Evaluation of Clinical, Radiomics and Molecular Features of Lung Metastasis in PDAC Patients (LUMACA Trial)
NCT ID: NCT04435067
Last Updated: 2020-07-16
Study Results
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Basic Information
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UNKNOWN
44 participants
OBSERVATIONAL
2020-05-27
2021-12-31
Brief Summary
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Detailed Description
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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.
Conditions
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Study Design
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COHORT
RETROSPECTIVE
Study Groups
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Cohort A
patients in whom lung metastasis were resected for therapeutic purposes
Analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia
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.
Radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor
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.
Cohort B
patients in whom lung metastasis were removed for diagnostic purposes only
Analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia
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.
Radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor
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.
Interventions
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Analysis of genetic mutations and the gene expression profile of lung metastasis and primary neoplasia
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.
Radiomics analysis on TAC imaging at diagnosis of lung metastasis and, if possible, of the primary tumor
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.
Eligibility Criteria
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Inclusion Criteria
* 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 with lung metastases synchronous with primary cancer. Contacts and Locations
18 Years
ALL
No
Sponsors
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IRCCS San Raffaele
OTHER
Responsible Party
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Michele Reni
MD
Principal Investigators
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Michele Reni, MD
Role: PRINCIPAL_INVESTIGATOR
IRCCSS Raffaele
Locations
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IRCCS San Raffaele Diagnostic Radiology Unit
Milan, , Italy
IRCCS San Raffaele Medical Oncology Unit
Milan, , Italy
IRCCS San Raffaele Pathological Anatomy Unit
Milan, , Italy
IRCCS San Raffaele Thoracic Surgery Unit
Milan, , Italy
Countries
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Central Contacts
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Facility Contacts
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References
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Arnaoutakis GJ, Rangachari D, Laheru DA, Iacobuzio-Donahue CA, Hruban RH, Herman JM, Edil BH, Pawlik TM, Schulick RD, Cameron JL, Meneshian A, Yang SC, Wolfgang CL. Pulmonary resection for isolated pancreatic adenocarcinoma metastasis: an analysis of outcomes and survival. J Gastrointest Surg. 2011 Sep;15(9):1611-7. doi: 10.1007/s11605-011-1605-8. Epub 2011 Jul 2.
Ceppa DP. Results of Pulmonary Resection: Sarcoma and Germ Cell Tumors. Thorac Surg Clin. 2016 Feb;26(1):49-54. doi: 10.1016/j.thorsurg.2015.09.007.
Okui M, Yamamichi T, Asakawa A, Harada M, Horio H. Resection for Pancreatic Cancer Lung Metastases. Korean J Thorac Cardiovasc Surg. 2017 Oct;50(5):326-328. doi: 10.5090/kjtcs.2017.50.5.326. Epub 2017 Oct 5.
Rama N, Monteiro A, Bernardo JE, Eugenio L, Antunes MJ. Lung metastases from colorectal cancer: surgical resection and prognostic factors. Eur J Cardiothorac Surg. 2009 Mar;35(3):444-9. doi: 10.1016/j.ejcts.2008.10.047. Epub 2009 Jan 10.
Yamashita K, Miyamoto A, Hama N, Asaoka T, Maeda S, Omiya H, Takami K, Doki Y, Mori M, Nakamori S. Survival Impact of Pulmonary Metastasis as Recurrence of Pancreatic Ductal Adenocarcinoma. Dig Surg. 2015;32(6):464-71. doi: 10.1159/000439545. Epub 2015 Oct 31.
Other Identifiers
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PACT32
Identifier Type: -
Identifier Source: org_study_id
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