Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	A 3-miRNA Signature Enables Risk Stratification in Glioblastoma Multiforme Patients with Different Clinical Outcomes
Δημιουργός/Συγγραφέας:	Bafiti, Vivi Ouzounis, Sotirios Chalikiopoulou, Constantina Grigorakou, Eftychia Grypari, Ioanna Maria Gregoriou, Gregory Theofanopoulos, Andreas Panagiotopoulos, Vasileios Prodromidi, Evangelia Cavouras, Dionisis Zolota, Vasiliki Kardamakis, Dimitrios [EL] Κατσίλα, Θεοδώρα[EN] Katsila, Theodora
Ημερομηνία:	2022-06-16
Γλώσσα:	Αγγλικά
ISSN:	1718-7729
DOI:	10.3390/curroncol29060345
Άλλο:	35735454
Περίληψη:	Malignant gliomas constitute a complex disease phenotype that demands optimum decision-making as they are highly heterogeneous. Such inter-individual variability also renders optimum patient stratification extremely difficult. microRNA (hsa-miR-20a, hsa-miR-21, hsa-miR-21) expression levels were determined by RT-qPCR, upon FFPE tissue sample collection of glioblastoma multiforme patients (n = 37). In silico validation was then performed through discriminant analysis. Immunohistochemistry images from biopsy material were utilized by a hybrid deep learning system to further cross validate the distinctive capability of patient risk groups. Our standard-of-care treated patient cohort demonstrates no age- or sex- dependence. The expression values of the 3-miRNA signature between the low- (OS > 12 months) and high-risk (OS < 12 months) groups yield a p-value of <0.0001, enabling risk stratification. Risk stratification is validated by a. our random forest model that efficiently classifies (AUC = 97%) patients into two risk groups (low- vs. high-risk) by learning their 3-miRNA expression values, and b. our deep learning scheme, which recognizes those patterns that differentiate the images in question. Molecular-clinical correlations were drawn to classify low- (OS > 12 months) vs. high-risk (OS < 12 months) glioblastoma multiforme patients. Our 3-microRNA signature (hsa-miR-20a, hsa-miR-21, hsa-miR-10a) may further empower glioblastoma multiforme prognostic evaluation in clinical practice and enrich drug repurposing pipelines.
Τίτλος πηγής δημοσίευσης:	Current oncology (Toronto, Ont.)
Τόμος/Κεφάλαιο:	29
Τεύχος:	6
Σελίδες:	4315-4331
Θεματική Κατηγορία:	[EL] Νεοπλάσματα. Όγκοι. Ογκολογία (περ. Καρκίνος, κακινογόνες ουσίες)[EN] Neoplasms. Tumors. Oncology (Incl.cancer, carcinogens) [EL] Βιοπληροφορική[EN] Bioinformatics [EL] Βιοχημεία[EN] Biochemistry [EL] Χημική Βιολογία[EN] Chemical Biology
Λέξεις-Κλειδιά:	Glioblastoma multiforme 3-microRNA signature Risk stratification Machine learning Image classification Pattern recognition
EU Grant:	RESEARCH–CREATE–INNOVATE
EU Grant identifier:	T2EDK-03153
Κάτοχος πνευματικών δικαιωμάτων:	© 2022 by the authors. Licensee MDPI, Basel, Switzerland.
Όροι και προϋποθέσεις δικαιωμάτων:	This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Ηλεκτρονική διεύθυνση στον εκδότη (link):	https://www.mdpi.com/1718-7729/29/6/345
Εμφανίζεται στις συλλογές:	Ινστιτούτο Χημικής Βιολογίας - Επιστημονικό έργο