Catholic University of the Sacred Heart, Rome, Italy.
Thoracic Surgery Unit, A. Gemelli University Hospital Foundation IRCCS, Rome, Italy.
BMC Cancer. 2023 Jun 13;23(1):540. doi: 10.1186/s12885-023-10997-x.
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.
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.
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.
5420 - 0002485/23 from Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore Ethics Committee.
clinicaltrial.gov - NCT05802771.
目前，肺癌患者的管理已经达到了高度复杂的水平。事实上，除了传统的临床变量（例如年龄、性别、TNM 分期）外，新的组学数据最近已被引入临床实践，从而使决策过程更加复杂。随着人工智能（AI）技术的出现，各种组学数据集可用于创建更准确的预测模型，为肺癌患者提供更好的护理铺平道路。
LANTERN 研究是一项多中心观察性临床试验，涉及来自五个不同欧洲国家的五个机构组成的多学科联盟。该试验的目的是通过创建数字人类化身（DHA），为肺癌患者开发准确的多个预测模型，DHA 是使用各种基于组学的变量并整合成熟的临床因素与基因组数据、定量成像数据等创建的患者的数字表示。通过招聘中心，将前瞻性地招募 600 名肺癌患者，并收集多组学数据。然后，将在尖端大数据分析的实验环境中对数据进行建模和参数化。所有数据变量都将根据基于变量特定域的共享通用本体进行记录，以增强其直接可操作性。然后，将启动探索性分析以启动生物标志物识别过程。项目的第二阶段将专注于通过先进的机器学习（ML）和 AI 技术为特定领域创建多个多变量模型。最后，将对开发的模型进行验证，以测试其稳健性、可转移性和泛化性，从而开发 DHA。所有潜在的临床和科学利益相关者都将参与 DHA 的开发过程。LANTERN 项目的主要目标是：i）开发用于肺癌诊断和组织学特征的预测模型；ii）为个体特定治疗建立个性化预测模型；iii）为预防保健策略和生活质量管理启用反馈数据循环。
LANTERN 项目将开发一个基于多组学数据集成的预测平台。这将增强生成重要和有价值的信息资产的能力，以识别可用于早期检测、改善肿瘤诊断和个性化治疗方案的新生物标志物。
Fondazione Policlinico Universitario Agostino Gemelli IRCCS - Università Cattolica del Sacro Cuore 伦理委员会，5420-0002485/23。
clinicaltrial.gov-NCT05802771。
