Dietary Habits, Metabolome, Immune Profile and Microbiota in Patients With Bone Sarcoma (Metabol-Sarc)

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

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.

Study Overview

• Status: Recruiting
• Conditions: Osteosarcoma; Ewing Sarcoma
• Intervention / Treatment: Other: EPIC-COS Food Frequency Questionnaire diet Evaluation; Other: Metabolome, Microbiota, Lymphocytes subpopulations

Detailed Description

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

• Study Type: Observational
• Enrollment (Estimated): 810

Contacts and Locations

• Study Contact: Name: Alessandra Longhi, MD; Phone Number: +39 (051) 6366-991; Email: alessandra.longhi@ior.it
• Study Contact Backup: Name: Inge Huybrechts, PhD; Email: huybrechtsl@iarc.fr

Study Locations

• Italy
  • Bologna, Italy, 40136
    • Recruiting
    • Rizzoli Orthopedic Institute - Bologna
    • Contact: Alessandra Longhi, MD; Phone Number: +39 (051) 6366.991; Email: alessandra.longhi@ior.it
  • Firenze, Italy, 50139
    • Not yet recruiting
    • Ospedale pediatrico Meyer - U.O. Pediatric Oncoematology
    • Contact: Angela Tamburini, MD
  • Milano, Italy, 20133
    • Not yet recruiting
    • IRCCS Istituto Nazionale Tumori - U.O. Pediatric Oncology
  • Pisa, Italy, 56126
    • Not yet recruiting
    • Azienda Ospedaliero Universitaria Pisana - U.O. Pediatric Oncoematology
    • Contact: Luca Coccoli, MD
  • Roma, Italy, 00144
    • Not yet recruiting
    • Regina Elena Cancer Center
    • Contact: Virginia Ferraresi, MD
  • Torino, Italy, 10126
    • Not yet recruiting
    • Ospedale Regina Margherita - U.O. Pediatric Oncoematology
    • Contact: Franca Fagioli, MD
  • Torino
    • Candiolo, Torino, Italy, 10060
      • Not yet recruiting
      • IRCCS Candiolo Cancer Institute
      • Contact: Giovanni Grignani, MD

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 10 years and older (Child, Adult, Older Adult)
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

• Patients will be selected from the central and satellite centers
• Control group will be selected from the same age, sex, geographic area of the recruited patients

Description

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

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Control
• Time Perspectives: Prospective

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort	Intervention / Treatment
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	Other: 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; Other Names: EPIC-FFQ diet Evaluation
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	Other: 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; Other Names: EPIC-FFQ diet Evaluation; Other: Metabolome, Microbiota, Lymphocytes subpopulations; At diagnosis before any treatment for bone sarcoma will be obtained : a blood sample for metabolomics analyses; a stool sample for microbiota analysis; Lymphocyte subpopulations (CD3, CD4, CD8, NK) will be analyzed in blood samples

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diet habits in patients versus case controls measured by EPIC COS FFQ	Diet habits from osteosarcoma and Ewing sarcoma patients will be compared with diet habits from a control population. The diet habits data will be evaluated EPIC COS FFQ( European Prospective Investigation Into Cancer and Nutrition Case Only Study Food Frequency Questionnaire) which report: the food consumptions in the last 12 months - Main food groups (water and other drinks, grain products, fruits and vegetables, legumes, meat and fish products, dairy products, sweets and savory snacks) FFQ-EPIC COS can be accessed on PubMed (PMID: 12484126 and PMID: 12484120).	At diagnosis, up to 4 years
Diet Quality Index -	Diet quality index from osteosarcoma and Ewing sarcoma patients will be compared with diet habits from a control population. Data will be accessed with EPIC COS FFQ( European Prospective Investigation Into Cancer and Nutrition Case Only Study Food Frequency Questionnaire ) - Diet quality index will be calculated to compare adherence to dietery guidelines and it will be expressed in percentage	At diagnosis, up to 4 years
Number of patients overweight and obese measured by Body mass index (BMI compared to controls)	Body Mass Index (BMI) measure will be achieved in patients and controls by impedance Tanita scale model BC545 based on height (in centimeters) and weight (in Kilograms) expressed in subjects >18yrs as 1) underweight if <18.5, 2) normal weight 18.5 to 25,3)overweight 25-30 and 4) obese >30. BMI measure will be achieved by impedance Tanita scale model BC545 in study patients at diagnosis and compared with a control subjects.	At diagnosis, up to 4 years
Body composition	Lean mass and fat mass will be calculated via impedance Tanita scale model BC545 as a percentage of total weight .Lean body mass is the difference between total body weight and body fat weight, expressed as percentage (%)	At diagnosis, up to 4 years

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Concentration of blood metabolites - Metabolome	Concentration of untargeted blood metabolites obtained via mass spectometry SANIST technique from blood of 55 patients and from 110 control subject blood. Metabolome will be analyzed in order to determine if there is an occurrence of altered or more recurrent metabolites in patients' blood compared to controls.	At diagnosis, up to 4 years
Microbiota	Microbiota will be analyzed with S16 method. Microbiota diversity and composition between patients and controls will be analyzed and expressed as alpha and beta diversity	At diagnosis, up to 4 years
Concentrations of lymphocytes subpopulation	Concentrations of (CD3,CD4.CD8,NK) lymphocytes subpopulation will be detected onceat diagnosis before any treatment for sarcoma and they will beexpressed as total number. The lymphocytes subpopulation will be measured once at diagnosis in study patients and matched controls.	At diagnosis, up to 4 years
Lipid profile and Glucidic profile	Fatty acids triglycerids(mg/dL), total cholesterol (mg/dL), HDLcholesterol (mg/dL) and LDL cholesterol (mg/dL), glucose (mg/dL) will be measured once in blood at diagnosis in study patients and control subjects	At diagnosis, up to 4 years

Collaborators and Investigators

• Sponsor: Istituto Ortopedico Rizzoli
• Collaborators: International Agency for Research on Cancer
• Investigators: Principal Investigator: Alessandra Longhi, MD, Istituto Ortopedico Rizzoli - Bologna

Publications and helpful links

General Publications

• 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.

Study record dates

Study Major Dates

• Study Start (Actual): March 10, 2021
• Primary Completion (Estimated): December 31, 2024
• Study Completion (Estimated): December 31, 2024

Study Registration Dates

• First Submitted: December 22, 2020
• First Submitted That Met QC Criteria: January 31, 2021
• First Posted (Actual): February 3, 2021

Study Record Updates

• Last Update Posted (Actual): August 4, 2023
• Last Update Submitted That Met QC Criteria: August 3, 2023
• Last Verified: August 1, 2023

More Information

Terms related to this study

• Keywords: Microbiota; Metabolome; Dietary habits; Bone sarcoma; Immune profile
• Additional Relevant MeSH Terms: Neoplasms, Connective and Soft Tissue; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Bone Tissue; Neoplasms, Connective Tissue; Sarcoma; Sarcoma, Ewing; Osteosarcoma
• Other Study ID Numbers: 919/2020/Oss/IOR

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No