Data mining analyses for precision medicine in acromegaly : a proof of concept
Gil, Joan (Institut d'Investigació Biomèdica Sant Pau)
Marques-Pamies, Montserrat (Institut Germans Trias i Pujol)
Sampedro, Miguel (Hospital Universitario de la Princesa (Madrid))
Webb, S. M 1952- (Institut d'Investigació Biomèdica Sant Pau)
Serra, Guillermo (Hospital Universitari Son Espases (Palma de Mallorca, Balears))
Salinas, Isabel (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Blanco, Alberto (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Valassi, Elena (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Carrato, Cristina (Institut Germans Trias i Pujol. Hospital Universitari Germans Trias i Pujol)
Picó Alfonso, Antonio M (Universidad Miguel Hernández de Elche. Departamento de Medicina Clínica)
García-Martínez, Araceli (Hospital General Universitario de Alicante (Alacant, País Valencià))
Martel-Duguech, Luciana (Hospital de la Santa Creu i Sant Pau (Barcelona, Catalunya))
Sardon, Teresa (Anaxomics Biotech S.L.)
Simó-Servat, Andreu (Hospital Universitari MútuaTerrassa (Terrassa, Catalunya))
Biagetti, Betina (Hospital Universitari Vall d'Hebron)
Villabona, Carles (Hospital Universitari de Bellvitge)
Cámara, Rosa (Hospital Universitari i Politècnic La Fe (València))
Fajardo-Montañana, Carmen (Hospital de La Ribera (Alzira). Servicio de Endocrinología)
Álvarez-Escolá, Cristina (Hospital Universitario La Paz (Madrid))
Lamas, Cristina (Hospital General Universitario de Albacete. Servicio de Endocrinología)
Alvarez, Clara V. (Universidade de Santiago de Compostela)
Bernabeu Morón, Ignacio (Complejo Hospitalario Universitario de Santiago de Compostela)
Marazuela, Mónica (Hospital Universitario de la Princesa (Madrid))
Jordà, Mireia (Institut Germans Trias i Pujol)
Puig-Domingo, Manel (Universitat Autònoma de Barcelona. Departament de Medicina)
Universitat Autònoma de Barcelona

Date:	2022
Abstract:	Predicting which acromegaly patients could benefit from somatostatin receptor ligands (SRL) is a must for personalized medicine. Although many biomarkers linked to SRL response have been identified, there is no consensus criterion on how to assign this pharmacologic treatment according to biomarker levels. Our aim is to provide better predictive tools for an accurate acromegaly patient stratification regarding the ability to respond to SRL. We took advantage of a multicenter study of 71 acromegaly patients and we used advanced mathematical modelling to predict SRL response combining molecular and clinical information. Different models of patient stratification were obtained, with a much higher accuracy when the studied cohort is fragmented according to relevant clinical characteristics. Considering all the models, a patient stratification based on the extrasellar growth of the tumor, sex, age and the expression of E-cadherin, GHRL, IN1-GHRL, DRD2, SSTR5 and PEBP1 is proposed, with accuracies that stand between 71 to 95%. In conclusion, the use of data mining could be very useful for implementation of personalized medicine in acromegaly through an interdisciplinary work between computer science, mathematics, biology and medicine. This new methodology opens a door to more precise and personalized medicine for acromegaly patients.
Grants:	Instituto de Salud Carlos III PM 15/00027
Note:	Altres ajuts: Novartis Farmacéutica (REMAH).
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Acromegaly ; Biomarkers ; Data Analysis ; Data Mining ; Humans ; Neoplasms ; Precision Medicine
Published in:	Scientific reports, Vol. 12 Núm. 1 (december 2022) , p. 8979, ISSN 2045-2322

DOI: 10.1038/s41598-022-12955-2
PMID: 35643771

14 p, 1.9 MB

The record appears in these collections:
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Institut d'Investigació en Ciencies de la Salut Germans Trias i Pujol (IGTP)
Research literature > UAB research groups literature > Research Centres and Groups (research output) > Health sciences and biosciences > Institut de Recerca Sant Pau
Articles > Research articles
Articles > Published articles