Lung Cancer
Conditions
Keywords
Biomarkers, Circulating tumor cells, Screening, Computer Tomography (CT Scan)
Brief summary
Validation of biomolecular markers in the circulation and radiomic features are the focus of this project.The aim is to assess the role of molecular and cellular biomarkers (exosomes antigens, Circulating tumor cells - CTCs, panel of mutations in circulating free DNA) and radiomic signature, as complementary to assist early detection of lung cancer by LDCT.
Interventions
OTHERLDCT (Low Dose CT)
validate the role of non-invasive molecular and cellular biomarkers and combined radiomic signature, as complementary tools to assist early detection of lung cancer by LDCT using bioinformatic techniques for the integration of the results
Sponsors
Ospedale San Raffaele
University of Paris 5 - Rene Descartes
European Institute of Oncology
Istituto Superiore di Sanità
Istituto Clinico Humanitas
Study design
Observational model
CASE_CONTROL
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
55 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* Age ≥ 55 years old and exposure to smoking more than 30 packs-year; which corresponds to 6-year risk of lung cancer, calculated according to the plco score (≥ 2%). * Smoker or former smoker Former smokers must have ceased smoking within the 15 years prior to enrollment in the study. * Absence of symptoms of lung cancer such as worsening of cough, hoarseness, hemoptysis and weight loss.
Exclusion criteria
* Previous diagnosis of lung cancer. * Positive extrapulmonary cancer history in the last 5 years (excluding in situ tumors or skin epidermoid tumor). * Performing a chest CT scan in the last 18 months. * Severe lung or extrapulmonary diseases that may preclude or invalidate appropriate therapy in case of diagnosis of malignant pulmonary neoplasia.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Obtaining biological samples, and correspondent clinical and imaging data to use, as fresh blood tissues or frozen stored tissues from lung cancer patients and controls obtained from the Division of Thoracic Surgery and LDCT lung-cancer screening program | 01 Jan 2018 - 01 Jan 2023 | 1.1 : Obtaining biological material from cancer cases and controls (clinical cases) and store in the biobank with clinical data and imaging for bio radiomic analysis. 1.2 : Identification and testing of methods of recruiting high-risk individuals for a lung-cancer screening program using available database to select very high risk individuals; 1.3 : Obtaining biological material from asymptomatic screening-detected cancer cases and controls and store in the biobank with clinical data and imaging. 1.4 : Assessment of compliance of the recruited population and assessment of mean lung-cancer risk. Verify the potential impact of molecular markers as a pre-screening test to better assess the risk of subjects, evaluate the impact on nodule management and number of false positive cases among screening process according to biostatistical analysis. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Tumor antigens identified by RPPA in lung cancer circulating exosome | 01 Jan 2018 - 01 Jan 2023 | Blood-derived exosomes will be collected. Exosome antigens assessment will be performed. Then, a bioinformatics analysis of the performance of exosome antigens as diagnostic markers for lung cancer will be performed. |
| Investigate the potential role of CTCs as diagnostic and prognostic tool in a screening content | 01 Jan 2018 - 01 Jan 2023 | 3.1 Samples collection and preparation: isolation and count of CTCs; 3.2 Evaluation of diagnostic role of CTCs in early stage lung cancers; 3.3 Evaluation of the prognostic value of the number of CTCs at diagnosis (measured in terms of progression free survival and overall survival); 3.4 Characterization of CTCs for the expression of EMT and correlation with angiogenesis pattern of primary tumor; 3.5 Biostatistical analysis of the results. |
| Development and validation of a panel of mutations on circulating DNA as diagnostic test for lung cancer. | 01 Jan 2018 - 01 Jan 2023 | 4.1 Samples collection and library preparation; 4.2 Standardisation of the technique; 4.3 Assessment of diagnostic role of the protein signature; 4.4 Bioinformatics analysis of the performance of the cell free DNA mutation signature as diagnostic tool for lung cancer |
| Investigate a radiomic signature to discriminate malignant lung nodule Background | 01 Jan 2018 - 01 Jan 2023 | 5.1 assess the association of imaging features with clinical data and histology; 5.2 Identification the radiomic signature, the combination of imaging features, able to characterize lung lesions; 5.3 Validation of the signature on a new subset of patients; 5.4 Assessment of the role of radiomic signature, together with circulating markers in predicting lung malignancy |
Countries
Italy
Contacts
Primary ContactGiulia Veronesi, MD
Outcome results
None listed