Project description:The diagnosis of Kawasaki disease (KD) is often difficult to distinguish from adenovirus (HAdV) and Group A streptococcal disease (GAS). We sought to: 1) to define the KD transcriptional signature that can aid in the diagnosis of complete and incomplete KD in children; 2) to identify specific biomarkers that objectively discriminate between KD and other mimicking conditions, including HAdV and 3) to test the prognostic utility of GEP to determine response to IVIG therapy and development of coronary artery lesions (CAL). Methods: Blood RNA samples were analyzed from 76 pediatric patients with complete KD, 13 with incomplete KD, 19 patients with HAdV, 17 patients with GAS disease, and age- and sex-matched healthy controls (HC). We used class comparisons (MW p< 0.01, Benjamini-Hochberg, and 1.25 fold change filter), class prediction, modular analysis and MDTH analyses to define the specificity of the KD profiles and identify markers of severity. Results: Statistical group comparisons identified 7,899 genes differentially expressed in 39 complete KD patients versus HC (KD biosignature). This signature was validated in another 37 patients with complete KD and in 13 patients with incomplete KD. Modular analysis in children with complete KD demonstrated overexpression of inflammation, neutrophils, myeloid cell, coagulation cascade, and cell cycle genes. The KNN class prediction algorithm identified 25-classifier genes that differentiated children with KD vs HAdV infection in two independent cohorts of patients with 96% (95% CI [80%-99%]) sensitivity and 95% [74%-99%] specificity. MDTH scores in KD patients significantly correlated with the baseline c-reactive protein (R=0.29, p=0.008) and was four fold higher than in children with HAdV (p<0.01). In addition, KD patients that remained febrile 36 hours after treatment with IVIG (non-responders) demonstrated higher baseline, pre-treatment MDTH values compared with responders [12,290 vs. 5,572 respectively; p=0.009]. Conclusion: Transcriptional signatures can be used as a tool to discriminate between KD and HAdV infection, and may also provide prognostic information. 113 samples, no replicates, 9 HAdV, 57 cKD, 12 FUO, 13 GAS, 3 GAS/SF, 5 inKD, 14 healthy control

Project description:The diagnosis of Kawasaki disease (KD) is often difficult to distinguish from adenovirus (HAdV) and Group A streptococcal disease (GAS). We sought to: 1) to define the KD transcriptional signature that can aid in the diagnosis of complete and incomplete KD in children; 2) to identify specific biomarkers that objectively discriminate between KD and other mimicking conditions, including HAdV and 3) to test the prognostic utility of GEP to determine response to IVIG therapy and development of coronary artery lesions (CAL). Methods: Blood RNA samples were analyzed from 76 pediatric patients with complete KD, 13 with incomplete KD, 19 patients with HAdV, 17 patients with GAS disease, and age- and sex-matched healthy controls (HC). We used class comparisons (MW p< 0.01, Benjamini-Hochberg, and 1.25 fold change filter), class prediction, modular analysis and MDTH analyses to define the specificity of the KD profiles and identify markers of severity. Results: Statistical group comparisons identified 7,899 genes differentially expressed in 39 complete KD patients versus HC (KD biosignature). This signature was validated in another 37 patients with complete KD and in 13 patients with incomplete KD. Modular analysis in children with complete KD demonstrated overexpression of inflammation, neutrophils, myeloid cell, coagulation cascade, and cell cycle genes. The KNN class prediction algorithm identified 25-classifier genes that differentiated children with KD vs HAdV infection in two independent cohorts of patients with 96% (95% CI [80%-99%]) sensitivity and 95% [74%-99%] specificity. MDTH scores in KD patients significantly correlated with the baseline c-reactive protein (R=0.29, p=0.008) and was four fold higher than in children with HAdV (p<0.01). In addition, KD patients that remained febrile 36 hours after treatment with IVIG (non-responders) demonstrated higher baseline, pre-treatment MDTH values compared with responders [12,290 vs. 5,572 respectively; p=0.009]. Conclusion: Transcriptional signatures can be used as a tool to discriminate between KD and HAdV infection, and may also provide prognostic information.

Project description:BACKGROUND:microRNAs (miRNAs) are considered promising cancer biomarkers, showing high reliability, sensitivity and stability. Our study aimed to identify associations between whole blood miRNA profiles, presence of circulating tumor cells (CTCs) and clinical outcome in post-operative early breast cancer patients (EBC) to assess the utility of miRNAs as prognostic markers in this setting. METHOD:A total of 48 post-operative patients, recruited in frame of the SUCCESS A trial, were included in this retrospective study and tested with a panel of 8 miRNAs (miR-10b, -19a, - 21, - 22, -20a, - 127, - 155, -200b). Additional 17 female healthy donors with no previous history of cancer were included in the study as negative controls. Blood samples were collected at different time points (pre-adjuvant therapy, post-adjuvant therapy, 2 years follow up), total RNA was extracted and the relative concentration of each miRNA was measured by quantitative PCR and compared in patients stratified on blood collection time or CTC detection. Furthermore, we compared miRNA profiles of patients, for each time point separately, and healthy donors. CTCs were visualized and quantified with immunocytochemistry analysis. Data were analyzed using non-parametric statistical tests. RESULTS:In our experimental system, miR-19a, miR-22 and miR-127 showed the most promising results, differentiating patients at different time points and from healthy controls, while miR-20a, miR-21 and miR-200b did not show any difference among the different groups. miR-10b and miR-155 were never detectable in our experimental system. With respect to patients' clinical characteristics, we found a significant correlation between miR-200b and lymph node status and between miR-20a and tumor type. Furthermore, miR-127 correlated with the presence of CTCs. Finally, we found a borderline significance between Progression Free Survival and miR-19a levels. CONCLUSIONS:This pilot study suggests that profiling whole blood miRNAs could help to better stratify post-operative EBC patients without any sign of metastasis to prevent later relapse or metastatic events.

Dataset Information

Diagnostic and prognostic potential of eight whole blood microRNAs for equine sarcoid disease.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets