Mathematical modeling of erythrocyte chimerism informs genetic intervention strategies for sickle cell disease.
Recent advances in gene therapy and genome-engineering technologies offer the opportunity to correct sickle cell disease (SCD), a heritable disorder caused by a point mutation in the β-globin gene. The developmental switch from fetal γ-globin to adult β-globin is governed in part by the transcription factor (TF) BCL11A. This TF has been proposed as a therapeutic target for reactivation of γ-globin and concomitant reduction of β-sickle globin. In this and other approaches, genetic alteration of a portion of the hematopoietic stem cell (HSC) compartment leads to a mixture of sickling and corrected red blood cells (RBCs) in periphery. To reverse the sickling phenotype, a certain proportion of corrected RBCs is necessary; the degree of HSC alteration required to achieve a desired fraction of corrected RBCs remains unknown. To address this issue, we developed a mathematical model describing aging and survival of sickle-susceptible and normal RBCs; the former can have a selective survival advantage leading to their overrepresentation. We identified the level of bone marrow chimerism required for successful stem cell-based gene therapies in SCD. Our findings were further informed using an experimental mouse model, where we transplanted mixtures of Berkeley SCD and normal murine bone marrow cells to establish chimeric grafts in murine hosts. Our integrative theoretical and experimental approach identifies the target frequency of HSC alterations required for effective treatment of sickling syndromes in humans. Our work replaces episodic observations of such target frequencies with a mathematical modeling framework that covers a large and continuous spectrum of chimerism conditions. Am. J. Hematol. 91:931-937, 2016. © 2016 Wiley Periodicals, Inc.
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachuetts.|Program for Evolutionary Dynamics, Harvard University, Cambridge, Massachuetts.
Philipp M
PM
Altrock
Division of Hematology/Oncology, Boston Children's Hospital and Harvard Medical School, Boston, Massachuetts.
Christian
C
Brendel
Division of Hematology/Oncology, Boston Children's Hospital and Harvard Medical School, Boston, Massachuetts.|Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachuetts.
Raffaele
R
Renella
Division of Hematology/Oncology, Boston Children's Hospital and Harvard Medical School, Boston, Massachuetts.|Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachuetts.|Howard Hughes Medical Institute, Cambridge, Massachuetts.|Harvard Stem Cell Institute, Harvard University, Cambridge, Massachuetts.
Stuart H
SH
Orkin
Division of Hematology/Oncology, Boston Children's Hospital and Harvard Medical School, Boston, Massachuetts.|Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, Massachuetts.|Harvard Stem Cell Institute, Harvard University, Cambridge, Massachuetts.
David A
DA
Williams
Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts.|Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachuetts.
Franziska
F
Michor
D000755:Anemia, Sickle Cell / Q000628:therapy*; D000818:Animals; D001853:Bone Marrow / Q000473:pathology; D002470:Cell Survival; D017690:Cell Transplantation; D016922:Cellular Senescence; D046528:Chimerism; D004912:Erythrocytes; D015316:Genetic Therapy / Q000379:methods*; D006412:Hematopoietic Stem Cells / Q000166:cytology; D006801:Humans; D051379:Mice; D008962:Models, Theoretical