Jump to Main Content

ASH Agenda

Precision Medicine: Tailoring Treatment and Monitoring Response to Therapy

Molecular profiling of DNA and RNA has provided valuable new insights into the genetic basis of non-malignant and malignant hematologic disorders as well as an increased understanding of basic mechanisms that regulate hematopoiesis. These advances have important implications for future research and clinical practice in such areas as molecular diagnostics, the implementation of gene or pathway-directed targeted therapies, and the use of such information to inform drug discovery.

In all hematologic malignancies, including acute and chronic leukemias, lymphomas, the myelodysplastic and myeloproliferative disorders, there are both inherited and somatic genetic alterations that contribute to predisposition, transformation, disease progression, responsiveness to therapy, and treatment complications. In addition, many non-malignant hematologic disorders have a genetic basis, including bone marrow failure syndromes, such as dyskeratosis congenita and severe congenital neutropenia, and hemoglobinopathies such as sickle cell disease. In fact, extremely common genetic disorders that affect coagulation (e.g., Factor V Leiden thrombophilia) are important co-factors increasing the susceptibility to deep vein thrombosis and pulmonary embolism in the general population.1 Historically, these genetic alterations have been identified by low-resolution or limited-scope genetic tests, such as karyotyping or single gene assays. However, recent technological advances have enabled the analyses of genomic and epigenomic variation in a comprehensive, high-throughput fashion using next generation sequencing. Moreover, there is growing interest in new areas of research, such as the epi-transcriptome and its relevance to health and disease.

These approaches have transformed the understanding of hematologic malignancies in recent years, with important implications for clinical care. Next generation sequencing has shown that each tumor type typically exhibits distinct constellations of genetic alterations that target one or more key cellular pathways that regulate cell growth and proliferation, evasion of the immune system, and other aspects of cancer behavior. Sequencing technologies can also help identify different types of genetic alterations, including single nucleotide mutations, gains and losses of DNA, chromosomal rearrangements, and epigenetic modifications, that may be present in a hematologic disease. In contrast, strategies that detect only particular types of genetic variations (such as karyotyping or sequencing of gene panels) often do not identify all of the relevant genetic changes.

Integrated genomic analysis has enabled the revision of the molecular classification of blood diseases and has uncovered genetic changes that may be used for classification and risk assignment. Further, new targets have been identified with this technique, such as genetic and epigenetic changes that may be used as prognostic markers and for monitoring disease response; germline/inherited mutations for use in genetic counseling and disease surveillance; and pathways and genes that, when mutated, may serve as targets for new therapy.

Maximizing the Impact of Precision Medicine: Priorities to Accelerate Progress
Enhancing precision medicine efforts in hematology will require that sequencing technologies be adopted in drug discovery efforts, and in the assessment of disease predisposition, and response to therapy. In addition, appropriate infrastructure must be developed to integrate genomic and epigenomic medicine into the clinic.

Next generation genome sequencing studies have shown that the genes encoding for a number of epigenetic modifying enzymes and reader proteins are recurrently mutated across the spectrum of hematologic disorders. For example, in approximately half of all acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS) patients, the disease is driven by a mutation of the epigenetic machinery. 2 Mutations in epigenetic modifiers are the most common alteration found in pediatric acute lymphocytic leukemia (ALL) at relapse. Despite high upfront cure rates of pediatric ALL, the cure rates of relapsed pediatric ALL remain dismal. How the resulting epigenetic dysregulation contributes to disease initiation, transformation and evolution, and shapes the disease time course as well as response to therapy remains poorly understood. Areas requiring investigation include, but are not limited, to the following:

1.1 Understanding the impact of currently used epigenetic therapies (e.g., hypomethylating agents) on pre-leukemic cells harboring mutations in epigenetic regulators may lead to early intervention approaches and new agents.
1.2 Determining risk factors for progression of clonal hematopoiesis. Large-scale resequencing studies have determined that cancer-associated genetic mutations can be detected in the peripheral blood of a large proportion of asymptomatic individuals, particularly with increasing age. This phenomenon has been termed “clonal hematopoiesis of indeterminate potential” or CHIP. While the presence of CHIP has been shown to statistically increase the likelihood of developing MDS and AML, increase the risk of cardiovascular events, and increase all-cause mortality, the vast majority of these individuals will live with benign, clonal hematopoiesis for the rest of their lives. This presents a paradox as these individuals carry a genetic profile associated with blood cancers, but most are not predestined to develop disease. Using CHIP to differentiate individuals who are at increased risk of hematopoietic transformation and other life-threatening complications from those who will likely live an otherwise healthy life is a high priority for blood cancer prevention. Similarly, elucidation of molecular mechanism(s) linking CHIP to adverse outcomes will inform about novel targets for personalized therapies.
1.3 Understanding how genomic and epigenomic factors influence the response to immunotherapeutic approaches, including chimeric antigen receptor (CAR) T-cell therapy, bispecific engager and payload-coupled immunotherapeutic approaches, and checkpoint blockade therapy. Such understanding has the potential to augment responsiveness to immunotherapy. In addition, these profiling technologies and insights will affect the diagnosis and treatment of autoimmune diseases and our understanding of the pathogenesis of graft-versus-host disease, which can lead to new mechanism-based therapies. They can also be used to improve our understanding of genetic/epigenetic factors that affect stem cell biology and engraftment, thus providing valuable insights for clinical transplantation.
1.4 Applying sensitive sequencing technologies for monitoring response to treatment and minimal residual disease (MRD) detection. Tracking genetic biomarkers with newer sequencing-based approaches may provide a more sensitive, less operator-dependent, and more consistent measurement of MRD compared with traditional flow cytometry or conventional antigen receptor PCR-based readouts. The deployment of next generation molecular MRD detection is one of the challenges in studying the kinetics of novel therapeutic agents in various hematopoietic malignancies.
1.5 Collecting genetic datasets that provide insights into inherited and acquired non-malignant hematologic diseases and storing those datasets in centralized repositories that allow for efficient analysis and interpretation. A large subset of heritable hematologic diseases has been linked to specific germline risk alleles, and the understanding of the role of somatic mutations (such as CHIP) in hematologic complications, including thrombosis, is rapidly changing. As the role of germline and somatic genetic variants in non-malignant hematologic diseases continues to evolve, it is critical to continue collating and curating this genetic information to enhance understanding of these diseases.
1.6 Using sophisticated analytical approaches to handle exceptionally large datasets. It will be critical to establish and nurture highly advanced computational and biostatistical expertise among new investigators in the hematology community.

While important information has been generated from sequencing studies in various hematologic diseases, for many subtypes of disease, an insufficient number of cases sequenced or a limited scope of sequencing has prevented researchers from gaining useful insights. This is particularly relevant for studies involving rare non-malignant hematologic diseases such as inherited platelet disorders, where several disease-causing mutations and variants remain unidentified, as well as studies that have employed sequencing for only a limited portion of the tumor genome.3 Whole-genome sequencing of large numbers of samples, with an emphasis on poorly studied and rare entities, is required to fully define the landscape of genetic changes underlying the development of both malignant and non-malignant hematologic diseases. Such data, in both raw and analyzed states, must be coalesced and made broadly available to empower research and inform clinical management of patients. Further, the extent to which malignant cells are distinct from normal cells needs to be more broadly elucidated because many hematopoietic cancers disturb epigenetic regulators, including both readers and writers of the epigenome (of which there are many), providing additional precision medicine opportunities.

Such studies are likely to reveal important associations between outcome and targetable mutations. Support for ongoing sequencing is necessary because high-resolution sequencing, beyond the completion of the initial phase of the NIH-led Cancer Genome Atlas, continues to uncover new genetic events that are critical for malignant transformation. An additional area of investigation is the identification of the genetic alterations and genomic variations that are associated with therapy-related toxicity, long-term complications such as life-threatening cardiac toxicity, and the risk of secondary malignancies.

A better understanding of genetic and epigenetic alterations that drive hematologic diseases is essential to guide drug discovery efforts. Recently approved drugs target somatic mutations identified in gene discovery studies; several have achieved a “breakthrough status” because they are tailored to specific genetic changes in tumor cells and show remarkable promise for treating hematologic disorders. Further, advanced genome sequencing studies have identified additional genetic changes that are attractive for similar targeted approaches. Pre-clinical assessment of novel agents relies on implementation of predictive disease models that accurately model hematologic diseases and inform the potential efficacy of novel therapeutic agents. The recent approval of several targeted therapeutics provides the opportunity to assess existing models for their ability to predict clinical outcomes and therefore be prioritized for future studies. Of note, there is increasing use of different preclinical modeling systems, including genetically engineered mouse models, patient-derived xenografts, and in vitro/in vivo systems that allow for diseased cells to be monitored and treated in a more representative microenvironment. There are increasing data to show the relevance of inherited and acquired genetic variation on pharmacologic efficacy and toxicities, and the field of pharmacogenomics is already having broad impact in the hematology field. Opportunities and challenges will include:

2.1 Defining the functional consequences of mutations to aid drug design.
2.2 Generating new cell lines and in vivo models that recapitulate the many genomic alterations found in human blood diseases and that are amenable to high throughput sequencing efforts. These tools should be made available to the community.
2.3 Assessing existing preclinical models for their ability to predict clinical outcomes, developing new models where needed, and developing evidence-based recommendations for the implementation of preclinical models. The field must continue to assess whether innovation in preclinical models increases the accuracy and throughput of preclinical therapeutic evaluation.
2.4 Developing pharmacokinetic, pharmacodynamic, and toxicology data for new drugs, including in tumor-bearing models, in efficient formats and timelines.
2.5 Providing a rapid pathway for translation from preclinical studies to early-phase clinical trials.
2.6 Improving the understanding of the functional consequences of mutations in disease subclones and the therapeutic targeting of complex cancer cell populations with evolving resistance mechanisms.
2.7 Developing an advanced understanding of modifications that occur at the epi-transcriptome level in normal and abnormal hematopoietic processes as potential treatment opportunities.
2.8 Identifying inherited and acquired genetic variants that impact pharmacokinetic and pharmacodynamic factors, and work to ensure there are clinical grade and reimbursable assays for pharmacogenomic biomarkers with clinical impact.

While genome sequencing is becoming increasingly routine, accurate bioinformatic analysis remains challenging, particularly for complex sequence mutations and rearrangements. In addition, the sequencing and analysis process produces immense amounts of raw data that must be appropriately categorized. Accurate and consistent analysis is particularly important for clinical sequencing. Another challenge is the variation in interrogating the non-coding genome and correlating the information with transcriptional and epigenetic data to provide a comprehensive, integrated portrait of the genomes of various hematologic diseases. The immense amount of sequencing data often exceeds the capacity to perform adequate bioinformatic analyses, where both costs and the lack of trained personnel represent significant limitations.

To integrate sequencing and analysis into both research and clinical applications, content-rich portals must be designed that can offer cost-effective and regulated access to raw genomic data for interrogating and sharing sequencing results without compromising patient privacy. To accomplish this, the following areas must be addressed:

3.1 Platforms must be sufficiently comprehensive to identify all relevant variant information.
3.2 Bioinformatic analysis must be robust, with rapid return of results.
3.3 Interpretation of the biologic and clinical relevance of genetic alterations must be reliable.
3.4 Tools must be able to evaluate and report inherited genetic variants, including those that may have important impact outside of the clinical area of study.
3.5 Platforms must be housed in diagnostic environments that adhere to CAP/CLIA and FDA regulations for appropriate applications.

An important prerequisite to clinical application of sequencing technology is establishing the clinical trial infrastructure to direct patients with “actionable” genetic or epigenetic alterations to trials of mutation-, gene-, or pathway-targeted agents. The need to organize this process efficiently is underscored by the fact that clinical sequencing will have to identify rare but traceable events (e.g., tyrosine kinase fusions in Ph-like ALL may serve as an appropriate analog). Therefore, the organization and implementation of clinical sequencing will require structural changes in the health-care sector:

4.1 Creation of genome diagnostic networks to address accrual of sufficient patients to enable adequate power; procurement of suitable tumor/non-tumor material for sequencing, pharmacodynamic studies, and correlative biology.
4.2 Engagement of the pharmaceutical industry to support trials of new or repurposed agents, particularly in uncommon diseases or special populations (such as the elderly, young children, or those with specific medical conditions).
4.3 Adoption of novel adaptive clinical trial designs that will help consolidate research timelines and offer better utility for studying specific biomarkers or patient subpopulations.
4.4 Development of a new regulatory model for rapid testing of novel agents in single patients with specific genetic alterations that may transect traditional boundaries in drug development when novel combinations from different sources may be indicated.
4.5 Education of the next generation of clinical investigators in genomics and epigenomics so that they incorporate genetic analysis into their clinical trial design, interpretation, and routine clinical care.



  1. Reitsma, PH. Genetics in thrombophilia. An update. Haemostaseologie. 2014 Dec 3;35(1).
  2. The Cancer Genome Atlas Research Network. Genomic and Epigenomic Landscapes of Adult De Novo Acute Myeloid Leukemia . N Engl J Med. 2013;368(22):2059-74
  3. Freson, K. Clinical Next Generation Sequencing to Identify Novel Platelet Disorders. Blood 2016;128(22)

Related Content