An observational study in Diffuse Large B Cell Lymphoma, sponsored by Istituto Romagnolo per lo Studio dei Tumori Dino Amadori IRST S.r.l. IRCCS. Recruiting at 4 sites in Italy. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2025-04-10.
Sponsored by Istituto Romagnolo per lo Studio dei Tumori Dino Amadori IRST S.r.l. IRCCS · Observational
This is a prospective and retrospective observational study. The primary objective is to identify new prognostic biomarkers for DLBCL patients in terms of progression-free survival (PFS) and able to add predictive capacity to recognized important clinical factors.
The secondary objectives are:
For each enrolled patient, immunohistochemical determinations will be performed: Cell of origin (COO) (Germinal Cell -GC- or activated B-cell - ABC- type according with Hans algorithm ), evaluation of cluster of differentiation antigen 20 (CD20), cluster of differentiation antigen 5 (CD5), cluster of differentiation antigen 10 (CD10), Bcl6, Bcl2 (cut off>50%), Multiple Myeloma 1 / Interferon Regulatory Factor 4 protein (MUM1/IRF4), c-myc (cut off>40%) and Ki67, fluorescence in situ hybridization (FISH) for c-myc and if rearranged, for Bcl2 e Bcl6 ). Moreover, paraffin embedded (FFPE) tumor specimens will be collected for RNA extraction and mRNA expression mutational and proteomics analysis, centralized at IRST-IRCCS.
Diffuse large B-cell lymphoma (DLBCL) is an heterogeneous group of cancers classified together on the basis of morphology, immunophenotype, genetic alterations and clinical behavior. The distinction of DLBCL into cell-of origin (COO) categories, based on patterns of gene expression reminiscent ( germinal center B-cell- the GC group and activated B-cell- the ABC group-), as defined and characterized by the Lymphoma \& Leukemia Molecular Profiling Project (LLMPP), has profound biological, prognostic and potential therapeutic implications and in addiction, the negative prognostic effect of myelocytomatosis oncogene (MYC), B-cell lymphoma 2 (BCL2) and B-cell lymphoma-6 (BCL6) alterations in DLBCL has been showed largely dependent on COO subtypes . Furthermore, the combination of BCL2, MYC and BCL6 alterations with IPI (International Prognostic Index), identifies markedly worse prognostic groups within individual COO subtypes. The original methods used to define these entities, performed gene expression profiling (GEP) using microarrays on RNA derived from frozen tissue (FT). Subsequently, in an attempt to determine COO in standard practice using commonly available formalin-fixed paraffin-embedded tissue (FFPE) less precise but relatively inexpensive binary immunohistochemical (IHC) methods has been used . However in particular in non GC, the rate of concordance was unsatisfactory. A high degree of agreement has been demonstrated instead in COO determining, with a signature of 20 genes from formalin-fixed paraffin embedded (FFPE) tumor specimens, with Lymph2Cx kit (nCounter® Technology, NanoString Technologies), becoming the gold standard suggested in World Health Organization (WHO) classification . However recently, was demonstrated that the COO and BCL2, MYC, BCL6 status are not enough to describe the molecular risk of these patients, suggesting a genetic substructure that still to be discovered . Moreover, the tumor microenvironment and in particular the ratio of immune effectors and checkpoint molecules also have a prognostic role in DLBCL. Besides, elevated frequency of myofibroblasts, dendritic cells, and cluster of differentiation 4 (CD4) positive T cells correlated with better outcomes.
In conclusion, a comprehensive genomic analysis of these patients and a deep characterization of the immune compartment and immune checkpoints (Nanostring, immunohistochemistry for BCL2, MYC, BCL6, mutation analysis, proteomic analysis etc.) joined with IPI score, will allow the creation of a mixed, molecular, clinical, index (MMCI) to identify extremely poor prognostic groups, within each COO subtype, to consider a risk-adapted treatments in future.
It is a prospective and retrospective observational study with a total duration of 36 months.
The primary objective is the identification of new prognostic biomarkers for DLBCL patients in terms of progression-free survival (PFS) and able to add predictive capacity to recognized important clinical factors.
The secondary objectives are:
For each enrolled patient, immunohistochemical determinations will be performed by each Pathology Unit: COO (GC o ABC type according with Hans algorithm ), evaluation of CD20, CD5, CD10, Bcl6, Bcl2 (cut off>50%), MUM1/IRF4, c-myc (cut off>40%) and Ki67, FISH for c-myc and if rearranged, for Bcl2 e Bcl6). Moreover, paraffin embedded (FFPE) tumor specimens will be collected for mRNA expression mutational and proteomics analysis, centralized at IRST-IRCCS.
1,868 studies on the registry are indexed under Lymphoma, Large B-Cell, Diffuse; 355 are open to participants now.
This study's planned enrollment of 300 is above the median of 150 across 185 observational studies indexed under Lymphoma, Large B-Cell, Diffuse.
Browse Lymphoma, Large B-Cell, Diffuse studies →Istituto Romagnolo per lo Studio dei Tumori Dino Amadori IRST S.r.l. IRCCS is the lead sponsor of 60 studies on the registry; 20 are open to participants now.
Counted across the registry records on this site, refreshed daily.
Prospective cohort: All patients with diagnosis of DLBCL afferring referred to IRST-IRCCS, Oncology-Hematology Units of AVR, S. Orsola Hospital (Bologna).
Retrospective cohort: Patients with diagnosis of DLBCL referred to IRST-IRCCS, from 2011 to 2017 for whom clinical data and FFPE samples are available.
Inclusion Criteria for the prospective cohort:
Inclusion Criteria for the retrospective cohort:
Exclusion Criteria:
Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
A line of therapy is one course of treatment, which may combine several drugs. First-line is the first course given; second-line follows when that stops working or is not tolerated.
“Two prior lines” means two courses that count separately under the study’s rules — not simply two drugs. Ask the study team if you are unsure how yours are counted.
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Line of therapy
A line of therapy is one course of treatment, which may combine several drugs. First-line is the first course given; second-line follows when that stops working or is not tolerated.
“Two prior lines” means two courses that count separately under the study’s rules — not simply two drugs. Ask the study team if you are unsure how yours are counted.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Informed consent
Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.
You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.
Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.
Prospective cohort: All patients with diagnosis of DLBCL afferring referred to IRST-IRCCS, Oncology-Hematology Units of AVR, S. Orsola Hospital (Bologna).
Other: Prospective cohort
Retrospective cohort: Patients with diagnosis of DLBCL referred to IRST-IRCCS, from 2011 to 2017 for whom clinical data and FFPE samples are available.
Other: Retrospective cohort
Immunohistochemical determinations: Cell of Origin (COO) (according with Hans algorithm), evaluation of Cluster of Differentiation (CD) (CD20, CD5, CD10), Bcl6, Bcl2 (cut off\>50%), MUM1/IRF4, c-myc (cut off\>40%) and Ki67, FISH for c-myc and if rearranged for Bcl2 e Bcl6. mRNA expression by Nanostring Single cell analysis Immune checkpoint expression Proteomic analysis Metabolic analysis Radiomic analysis
Immunohistochemical determinations: Cell of Origin (COO) (according with Hans algorithm), evaluation of Cluster of Differentiation (CD) (CD20, CD5, CD10), Bcl6, Bcl2 (cut off\>50%), MUM1/IRF4, c-myc (cut off\>40%) and Ki67, FISH for c-myc and if rearranged for Bcl2 e Bcl6. mRNA expression by Nanostring Single cell analysis Immune checkpoint expression Proteomic analysis Metabolic analysis Radiomic analysis
identification of new prognostic biomarkers
To identify new prognostic biomarkers for DLBCL patients that combined to clinical factors (IPI) are able to create a MMCI, predictive in terms of progression-free survival (PFS) of DLBCL patients.
Time frame: 3 years
identification of molecular and clinical parameters
to identify molecular and clinical parameters associated with overall survival (OS) and objective response rate (ORR)
Time frame: 3 years
characterization of tissue and circulating immune microenvironment
to characterize tissue and circulating immune microenvironment by bulk and single cell transcriptomics
Time frame: 3 years
immune checkpoint genes analysis
to assess the correlation between the expression of immune checkpoint genes and mRNA signatures
Time frame: 3 years
mutational status
describe the mutational status of a panel of genes relevant to DLBCL pathogenesis
Time frame: 3 years
Correlation of protein expression, mutational status and the mRNA signatures
assess the correlation between protein expression, mutational status and the mRNA signatures.
Time frame: 3 years
To analyze the correlation between radiomic features from PET images, tumor characteristics and clinical outcomes, through a multi-omics artificial intelligence approach using ROC algorithm. .
Investigate the correlation between radiomic features obtained from PET images, tumour characteristics and clinical outcomes (PFS, OS, ORR). ROC (Receiver operating characteristic) curve will be computed and compared between the models. Depending on the outcome (time-to-event or binary) different regression models (Cox model for PFS and OS and logistic model for ORR) will be used.
Time frame: 3 years
To analyze the correlation between radiomic features from PET images, tumor characteristics and clinical outcomes, through a multi-omics artificial intelligence approach using c-index algorithm.
Investigate the correlation between radiomic features obtained from PET images, tumour characteristics and clinical outcomes (PFS, OS, ORR). C-index curve will be computed and compared between the models. Depending on the outcome (time-to-event or binary) different regression models (Cox model for PFS and OS and logistic model for ORR) will be used.
Time frame: 3 years
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Lymphoma, Large B-Cell, Diffuse →
Istituto Romagnolo per lo Studio dei Tumori Dino Amadori IRST S.r.l. IRCCS