Project description:Comparison of genes associated with the EMT between cytotrophoblast cells (CTB) and extravillous trophoblast cells (EVT) from normal third trimester placenta and abnormally invasive placenta (AIP)
Project description:Early-onset preeclampsia (EOPE) is a severe pregnancy complication associated with significant maternal and fetal morbidity and mortality. Currently, there is a critical need for accurate, non-invasive biomarkers to facilitate early diagnosis and effective management of EOPE. In this study, we aimed to investigate the transcriptional alterations and non-invasive biomarker potential of peripheral blood microRNAs in patients with EOPE. Through our research, we successfully identified two reliable plasma miRNA biomarkers and proposed a circulating two-miRNA panel for the non-invasive early detection of EOPE. Additionally, we independently validated our findings in different patient cohorts using various technological platforms.
Project description:Magnetic resonance imaging (MRI) and ultrasound methods used for the diagnosis of an abnormally invasive placenta (AIP) have a wide range of sensitivity (Se, 33-93%) and specificity (Sp, 71-100%) levels, which results in a high risk of unfavorable maternal and perinatal outcomes. The relevance of optimizing the diagnosis of AIP is beyond doubt. Given the epigenetic nature of trophoblast invasion, we aimed to quantitate microRNAs and proteins of their target genes that are potentially associated with AIP in blood plasma samples from 64 pregnant women at gestation weeks 30-34 by reverse transcription coupled with polymerase chain reaction (RT-PCR) and Western blotting, respectively. Statistically significant increases in the expression levels of hsa-miR-17-5p, hsa-miR-21-5p, hsa-miR-25-3p, hsa-miR-92a-3p, and hsa-miR-320a-3p were revealed in the groups of women with AIP (accreta, increta, percreta) relative to the group of women with scars on the uterus or to the group with placenta previa. Opposite changes in the expression level of "gene-target protein/miRNA" pairs were found for the α-subunit of the clusterin secretory form and any of the hsa-miR-21-5p, hsa-miR-25-3p, hsa-miR-92a-3p, hsa-miR-320a-3p, and hsa-miR-17-5p in all cases of AIP. The developed logistic regression models to diagnose AIP cases of various severity gave Se values of 88.8-100% and Sp values of 91.6-100% using a combination of hsa-miR-21-5p, hsa-miR-92a-3p, hsa-miR-320a-3p, or clusterin levels.
Project description:Acute pulmonary embolism (APE) remains among the most formidable challenges facing public health practice in the 21st century. Accurate diagnosis of APE is severely hindered by the lack of biomarkers with both high sensitivity and specificity. MicroRNAs (miRNAs) involve various pathophysiologic processes underlying multitudinous diseases. Accmulating evidences point to the fact that miRNAs may serve as ideal biomarkers.The aim of the present study was to explore the potential of plasma miRNAs as biomarkers for diagnosis of APE.
Project description:Acute pulmonary embolism (APE) remains among the most formidable challenges facing public health practice in the 21st century. Accurate diagnosis of APE is severely hindered by the lack of biomarkers with both high sensitivity and specificity. MicroRNAs (miRNAs) involve various pathophysiologic processes underlying multitudinous diseases. Accmulating evidences point to the fact that miRNAs may serve as ideal biomarkers.The aim of the present study was to explore the potential of plasma miRNAs as biomarkers for diagnosis of APE. Two TaqMan miRNA arrays were performed on plasma of 10 APE patients and 10 healthy controls.
Project description:Purpose: PCa is the second most commonly diagnosed malignancy in men. PCa Diagnosis are based on biopsy sampling that is an invasive, expensive procedure and does not accurately represent multifocal disease. It is desirable to have an easily accessible, minimally invasive way to accurately determine the molecular signature of patient’s tumor that can aid in diagnosis and risk stratification. Methods:we enrolled a total of 70 patients underwent 12-core transrectal ultrasound (TRUS) biopsy of which 48% had cancer in the diagnosis. The mean age at diagnosis was 67.15 (IR 55/75), the mean PSA (ng/ml) at diagnosis was 7.8 (IR 4.1/13.4) and the mean TRUS Volume (ml) was 53.5 (IR 29/86). The cancer biopsy presented 73.1% of positive core. Among all cancer patients, 57% showed a High grade of cancer status (Grade 3). Controls are patients with Benign Prostate Hyperplasia (BPH). MicroRNA-expression profiling (NGS analysis) was performed to identify tumor-related microRNAs (miRs) and determine their association with clinicopathological characteristics. Results: The expression of miRs -4732-3p, let7a, 26b-5p, 98-5p, 30c-5p and 21-5p may identified Prostate Cancer in plasma samples. Higher expression of mir-4732-3p is associated with a high grade tumor Conclusions: miRs signature discriminate Prostate cancer in plasma better to PSA values and is associated with high grade tumor status
Project description:To find potential biomarkers and molecular mechanism for placenta accreta spectrum disorders , we identified the differently expressed patterns of lncRNAs and mRNAs in invasive placneta and adherent normal placenta tissues. The results provided a novel insight into the pathogenesis of placenta accreta spectrum disorders .
Project description:MicroRNAs (miRNAs) are small endogenous non-coding RNA molecules capable of regulating gene expression at the post-transcriptional level either by translational inhibition or mRNA degradation and have recently been importantly related to the diagnosis and prognosis of the most relevant endocrine disorders. The endocrine system comprises various highly vascularized ductless organs regulating metabolism, growth and development, and sexual function. Endocrine disorders constitute the fifth principal cause of death worldwide, and they are considered a significant public health problem due to their long-term effects and negative impact on the patient's quality of life. Over the last few years, miRNAs have been discovered to regulate various biological processes associated with endocrine disorders, which could be advantageous in developing new diagnostic and therapeutic tools. The present review aims to provide an overview of the most recent and significant information regarding the regulatory mechanism of miRNAs during the development of the most relevant endocrine disorders, including diabetes mellitus, thyroid diseases, osteoporosis, pituitary tumors, Cushing's syndrome, adrenal insufficiency and multiple endocrine neoplasia, and their potential implications as disease biomarkers.
Project description:The paper "Metabolomic Machine Learning Predictor for Diagnosis and Prognosis of Gastric Cancer" addresses the need for non-invasive diagnostic tools for gastric cancer (GC). Traditional methods like endoscopy are invasive and expensive. The authors conducted a targeted metabolomics analysis of 702 plasma samples to develop machine learning models for GC diagnosis and prognosis. The diagnostic model, using 10 metabolites, achieved a sensitivity of 0.905, outperforming conventional protein marker-based methods. The prognostic model effectively stratified patients into risk groups, surpassing traditional clinical models.
I have successfully reproduced the diagnosis model from the paper. This machine learning-based system differentiates GC patients from non-GC controls using metabolomics data from plasma samples analyzed by liquid chromatography-mass spectrometry (LC-MS). The model focuses on 10 metabolites, including succinate, uridine, lactate, and serotonin. Employing LASSO regression and a random forest classifier, the model achieved an AUROC of 0.967, with a sensitivity of 0.854 and specificity of 0.926. This model significantly outperforms traditional diagnostic methods and underscores the potential of integrating machine learning with metabolomics for early GC detection and treatment.