An European Platform for Translational Research in Myelodysplastic Syndromes
Study Details
Study Description
Brief Summary
Rationale Myelodysplastic syndromes (MDS) are rare cancers with unmet medical needs. Study of MDS has been rapidly transformed by genome characterization.
The investigators hypothesize that comprehensive analyses of large patient population will allow to correctly estimate the effect of each mutation on clinical outcomes, and that niche factors and immune dysfunctions may influence the development of MDS, clonal evolution and response to treatments
Aims
1- Investigate gene mutations, niche factors and immune dysfunctions influencing the development of MDS, and define biomarkers for early identification of individuals at risk; 2- Develop prognostic models for MDS patients through integration of comprehensive genomic/clinical information; 3- Define biomarkers to better stratify the individual probability of response to specific treatments
Methods EuroBloodNet, the European Reference Network in rare hematological diseases, will provide a basis for research activities. Study of genomic features of clonal dominance in elderly subjects enrolled in large population-based studies and description of the dynamics of clonal establishment and evolution; study of bone marrow microenvironment to identify immune dysfunctions influencing MDS development. Development of inclusive statistical models to accurately predict clinical outcome at individual level, based on large MDS populations with comprehensive genomic/clinical data. Finally, analysis of mutational screening and immune profiles from patients enrolled in prospective trials, to provide evidence on genetic/immunologic profiles associated with probability of response to specific compounds
Expected results To characterize how clonal hematopoiesis relates to the induction of MDS clinical phenotype, and to test the utility of gene sequencing to detect subjects at risk of developing MDS. To define effective prognostic systems and biomarkers to stratify the individual probability of response to treatment
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
MDS typically occurs in elderly people and a portion of these subjects evolve into acute myeloid leukemia (AML). The natural history of MDS is highly heterogeneous, and therefore a risk-adapted treatment strategy is mandatory.
The presence of mutations in a given individual has only limited predictive power, as conversion to MDS is rare regardless of mutation status. In addition, in patients with overt MDS, genetic abnormalities explain only a proportion of the total hazard for survival, meaning that a large percentage is still associated with clinical and non-mutational factors. Comprehensive analyses of large patient populations are warranted to correctly estimate the independent effect of each mutation on clinical outcome and response to treatment.
Moreover, environmental factors influencing the development of MDS and the probability of response to specific treatments are to be characterized. They include alterations in the immune system. In this context, a significant association was found between autoimmune disorders and MDS, and activation of the inflammasome may contribute to MDS development
AIMS 1- Investigate gene mutations, niche factors and immune dysfunctions influencing the development of MDS, and define biomarkers for early identification of individuals at risk; 2- Develop prognostic models for MDS patients through integration of comprehensive genomic/clinical information; 3- Define biomarkers to better stratify the individual probability of response to specific treatments
EXPERIMENTAL DESIGN
AIM1
1a) The investigators will analyze the genomic features of clonal dominance and ineffective hematopoiesis in elderly subjects enrolled in different population-based studies.
Peripheral blood samples will be available for biological investigations. A low-cost, high-throughput platform for mutation screening of 72 genes known to be relevant in MDS will be used.
1b) In order to gain further insight into the MDS genetic heterogeneity, the investigators will perform DNA sequencing in hematopoietic progenitors single cells to clarify the clonal architecture of marrow dysplasia in HSC, the dynamics of clonal establishment and expansion during hematopoietic differentiation, and their relationship with the disease phenotype and evolution
1c) In selected elderly individuals, the investigators will study the transcriptome (RNA sequencing) of isolated mesenchymal stromal cells (MSC) and marrow microenvironment (i.e., innate ad adaptive immunity) with the aim to identify niche factors that may influence the development of a MDS phenotype in elderly subjects with clonal hematopoiesis. Moreover, in patients suffering from both MDS and autoimmune disorder, the investigators will analyze immunological parameters. They will be compared with those of patients with MDS but without immune disorder, and patients with immune disorders without MDS
AIM2
In myeloid malignancies, it was shown that large knowledge banks of matched genomic-clinical data can improve clinical decision-making.
In the present project, basing on large MDS populations with comprehensive genomic and clinical data available within EuroBloodNet network (data on >3000 patients will be available), the investigators will develop inclusive, multistage statistical models (Bayesian network analysis and clustering) to accurately predict clinical outcomes in MDS at individual-patient level. The investigators plan to define 2 homogenous clinical cohorts in order to define distinct patterns and genetic groups within MDS and to independently validate their predictive value. As a research tool, the investigators plan to create a prototype portal within our EuroBloodNet website that allows outcome predictions to be generated based on this data set for user-defined constellations of genomic features and clinical variables. The reliability of this tool on clinical decision making will be tested in a prospective observational trial in the context of EuroBloodNet
AIM3
The investigators will analyze the mutational status and immune landscape associated with response to HMA in MDS patients enrolled in prospective clinical trials conducted within the EuroBloodNet network. Patients treated with azacitidine from prospective studies will be available for biological investigations to define biomarkers associated with clinical response. Validation of biomarkers will then be performed in an independent cohort. In all these studies, biobanking of bone marrow (BM) and peripheral blood (PB) samples has been systematically performed, providing a unique resource to be investigated within this proposal. Data on mutational screening and immune profiles are already available in most patients, and were obtained by comparable methods. For mutation screening, a NGS approach covering key genes involved in myeloid malignancies and the response to HMA was used. For a comprehensive immunological characterization of T lymphocytes, NK cells and ILC cells, standardized flow cytometric protocols were used, which will provide novel insights into frequency, differentiation and activity of these cells in response to therapy. Complementary immunoassays based on Luminex technology will be used to quantify secretory proteins (cytokines, chemokines, growth factors) in BM and PB plasma samples.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Clonal hematopoiesis (AIM 1) The investigators will analyze the genomic features of clonal dominance and ineffective hematopoiesis in elderly subjects enrolled in two population-based studies: "Health and Anemia" study [Haematologica 2010;95:1849], and "Monzino 80-plus" study [BMC Neurol.2011;11:54, validation cohort]. Overall in 5000 subjects aged >65y peripheral blood samples (in some cases collected at different time points) will be available for biological investigations. |
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| Innovative predictive models in MDS (AIM2) The investigators will base on large retrospectove adult MDS population with comprehensive genomic and clinical data available within EuroBloodNet network (data on 3000 patients will be available), to accurately predict clinical outcomes in MDS at individual-patient level. The investigators plan to define 2 homogenous clinical cohorts (learning and testing cohort at 2:1 ratio) in order to define distinct patterns and genetic groups within MDS and to independently validate their predictive value. |
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| Predictive biomarkers in MDS (AIM3) The investigators will analyze MDS patients enrolled in prospective clinical trials conducted within the EuroBloodNet network. Overall 350 patients treated with azacitidine from prospective studies (VidazaAllotrial, RELAZA02 trial, AZA-Ida study, intensive AZA study) will be available for biological investigations to define biomarkers associated with clinical response. Validation of biomarkers will then be performed in an independent cohort including 320 patients (AZA-PLUS trial). In all these studies, biobanking of bone marrow (BM) and peripheral blood (PB) samples has been systematically performed, providing a unique resource to be investigated within this proposal. |
Outcome Measures
Primary Outcome Measures
- DNA mutations in hematopoietic cells [0-24 months]
The investigotors will study the prevalence and type of somatic mutations by a low-cost, high-throughput platform including 72 genes, relevant in myeloid neoplasms.
- RNA expression on hematopoietic progenitors and mesenchymal stromal cells [6-24 months]
The investigators will study the genes diffentially expressed between cell populations of interest and normal controls
- Predictive biomarkers for survival and response to treatment [0-30 months]
The investigators will define, by innovative bayesian and clustering models, independent clinical and molecular factors associated to the probability of survival and response to specific treatments.
- Frequency and function of T lymphocytes, NK cells and ILC cells [6-30 motnhs]
The investigators will analyse by flow-cytometry the frequency of T lymphocytes, NK cells and ILC cells during different disease stages and in response to therapy. Complementary immunoassays based on Luminex technology will be used to quantify secretory proteins (cytokines, chemokines, growth factors).
Eligibility Criteria
Criteria
AIM 1
Inclusion Criteria:
- Individuals aged 65 years or older from population-based studies (retrospective cohort)
Exclusion Criteria:
- lack of biological samples availability
AIM 2
Inclusion Criteria:
- adults patients (>18 years) with a diagnosis of MDS according to WHO criteria (retrospective cohort)
Exclusion Criteria:
- lack of availability of information on clinical and DNA mutational screening data
AIM 3
Inclusion Criteria:
- adults patients (>18 years) with a diagnosis of MDS according to WHO criteria and treated with HMAs
Exclusion Criteria:
- lack of biological samples availability
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Service d'hématologie séniors - Hôpital St Louis / Université Paris 7 | Paris | France | 75475 | |
| 2 | University of Leipzig Medical Center | Leipzig | Germany | 04103 | |
| 3 | Istituto Clinico Humanitas | Rozzano | Milan | Italy | 20089 |
| 4 | Josep Carreras Leukaemia Research Institute (IJC) | Barcelona | Spain | 08916 |
Sponsors and Collaborators
- Istituto Clinico Humanitas
Investigators
- Principal Investigator: Matteo Della Porta, MD, HUMANITAS Cancer Center
Study Documents (Full-Text)
None provided.More Information
Publications
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- Della Porta MG, Jackson CH, Alessandrino EP, Rossi M, Bacigalupo A, van Lint MT, Bernardi M, Allione B, Bosi A, Guidi S, Santini V, Malcovati L, Ubezio M, Milanesi C, Todisco E, Voso MT, Musto P, Onida F, Iori AP, Cerretti R, Grillo G, Molteni A, Pioltelli P, Borin L, Angelucci E, Oldani E, Sica S, Pascutto C, Ferretti V, Santoro A, Bonifazi F, Cazzola M, Rambaldi A. Decision analysis of allogeneic hematopoietic stem cell transplantation for patients with myelodysplastic syndrome stratified according to the revised International Prognostic Scoring System. Leukemia. 2017 Nov;31(11):2449-2457. doi: 10.1038/leu.2017.88. Epub 2017 Mar 21.
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