Molecular Disease Profile of Hematological Malignancies

Study Overview
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Brief Summary
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In this prospective multicentric study, the University of Pavia together with the Fondazione IRCCS Policlinico San Matteo, Pavia and the IRCCS Fondazione Maugeri, Pavia, Italy will provide a systematic analysis of gene mutations in hematological malignancies by using NGS techniques. Patients with a conclusive diagnosis of haematological malignancies according to WHO criteria referred to the Rete Ematologica Lombarda clinical network (REL, www.rel-lombardia.net) will be enrolled. The investigators will analyse genomic DNA extracted from hematopoietic cells at different time points of patient disease. The study contemplates the use of molecular platforms (Next Generation Sequencing, NGS) aimed at the identification of recurrent mutations in myeloid and lymphoid neoplasms, respectively. Screening of gene mutations by NGS will be prospectively implemented in the context of REL clinical network. Patient samples will be analyzed at diagnosis and sequentially during the course of the disease at specific timepoints. The researchers will analyze the correlations between somatic mutations, specific clinical phenotypes (according to the WHO classification) and disease evolution. This will allow to: 1) identify new recurrent genetic mutations involved in the molecular pathogenesis of hematological malignancies; 2) define the role of mutated genes, distinguishing between genes which induce a clonal proliferation of hematopoietic stem cells, and genes which determine the clinical phenotype of the disease; 3) identify mutations which are responsible for disease evolution; 4) define the diagnostic/prognostic role of the identified mutations, and update the current disease classifications and prognostic scores by including molecular parameters. A systematic biobanking of biological material will be provided.

Detailed Description
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BACKGROUND Molecular medicine is the branch of knowledge whose purpose is to elucidate the genetic basis of the diseases, to improve the diagnostic definition and prognostic assessment of patients and to contribute to the development of innovative treatments. Genomic information is increasingly being used in the treatment decision making process for individual patients. The clinical implementation of molecular medicine requires systematic approaches based on the integration of scientific, medical and technological expertises. Hematological malignancies include leukemia, lymphoma, and multiple myeloma. The molecular basis of many hematological neoplasms are still unknown. At the present of researchers' knowledge, scientists know that hematological malignancies are mostly dynamic diseases that arise from a large series of primary and secondary biological and genetic events (i.e. driver and passenger mutations). The Identification of key molecular changes that drive tumour development and progression is essential for the development of new targeted and personalized therapies. Hematological malignancies typically occur in elderly people and, as a result of population aging, represent a growing critical issue for health policies. Hematological malignancies are an ideal context for the implementation of molecular medicine. The paradigmatic example of this is chronic myeloid leukemia, in which the discovery of the molecular basis (the fusion gene BCR/ABL1) has been translated into major clinical advances in diagnosis, treatment and disease monitoring. The World Health Organization (WHO) classification of myeloid and lymphoid neoplasm published in 2008 introduced many genetic changes in the diagnostic definition of blood cancers. Since 2008 plenty of genetic lesions have been identified in many hematological malignancies and the next WHO classification will include many of them. Next generation sequencing (NGS) techniques gave the best contribute to these findings. NGS use high-technology tools that can sequence, in a short time and with relatively low costs, the whole genome or a specific part of it (e.g. exome or targeted genes). The advantage of NGS compared to standard sequencing consists in higher efficiency (a large amount of genes rapidly analysed in a large amount of samples) and higher sensitivity (capacity of detecting mutations in very small clones of neoplastic cells). In last years the availability of new technologies for genomic has enabled the high-throughput screening of somatic mutations in hematological malignancies. It is expected that the results of these studies will significantly improve the management of individual patients through the implementation of innovative diagnostic/prognostic systems and the development of therapeutic strategies based on individual genomic profile. The Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo and University of Pavia has significantly contributed to the definition of molecular basis of hematological malignancies. In 2005 the University of Pavia described the diagnostic and prognostic significance of the JAK2 V617F mutation in myeloproliferative neoplasms (MPN): this mutation was included into the WHO classification of MPN and innovative anti-JAK2 drugs were developed. In 2010, the University of Pavia joined the Cancer Genome Project, a consortium of international research Centers coordinated by the Wellcome Trust Sanger Institute of Cambridge with the aim to elucidate the molecular basis of cancer. In this context, by using massive genome sequencing, recurrent mutations in SF3B1 gene - that encode for a core component of RNA splicing machinery - were described in myelodysplastic syndromes. Moreover in last years, researchers from the University of Pavia gave a significant contribution in the definition of the molecular basis of lymphoid neoplasms (i.e., BRAF V600E mutation in Hairy cell Leukemia, MYD88 L265P mutation in Waldenstrom disease, and SF3B1 mutations in Chronic Lymphocytic Leukemia). Finally, in the very last months the Universisty of Pavia had a key role in the identification of CALR mutations in JAK2-negative MPN. This is again an important finding in the comprehension of the genetic basis of this groups of diseases. In addition to the implementation of next-generation techniques (NGS) for genomic analysis, there is clearly a need to develop effective solutions to analyze and integrate molecular and clinical data of large patient populations, in order to fully understand the relationship between genotype and the clinical expression of a disease. The implementation of molecular medicine requires systematic approaches based on the integration of scientific, clinical and technological expertise. In Italy, the ideal context for the development of molecular medicine programs is represented by hematological regional networks. They represent an innovative model of organization and collaboration, based on the networking of health care facilities. The Rete Ematologica Lombarda (REL, www.rel-lombardia.net) brings together 11 hematological referral centres and has recently provided the basis for a systematic study of these diseases. The strategic objective of REL clinical network is to ensure the better access to the health care facilities, the high quality of services and the continuity of care for all the hematological patients. REL clinical network can give a crucial contribute on the translational research on hematological malignancies and recently, with this purpose, the Regione Lombardia in January 2014 financed a biotechnology cluster for the implementation of genomic analysis and the development of new treatments for hematological diseases. The REL biotechnology cluster (www.relab-lombardia.net) involves the Department of Hematology Oncology, Fondazione IRCCS Policlinico S. Matteo, the University of Pavia, the biotech company Clonit (www.clonit.it) and the pharmaceutical company Novartis. This cluster aims to investigate the molecular basis of hematological malignancies and to develop personalized treatments. GENERAL POURPOSE of the STUDY In this study, the Department of Hematology Oncology, Fondazione IRCCS Policlinico San Matteo, Pavia in collaboration with the University of Pavia and the IRCCS Fondazione Maugeri, Pavia will provide a systematic analysis of gene mutations in hematological malignancies by using NGS techniques. Patients with a conclusive diagnosis of haematological malignancies according to WHO criteria referred to the REL clinical network will be enrolled. The researchers will analyse genomic DNA and RNA extracted from hematopoietic cells at different time points of patient disease. The study contemplates the use of two optimized molecular platforms aimed at the identification of recurrent mutations in myeloid and lymphoid neoplasms, respectively. Screening of gene mutations by NGS will be prospectively implemented in the context of REL clinical network. Patient samples will be analyzed at diagnosis and sequentially during the course of the disease at specific timepoints. The investigators will analyze the correlations between somatic mutations, specific clinical phenotypes (according to the WHO classification) and disease evolution. This will allow to: 1) identify new recurrent genetic mutations involved in the molecular pathogenesis of hematological malignancies; 2) define the role of mutated genes, distinguishing between genes which induce a clonal proliferation of hematopoietic stem cells, and genes which determine the clinical phenotype of the disease; 3) identify mutations which are responsible for disease evolution; 4) define the diagnostic/prognostic role of the identified mutations, and update the current disease classifications and prognostic scores by including molecular parameters. A systematic biobanking of biological material will be provided. OBJECTIVES The general objective of the study is to perform a systematic analysis of gene mutations associated to hematological malignancies by using a NGS targeted sequencing approach. ENDPOINTS: Cumulative incidence (%) of gene mutations in principal clone and subclones in each hematological malignancy Genotype - phenotype correlations between clinical characteristics and mutational status, evaluated by the Fisher's exact test (for categorical variables) or by the Mann-Whitney or the Kruskall-Wallis tests (for quantitative variables compared in two or more groups of patients, respectively) with p-value Overall survival and disease free survival according to clinical and biological risk factors at diagnosis and during disease evolution, evaluated by the Kaplan-Meier product limit method and the Cox proportional hazard model both for time-dependent and not time-dependent covariates PATIENTS SELECTION: Inclusion criteria: Conclusive diagnosis of myeloid or lymphoid neoplasm according to 2008 WHO criteria age ≥ 18 years. There is no upper age limit signed written informed consent Exclusion criteria: severe neurological or psychiatric disorder interfering with ability to give an informed consent no written informed consent no consent for biobanking 7. STUDY DESIGN : This is a multicentric, prospective, observational study. All patients with a diagnosis of hematological malignancy according to WHO classification performed within REL clinical network are intended to be enrolled. 8. ASPECTS OF GOOD CLINICAL PRACTICE, DATA PRIVACY Biobanking is governed under the general regulatory framework for biomedical research. This is a mosaic of formal legal instruments and regulatory bodies put in place at national and European levels, as well as more informal types of governance tools and instruments such as professional guidelines and best practice. Regulation of biomedical research consists of binding and non-binding legal instruments at both national and European levels. This is in the form of specific law for medical research - for example the Council of Europe Oviedo Convention 1997 - and more general legal instruments - such as human rights and data protection law - some of which have relevance for biobanking. Responsibility for the oversight of research and ensuring compliance with the legal requirements has largely been delegated to national bodies, such as research ethics committees. 8.1 DATA COLLECTION The study contemplate the collection of clinical and biological indispensable data for a precise diagnostic and prognostic standard definition in a ad-hoc electronic CRF and the analysis of specific genes that can be involved in the molecular basis of the diseases through a NGS techniques. 8.2 CLINICAL DATA WAREHOUSE (Informatics for Integrating Biology and the Bedside, I2B2) Informatics for Integrating Biology and the Bedside (i2b2, www.i2b2.org) is an open source clinical data warehouse, which is efficiently interrogated to find sets of interesting patients preserving their privacy through a query tool interface. Within this architecture, interoperable server-side software objects, called cells, are able to exchange information with each other, relying on web services technology. In order to support and improve the efficiency of clinical research in oncology, the University of Pavia and the IRCCS Fondazione Salvatore Maugeri of Pavia developed and implemented a novel ICT platform, called Onco-i2b2, grounded on the i2b2 software and installed in the IRCCS Fondazione S. Maugeri, Pavia. Onco-i2b2 is able to integrate data from different sources inside the i2b2 data warehouse through the implementation of a complex IT architecture, which includes development of new i2b2-cells for data analysis. As result of this project, hospital researchers have been enabled to obtain information from the pathology database, from a biobank management system and to merge them with the clinical information present in the hospital information system, in order to select interesting patients with a specific phenotype of interest. 8.3 TECHNICAL DESCRIPTION OF PSEUDONYMIZATION PROCESS AND USED TOOLS Actually a specific regulation at national level for technical aspects relate to biobank does not exist, but some workgroups of experts (e.g. AIOM e SIAPEC-IAP) have raised up initiatives for defining and harmonizing the existing national general procedures. A brief list of structural and technological requirements can be identified in: Definition of a programmatic documentation with objective of the biobank, a functional specifications to be performed, the type of the preserved material, number of expected specimens, methods of drawdown, processing and conservation, management of information, specimens transport and reception from the receiving unit, management of the possible biological risk and an economic plan for medium-large period Logical definition of the dedicated locals, conditioning systems and access control. In addiction temperature of the cryo-containers have to be monitored continuously. Disaster recovery plan for equipment and cryo containers has to be defined (e.g. use of systems for electrical continuity or list of competent staff that should intervene when special events occur) Use of a certified quality system for each step of the different procedures is recommended, keeping track of data quality from the acquisition of the informed consent to the storage of the specimen Definition of a dedicated information system for managing the biobank samples , related to clinical information stored in the hospital information system, to track the specimen movements and update the follow-up data deriving by the scientific research performed. Disaster recovery plan also for the IT architecture has to be implemented. It consists in an incremental backup of all biobank data that allows the IT system managers to restore all the information in any period of time In the Bruno Boerci oncologic biobank each biological specimen is identified by a specific code, printed on the tube using a data matrix barcode (a bi-dimensional bar code readable through the use of a laser scanner), and stored in the biobank database and managed by the biobank management software, that allows also to view its position inside the biobank cryo container. Clinical data for each follow up are collected automatically retrieving data from the hospital information system. Clinical data and biobank information are constantly and continually inserted in clinical data warehouse by an automatic update procedure. Clinical and pathological data are codified using SNOMED, TNM and ICD9-CM standards. The use of the BRISQ system for data standardization (Biospecimen Reporting for Improved Study Quality, Biopreservation and Biobanking, 2011) is recommended, but not implemented yet. 8.4 TRANSFER OF PATIENTS SAMPLES AND BIOBANK SAMPLES ENTRANCE Bio specimens anonymisation (or better, de-identification) has to be performed in to assure high levels of data privacy. The terminology used in the European documents identifies the term 'anonymized' when biological material is stored alongside associated information, such as the type of tumour, medical treatment, donor's age and so forth, but all information that would allow identification of the research participant or patient is stripped, either irreversibly (unlinked anonymized) or reversibly (linked anonymized). In the case of linked anonymized samples, identification is possible by a code, to which researchers or other users of the material-as part of the definition of the term 'reversibly/linked anonymized'-do not have access. Coded samples have the same characteristics as linked (reversibly) anonymized samples, the only difference being that researchers and users have access to the code. In this project the use of coded-anonymisation is preferred in order to have an adequate level of privacy security and feasibility of research activities. The proposed architecture that will implement this type of de -identification requires the definition of a code that identifies the bio specimen from the beginning and a second code that will be generated before the specimen will be stored in the biobank. A third code will automatically generated during the acceptance phase of the specimen and will be stored in a separate location. In this way the information related to the first code and those related to the final one are totally decoupled, unless the third code is known: this happens only when researchers need to access to both data concurrently. 9 MOLECOLAR ANALYSIS The molecular analysis is performed by using 2 different NGS platforms for the target-resequencing. The platforms are outlined on the basis of the most recent literature on the molecular biology of myeloid and lymphoid neoplasm. It is noteworthy that the efforts of the scientific community in this area are huge, and this contributes to a continuous flow of new information and discoveries, with the consequent possibility of modifying the platforms.

Official Title
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Molecular Disease Profile of Haematological Malignancies. A Prospective Registry Study by the Rete Ematologica Lombarda (REL) Clinical Network

Conditions
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Hematological Malignancies

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Conclusive diagnosis of myeloid or lymphoid neoplasm according to 2008 WHO criteria age ≥ 18 years. There is no upper age limit signed written informed consent Exclusion criteria: severe neurological or psychiatric disorder interfering with ability to give an informed consent no written informed consent

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Patients with hematological malignancies<br>Patients with a conclusive diagnosis of haematological malignancies according to WHO criteria referred to the Rete Ematologica Lombarda (REL) clinical network will be enrolled. The investigators will analyse genomic DNA extracted from hematopoietic cells at different time points of patient disease. The study contemplates the use of two optimized molecular platforms aimed at the identification of recurrent mutations in myeloid and lymphoid neoplasms, respectively. Screening of gene mutations by NGS will be prospectively implemented in the context of REL clinical network. Patient samples will be analyzed at diagnosis and sequentially during the course of the disease at specific timepoints. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Cumulative incidence of gene mutations in principal clone and subclones in each hematological malignancy |  | 3 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Genotype-phenotype correlations between clinical characteristics and mutational status |  | 3 years | 
| Overall survival and disease-free survival according to clinical and biological risk factors at diagnosis and during disease evolution |  | 3 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Prognosis, Hematological malignancies, Next Generation Sequencing, Genotype-phenotype correlations, Diagnosis