Project description:Purpose: Extracellular vesicle (EV)‑derived microRNAs (miRNAs) are a class of circulating miRNAs located in the plasma that are are now considered the next generation of cancer “theranostic” tools, with a strong clinical relevance. Although the potential role of EV-packaged miRNAs in breast cancer diagnosis has been widely reported, further studies are still demanded to address this challenging issue. The present study examined the expression profiles of EVs and circulating miRNAs with the aim of identifying novel miRNA signatures in breast cancer, and verify their diagnostic accurancy.
Project description:Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Controls: 5 cases; ER +/HER2- breast cancer patients : 11 cases
Project description:Transcriptional profiling of Homo sapiens inflammatory skin diseases (whole skin biospies): Psoriasis (Pso), vs Atopic Dermatitis (AD) vs Lichen planus (Li), vs Contact Eczema (KE), vs Healthy control (KO) In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation. In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation.
Project description:Cervical cancer is a global public health subject as it affects women in the reproductive ages, and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50% mortality rate. Poor awareness and access to effective diagnosis have led to this enormous disease burden, calling for point-of-care, minimally invasive diagnosis methods. Here, an end-to-end quantitative approach for a new kind of diagnosis has been developed, comprising identification of optimal biomarkers, design of the sensor, and simulation of the diagnostic circuit. Using miRNA expression data in the public domain, we identified circulating miRNA biomarkers specific to cervical cancer using multi-tier screening. Synthetic riboregulators called toehold switches specific for the biomarker panel were then designed. To predict the dynamic range of toehold switches for use in genetic circuits as biosensors, we developed a generic grammar of these switches, and built a multivariate linear regression model using thermodynamic features derived from RNA secondary structure and interaction. The model yielded predictions of toehold efficacy with an adjusted R2 = 0.59. Reaction kinetics modelling was performed to predict the sensitivity of the second-generation toehold switches to the miRNA biomarkers. Simulations showed a linear response between 10nM and 100nM before saturation. Our study demonstrates an end-to-end workflow for the efficient design of genetic circuits geared towards the effective detection of unique genomic signatures that would be increasingly important in today’s world. The approach has the potential to direct experimental efforts and minimise costs. All resources are provided open-source (https://github.com/igem2019) under GNU GPLv3 licence.
Project description:Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer. Background MicroRNA expression is frequently dysregulated in cancer and it could be used potentially as a disease classifier and a prognostic tool in cancer. It has been reported that the cancer associated specific microRNAs were stably detected in blood. The objective of this study was to discover a panel of circulating microRNAs as potential ER+/HER2- breast cancer biomarkers. Methods We compared levels of circulating microRNAs in blood samples from 11 ER+/HER2- advanced breast cancer patients with age-matched 5 control subjects by using microarray-based expression profiling. We validated the level of microRNAs by real-time quantitative polymerase cycle reaction (RT-qPCR) in 40 control subjects, 180 early breast cancer patients (EBC), and 52 metastatic breast cancer patients (MBC). Then, we assessed the association between the levels of microRNA and clinical outcomes of ER+/HER2- metastatic breast cancer.