Urinary microRNAs: Looking for a New Tool in Diagnosis, Prognosis, and Monitoring of Renal Cancer

Oto, Júlia; Plana, Emma; Sánchez-González, José Vicente; García-Olaverri, Jorge; Fernández-Pardo, Álvaro; España, Francisco; Martínez-Sarmiento, Manuel; Donoso, C.D. Vera; Navarro, Silvia; Medina, Pilar

doi:10.1007/s11934-020-0962-9

Cited by 27 publications

(25 citation statements)

References 41 publications

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“…miR-331-3p has been recently postulated as predictor of recurrence in esophageal adenocarcinoma [45] and as regulator in pancreatic cancer [46]. miR-126-5p has been studied in cervical cancer [47] and renal cell carcinoma [48]. miR-23a-3p and miR-23b-3p regulate the expression of proapoptotic proteins in human pancreatic beta-cells [49].…”

Section: Discussionmentioning

confidence: 99%

microRNAs and Markers of Neutrophil Activation as Predictors of Early Incidental Post-Surgical Pulmonary Embolism in Patients with Intracranial Tumors

Oto

Plana

Solmoirago

et al. 2020

Cancers

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Venous thromboembolism (VTE) is a common complication of cancer that severely increases morbidity and mortality. Patients with intracranial tumors are more likely to develop VTE than patients with cancers at other sites. Conversely, limited tools exist to identify patients with high thrombotic risk. Upon activation, neutrophils release their content through different mechanisms triggering thrombosis. We explored the ability of microRNAs (miRNAs) and plasma markers of neutrophil activation measured before surgery to predict the risk of early post-surgical pulmonary embolism (PE) in glioma and meningioma patients. We recruited and prospectively followed 50 patients with glioma and 50 with meningioma, 34% of whom in each group developed an early objectively-diagnosed post-surgical PE. We measured miRNA expression and neutrophil markers (cell-free DNA, nucleosomes, calprotectin and myeloperoxidase) before surgery. In glioma patients, we adjusted and validated a predictive model for post-surgical PE with 6 miRNAs: miR-363-3p, miR-93-3p, miR-22-5p, miR-451a, miR-222-3p and miR-140-3p (AUC = 0.78; 95% Confidence Interval (CI) [0.63, 0.94]) and another with cfDNA and myeloperoxidase as predictors (AUC = 0.71; 95% CI [0.52, 0.90]). Furthermore, we combined both types of markers and obtained a model with myeloperoxidase and miR-140-3p as predictors (AUC = 0.79; 95% CI [0.64, 0.94]). In meningioma patients we fitted and validated a predictive model with 6 miRNAs: miR-29a-3p, miR-660-5p, miR-331-3p, miR-126-5p, miR-23a-3p and miR-23b-3p (AUC = 0.69; 95% CI [0.52, 0.87]). All our models outperformed the Khorana score. This is the first study that analyzes the capability of plasma miRNAs and neutrophil activation markers to predict early post-surgical PE in glioma and meningioma patients. The estimation of the thrombotic risk before surgery may promote a tailored thromboprophylaxis in a selected group of high-risk patients, in order to minimize the incidence of PE and avoid bleedings.

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Section: Discussionmentioning

confidence: 99%

microRNAs and Markers of Neutrophil Activation as Predictors of Early Incidental Post-Surgical Pulmonary Embolism in Patients with Intracranial Tumors

Oto

Plana

Solmoirago

et al. 2020

Cancers

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“…Urinary miRNA have been investigated in several studies showing a promising role as biomarker candidates for RCC [35]. In particular, miRNA have shown the most promising characteristics in RCC diagnosis.…”

Section: Liquid Biopsy (Blood-based and Urinary Biomarkers)mentioning

confidence: 99%

Biomarkers for Renal Cell Carcinoma Recurrence: State of the Art

et al. 2021

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Purpose of Review We aim to summarize the current state of art about the possible use of biomarkers for predicting renal cell carcinoma (RCC) recurrence after curative treatment. In addition, we aim to provide a snapshot about the clinical implication of biomarkers use for follow-up planification. Recent Findings A wide variety of biomarkers have been proposed. RCC biomarkers have been individuated in tumoral tissue, blood, and urine. A variety of molecules, including proteins, DNA, and RNA, warrant a good accuracy for RCC recurrence and progression prediction. Their use in prediction models might warrant a better patients’ risk stratification. Summary Future prognostic models will probably include a combination of classical features (tumor grade, stage, etc.) and novel biomarkers. Such models might allow a more accurate treatment and follow-up planification.

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“…Since a growing number of studies have shown that almost all biomolecules (including small noncoding RNA such as miRNAs, piRNAs and tsRNAs) packed into extracellular vesicles which could be detected in the body fluid specimens [39] , it is feasible and urgent to develop the miRNA-based non-invasive detection system [40] . The system would allows repeated sampling and real-time monitoring of disease progression and of response to treatment [ 41 , 42 ]. We present here some of miRNAs which might most effectively reflect the physiological and pathological characteristics of RCC ( Table 2 ).…”

Section: Micrornamentioning

confidence: 99%