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

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Published in:

Open Access 01-12-2023 | Lung Cancer | Study Protocol

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

Authors: Filippo Lococo, Luca Boldrini, Charles-Davies Diepriye, Jessica Evangelista, Camilla Nero, Sara Flamini, Angelo Minucci, Elisa De Paolis, Emanuele Vita, Alfredo Cesario, Salvatore Annunziata, Maria Lucia Calcagni, Marco Chiappetta, Alessandra Cancellieri, Anna Rita Larici, Giuseppe Cicchetti, Esther G.C. Troost, Róza Ádány, Núria Farré, Ece Öztürk, Dominique Van Doorne, Fausto Leoncini, Andrea Urbani, Rocco Trisolini, Emilio Bria, Alessandro Giordano, Guido Rindi, Evis Sala, Giampaolo Tortora, Vincenzo Valentini, Stefania Boccia, Stefano Margaritora, Giovanni Scambia

Published in: BMC Cancer | Issue 1/2023

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Abstract

Background

The 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.

Methods

The 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.

Discussion

The 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 number

5420 − 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS – Università Cattolica del Sacro Cuore Ethics Committee.

Trial registration

clinicaltrial.gov - NCT05802771.
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Metadata
Title
Lung cancer multi-omics digital human avatars for integrating precision medicine into clinical practice: the LANTERN study
Authors
Filippo Lococo
Luca Boldrini
Charles-Davies Diepriye
Jessica Evangelista
Camilla Nero
Sara Flamini
Angelo Minucci
Elisa De Paolis
Emanuele Vita
Alfredo Cesario
Salvatore Annunziata
Maria Lucia Calcagni
Marco Chiappetta
Alessandra Cancellieri
Anna Rita Larici
Giuseppe Cicchetti
Esther G.C. Troost
Róza Ádány
Núria Farré
Ece Öztürk
Dominique Van Doorne
Fausto Leoncini
Andrea Urbani
Rocco Trisolini
Emilio Bria
Alessandro Giordano
Guido Rindi
Evis Sala
Giampaolo Tortora
Vincenzo Valentini
Stefania Boccia
Stefano Margaritora
Giovanni Scambia
Publication date
01-12-2023
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2023
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-023-10997-x

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