Science & Medicine

At last: A genetic atlas of MPN prognostic mutations.

Editor’s Note: This critically important paper deserves a more comprehensive review. Due to extreme time pressures and the frequent  power outages accompanying this week’s storm, only a cursory overview was attempted and rushed to press without factcheck or review.  Errors are sure to result.  We justify publication only because the full text is made freely available by the New England Journal of Medicine and   urge readers to take advantage of the opportunity  “Classification and Personalized Prognosis in Myeloproliferative Neoplasm,: (Grinfeld et al,., NEJM, 2018)

A façade of benign myeloproliferation masks a clone of transformed hematopoietic stem cells capable of expansion and transformation to an aggressive form of bone marrow failure or acute leukemia.     Jerry L. Spivak, MD, “Myeloproliferative Neoplasms,” (NEJM 2017)

Published just a month before the ASH San Diego meeting, “Classification and Personalized Prognosis in Myeloproliferative Neoplasm, is a landmark document in the history of MPNs. reminiscent of William Dameshek’s “Some Speculations on the Myeloproliferative Syndromes,” (Blood, 1951).

This comprehensive analysis of the predicted outcomes of MPN disease based on what we currently know about the MPN mutational landscape is an historic event in the long and tortured attempt to understand and treat the myeloproliferatife neoplasms.  For too long has our family of phenotypically related genomic diseases been assessed based essentially on patient presentation, clinical data and traditional blood tests plus a handful of biomarkers notably JAK2 and CALR status and visual inspection of blood morphology and marrow fibrosis obtained through bone marrow biopsy.

In the absence of a clear picture of the genetic, mutational and epigenetic factors behind the etiology of MPNs, our physicians had little choice.  Until now, the clinical approach to diagnosis and treatment relied on observation of the effects mutant clones produce rather than identification of the factors initiating and driving disease.

“It is possible,” wrote Dameshek in his MPN founding document, “that these various conditions — ‘myeloproliferative disorders’ —  are all somewhat variable manifestations of proliferative activity of the bone marrow cells, perhaps due to a hitherto undiscovered stimulus.”  Dameshek’s speculations are both confirmed — and significant undiscovered stimuli unmasked — in “Classification.”

Proceeding in a direct line from the multiple lab revelations of the JAK2 v617f mutation in 2005 and CALR discoveries of 2013 by Robert Kralovics and Tony Green, this paper produced by a largely English consortium with participation by American and European researchers,  launches MPN diagnostics and treatment into the contemporary era of genetic-based precision medicine.

Here are some key practical findings:

The authors identified eight MPN subgroups based on mutational findings:

  1. TP53 mutation, occurring late in the disease process, w poor prognosis and high risk of transformation to AML
  2. Spliceosome or chromatin mutations — co-elements in gene expression based on removing introns from an RNA transcript — create increased risk for MF transformation and shorter event free survival. This group includes LOH at chromosome 4q and aberrations in chromosomes 7 and 7q.
  3. CALR mutation.. co-occurring with LOH at chromosome 19 and deletion at chromosome 20q — or those with MPL mutations generally present with ET or MF.  Those patients with MPL-mutated myelofibrosis had an elevated rate of AML transformation vs the JAK2 heterozygous subgroup.
  4. MPL mutated myelofibrosis, elevated risk of AML transformation
  5. Heterozygous JAK2 common in mutated ET patients and some PV patients, with favorable outcomes.
  6.  JAK2 homozygous patients with NFE2 mutation, more frequent MF transformation
  7. Myeloprofileration with recognizabb;e driver mutation but no identified class-defining drivers. generally benign outcome
  8. No detectable driver mutations typically young, female and diagnosed with ET with generally benign outcomes.

Mutations in spliceosome components, epigenetic regulators and the RAS pathway are strongly associated with accelerated phase (myelofibrosis) as compared with chronic phase disease as were male sex, older age and germline loci associated with platelet count and red cell variable.

The order in which mutations are acquired influence disease phenotype. CALR and MPL mutations occur more commonly early in disease. Mutations in NRASA, TP53, PPMID and NFE2 are acquired significantly later in disease.

Some earlier occurring mutation such as SF3B1 and DNMT3A are associated with age related clonal hematopoiesis sugging MPNs could arise from a previously asyptomatic clone,

“A key determinant of treatment,” write the authors “is the predicted prognosis…Patients who are expected to have a benign future clinical course would proably benefit from treatments that are aimed at minimizing thrombotic risk and those who are expected to have progression to leukemia or myelofibrotic bone marrow failure could be candidates for intensive therapy or clinical trials of new agents.”

Application of elements of this prognostic model can be accessed in An MPN Personalized Risk Calculator, available at  https://cancer.sanger.ac.uk/mpn-multistage/

“This research proves the potential of personalized medicine, using genetics,” Peter Campbell, MD, PhD, head of cancer, aging and somatic mutation at Wellcome Sanger Institute and joint head of the Cancer Genome Project, said in a press release. “Modern genomics will empower clinicians and support their decisions regarding the best therapies and clinical trials for each patient. We hope our study will be a game changer for patients with these blood cancers by providing better predictions for how their disease may behave in the future, and inform treatment choice.”

Now the question is, what do we do about it?

There are two challenges in future therapy for myeloproliferative neoplasms: accurate genetic determination of disease etiology as opposed to phenotypic, identification of patients at risk for disease transformation  and creation of interventions to disrupt the myeloproliferative pathology and restore hematopoietic homeostasis.,   Gene-expression profiling is likely to be the most productive approach for defining risk and targeting therapy. This work helps move us along that path.

Combine this graphic template of genomic classifications and outcomes together with CRISPR technology and CAR-T and related immunotherapies and the phenomenal results already achieved in related hematologic pathologies and we can get some idea of the bright future ahead for MPN diagnosis, risk stratification and treatment.

What’s keeping us from moving ahead?

The genomic characterization of patients with myeloproliferative neoplasms offers the potential for personalized diagnosis, risk stratification, and treatment. This potential has failed to be realized in the past.   Most MPN patients are cared for by non-specialists.  At this stage of common medical practice we have not come close to realizing that potential because virtually no MPN patients have mutational or karyotype analyses done and their physicians generally rely on clinical results, traditional biomarkers and the very few mostly palliative therapeutic options based on cytoreduction and reduction of vascular risk currently available and hematopoietic stem cell transplant as a last option.

This focus on treating the symptoms of disease and not the underlying sources of proliferation has resulted in successful patient management in long-term chronic manifestations of MPNs but dramatic failure upon transformation to more acute forms of late state myelofibrosis and acute myeloid leukemia.

Now that we have an expanded roadmap and clear directions to fill in the missing pieces, now that we have genetic sequencing commonly available even in hand held units, the “Classifications” may help usher in a new era of precision genomic medicine driving MPN diagnosis and treatment.

Take me back to the Contents

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