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| Name | Class |
|---|---|
| Ziekenhuis Oost-Limburg | OTHER |
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Complete resection is the mainstay of treatment for stage I-IIIA resectable non-small cell lung cancer (NSCLC). However rates of recurrence of disease are high, with five-year survival rates ranging between 73% (stage IA) and 24% (stage IIIA). Therefore, a prognostic biological marker that stratifies between NSCLC patients whom surgery cures versus patients in whom surgery would be futile due to early disease relapse after surgery is eagerly awaited.
The primary objective of this prospective study is to establish a prognostic marker of early disease progression after complete surgical resection in patients with stages I to IIIA NSCLC. For this purpose the investigator will compare the metabolic profile with disease progression or death within one year after complete surgical resection to the patients with a progression free survival. Furthermore the investigator will evaluate the changes in the metabolic profile after surgery and if changes in this metabolic profile over time can predict disease recurrence before it becomes clinically apparent.
Introduction: Precision medicine relies on validated biomarkers that can accurately classify patients by their probable disease risk, prognosis and/or response to treatment. Metabolomics is particularly promising for biomarker development because altered metabolism is considered a hallmark of cancer. The measurement of the metabolomic plasma profile is cheap (+-50 EUR) and fast (+-17 min), with a high information throughput on a per sample base.
Rationale: Complete resection is the mainstay of treatment for stage I-IIIA resectable non-small cell lung cancer (NSCLC). However rates of recurrence of disease are high, with five-year survival rates ranging between 73% (stage IA) and 24% (stage IIIA). Therefore, a prognostic biological marker that stratifies between NSCLC patients whom surgery cures versus patients in whom surgery would be futile due to early disease relapse after surgery is eagerly awaited.
Study objective: The primary study hypothesis is that the metabolic plasma profile is a predictive marker of early disease progression after complete surgical resection in patients with pathological stages I to IIIA NSCLC. The secondary study hypothesis is that the level of dissimilarity between the metabolic profile before surgery and the metabolic profile after surgery, is a predictor for disease recurrence (in which the extreme case would be, that a normalization of the metabolic profile to the profile of a healthy person, is indicative of a good prognosis).
Study design: Prospective, interventional design
Study population: Stage I-IIIA NSCLC patients who will undergo complete surgical resection willing to provide a written informed consent.
Number of patients: 200 patients with stage I-IIIA NSCLC who will undergo thoracic surgery with a curative intent will be included.
Main study parameters/endpoints: Recurrence free survival, overall survival, metabolic phenotype, presence or absence of hot-spot mutations in tested proto-oncogenes and tumor suppressor genes in circulating tumor DNA (ctDNA) in blood plasma, the tumor tissue and possibly positive lymph nodes, 43 items of the EORTC quality of life questionnaire C30 and LC13.
Nature and extent of the burden and risks associated with participation: Subjects will be asked to give consent to take 10-30 ml of blood at several moments throughout the disease course and in follow-up. Furthermore, the participants need to give their permission to use the resected tumor/lymph node tissue for genetic testing. Clinical parameters will be pooled in a database in a confidential way.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Additional blood sampling | Other | non-small cell lung cancer (NSCLC) |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Additional blood sampling | Other | Establish predictive markers for early disease progression after complete surgical resection in patients with stage I to IIIA NSCLC. |
|
| Measure | Description | Time Frame |
|---|---|---|
| The metabolic profile in plasma measured by Nuclear Magnetic Resonance (NMR) | The metabolic profile in plasma measured by Nuclear Magnetic Resonance (NMR) spectroscopy predicts disease disease recurrence within one year after surgical resection. | baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Change in the metabolic profile in plasma measured by Nuclear Magnetic Resonance (NMR) | The degree of change in the metabolic profile in plasma before and after surgery correlates with the risk for early disease recurrence. | screening, day 1, week 1, week 4, week 6, week 12, week 52 |
| Change in ctDNA mutations in plasma |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Michiel Thomeer, prof. dr. | Hasselt University | Principal Investigator |
| Elien Derveaux, drs. | Hasselt University | Study Chair |
| Liesbet Mesotten, prof. dr. | Hasselt University | Study Chair |
| peter Adriaensens, prof. dr. | Hasselt University | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| OLV ziekenhuis Aalst | Aalst | Belgium | ||||
| Ziekenhuis Oost-Limburg |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 28061019 | Background | Louis E, Cantrelle FX, Mesotten L, Reekmans G, Bervoets L, Vanhove K, Thomeer M, Lippens G, Adriaensens P. Metabolic phenotyping of human plasma by 1 H-NMR at high and medium magnetic field strengths: a case study for lung cancer. Magn Reson Chem. 2017 Aug;55(8):706-713. doi: 10.1002/mrc.4577. Epub 2017 Feb 27. | |
| 27642271 | Background |
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still no plan for, but open for sharing after discussion with participating groups
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| ID | Term |
|---|---|
| D002289 | Carcinoma, Non-Small-Cell Lung |
| ID | Term |
|---|---|
| D002283 | Carcinoma, Bronchogenic |
| D001984 | Bronchial Neoplasms |
| D008175 | Lung Neoplasms |
| D012142 | Respiratory Tract Neoplasms |
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The degree of change in ctDNA mutations in plasma before and after surgery correlates with the risk for early disease recurrence. |
| day 1, week 12, week 52 |
| Correlation between presence or absence Hotspot mutations and the metabolic profile in plasma | A specific metabolic profile in plasma measured by Nuclear Magnetic Resonance (NMR) spectroscopy correlates with the presence of absence of certain ctDNA mutations in plasma | day 1, week 12, week 52 |
| Metabolic profile of the primary tumor | The metabolic profile of the primary tumor correlates with the metabolic profile in plasma | day 1 |
| Genk |
| 3600 |
| Belgium |
| UZ Gent | Ghent | 9000 | Belgium |
| AZ Delta | Roeselare | 8800 | Belgium |
| Beger RD, Dunn W, Schmidt MA, Gross SS, Kirwan JA, Cascante M, Brennan L, Wishart DS, Oresic M, Hankemeier T, Broadhurst DI, Lane AN, Suhre K, Kastenmuller G, Sumner SJ, Thiele I, Fiehn O, Kaddurah-Daouk R; for "Precision Medicine and Pharmacometabolomics Task Group"-Metabolomics Society Initiative. Metabolomics enables precision medicine: "A White Paper, Community Perspective". Metabolomics. 2016;12(10):149. doi: 10.1007/s11306-016-1094-6. Epub 2016 Sep 2. |
| 24958139 | Background | Beger RD. A review of applications of metabolomics in cancer. Metabolites. 2013 Jul 5;3(3):552-74. doi: 10.3390/metabo3030552. |
| 26949046 | Result | Louis E, Adriaensens P, Guedens W, Bigirumurame T, Baeten K, Vanhove K, Vandeurzen K, Darquennes K, Vansteenkiste J, Dooms C, Shkedy Z, Mesotten L, Thomeer M. Detection of Lung Cancer through Metabolic Changes Measured in Blood Plasma. J Thorac Oncol. 2016 Apr;11(4):516-23. doi: 10.1016/j.jtho.2016.01.011. Epub 2016 Feb 29. |
| 26487580 | Result | Louis E, Adriaensens P, Guedens W, Vanhove K, Vandeurzen K, Darquennes K, Vansteenkiste J, Dooms C, de Jonge E, Thomeer M, Mesotten L. Metabolic phenotyping of human blood plasma: a powerful tool to discriminate between cancer types? Ann Oncol. 2016 Jan;27(1):178-84. doi: 10.1093/annonc/mdv499. Epub 2015 Oct 20. |
| D013899 |
| Thoracic Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
| D008171 | Lung Diseases |
| D012140 | Respiratory Tract Diseases |