Dietary Habits, Metabolome, Immune Profile and Microbiota in Patients With Bone Sarcoma

NCT ID: NCT04735289

Last Updated: 2023-08-04

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

810 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-03-10

Study Completion Date

2024-12-31

Brief Summary

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Osteosarcoma and Ewing sarcoma treatment has not changed in the last 30 years.

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.

Detailed Description

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MATERIALS \& METHODS A population of 270 patients of \>12 yrs old (pediatric and adults) with new diagnosis of osteosarcoma and Ewing sarcoma will be included. A detailed dietary intake assessment will be done with EPIC-COS food frequency questionnaire (FFQ) and anthropometric measures (Weight, Height, body fat/lean mass composition) will be taken at diagnosis before treatment and compared to 540 controls matched by age, sex, and italian geographic area.

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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Osteosarcoma Ewing Sarcoma

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

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

Intervention Type OTHER

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

Intervention Type OTHER

Anthropometric measurements (Body mass Index, Lean and fat body composition evaluation) and diet habits evaluation with EPIC-COS-FFQ

Metabolome, Microbiota, Lymphocytes subpopulations

Intervention Type OTHER

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

Intervention Type OTHER

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

Intervention Type OTHER

Other Intervention Names

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EPIC-FFQ diet Evaluation

Eligibility Criteria

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Inclusion Criteria

* Osteosarcoma and Ewing sarcoma first diagnosis
* 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

* Other tumor type
* Not able to understand the questionnaire
* Patient diagnosed for malignant tumor during the last 5 years
Minimum Eligible Age

12 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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International Agency for Research on Cancer

OTHER

Sponsor Role collaborator

Istituto Ortopedico Rizzoli

OTHER

Sponsor Role lead

Responsible Party

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Alessandra Longhi,MD

Principal Investigator

Responsibility Role 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

Site Status NOT_YET_RECRUITING

Rizzoli Orthopedic Institute - Bologna

Bologna, , Italy

Site Status RECRUITING

Ospedale pediatrico Meyer - U.O. Pediatric Oncoematology

Florence, , Italy

Site Status NOT_YET_RECRUITING

IRCCS Istituto Nazionale Tumori - U.O. Pediatric Oncology

Milan, , Italy

Site Status NOT_YET_RECRUITING

Azienda Ospedaliero Universitaria Pisana - U.O. Pediatric Oncoematology

Pisa, , Italy

Site Status NOT_YET_RECRUITING

Regina Elena Cancer Center

Roma, , Italy

Site Status NOT_YET_RECRUITING

Ospedale Regina Margherita - U.O. Pediatric Oncoematology

Torino, , Italy

Site Status NOT_YET_RECRUITING

Countries

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Italy

Central Contacts

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Alessandra Longhi, MD

Role: CONTACT

+39 (051) 6366-991

Inge Huybrechts, PhD

Role: CONTACT

Facility Contacts

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Giovanni Grignani, MD

Role: primary

Alessandra Longhi, MD

Role: primary

+39 (051) 6366.991

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.

Reference Type RESULT
PMID: 28934351 (View on PubMed)

Garrett WS. Cancer and the microbiota. Science. 2015 Apr 3;348(6230):80-6. doi: 10.1126/science.aaa4972.

Reference Type RESULT
PMID: 25838377 (View on PubMed)

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.

Reference Type RESULT
PMID: 27974040 (View on PubMed)

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.

Reference Type RESULT
PMID: 29558948 (View on PubMed)

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.

Reference Type RESULT
PMID: 32471029 (View on PubMed)

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.

Reference Type RESULT
PMID: 26331920 (View on PubMed)

Other Identifiers

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919/2020/Oss/IOR

Identifier Type: -

Identifier Source: org_study_id

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