Induced pluripotent stem cell modeling of malignant hematopoiesis

Exp Hematol. 2019 Mar:71:68-76. doi: 10.1016/j.exphem.2019.01.002. Epub 2019 Jan 16.


The ability to epigenetically reprogram differentiated somatic cells to pluripotency resulting in the discovery of induced pluripotent stem cells (iPSCs), has unlocked fundamental biologic insights into numerous genetic diseases. These insights have resulted from the key property of iPSCs to differentiate into all cell lineages in an unlimited manner while maintaining the genetic identity of the originating cell. iPSCs have been utilized to investigate both monogenic and complex genetic disorders spanning hereditary and acquired diseases. Recently, iPSCs have been utilized to model human cancer, with a specific focus on modeling conditions of malignant hematopoiesis. In addition to serving as a genetic disease model in cancer, iPSCs can also be used as a tool to address a key question in interrogating the interaction between the cancer epigenome-genome. Specifically, how does reprogramming the epigenome affect cancer phenotype and specifically malignant hematopoiesis? This review will address this question and highlight the state of the field in generating iPSCs from hematologic malignancies, key biologic insights that can be uniquely generated from cancer-derived iPSCs, and their clinical applications. Last, challenges to expanding the use of iPSC modeling in blood cancers will be discussed.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Biomarkers
  • Cell Differentiation
  • Cell Transformation, Neoplastic* / genetics
  • Cell Transformation, Neoplastic* / metabolism
  • Cellular Reprogramming
  • Chromosome Aberrations
  • Gene Editing
  • Hematologic Neoplasms / etiology*
  • Hematologic Neoplasms / metabolism*
  • Hematologic Neoplasms / pathology
  • Hematopoiesis*
  • Humans
  • Induced Pluripotent Stem Cells / cytology*
  • Induced Pluripotent Stem Cells / metabolism*
  • Models, Biological*


  • Biomarkers