AFB1). Here, the metal ion Mn2+ required for the DNAzyme to drive a DNA walker is wrapped in UIO-66(Zr)-(COOH)2 and AFB1 triggers the DNAzyme walking strands to automatically and continuously cut the tetraferrocene-labeled substrate strands, which results in a significant decrease in the electrochemical signal. Under the optimal conditions, the concentration dependence of AFB1 is linear in the concentration range of 0.1 pg mL-1 to 0.195 µg mL-1, and the limit of detection is as low as 4.8 fg mL-1. The sensor displayed good performance even for samples with a complex matrix, such as a peanut sample. The recoveries of AFB1 obtained ranged from 95.5 to 106.8%. The developed sensing platform is reagent-less, self-powered, and highly sensitive. It holds great potential for detection of AFB1 in environmental and food samples.

A Sensitive Thrombin Aptasensor Based on Target Circulation Strategy.

A convenient homogeneous electrochemical thrombin sensor based on potential-assisted Au-S deposition and a dual signal amplification strategy was established in this study. Potential-assisted Au-S deposition does not require the modification of the gold electrode, thus eliminating the tedious pre-modification of the electrode. To better amplify the output signal, both ends of the signal hairpin probes were modified with a new electroactive substance, tetraferrocene, which was synthesized by the authors. Thrombin was immediately hybridized with a thiol-modified probe to open the stem-loop structure. After chain hybridization, thrombin was replaced and participated in the next round of the reaction; thus, the cascade amplification of the signal was realized. The hybrid chain formed an Au-S deposition under potential assistance, and the electrochemical signal of tetraferrocene could then be measured through differential pulse voltammetry (DPV) and consequently used for the quantitative detection of target thrombin. In addition, the detection limit of thrombin was as low as 0.06 pmol/L, and the detection of common interfering proteins was highly specific.

Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma.

BACKGROUND: Tumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory. METHODS: RNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes. RESULTS: LUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein-protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value. CONCLUSION: mRNAsi-related hub genes could be a potential biomarker of LUSC.

Weighted Gene Coexpression Network Analysis of Features That Control Cancer Stem Cells Reveals Prognostic Biomarkers in Lung Adenocarcinoma.

Purpose We aimed to identify new prognostic biomarkers of lung adenocarcinoma (LUAD) based on cancer stem cell theory. Materials and Methods: RNA-seq and microarray data were obtained with clinical information downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant module and hub genes. The hub genes were validated via microarray data from GEO, and a prognostic signature with prognostic hub genes was constructed. Results LUAD patients enrolled from TCGA had a higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. Some clinical features and prognoses were found to be highly correlated with mRNAsi. WGCNA found that the green module and blue module were the most significant modules related to mRNAsi; 50 key genes were identified in the green module and were enriched mostly in the cell cycle, chromosome segregation, chromosomal region and microtubule binding. Six hub genes were revealed through the protein-protein interaction (PPI) network and Molecular Complex Detection (MCODE) plugin of Cytoscape software. Based on external verification with the GEO database, these six genes are not only expressed at different levels in LUAD and normal tissues but also associated with different clinical features. In addition, the construction of a prognostic signature with three hub genes showed high predictive value. Conclusion mRNAsi-related biomarkers may suggest a new potential treatment strategy for LUAD.