The study is a prospective observational single-center cohort study which compare the gut microbiome of newly diagnosed Diffuse Large B-cell Lymphoma patients with the gut microbiome of healthy controls. Furthermore the impact of lymphoma treatment, immune phenotypes, cytokine profiles, metabolomics, inflammation, driver mutations, comorbidity, body composition and lifestyle on the microbiome is also investigated
Microbiota refers to an ecological community of commensal, symbiotic and pathogenic microorganisms that colonize the various compartments within the human body including the gastrointestinal tract. The composition has been shown to play an important role in the pathophysiology of many diseases as well as influence host homeostatic processes such as regulation of metabolic processes, defense against pathogens, immune system development, regulation of the immune response and inflammation. However, the connection between the gut microbiota and lymphoma remain poorly understood. The purpose of this study is to evaluate the composition and diversity of the gut microbiome in a large homogeneous group of patients with newly diagnosed and treatment-naive Diffuse Large B-cell Lymphoma (DLBCL). The investigators aim to identify the relationship between the intestinal microbiota, clinical and molecular subtypes of DLBCL and outcome of the disease. The association between nutrition, physical activity, body composition, toxicity to the antineoplastic therapy, infections, use of antibiotics, comorbidity and tumor genetics versus gut microbiota composition and diversity is also explored. The project is carried out in collaboration between clinical departments, institutes and laboratories with expertise in microbiology, hematology, pathology, nutrition, molecular biology, immunology and bioinformatics. Hypothesis of the study are: 1. Patients with DLBCL have distinct baseline microbiota signatures that differ from healthy subjects. 2. Significant changes in the microbiota composition and diversity can be identified during and after treatment (immunochemotherapy) of DLBCL. 3. Lymphoma response and outcome is affected by the composition and diversity of the DLBCL microbiota. 4. The intestinal microbiota changes towards a microbiota more like the microbiota of healthy controls in patients who remain in lymphoma remission one year after completion of therapy. 5. Distinct DLBCL microbiota profiles are associated with treatment-related toxicity. 6. The intestinal microbiota affects the risk of infections (clinically and/or microbiologically documented). 7. The intestinal microbiota is affected using antibiotics both as prophylaxis and treatment of infections. 8. The DLBCL microbiota depends on the dietary intake, smoking, physical activity and the body composition. 9. Distinct intestinal microbiota signatures can be associated with molecular subtypes of DLBCL (or vice versa) 10. The JAK2V617F, TET2, DNMT3A and ASXL1 mutations affect the intestinal microbiota signature and are associated with comorbidity and outcome in DLBCL 11. There is a vicious circle between intestinal dysbiosis and lymphoma with the crosstalk between the gut microbiota and the cancer being expressed as alterations in the profile of cytokines, chemokines and growth factors; an immune response reflected by immunophenotypic profiles of peripheral blood mononuclear cells; and characteristic metabolite signatures in the blood.
Study Type
OBSERVATIONAL
Enrollment
200
Analysis of microbiome, mutations, alterations in body composition and lifestyle
Zealand University Hospital, Department of Hematology
Roskilde, Region Sjælland, Denmark
RECRUITINGIntestinal microbiota baseline characterization
Assessment using amplicon-based sequencing of ribosomal (r)RNA genes
Time frame: 1.5 years
Intestinal microbiota characterization at mid-, post-treatment and at follow up
Assessment using amplicon-based sequencing of ribosomal (r)RNA genes
Time frame: 2.5 years
Assessment of habitual diet
Food frequency questionnaire (FFQ)
Time frame: 2.5 years
Assessment of energy and macronutrient intake
24h dietary recalls
Time frame: 2.5 years
Assessment of physical activity
International physical activity questionnaire (IPAQ)
Time frame: 2.5 years
Body composition
Body composition according to bioelectrical impedance analysis (BIA) using BioScan touch i8 - IVF version
Time frame: 2.5 years
Smoking
Packages (baseline lifestyle questionnaire)
Time frame: 2.5 years
Alcohol intake
Units (baseline lifestyle questionnaire)
Time frame: 2.5 years
Treatment-related toxicity
Treatment-related toxicity (CTCAE criteria)
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Time frame: 1.5 years
Antibiotics
Use of any type of prophylactic and therapeutic antibiotics during treatment (baseline lifestyle questionnaire)
Time frame: 1.5 years
Statins
Use of any type of statins during treatment registered in the Shared Medication Record (FMK)
Time frame: 1.5 years
Medication
Use of any type of medication registered in the Shared Medication Record (FMK)
Time frame: 1.5 years
Infections
Clinical infections during treatment
Time frame: 1.5 years
Lymphoma response
Lymphoma response after completion of first line treatment (Lugano criteria)
Time frame: 1.5 years
Molecular signatures
Molecular signatures in standard clinical practice according to Hans classification (cell of origin (COO))
Time frame: 1.5 years
Chromosome abnormalities
Molecular signatures in standard clinical practice (fluorescent in situ hybridization (FISH))
Time frame: 1.5 years
Mutations
JAK2V617F, TET2, DNMT3A and ASXL1 mutation analyses (%VAF)
Time frame: 1.5 years
Cytokine profiles
Magnetic bead-based assays
Time frame: 1.5 years
Metabolite signatures
Metabolomic profiling by a combination of GC and LC coupled with MS
Time frame: 1.5 years
Peripheral blood mononuclear cell (PBMC) profiles
PBMC profiles according to flow cytometry
Time frame: 1.5 years