VAE-Surv: A novel approach for genetic-based clustering and prognosis prediction in myelodysplastic syndromes

作者：C. Rollo, C. Pancotti, Flavio Sartori, Isabella Caranzano, S. D'amico, L. Carota, Francesco Casadei, G. Birolo, L. Lanino, Elisabetta Sauta, G. Asti, Alessandro Buizza, Mattia Delleani, Elena Zazzetti, M. Bicchieri, G. Maggioni, P. Fenaux, U. Platzbecker, M. Díez-Campelo, T. Haferlach, G. Castellani, Matteo Giovanni Della Porta, P. Fariselli, T. Sanavia · 发表于：Comput. Methods Programs Biomed. · 年份：2025 · DOI：10.1016/j.cmpb.2025.108605 · 被引用次数：3 · 研究领域：Medicine、Computer Science

BACKGROUND AND OBJECTIVES Several computational pipelines for biomedical data have been proposed to stratify patients and to predict their prognosis through survival analysis. However, these analyses are usually performed independently, without integrating the information derived from each of them. Clustering of survival data is an underexplored problem, and current approaches are limited for biomedical applications, whose data are usually heterogeneous and multimodal, with poor scalability for high-dimensionality. METHODS We introduce VAE-Surv, a multimodal computational framework for patients' stratification and prognosis prediction. VAE-Surv integrates a Variational Autoencoder (VAE), which reduces the high-dimensional space characterizing the molecular data, with a deep survival model, which combines the embedded information with the clinical features. The VAE embedding step prioritizes local coherence within the feature space to detect potential nonlinear relationships among the molecular markers. The latent representation is then exploited to perform K-means clustering. To test the clinical robustness of the algorithm, VAE-Surv was applied to the Genomed4all cohort of Myelodysplastic Syndromes (MDS), comparing the identified subtypes with the World Health Organization (WHO) classification. The survival outcome was compared with the state-of-the-art Cox model and its penalized versions. Finally, to assess the generalizability of the results, the method was also validat...