Scientific Reports (May 2022)

Data mining analyses for precision medicine in acromegaly: a proof of concept

  • Joan Gil,
  • Montserrat Marques-Pamies,
  • Miguel Sampedro,
  • Susan M. Webb,
  • Guillermo Serra,
  • Isabel Salinas,
  • Alberto Blanco,
  • Elena Valassi,
  • Cristina Carrato,
  • Antonio Picó,
  • Araceli García-Martínez,
  • Luciana Martel-Duguech,
  • Teresa Sardon,
  • Andreu Simó-Servat,
  • Betina Biagetti,
  • Carles Villabona,
  • Rosa Cámara,
  • Carmen Fajardo-Montañana,
  • Cristina Álvarez-Escolá,
  • Cristina Lamas,
  • Clara V. Alvarez,
  • Ignacio Bernabéu,
  • Mónica Marazuela,
  • Mireia Jordà,
  • Manel Puig-Domingo

DOI
https://doi.org/10.1038/s41598-022-12955-2
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 14

Abstract

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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.