Dietary Habits, Metabolome, Immune Profile and Microbiota in Patients With Bone Sarcoma
NCT ID: NCT04735289
Last Updated: 2023-08-04
Study Results
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Basic Information
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UNKNOWN
810 participants
OBSERVATIONAL
2021-03-10
2024-12-31
Brief Summary
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For other types of cancer the epidemiologic and prognostic correlations between dietary behavior, lifestyle and metabolic alterations (i.e.obesity, insulin-resistance) are well known (breast cancer, prostate cancer, colon cancer). However, no epidemiological or prognostic data are available about the metabolic profile and lifestyle behaviors in patients with osteosarcoma and Ewing'sarcoma and only few preclinical studies are available. An in vitro study showed a higher glucose and glutamine consumption from metastatic osteosarcoma cells compared to primary tumor osteosarcoma cells. The effect of the intestinal microbiota into the metabolism of nutrients, drugs, inflammation, epigenetic and immune response was found not only correlated to gastrointestinal tumors but also to other tumors outside gastrointestinal system as well The aim of this study is to investigate if there are differential dietary habits, metabolome, microbiota or immune profile in patients with bone sarcoma compared to a control population in a 1:2 multicenter study.
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Detailed Description
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In addition, inside this main study a pilot study of 55 patients and 110 controls of same age, sex, geographic area will be performed for analysis of metabolome, microbiota, and immune profile.
At diagnosis, before any treatment , a blood sample will be obtained for metabolomics analyses (untargeted approach with over 100.000 of metabolites, (Mass Spectrometry method) and to evaluate lymphocyte subpopulations (CD3, CD4, CD8, NK) in blood. Microbiota will be analyzed in donated stool samples using the S16 method. All data will be analyzed for inter-correlations among the different parameters and to investigate putative associations with EPIC-COS Food Frequency questionnaires and anthropometric data .
STATISTICAL ANALYSIS Conditional logistic regression analyses will be used to calculate odds ratio (OR) and 95% confidence interval (CI) to investigate associations between dietary habits and bone sarcoma risk in the case control study. An odds ratio of 1.6 with a potency of 85% was considered in the sample size calculations, leading to a target sample size of 270 cases with 540 matched healthy controls.
For the pilot cohort samples of 55 cases and 110 controls will be analyzed for metabolome, microbiota and immune profile. According to the results of this pilot study further cases among the population of FFQ study will undertake further analysis of metabolome and/or microbiota and/or lymphocyte subpopulation to confirm the results of pilot study.
OBJECTIVES OF THE STUDY
1. Compare the diet habits and anthropometric measures in bone sarcoma patients at diagnosis with matched controls
2. Pilot study: in the first 55 pts and their matched 110 healthy voluntary controls will be explored:
1. the occurrence of altered or more recurrent metabolites in patients' blood compared to controls
2. different microbiota diversity and composition between patients and case controls
3. different lymphocytes subpopulations composition.
Bioinformatics analysis will be performed to investigate these objectives
Conditions
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Study Design
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CASE_CONTROL
PROSPECTIVE
Study Groups
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GROUP 1 - 215 Patients and 430 Control cases (1:2)
Patients of \>= 12 years old (pediatric and adults) with new diagnosis of osteosarcoma and Ewing sarcoma will be included
* Localized and metastatic
* Male and female
Control cases matched by age, sex and italian geographic area
EPIC-COS Food Frequency Questionnaire diet Evaluation
Anthropometric measurements (Body mass Index, Lean and fat body composition evaluation) and diet habits evaluation with EPIC-COS-FFQ
GROUP 2 - Pilot Phase :55 Patients and 110 Control cases (1:2)
* Patients of \>= 12 years old (pediatric and adults) with new diagnosis of osteosarcoma and Ewing sarcoma will be included Localized and metastatic Male and female
* Control cases matched by age, sex, and geographic area
EPIC-COS Food Frequency Questionnaire diet Evaluation
Anthropometric measurements (Body mass Index, Lean and fat body composition evaluation) and diet habits evaluation with EPIC-COS-FFQ
Metabolome, Microbiota, Lymphocytes subpopulations
At diagnosis before any treatment for bone sarcoma will be obtained :
1. a blood sample for metabolomics analyses
2. a stool sample for microbiota analysis
3. Lymphocyte subpopulations (CD3, CD4, CD8, NK) will be analyzed in blood samples
Interventions
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EPIC-COS Food Frequency Questionnaire diet Evaluation
Anthropometric measurements (Body mass Index, Lean and fat body composition evaluation) and diet habits evaluation with EPIC-COS-FFQ
Metabolome, Microbiota, Lymphocytes subpopulations
At diagnosis before any treatment for bone sarcoma will be obtained :
1. a blood sample for metabolomics analyses
2. a stool sample for microbiota analysis
3. Lymphocyte subpopulations (CD3, CD4, CD8, NK) will be analyzed in blood samples
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
* No previous chemotherapy treatment
* ≥ 12 years old
* Able to understand the questionnaire
* No malignant tumor diagnosis for the last 5 years
* Control case should have a range of +/- 2 years old for patients \>= 21 years old. For patients between 12 and 21 years old the difference should be +/- 1 years.
Exclusion Criteria
* Not able to understand the questionnaire
* Patient diagnosed for malignant tumor during the last 5 years
12 Years
ALL
Yes
Sponsors
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International Agency for Research on Cancer
OTHER
Istituto Ortopedico Rizzoli
OTHER
Responsible Party
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Alessandra Longhi,MD
Principal Investigator
Principal Investigators
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Alessandra Longhi, MD
Role: PRINCIPAL_INVESTIGATOR
Istituto Ortopedico Rizzoli - Bologna
Locations
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IRCCS Candiolo Cancer Institute
Candiolo, Torino, Italy
Rizzoli Orthopedic Institute - Bologna
Bologna, , Italy
Ospedale pediatrico Meyer - U.O. Pediatric Oncoematology
Florence, , Italy
IRCCS Istituto Nazionale Tumori - U.O. Pediatric Oncology
Milan, , Italy
Azienda Ospedaliero Universitaria Pisana - U.O. Pediatric Oncoematology
Pisa, , Italy
Regina Elena Cancer Center
Roma, , Italy
Ospedale Regina Margherita - U.O. Pediatric Oncoematology
Torino, , Italy
Countries
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Central Contacts
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Facility Contacts
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Giovanni Grignani, MD
Role: primary
Angela Tamburini, MD
Role: primary
Luca Coccoli, MD
Role: primary
Virginia Ferraresi, MD
Role: primary
Franca Fagioli, MD
Role: primary
References
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Fulbright LE, Ellermann M, Arthur JC. The microbiome and the hallmarks of cancer. PLoS Pathog. 2017 Sep 21;13(9):e1006480. doi: 10.1371/journal.ppat.1006480. eCollection 2017 Sep. No abstract available.
Garrett WS. Cancer and the microbiota. Science. 2015 Apr 3;348(6230):80-6. doi: 10.1126/science.aaa4972.
Lynch SV, Pedersen O. The Human Intestinal Microbiome in Health and Disease. N Engl J Med. 2016 Dec 15;375(24):2369-2379. doi: 10.1056/NEJMra1600266. No abstract available.
Soldati L, Di Renzo L, Jirillo E, Ascierto PA, Marincola FM, De Lorenzo A. The influence of diet on anti-cancer immune responsiveness. J Transl Med. 2018 Mar 20;16(1):75. doi: 10.1186/s12967-018-1448-0.
Fritsche-Guenther R, Gloaguen Y, Kirchner M, Mertins P, Tunn PU, Kirwan JA. Progression-Dependent Altered Metabolism in Osteosarcoma Resulting in Different Nutrient Source Dependencies. Cancers (Basel). 2020 May 27;12(6):1371. doi: 10.3390/cancers12061371.
Albini A, Briga D, Conti M, Bruno A, Farioli D, Canali S, Sogno I, D'Ambrosio G, Consonni P, Noonan DM. SANIST: a rapid mass spectrometric SACI/ESI data acquisition and elaboration platform for verifying potential candidate biomarkers. Rapid Commun Mass Spectrom. 2015 Oct 15;29(19):1703-10. doi: 10.1002/rcm.7270.
Other Identifiers
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919/2020/Oss/IOR
Identifier Type: -
Identifier Source: org_study_id
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