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A miRNA signature for early non-invasive diagnosis of pre-eclampsia

ABSTRACT: Background: Preeclampsia (PE) is a multi-systemic maternal syndrome with substantial maternal and fetal morbidity and mortality. Currently, there is no clinically viable non-invasive biomarker assay for early detection, thus limiting the effective prevention and therapeutic strategies for PE. Methods: We conducted a discovery-training-validation three-phase retrospective and prospective study with cross-platform and multicenter cohorts. The initial biomarkers were discovered and verified in tissue specimens by small RNA sequencing and qRT-PCR. A miRNA signature (miR2PE-score) was developed using the Firth’s bias-reduced logistic regression analysis, and subsequently validated in two independent multinational retrospective cohorts and two prospective plasma cohorts. Results: We initially identified five PE-associated differentially expressed miRNAs from miRNA sequencing data and subsequently validated two miRNAs (miR-196b-5p and miR-584-5p) as robust biomarkers by association analysis with clinical characteristics and qRT-PCR in tissue specimens in the discovery phase. Using the Firth’s bias-reduced logistic regression analysis, we developed the miR2PE-score for the early detection of PE. The miR2PE-score showed a high diagnostic performance with an area under the receiver operating characteristic curve (AUROC) of 0.920, 0.848, 0.864 and 0.812 in training, internal and two external validation cross-platform and multicenter cohorts, respectively. Finally, we demonstrated the non-invasive diagnostic performance of the miR2PE-score in two prospective plasma cohorts with AUROC of 0.933 and 0.787. Furthermore, the miR2PE-score revealed superior performance in non-invasive diagnosis compared with previously published miRNA biomarkers. Conclusions: We developed and validated a novel and robust blood-based miRNA signature, which may serve as a promising clinically applicable non-invasive tool for the early detection of PE.

ORGANISM(S): Homo sapiens

PROVIDER: GSE206988 | GEO | 2022/09/21

REPOSITORIES: GEO

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Project description:Importance: Severe alcoholic hepatitis (AH) is a highly lethal disease with a 3-month mortality up to 50%. Corticosteroids are the current standard of care although nearly 40% of the patients do not respond and accurate pre-treatment predictors of survival are lacking. Objective: To develop a prognostic score based on molecular and clinical variables before initiation of corticosteroids. Design, Setting, and Participants: Gene expression profiling of fixed liver biopsy obtained for diagnosis of severe AH assessed in 3 independent cohorts (1 prospective cohort for prognostic gene signature and integrative score derivation, and 2 retrospective cohorts for validation). Samples were obtained from 4 European and 1 US medical centers between July 2006 and February 2015. Exposures: Biopsy proven severe AH patients treated with corticosteroids. Main Outcome Measures: Identification of a gene signature combined with a validated clinical index to develop an integrative prognostic score of survival without death or liver transplantation in a derivation cohort (n=71). Prognostic performance of the score was validated in an independent multi-center validation cohort 1 (n=48). Finally, the score was implemented in an FDA-approved clinical diagnostic platform (NanoString) and tested in another independent validation cohort 2 (n=20). Results: A prognostic score, integrating a 123-gene signature and the model for end-stage liver disease (gs-MELD score), was defined in the derivation cohort, in which poor- and good-prognosis patients were discriminated with a cut-off value of 2.66 at 3 months (event-free survival rates of 32% vs. 76%, respectively, p<.001) and 6 months (26% vs. 65%, respectively, p<.001). In the validation cohort 1, the score similarly discriminated poor- and good-prognosis patients at 3 months (43%, [95% CI, 26%-70%] vs. 96% [95% CI, 89%-100%], respectively, p<.001, c-index of 0.83 [95% CI, 0.66-0.99]) and 6 months (34% [95% CI, 18%-61%] vs 84% [95% CI, 72%-100%], respectively, p<.001, c-index of 0.80 [95% CI, 0.66-0.94]), and outperformed other existing clinical indices. The NanoString-based gs-MELD score remained predictive of 3- (p=.03) and 6-month (p=.009) even-free survival in the validation cohort 2. Conclusion and Relevance: The gs-MELD score, incorporating clinically applicable gene signature test and the MELD score, enables pre-treatment survival prediction in severe AH patients.

Project description:Background and Objective: Neoadjuvant chemotherapy (NAC) followed by cystectomy is the standard of care in muscle-invasive bladder cancer (MIBC). Pathological response has been associated with longer survival, but no currently available clinicopathological variables can identify patients likely to respond, highlighting the need for predictive biomarkers. We sought to identify a predictive signature of response to NAC integrating clinical score, taxonomic subtype, and gene expression. Material and Methods: From 1994 to 2014, pre-treatment tumor samples were collected from MIBC patients (stage T2-4N0/+M0) at two Spanish hospitals. A clinical score was determined based on stage, hydronephrosis and histology. Taxonomic subtypes (BASQ, luminal, and mixed) were identified by immunohistochemistry. A custom set of 41 genes involved in DNA damage repair and immune response was analyzed in 84 patients with the NanoString nCounter platform. Genes related to pathological response were identified by LASSO penalized logistic regression. NAC consisted of cisplatin/methotrexate/vinblastine until 2000, after which most patients received cisplatin/gemcitabine. The capacity of the integrated signature to predict pathological response was assessed with AUC. Overall survival (OS) and disease-specific survival (DSS) were analyzed with the Kaplan-Meier method. Results: LASSO selected eight genes to be included in the signature (RAD51, IFNγ, CHEK1, CXCL9, c-MET, KRT14, HERC2, FOXA1). The highest predictive accuracy was observed with the inclusion in the model of only three genes (RAD51, IFNɣ, CHEK1). The integrated clinical-taxonomic-gene expression signature including these three genes had a higher predictive ability (AUC=0.71) than only clinical score plus taxonomic subtype (AUC=0.58) or clinical score alone (AUC=0.56). This integrated signature was also significantly associated with OS (p=0.02) and DSS (p=0.02). Conclusions: We have identified a predictive signature for response to NAC in MIBC patients that integrates the expression of three genes with clinicopathological characteristics and taxonomic subtypes. Prospective studies to validate these results are ongoing.

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A miRNA signature for early non-invasive diagnosis of pre-eclampsia

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