Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Philipone Elizabeth
PROVIDER: S-ECPF-GEOD-62809 | biostudies-other |
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias Comparison of 10 samples from non-progressive leukoplakias (did not turn into oral squamous cell carcinoma), with 10 samples from progressive leukoplakias (turned into oral squamous cell carcinoma w/in 5 yrs)
2015-02-01 | E-GEOD-62809 | biostudies-arrayexpress
Project description:Predictive Value of MicroRNAs in the Progression of Oral Leukoplakias
2015-02-01 | GSE62809 | GEO
Project description:Breast cancer (BrC) is the most frequent malignancy and the leading cause of cancer death among women worldwide. Approximately 70% of BrC are classified as luminal-like subtype, expressing the estrogen receptor. One of the most common and effective adjuvant therapies for this BrC subtype is endocrine therapy. However, its effectiveness is limited, with relapse occurring in up to 40% of patients. Because microRNAs have been associated with several mechanisms underlying endocrine resistance and sensitivity, they may serve as predictive and/or prognostic biomarkers in this setting. Hence, the main goal of this study was to investigate whether miRNAs deregulated in endocrine-resistant BrC may be clinically relevant as prognostic and predictive biomarkers in patients treated with adjuvant endocrine therapy. A global expression assay allowed for the identification of microRNAs differentially expressed between luminal BrC patients with or without recurrence after endocrine adjuvant therapy. Then, six microRNAs were chosen for validation using quantitative reverse transcription polymerase chain reaction in a larger set of tissue samples. Thus, miR-30c-5p, miR-30b-5p, miR-182-5p, and miR-200b-3p were found to be independent predictors of clinical benefit from endocrine therapy. Moreover, miR-182-5p and miR-200b-3p displayed independent prognostic value for disease recurrence in luminal BrC patients after endocrine therapy. Our results indicate that selected miRNAs' panels may constitute clinically useful ancillary tools for management of luminal BrC patients. Nevertheless, additional validation, ideally in a multicentric setting, is required to confirm our findings.
| S-EPMC6749838 | biostudies-literature
Project description:Host microRNAs can influence the cytokine storm associated SARS-CoV-2 infection and proposed as biomarkers for COVID-19 disease. In the present study, serum MiRNA-106a and miRNA-20a were quantified by real time-PCR in 50 COVID-19 patients hospitalized at Minia university hospital and 30 healthy volunteers. Profiles of serum inflammatory cytokines (TNF-α, IFN-γ, and IL-10) and TLR4 were analyzed by Eliza in patients and controls. A highly significant decrease (P value = 0.0001) in the expressions of miRNA-106a and miRNA-20a was reported in COVID-19 patients compared to controls. A significant decrease in the levels of miRNA-20a was also reported in patients with lymphopenia, patients having chest CT severity score (CSS) > 19 and in patients having O2 saturation less than 90%. Significantly higher levels of TNF-α, IFN-γ, IL-10 and TLR4 were reported in patients compared to controls. IL-10 and TLR4 levels were significantly higher in patients having lymphopenia. TLR-4 level was higher in patients with CSS > 19 and in patients with hypoxia. Using univariate logistic regression analysis, miRNA-106a, miRNA-20a, TNF-α, IFN-γ, IL-10 and TLR4 were identified as good predictors of disease. Receiver operating curve showed that the downregulation of miRNA-20a in patients having lymphopenia, patients with CSS > 19 and patients with hypoxia could be a potential biomarker with AUC = 0.68 ± 0.08, AUC = 0.73 ± 0.07 and AUC = 0.68 ± 0.07 respectively. Also, ROC curve showed accurate association between the increase of serum IL-10 and TLR-4 and lymphopenia among COVID-19 patients with AUC = 0.66 ± 0.08 and AUC = 0.73 ± 0.07 respectively. ROC curve showed also that serum TLR-4 could be a potential marker for high CSS with AUC = 0.78 ± 0.06. A negative correlation was detected between miRNA-20a with TLR-4 (r = - 0.30, P value = 0.03). We concluded that, miR-20a, is a potential biomarker of COVID-19 severity and blockade of IL-10 and TLR4 may constitute a novel therapy for COVID-19 patients.
| S-EPMC9979137 | biostudies-literature
Project description:The overall 5-year survival for melanoma is 91%. However, if distant metastasis occurs (stage IV), cure rates are < 15%. Hence, melanoma detection in earlier stages (stages I-III) maximises the chances of patient survival. We measured the expression of a panel of 17 microRNAs (miRNAs) (MELmiR-17) in melanoma tissues (stage III; n = 76 and IV; n = 10) and serum samples (collected from controls with no melanoma, n = 130; and patients with melanoma (stages I/II, n = 86; III, n = 50; and IV, n = 119)) obtained from biobanks in Australia and Germany. In melanoma tissues, members of the 'MELmiR-17' panel were found to be predictors of stage, recurrence, and survival. Additionally, in a minimally-invasive blood test, a seven-miRNA panel (MELmiR-7) detected the presence of melanoma (relative to controls) with high sensitivity (93%) and specificity (≥ 82%) when ≥ 4 miRNAs were expressed. Moreover, the 'MELmiR-7' panel characterised overall survival of melanoma patients better than both serum LDH and S100B (delta log likelihood = 11, p < 0.001). This panel was found to be superior to currently used serological markers for melanoma progression, recurrence, and survival; and would be ideally suited to monitor tumour progression in patients diagnosed with early metastatic disease (stages IIIa-c/IV M1a-b) to detect relapse following surgical or adjuvant treatment.
| S-EPMC4534690 | biostudies-literature
Project description:BACKGROUND: While several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer. RESULTS: We used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression. CONCLUSIONS: We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.
| S-EPMC2821358 | biostudies-literature
Project description:We aimed to evaluate the value of ATN biomarker classification system (amyloid beta [A], pathologic tau [T], and neurodegeneration [N]) for predicting conversion from mild cognitive impairment (MCI) to dementia. In a sample of people with MCI (n = 415) we assessed predictive performance of ATN classification using empirical knowledge-based cut-offs for each component of ATN and compared it to two data-driven approaches, logistic regression and RUSBoost machine learning classifiers, which used continuous clinical or biomarker scores. In data-driven approaches, we identified ATN features that distinguish normals from individuals with dementia and used them to classify persons with MCI into dementia-like and normal groups. Both data-driven classification methods performed better than the empirical cut-offs for ATN biomarkers in predicting conversion to dementia. Classifiers that used clinical features performed as well as classifiers that used ATN biomarkers for prediction of progression to dementia. We discuss that data-driven modeling approaches can improve our ability to predict disease progression and might have implications in future clinical trials.
| S-EPMC8842842 | biostudies-literature
Project description:BackgroundThe predictive value of bleeding risk scores for atrial fibrillation in older patients is not as well known. The goal of this study was to evaluate the predictive value of HASBLED, ORBIT and ATRIA for major bleeding (MB) and intracranial hemorrhage (ICH) in patients ≥ 75 years with atrial fibrillation and oral anticoagulation (OAC).MethodsA retrospective unicenter study including patients ≥ 75 years with atrial fibrillation (AF) and OAC. A total of 7613 patients ≥ 75 years with AF and OAC included between 2014 and 2018 (registry: NCT04364516). We analyzed the discriminative value of HASBLED, ATRIA and ORBIT scores for bleeding endpoints (major bleeding as primary endpoint and intracerebral hemorrhage as secondary). Cox regression was used to predict major bleeding with each scale and also for searching other variables potentially predictor of major bleeding. Model discrimination was assessed using Harrell's C-statistic. Calibration was assessed with goodness-of-fit test proposed by Gronnesby and Borgan.ResultsDuring a mean follow up of 4.0 years (IQR: 2.4-5.7 years), 729 patients developed MB (2.61 per 100 patients/year) and 243 patients developed ICH (0.85 per 100 patients/year). Three scores showed a low discrimination for major bleeding, being ORBIT the best (HASBLED C statistic = 0.557; ATRIA C statistic = 0.568; ORBIT C statistic = 0.595) and also a low discrimination for ICH (HASBLED C statistic = 0.509; ATRIA C statistic = 0.522; ORBIT C statistic = 0.526). Among the variables that are part of the scores and other baseline characteristics, after multivariable adjustment only sex (male), dementia, prior admission for bleeding, anemia and liver disease were found as a predictors of MB.ConclusionsIn older patients under oral anticoagulation with atrial fibrillation, the risk scores HASBLED, ATRIA and ORBIT showed a weak discrimination for major bleeding and intracranial hemorrhage. Therefore, other better alternatives should be evaluated for this purpose.
| S-EPMC10568544 | biostudies-literature
Project description:Sub-optimal fetal development is associated with an increased risk of developing cardiovascular disease, type 2 diabetes (T2D) and adiposity later in life. However, definitions of intrauterine growth restriction (IUGR) and small for gestational age (SGA) are based on simple statistical approaches that may misclassify infants with a normal developmental profile and vice versa. We used an unbiased global profiling approach to identify gene expression patterns in umbilical cord tissue from 38 infants and identified a set of 466 genes which separated the subjects into 2 distinct groups – one biased towards lower birth weight and one biased towards normal birth weight. The data suggest that approximately 30% of children of normal size have a molecular profile more typical of impaired fetal development and who may be on a programmed trajectory. Differences in expression between the two groups encompassed 384 upregulated and 82 downregulated genes. Molecular profiling at birth may have utility in identifying markers that potentially reflect antenatal developmental and may be predictive of future phenotypic development after birth. Importantly, it may provide an alternative to the current classification of infants using birth weights. RNA from umbilical cord tissue from full term neonates was extracted and hybridized. Separation into 2 distinct groups, independent of birth weight, but based solely on gene expression levels was analysed by Genespring. After appropriate statistical analysis, one group was keenly associated with a higher birth weight (22 samples) while the other was associated with a lower birth-weight (18 samples). Technical replicates were included for all 40 samples.
2011-10-20 | E-GEOD-24818 | biostudies-arrayexpress
Project description:Sub-optimal fetal development is associated with an increased risk of developing cardiovascular disease, type 2 diabetes (T2D) and adiposity later in life. However, definitions of intrauterine growth restriction (IUGR) and small for gestational age (SGA) are based on simple statistical approaches that may misclassify infants with a normal developmental profile and vice versa. We used an unbiased global profiling approach to identify gene expression patterns in umbilical cord tissue from 38 infants and identified a set of 466 genes which separated the subjects into 2 distinct groups – one biased towards lower birth weight and one biased towards normal birth weight. The data suggest that approximately 30% of children of normal size have a molecular profile more typical of impaired fetal development and who may be on a programmed trajectory. Differences in expression between the two groups encompassed 384 upregulated and 82 downregulated genes. Molecular profiling at birth may have utility in identifying markers that potentially reflect antenatal developmental and may be predictive of future phenotypic development after birth. Importantly, it may provide an alternative to the current classification of infants using birth weights.
2011-10-21 | GSE24818 | GEO