Big data and biomarker design
An ever-increasing amount of available data in cancer research, obtained from various ‘omics’ technologies (genomics, radiomics, proteomics, etc.), remains underutilized. This data holds potential for diagnosing cancer types, planning therapy, assessing response, and monitoring progress. We study the properties of existing tumor quantifiers (e.g., heterogeneity, morphological features) to identify those that can serve as indicators of disease status. Additionally, we introduce new properties derived from mathematical models, which could function as prognostic and response biomarkers. Furthermore, we investigate methods to combine these biomarkers into more sophisticated prognostic and predictive models.
Publications
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Growth dynamics of lung nodules: implications for classification in lung cancer screeningB. Ocaña-Tienda, A. Eroles-Simó, J. Pérez-Beteta, E. Arana, V. M. Pérez-GarcíaCancer Imaging 24, 113 (2024)
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Morphological MRI features as prognostic indicators in brain metastasesOcaña-Tienda B, Pérez-Beteta J, Ortiz de Mendivil A, Asenjo B, Albillo D, Pérez-Romasanta LA, LLorente M, Carballo N, Arana E, Pérez-García VM.Cancer Imaging 24, 111 (2024)
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Radiation necrosis after radiation therapy treatment of brain metastases: A computational approachBeatriz Ocana-Tienda, Odelaisy Leon-Triana, Julian Perez-Beteta, Juan Jiménez-Sánchez, Victor M. Perez-GarciaPLOS Computational Biology 20(1) e1011400 (2024)
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Variable selection for dimensionality reduction of biological datasets through bootstrapping of correlation networksD.G. Aragones, M. Palomino, J. Sicilia, G. Crainiciuc, I. Ballesteros, F. Sánchez-Cabo, A. Hidalgo, G.F. CalvoComputers in Biology and Medicine 168, 107827 (2024).
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Volumetric Analysis: Rethinking Brain Metastases Response AssessmentB Ocaña-Tienda, J Pérez-Beteta, JA Romero-Rosales, B Asenjo, A Ortiz, LA Pérez Romasanta, JD Albillo, F Nagib, M Vidal Denis, B. Luque, E. Arana, VM Pérez-GarcíaNeuro-Oncoloy Advances 6(1), 1-9 (2024)
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A comprehensive dataset of annotated brain metastasis MR images with clinical and radiomic dataOcaña-Tienda B, Pérez-Beteta J, Villanueva JD, Romero JA, Molina D, Suter Y, Asenjo B, Albillo D, Ortiz A, Pérez-Romasanta LA, González E, Llorente M, Carballo N, Nagib F, Vidal M, Luque B, Reyes M, Arana E, Pérez-García VMScientific Data 10, 208 (2023)
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The shape of cancer relapse: Topological data analysis predicts recurrence in paediatric acute lymphoblastic leukaemiaS. Chulián, B. J. Stolz, A. Martínez-Rubio, C. Blázquez-Goñi, J. F. Rodríguez, T. Caballero, A. Molinos, M. Ramírez-Orellana, A. Castillo, J. L. Fuster, A. Minguela, M. V. Martínez, M. Rosa, V. M. Pérez-García, H. ByrnePLOS Computational Biology 19(8) e1011329 (2023)
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Behavioural immune landscapes of inflammationCrainiciuc G, Palomino-Segura M, Molina-Moreno M, Sicilia J, Aragones DG, Li JLY, Madurga R, Adrover JM, Aroca-Crevillén A, Martin-Salamanca S, Del Valle AS, Castillo SD, Welch HCE, Soehnlein O, Graupera M, Sánchez-Cabo F, Zarbock A, Smithgall TE, Di Pilato M, Mempel TR, Tharaux PL, González SF, Ayuso-Sacido A, Ng LG, Calvo GF, González-Díaz I, Díaz-de-María F, Hidalgo A.Nature 601, 415-421 (2022)
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Growth dynamics of brain metastases differentiate radiation necrosis from recurrenceB. Ocaña-Tienda, J. Pérez-Beteta, D. Molina-García, B. Asenjo, A. Ortiz de Mendivil, D. Albillo, LA Pérez-Romasanta, E. González del Portillo, M. Llorente, N. Carballo, E. Arana, Víctor M Pérez-GarcíaNeurooncology Advances (2022) vdac179
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Patient-specific forecasting of post-radiotherapy prostate-specific antigen kinetics enables early prediction of biochemical relapseG. Lorenzo, N. di Muzio, C. L. Deantoni, C. Cozzarini, A. Fodor, A. Briganti, F. Montorsi, V. M. Pérez-García, H. Gómez, A. RealiiScience 25, 105430 (2022)
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Evolutionary dynamics at the tumor edge reveals metabolic imaging biomarkersJ. Jiménez-Sánchez, J.J. Bosque, G.A. Jiménez-Londoño, D. Molina-García, A. Martínez-Rubio, J. Pérez-Beteta, C. Ortega-Sabater, A.F Honguero-Martínez, A.M. García-Vicente, G.F. Calvo, V.M. Pérez-GarcíaProceedings of the National Academy of Sciences (USA) 118(6) e2018110118 (2021).
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High-dimensional Analysis of Single-cell Flow Cytometry Data Predicts Relapse in Childhood Acute Lymphoblastic LeukemiaS. Chulián, A. Martínez-Rubio, V.M. Pérez-García, M. Rosa, C. Blázquez-Goñi, J.F. Rodríguez Gutiérrez, L. Hermosín-Ramos, A. Molinos-Quintana, T. Caballero-Velázquez, M. Ramírez-Orellana, A. Castillo Robleda, J.L Fernández-MartínezCancers 13(1), 17 (2021).
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Tumor width on T1-weighted MRI images of glioblastoma as a prognostic biomarker: A mathematical modelJ. Pérez Beteta, J. Belmonte-Beitia, V.M. Pérez-GarcíaMathematical Modelling of Natural Phenomena 15, 10 (2020)
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Universal scaling laws rule explosive growth in human cancersV.M. Pérez-García, G.F. Calvo, J.J. Bosque, O. León-Triana, J. Jiménez-Sánchez, J. Pérez-Beteta, J. Belmonte-Beitia, M. Valiente, L. Zhu, P. García-Gómez, P. Sánchez-Gómez, E. Hernández, R. Hortigüela, Y. Azimzade, D. Molina-García, A.Martínez-Rubio, A. Acosta, A. Ortiz de Mendivil, F. Vallette, P. Schucht, M. Murek, M.Pérez-Cano, D.Albillo, AF Honguero, G.A. Jiménez, E. Arana, AM García-VicenteNature Physics 16, 1232-1237 (2020)
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Approaching the Rank Aggregation Problem by Local Search-based Metaheuristics.J.A. Aledo, J.A. Gámez, D. Molina.Journal of Computational and Applied Mathematics 354, 445-456 (2019)
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Prognostic models based on imaging findings in glioblastoma: Human versus MachineD. Molina-García, L. Vera, J. Pérez-Beteta, E. Arana, V.M. Pérez-GarcíaScientific Reports 9:5982 (2019)
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Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardizationD. Molina, J. Pérez-Beteta, A. Martínez-González, J. Martino, C. Velasquez, E. Arana, V.M. Pérez-GarcíaPLoS One 12(6):e0178843 (2017)
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Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardizationD. Molina, J. Pérez-Beteta, A. Martínez-González, C. Velásquez, J. Martino, B. Luque, A. Revert, I. Herruzo, E. Arana, V.M. Pérez-GarcíaNeuro-Oncology 19 (3): iii44 (2017)
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Towards individualized survival prediction in glioblastoma patients using machine learning methodsL. Vera, J. Pérez-Beteta, D. Molina, J.M. Borrás, M. Benavides, J.A. Barcia, C. Velásquez, D. Albillo, P. Lara, V.M. Pérez-GarcíaNeuro-Oncology 19(3):iii84-iii84 (2017)
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Influence of grey level and space discretization on brain tumor heterogeneity measures obtained from MRIsD. Molina, J. Pérez-Beteta, A. Martínez-González, J. Martino, C. Velasquez, E. Arana, V.M. Pérez-GarcíaComputers in Biology and Medicine 78, 49-57 (2016)
Projects
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James S. Mc Donnell Foundation (USA) (2015 - 2016)
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James S. Mc. Donnell Foundation (USA) (2018 - 2021)
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FECYT: Fundación Española para la Ciencia y la Tecnología (2018 - 2020)
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Ministerio de Economía y Competitividad (2016 - 2019)
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Ministerio de Ciencia e Innovación (Spain) (2020 - 2023)
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Junta de Andalucía (2020 - 2023)
Collaborators
Big data and biomarker design at MOLAB is developed in collaboration with Estanislao Arana (Fundación Instituto Valenciano de Oncología, Valencia, Spain) and Mauricio Reyes and is Medical Image Analysis group (ARTORG center, Bern, Switzerland). To this end, medical imaging and clinical data have been provided by our collaborators in different medical institutions: Hospital 12 de Octubre de Madrid, Hospital General de Ciudad Real, Hospital Universitario Marqués de Valdecilla de Santander, Hospital Virgen de la Salud de Toledo, Hospital Regional Universitario de Málaga, MD Anderson Cancer Center de Madrid, Hospital Universitario de Sanchinarro de Madrid, Hospital Universitario de Salamanca, Hospital de Manises and Instituto Valenciano de Oncología.
Andrés Hidalgo(Yale Shool of Medicine, New Haven, Connecticut, USA); Iván Ballesteros (CNIC-Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain); Manuel Ramírez Orellana (Hospital Infantil Universitario Niño Jesús, Madrid, Spain); Francisco Monroy Muñoz (Hospital Universitario 12 de Octubre, Madrid, Spain); Carlos Torroja Fungairiño (CNIC-Centro Nacional de Investigaciones Cardiovasculares Carlos III, Madrid, Spain); Diego Herráez Aguilar (Universidad Francisco de Vitoria, Madrid, Spain).
- Luis Vera Ramírez
- Carlos Velásquez Rodríguez
- Philippe Schucht
- Victor M. Pérez García
- Julián Pérez Beteta
- David Molina García
- Álvaro Martínez Rubio
- Alicia Martínez González
- Juan Jiménez Sánchez
- Gabriel Fernández Calvo
- Salvador Chulián García
- Jesús Bosque Martínez
- Juan Belmonte Beitia
- Estanislao Arana Fernández de Moya
- David G. Aragonés González
- José David Albillo Labarra
- María Rosa Durán
