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

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.

Leukocyte Telomere Length and Neuregulin-4 Levels in Female Patients with Acromegaly: The Relationship between Disease Activity and Body Fat Distribution

“…When the patients were divided in terms of disease activity, body fat mass and percentage were higher, and the rate of lean body mass was lower in the CA group compared to the AA group. In addition, Gil et al have stated that the treatment of acromegaly impacts body composition [ 42 ]. In our study, when the patient group was divided into two groups in terms of medical treatment, body composition, metabolic parameters, LTL and neuregulin-4 were found to be similar between the groups.…”

Visualization and Analysis of the Data Mining Domain of Scientific Medical Publications in the Web of Science Database Using Co-word Analysis

“…In this way, researchers from different fields can conduct data mining-related research with specific goals (21). On the other hand, because this field is closely related to technology, it can be introduced to the world day-by-day more than in the past, and it will probably be used with new and diverse purposes in various research areas (22).…”

Predictors of morphofunctional features of somatotrophic tumors and of the effectiveness of treatment with first-generation somatostatin receptor ligands

“…По данным S. Găloiu et al, при достижении контроля акромегалии стандартизированный коэффициент смертности (Standardized Mortality Ratio -SMR) составляет 0,71, тогда как при величине инсулиноподобного фактора роста-1 (ИФР-1) индекса (ИИ) более 1 SMR повышается до 1,51. Высокая доля неудачных терапевтических исходов МТ определяет необходимость расширения лекарственной базы с подключением новых инновационных препаратов, способных оптимизировать лечебное пособие у конкретного пациента [16][17][18].…”

“…2) валидизация предикторов избирательной чувствительности опухолевых клеток к таргетному действию АС1 и АС2, позволяющему обеспечить гарантированный биохимический и опухолевый ответ и поддержать достойное качество жизни [17].…”