GENOMED4ALL: Improving MDS Classification and Prognosis by AI

NCT ID: NCT04889729

Last Updated: 2022-09-09

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 13284 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2021-03-15
• Study Completion Date: 2024-12-31

Brief Summary

Myelodysplastic syndromes (MDS) typically occur in elderly people. Current disese classifcation system and prognostic scores (International Prognostic Scoring System, IPSS) present limitations and in most cases fail to capture reliable prognostic information at individual level. Study of MDS has been rapidly transformed by genome characterization and there is increasing evidence that mutation screening may add significant information to currently available prognostic scores. The project will aim to develop artificial intelligence (AI)-based solutions to improve MDS classification and prognostication, through the implementation of a personalized medicine approach. In close collaboration with the European Reference Network on Rare Hematological Diseases (ERN-EuroBloodNet, FPA 739541), GENOMED4ALL involves multiple clinical partners from the network, while leveraging on healthcare information and repositories that will be gathered incorporating interoperability standards as promoted by ERN-EuroBloodNet central registry, the European Rare Blood Disorders Platform (ENROL, GA 947670).

Detailed Description

Myelodysplastic syndromes (MDS) typically occur in elderly people. Patients present peripheral blood cytopenia, and with time a portion of these subjects evolve into acute myeloid leukaemia (AML). The natural history of MDS is heterogeneous ranging from conditions with a near-normal life expectancy to forms close to AML, and therefore a risk-adapted treatment strategy is mandatory. Current prognostic scores (Revised International Prognostic Scoring System, IPSS-R) present limitations, and in most cases fail to capture reliable prognostic information at individual level.

Study of MDS has been rapidly transformed by genome characterization. Somatic mutations occur in the genomes of hematopoietic stem cells at a low, but detectable frequency during normal DNA replication. Any genetic alteration that causes a selective advantage relative to other self-renewing cells will lead to clonal dominance (clonal haematopoiesis, CH). The consequence of CH is genomic instability leading to increased risk of acquiring additional mutations and to develop MDS, solid cancer and other illnesses. The time and place of individual mutations and their clonal emergence during the course of the disease are central issues for a better comprehension of MDS pathogenesis and phenotype and for the development of cancer preventive strategies.

Important steps forward have been made in defining the molecular architecture of MDS. The MDS associated with 5q deletion derives from the haploinsufficiency of RPS14 gene. Genes encoding for spliceosome components were identified in a high proportion of subjects with MDS. There is a close relationship between ring sideroblasts and SF3B1 mutations, which is consistent with a causal relationship. In addition, an increasing number of genes have been found to carry recurrent mutations in MDS, involved in DNA methylation (DNMT3A, TET2, IDH1/2), chromatin modification (EZH2, ASXL1), transcriptional regulation (RUNX1), signal transduction (KRAS, CBL).

Gene mutations have been reported to influence survival and risk of disease progression in MDS, and the evaluation of the mutation status may add significant information to currently used prognostic scores. For instance, we found that SF3B1 mutations were independent predictors of favorable prognosis, while driver mutations of ASXL1, SRSF2, RUNX1, TP53 and EZH2 genes were associated with a reduced probability of survival. MDS with ring sideroblasts provide the best evidence that the identification of the mutant gene responsible for the initial clone is relevant to clinical outcome. In fact, ring sideroblasts may be found not only in patients with a founding mutation in SF3B1, but also in those with an initiating oncogenic lesion in SRSF2. However, the median leukemia-free survival is >10 years in the former vs <2 years in the latter.

Moreover, mutation screening may affect clinical decision making : a) in MDS with 5q-, subjects carrying TP53 mutations have a higher risk of leukemic progression and a lower probability of response to lenalidomide; b) in patients receiving HSCT, TP53 mutations predict high probability of relapse; c) SF3B1 mutations are associated with increased probability of erythroid response to TGFb inhibitors (luspatercept), and d) TET2 mutations might be associated with response to HMA.

Despite these findings, caution is needed against immediately adopting such mutational testing in clinical practice. First, 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 associated with specific treatments, meaning that a large percentage is still associated with clinical and non-mutational factors. Comprehensive analyses of large patient population and new methods to study gene-gene interactions and genoptype-phenotype correlations are warranted to correctly estimate the independent effect of each genomic abnormality on clinical outcome and response to treatment.

By combining an already available, large amount of sequenced genomic data and clinical information, the authors hypothesize that AI will allow to understand better MDS biology and classification, enhance prognostic/predictive capacity of currently available tools and apply treatments in a more targeted way, thus facilitating the implementation of personalized medicine program across EU.

Conditions

Myelodysplastic Syndromes

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: RETROSPECTIVE

Study Groups

GENOMED4ALL - MDS patients

Information on targeted mutation screening (NGS including 60 genes related to MDS) from 13284 MDS patients

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Patients affected by MDS according WHO criteria > 18 years old
• Avaliability of clinical and hematological information
• Availability of information on targeted mutation screening

Exclusion Criteria

• none of the above

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Istituto Clinico Humanitas

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Federico Alvarez

Role: PRINCIPAL_INVESTIGATOR

UNIVERSIDAD POLITECNICA DE MADRID SPAIN

Lucia Comnes

Role: PRINCIPAL_INVESTIGATOR

DATAWIZARD SRL ITALY

Mar Manu Pereira

Role: PRINCIPAL_INVESTIGATOR

FUNDACIO HOSPITAL UNIVERSITARI VALL D'HEBRON - INSTITUT DE RECERCA SPAIN

Pierre Fenaux

Role: PRINCIPAL_INVESTIGATOR

ASSISTANCE PUBLIQUE HOPITAUX DE PARIS FRANCE

Torsten Haferlach

Role: PRINCIPAL_INVESTIGATOR

MLL MUNCHNER LEUKAMIELABOR GMBH GERMANY

Maria Diez Campelo

Role: PRINCIPAL_INVESTIGATOR

Instituto de investigacion biomedica de Salamanca, IBSAL SPAIN

Uwe Platzbecker

Role: PRINCIPAL_INVESTIGATOR

UNIVERSITAET LEIPZIG GERMANY

Gastone Castellani

Role: PRINCIPAL_INVESTIGATOR

ALMA MATER STUDIORUM - UNIVERSITA DI BOLOGNA ITALY

Andres Krogh

Role: PRINCIPAL_INVESTIGATOR

KOBENHAVNS UNIVERSITET DENMARK

Babita Singh

Role: PRINCIPAL_INVESTIGATOR

FUNDACIO CENTRE DE REGULACIO GENOMICA SPAIN

Piero Fariselli

Role: PRINCIPAL_INVESTIGATOR

UNIVERSITA DEGLI STUDI DI TORINO ITALY

Kostantinos Marias

Role: PRINCIPAL_INVESTIGATOR

IDRYMA TECHNOLOGIAS KAI EREVNAS GREECE

Mar Mañu Pereira

Role: PRINCIPAL_INVESTIGATOR

European Reference Network on Rare Hematological Diseases (ERN-EuroBloodNet)

Locations

Istituto Clinico Humanitas

Milan, , Italy

Countries

Italy

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Reference Type: DERIVED

PMID: 36436542 (View on PubMed)

Other Identifiers

GENOMED4ALL: MDS

Identifier Type: -

Identifier Source: org_study_id