Establishment of a direct quantitative method for measurement of microRNA-224 in serum by UHPLC/MS/MS

LC-MS-Based Direct Quantification of MicroRNAs in Rat Blood

MicroRNA (miRNA) has recently garnered significant research attention, owing to its potential as a diagnostic biomarker and therapeutic target. Liquid chromatography-mass spectrometry (LC-MS) offers accurate quantification, multiplexing capacity, and high compatibility with various matrices. These advantages establish it as a preferred technique for detecting miRNA in biological samples. In this study, we presented an LC-MS method for directly quantifying seven miRNAs (rno-miR-150, 146a, 21, 155, 223, 181a, and 125a) associated with immune and inflammatory responses in rat whole blood. To ensure miRNA stability in the samples and efficiently purify target analytes, we compared Trizol- and proteinase K-based extraction methods, and the Trizol extraction proved to be superior in terms of analytical sensitivity and convenience. Chromatographic separation was carried out using an oligonucleotide C18 column with a mobile phase composed of N-butyldimethylamine, 1,1,1,3,3,3-hexafluoro-2-propanol, and methanol. For MS detection, we performed high-resolution full scan analysis using an orbitrap mass analyzer with negative electrospray ionization. The established method was validated by assessing its selectivity, linearity, limit of quantification, accuracy, precision, recovery, matrix effect, carry-over, and stability. The proposed assay was then applied to simultaneously monitor target miRNAs in lipopolysaccharide-treated rats. Although potentially less sensitive than conventional methods, such as qPCR and microarray, this direct-detection-based LC-MS method can accurately and precisely quantify miRNA. Given these promising results, this method could be effectively deployed in various miRNA-related applications.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

Cancer drug resistance related microRNAs: recent advances in detection methods

MiRNAs are related to cancer drug resistance through various mechanisms. The advanced detection methods for the miRNAs are reviewed.

The Role of microRNA in Pancreatic Cancer

MicroRNAs (miRNAs) are small ribonucleic acid molecules that play a key role in regulating gene expression. The increasing number of studies undertaken on the functioning of microRNAs in the tumor formation clearly indicates their important potential in oncological therapy. Pancreatic cancer is one of the deadliest cancers. The expression of miRNAs released into the bloodstream appears to be a good indicator of progression and evaluation of the aggressiveness of pancreatic cancer, as indicated by studies. The work reviewed the latest literature on the importance of miRNAs for pancreatic cancer development.

Highly Sensitive and Specific Mass Spectrometric Platform for miRNA Detection Based on the Multiple-Metal-Nanoparticle Tagging Strategy

The multiple-metal-nanoparticle tagging strategy has generally been applied to the multiplexed detection of multiple analytes of interest such as microRNAs (miRNAs). Herein, it was used for the first time to improve both the specificity and sensitivity of a novel mass spectroscopic platform for miRNA detection. The mass spectroscopic platform was developed through the integration of the ligation reaction, hybridization chain reaction amplification, multiple-metal-nanoparticle tagging, and inductively coupled plasma mass spectrometry. The high specificity resulted from the adoption of the ligation reaction is further enhanced by the multiple-metal-nanoparticle tagging strategy. The combination of hybridization chain reaction amplification and metal nanoparticle tagging endows the proposed platform with the feature of high sensitivity. The proposed mass spectrometric platform achieved quite satisfactory quantitative results for Let-7a in real-world cell line samples with accuracy comparable to that of the real-time quantitative reverse-transcriptase polymerase chain reaction method. Its limit of detection and limit of quantification for Let-7a were experimentally determined to be about 0.5 and 10 fM, respectively. Furthermore, due to the unique way of utilizing the multiple-metal-nanoparticle tagging strategy, the proposed platform can unambiguously discriminate between the target miRNA and nontarget ones with single-nucleotide polymorphisms based on their response patterns defined by the relative mass spectral intensities among the multiple tagged metal elements and can also provide location information of the mismatched bases. Its unique advantages over conventional miRNA detection methods make the proposed platform a promising and alternative tool in the fields of clinical diagnosis and biomedical research.