Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study

被引:11
|
作者
Lococo, Filippo [1 ,2 ]
Boldrini, Luca [1 ,3 ]
Diepriye, Charles-Davies [3 ]
Evangelista, Jessica [1 ,2 ]
Nero, Camilla [1 ,4 ]
Flamini, Sara [2 ]
Minucci, Angelo [1 ,5 ]
De Paolis, Elisa [5 ,6 ]
Vita, Emanuele [1 ,7 ]
Cesario, Alfredo [1 ,8 ,9 ]
Annunziata, Salvatore [1 ,10 ]
Calcagni, Maria Lucia [1 ,10 ]
Chiappetta, Marco [1 ,2 ]
Cancellieri, Alessandra [1 ,11 ]
Larici, Anna Rita [1 ,12 ]
Cicchetti, Giuseppe [1 ,12 ]
Troost, Esther G. C. [13 ,14 ,15 ,16 ,17 ,18 ,19 ,20 ,21 ,22 ]
Roza, Adany [23 ]
Farre, Nuria [24 ]
Ozturk, Ece [25 ,26 ]
Van Doorne, Dominique [27 ]
Leoncini, Fausto [1 ,28 ]
Urbani, Andrea [1 ,6 ,29 ]
Trisolini, Rocco [1 ,28 ]
Bria, Emilio [1 ,7 ]
Giordano, Alessandro [1 ,10 ]
Rindi, Guido [1 ,11 ]
Sala, Evis [1 ,12 ]
Tortora, Giampaolo [1 ,7 ]
Valentini, Vincenzo [1 ,3 ]
Boccia, Stefania [1 ,30 ]
Margaritora, Stefano [1 ,2 ]
Scambia, Giovanni [1 ,4 ]
机构
[1] Univ Cattolica Sacro Cuore, Rome, Italy
[2] A Gemelli Univ Hosp Fdn IRCCS, Thorac Surg Unit, Rome, Italy
[3] A Gemelli Univ Hosp Fdn IRCCS, Radiotherapy Unit, Rome, Italy
[4] A Gemelli Univ Hosp Fdn IRCCS, Dept Woman & Child Hlth & Publ Hlth, Div Oncol Gynecol, Rome, Italy
[5] A Gemelli Univ Hosp Fdn IRCCS, Dept Unit Mol & Genom Diagnost, Genom Core Facil, Gemelli Sci & Technol Pk G STeP, Rome, Italy
[6] A Gemelli Univ Hosp Fdn IRCCS, Clin Chem Biochem & Mol Biol Operat UOC, Rome, Italy
[7] A Gemelli Univ Hosp Fdn IRCCS, Med Oncol, Largo A Gemelli 8, Rome, Italy
[8] A Gemelli Univ Hosp Fdn IRCCS, Open Innovat, Sci Directorate, Rome, Italy
[9] Gemelli Digital Med & Hlth Srl, Rome, Italy
[10] A Gemelli Univ Hosp Fdn IRCCS, Nucl Med Unit, GsteP Radiopharm TracerGLab, Rome, Italy
[11] A Gemelli Univ Hosp Fdn IRCCS, Inst Pathol, Rome, Italy
[12] A Gemelli Univ Hosp Fdn IRCCS, Adv Radiodiagnost Ctr, Dept Diagnost Imaging Oncol Radiotherapy & Hemato, Rome, Italy
[13] Tech Univ Dresden, Fac Med, Dept Radiotherapy & Radiat Oncol, Dresden, Germany
[14] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Dresden, Germany
[15] Helmholtz Zentrum Dresden Rossendorf, Inst Radiooncol OncoRay, Rossendorf, Germany
[16] Tech Univ Dresden, Fac Med, OncoRay Natl Ctr Radiat Res Oncol, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany
[17] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, OncoRay Natl Ctr Radiat Res Oncol, Helmholtz Zentrum Dresden Rossendorf, Dresden, Germany
[18] German Canc Consortium DKTK, Partner Site Dresden, Dresden, Germany
[19] German Canc Res Ctr, Heidelberg, Germany
[20] Natl Ctr Tumor Dis NCT, Partner Site Dresden, Dresden, Germany
[21] Tech Univ Dresden, Univ Hosp Carl Gustav Carus, Dresden, Germany
[22] Helmholtz Zentrum Dresden Rossendorf HZDR, Helmholtz Assoc, Dresden, Germany
[23] Univ Debrecen, Fac Med, Dept Publ Hlth & Epidemiol, ELKH DE Publ Hlth Res Grp, Debrecen, Hungary
[24] Hosp Santa Creu & St Pau IR HSCSP, Inst Recerca, Barcelona, Spain
[25] Sch Med, Istanbul, Turkiye
[26] Koc Univ, Res Ctr Translat Med KUTTAM Sariyer, Istanbul, Turkiye
[27] Univ Turin, Acad Expert Patient ADPEE EUPATI, Dept Philosophy & Educ Sci, Turin, Italy
[28] A Gemelli Univ Hosp Fdn IRCCS, Intervent Pulmonol Unit, Rome, Italy
[29] Univ Cattolica Sacro Cuore, Dept Basic Biotechnol Sci, Intensivol & Perioperat Clin, Rome, Italy
[30] Univ Cattolica Sacro Cuore, Dept Life Sci & Publ Hlth, Rome, Italy
关键词
Lung cancer; Artificial intelligence (AI); Digital human avatars (DHA); Personalize medicine; Machine learning; System medicine; Precision medicine; Genomics; Radiomics; Big data;
D O I
10.1186/s12885-023-10997-x
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundThe current management of lung cancer patients has reached a high level of complexity. Indeed, besides the traditional clinical variables (e.g., age, sex, TNM stage), new omics data have recently been introduced in clinical practice, thereby making more complex the decision-making process. With the advent of Artificial intelligence (AI) techniques, various omics datasets may be used to create more accurate predictive models paving the way for a better care in lung cancer patients.MethodsThe LANTERN study is a multi-center observational clinical trial involving a multidisciplinary consortium of five institutions from different European countries. The aim of this trial is to develop accurate several predictive models for lung cancer patients, through the creation of Digital Human Avatars (DHA), defined as digital representations of patients using various omics-based variables and integrating well-established clinical factors with genomic data, quantitative imaging data etc. A total of 600 lung cancer patients will be prospectively enrolled by the recruiting centers and multi-omics data will be collected. Data will then be modelled and parameterized in an experimental context of cutting-edge big data analysis. All data variables will be recorded according to a shared common ontology based on variable-specific domains in order to enhance their direct actionability. An exploratory analysis will then initiate the biomarker identification process. The second phase of the project will focus on creating multiple multivariate models trained though advanced machine learning (ML) and AI techniques for the specific areas of interest. Finally, the developed models will be validated in order to test their robustness, transferability and generalizability, leading to the development of the DHA. All the potential clinical and scientific stakeholders will be involved in the DHA development process. The main goals aim of LANTERN project are: i) To develop predictive models for lung cancer diagnosis and histological characterization; (ii) to set up personalized predictive models for individual-specific treatments; iii) to enable feedback data loops for preventive healthcare strategies and quality of life management.DiscussionThe LANTERN project will develop a predictive platform based on integration of multi-omics data. This will enhance the generation of important and valuable information assets, in order to identify new biomarkers that can be used for early detection, improved tumor diagnosis and personalization of treatment protocols.Ethics Committee approval number5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Universita Cattolica del Sacro Cuore Ethics Committee.
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页数:8
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