Evaluation of Clinical, Radiomics and Molecular Features of Lung Metastasis in PDAC Patients (LUMACA Trial)

Study Overview
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Brief Summary
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The aim of this study is the characterization from epidemiological, radiomics and molecular point of view of lung metastasis of patients at beginning affected by pancreatic adenocarcinoma (PDAC), which after the resection of primitive tumor have met with initial recurrence of the disease exclusively at the lung level.

Detailed Description
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Radical surgical treatment of primitive PDAC, associated with adjuvant cancer treatments, is possible only in 15-20% of patients, and, to date, represents the best therapeutic strategy. Nevertheless, remote recurrence is frequent after radical surgical treatment of primitive neoplasia. Among the main locations of metastasis from PDAC, the lung represent the second metastatic location with a better prognosis than other remote metastasis. Surgical treatment of lung metastasis has a consolidated role in the treatment of other neoplasms such as sarcomas, colorectal and renal neoplasms while in the context of PDAC the resection of lung metastases is a rather rare and also debated event. In absence of consolidated data on the results of surgical treatment and on the clinical outcomes of patients with lung metastasis from PDAC the investigators designed this retrospective observational study in order to analyze the clinical and pathological characteristics of patients suffering from lung metastasis from PDAC treated at San Raffaele Hospital in a period between 2008 and 2019. To this purpose, the investigators will analyze and compare two patient cohorts: 1-patients in whom lung metastasis were resected for therapeutic purposes; 2-patients in whom lung metastasis were removed for diagnostic purposes only. An analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia will also be performed to evaluate any predictive elements of lung metastasis and the prognostic role of these mutations. In parallel, the investigators will perform radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor. All the data necessary for the completion of the study were collected as part of the usual outpatient visits in the appropriate outpatient medical records and include: date of birth, date of diagnosis, gender, performance status, stage of the disease, comorbidity, concomitant chronic therapies, level of tumor markers (CEA and Ca19.9) before treatment and variations during therapy, type of chemotherapy, start and end date of chemotherapy, number of cycles, possible dosage reduction of the drugs used in the various chemotherapy regimes, dates and results of instrumental revaluations according to RECIST 1.1, main chemotherapy toxicities and grade according to CTCAE 5.0, date and type of surgery, mutation analysis results and last follow-up date. In the event of death, the dates of death are communicated by the registry office of the municipality of residence of the patient, according to the official procedure. All data will be collected in an electronic database in coded form (pseudonymization). Power size calculation: All patients who meet the inclusion and exclusion criteria and who have been treated at the Medical Oncology and Thoracic Surgery Units of the San Raffaele Hospital between 2008 and 2019 will be taken into consideration, for a total of 44 patients. To identify predictive and/or prognostic clinical and pathological factors that can influence the outcome of these patients, the two cohorts described above will be analyzed and compared through univariate and multivariate analyzes. Overall survival (OS) and progression-free survival (PFS) will also be assessed using the Kaplan Meier method and the long-rank test will be used to compare OS and PFS between the two cohorts under study. All tests will be double-tailed and a p <0.05 will be considered significant. The ninety-five percent confidence intervals (CI) will be calculated to assess the accuracy of the estimates obtained.

Official Title
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Retrospective Observational Study on Patients With Lung Metastases From Pancreatic Adenocarcinoma: Evaluation of Clinical Features and Correlation With Molecular and Radiomics Features

Conditions
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Pancreas Adenocarcinoma

Intervention / Treatment
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* Genetic: Analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia
* Other: Radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Cytological/histological diagnosis of pancreatic adenocarcinoma as a primary tumor and localization of adenocarcinoma compatible with pancreatic primitivity for lung metastasis; Previous surgical resection of the primary tumor; Exclusive presence of single or multiple lung metastasis at disease recurrence; Radical or diagnostic excision of lung metastasis; Informed patient consent (for currently living patients). Exclusion Criteria: Patients not undergoing lung resection surgery for diagnostic and/or therapeutic purposes for cardiac or respiratory functional contraindication. Patients with lung metastases synchronous with primary cancer. Contacts and Locations

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Cohort A<br>patients in whom lung metastasis were resected for therapeutic purposes | Genetic: Analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia<br>* The mutational analysis of the main oncogenes and tumor suppressor genes involved in the genesis and tumor progression will be performed on the genomic DNA extracted from each sample using the Ion Torrent TM Oncomine TM Comprehensive Assay version 3 (OCAv3) kit. This panel includes 161 cancer-related genes and allows the identification of all genomic alterations affecting oncogenes and recurrently altered tumor suppressor genes in solid tumors. The study of gene expression will be carried out using Nanostring Technology using the Pancancer IO 360 TM panel which allows simultaneous analysis for each sample of multiple mRNAs associated with crucial pathways in carcinogenesis and the immunological profile of the tumor, defining its up and down conditions gene regulation.<br>Other: Radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor<br>* This study will be performed using the SPAARC IBSI (International Biomarker Standardization Initiative) compliant software implemented in the MatLab environment (MathWorks, Boston, USA) through several steps: (a) CT imaging retrieval, (b) image segmentation and rendering, (c) feature extraction and (d) qualification/quantification. Approximately 200 radiomics characteristics will be extracted, such as: Morphology, Statistical, Intensity Histogram, Gray Level Co-occurrence Matrix 3D_average, Gray Level Co-occurrence Matrix 3D_combined, Gray Level Run Length 3D_average, Gray Level Run Length 3D_combined, Gray Level Size Zone Matrix 3D, Neighbor Gray Tone Difference Matrix 3D, Gray Level Distance Zone Matrix 3D.<br>|
| Cohort B<br>patients in whom lung metastasis were removed for diagnostic purposes only | Genetic: Analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia<br>* The mutational analysis of the main oncogenes and tumor suppressor genes involved in the genesis and tumor progression will be performed on the genomic DNA extracted from each sample using the Ion Torrent TM Oncomine TM Comprehensive Assay version 3 (OCAv3) kit. This panel includes 161 cancer-related genes and allows the identification of all genomic alterations affecting oncogenes and recurrently altered tumor suppressor genes in solid tumors. The study of gene expression will be carried out using Nanostring Technology using the Pancancer IO 360 TM panel which allows simultaneous analysis for each sample of multiple mRNAs associated with crucial pathways in carcinogenesis and the immunological profile of the tumor, defining its up and down conditions gene regulation.<br>Other: Radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor<br>* This study will be performed using the SPAARC IBSI (International Biomarker Standardization Initiative) compliant software implemented in the MatLab environment (MathWorks, Boston, USA) through several steps: (a) CT imaging retrieval, (b) image segmentation and rendering, (c) feature extraction and (d) qualification/quantification. Approximately 200 radiomics characteristics will be extracted, such as: Morphology, Statistical, Intensity Histogram, Gray Level Co-occurrence Matrix 3D_average, Gray Level Co-occurrence Matrix 3D_combined, Gray Level Run Length 3D_average, Gray Level Run Length 3D_combined, Gray Level Size Zone Matrix 3D, Neighbor Gray Tone Difference Matrix 3D, Gray Level Distance Zone Matrix 3D.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Clinical and pathological features of lung metastasis | Analyze the clinical and pathological characteristics of the two cohorts of patients affected by lung metastasis from PDAC | 6 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Molecular and radiomics features of lung metastasis | Correlate the pathological characteristics of the two cohorts of patients affected by lung metastasis from PDAC with radiomics and molecular features, in order to identify prognostic and/or predictive factors related to lung metastasis in the PDAC | 18 months | 
| Differences between the two cohorts | Highlight any differences between the two cohorts of patients examined | 18 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Pancreas Adenocarcinoma, Lung Metastasis, Gene Expression, Molecular analysis, Radiomics