... Allison F Scalora, MS2, Roy Sabo, PhD3, Gary Lee Simmons, DO2, Masoud Manjili, PhD4, William B Clark, MD, MS2, John M McCarty, MD2, Harold M Chung ...
Dynamical System Interactions between T Cells and Monocytes Shape Alloreactivity Following Stem Cell Transplantation Yeri Park, BS1, Charles E. Hall, MS2, Allison F Scalora, MS2, Roy Sabo, PhD3, Gary Lee Simmons, DO2, Masoud Manjili, PhD4, William B Clark, MD, MS2, John M McCarty, MD2, Harold M Chung, MD2, Catherine H Roberts, PhD2 and Amir A. Toor, MD2 (1) Virginia Commonwealth University School of Medicine, Richmond, VA, (2) Bone Marrow Transplant, VCU Massey Cancer Center, Richmond, VA, (3) Biostatistics, Virginia Commonwealth University, Richmond, VA, (4)Microbiology and Immunology, VCU Massey Cancer Center, Richmond, VA
Introduction
Methods
• The dynamical systems model of stem cell transplantation is based on the premise that clinical outcomes are determined by the integrated immune response to the cumulative genomic differences between transplant donors and recipient. • This immune response occurs as a logistic function of time and is modulated by the cumulative antigen array encountered by donor T cells and the intensity of immune suppression. • This implies that immune responses may be quantified, and can be regarded as a physical parameter. • A consequence of this dynamical system model of stem cell transplantation is that while the total antigenic burden in an individual cannot be determined, immune reconstitution may allow estimation of this unmeasured antigenic burden. This may be accomplished by studying the interaction of antigen presenting cell (monocyte) and T cell interactions as interdependent physical quantities, analogous to physical quantities such as mass and acceleration.
To quantitatively model donor T cell responses to recipient antigens, one may consider the donor‐derived T cell counts at various time points, and model the relative concentrations of various T cell subsets, as coordinates in an immune phase space. Phase space is a parameter‐ space representing all the possible values a variable such as cell counts may take. Relative changes in cell counts over time may be evaluated as displacement of the phase space coordinates, in other words vectors in the immune phase space (Figure 2).
Results
Dynamical Modeling of Immune Reconstitution post SCT 2D & 3D Vector Magnitudes & Angels y
d60/90
CD4+
d60/90
CD3+ /L
ν = √ x 2 + y2 tan θ = y /x tan -1= θ
ν
y
a = √ i2 + j2 +k2 z
i
a
k
CD8+
θ d0
x
x j
Monocytes/L
Monocytes
When available, the monocyte count and the calculated ddCD3, 4 & 8 values at day 60 & 90, were plotted as coordinates in two or three dimensions representing the immune phase space. The line connecting the origin (d0) with the intercept represented the vector magnitude and direction of immune reconstitution.
< 325 > 325 Total P value < 325 > 325 Total P value
Patients • After obtaining permission from the institutional review board at Virginia Commonwealth University, the medical records of 55 patients transplanted between 2009 and 2015 were reviewed retrospectively. • Fifty‐two patients were evaluable; 41 of the 51 patients were enrolled on a prospective randomized phase II clinical trial, approved by the (ClinicalTrials.gov Identifier: NCT00709592). • To be eligible, patients had to be ≤70 years of age, with recurrent or high‐risk hematological malignancy. • The patients were required to have a 7/8 or 8/8 locus matched related (MRD) or unrelated donor (URD), with high‐resolution typing performed for HLA‐A, B, C and DRB1. • Conditioning therapy was with rabbit‐anti‐thymocyte globulin (ATG), given from day –9 to –7 (ATG 7.5 mg/kg or ATG 5.1 mg/kg), followed by total body irradiation (TBI) to a total dose of 4.5 Gray (Toor et al, BBMT 2015). • Absolute monocyte counts (μL‐1) (AMC) measured as a part of routine clinical care of the patients following SCT were recorded. • Donor‐derived CD3+ T cell count (ddCD3) was calculated, at approximately 4, 8 & 12 weeks following SCT using the equation; ddCD3=Absolute CD3+ cell ct * (%donor T cell chimerism/100) • ddCD4 & ddCD8 counts were calculated similarly
52
Gender ‐Male
33
Age (median)
57 (40‐69)
Donor MRD
23
URD
29
Diagnosis MM
11
NHL
21
AML
5
MDS/MF
3
CLL/PLL
12
Prior auto transplant
Alive 8 23 31
Total 18 30 48
Remission 5 23 28
17 31 48
Acute GVHD
19 5.04 (1.56‐10.36)
ATG dose 7.5 mg/kg
13
5 mg/kg
39
3D Vector Magnitude
Alive
Deceased
288
25
7
32
FET P value
0.0015
300
45
Remission
Relapse
3
10
22
11
13 33
0.012 No GVHD 12 9 21
GVHD
17 31 48
46 NO GVHD
300
19
12
31
0.994
• 3D vector calculations discriminate between patients with different clinical outcomes, with both magnitude and angles being significantly different. • Different angles are consistent with a CD4+ T cell bias towards GVHD occurrence and lower relapse risk • 3D Vector magnitude was significant in Mono/ddCD3/NK cell interaction at day 90 Monocyte/ddCD4/ddCD8/day 90
N
MAGNITUDE
T test
ANGLE
T test
8
827
0.01
66
0.000008
Acute GVHD
N 7
MAGNITUDE 696
T test 0.08
ANGLE 18
15
606
0.09
17
0.01
0.04
17
0.001
Chronic GVHD
17
167
0.01
49
0.000027
Chronic GVHD
Cumulative GVHD
25
741
0.02
55
0.000634
Cumulative GVHD
22
625
No GVHD
21
433
No GVHD
20
423
Relapse
19
466
0.10
24
Relapse
19
422
Remission
23
605
26
705
23 0.000086
53
Immune Phase Space Plots
N
CD34 dose/KG (median)
Deceased 10 7 17 0.0324 Relapse 12 8 20 0.0051 Cumulative GVHD 5 22 27 0.0074
• 2D vector calculations discriminate between patients with different clinical outcomes, with both magnitude and angles being significantly different. • Different angles are consistent with a T cell bias towards GVHD occurrence and lower relapse risk • 2D Vector magnitude was significant in ddCD4/ddCD8 interactions at day 90 Monocyte/ddCD3/day 90
Remission
Demographics
3D vectors/Monocyte x ddCD4 x ddCD8/day 60
2D Vector/MonocytexddCD3/day 60 2D Vector Magnitude < 325 > 325 Total FET P value
• Immune phase space plots show regions of probability distributions for cumulative acute and chronic GVHD as well as relapse for day 60 and 90. • There is a reciprocal distribution between the two parameters studied. • Data points are intersection of the ddCD3 and monocyte count coordinates.
t test 0.01
7 0.07
6
0.0002
17
Conclusions • T cell and T cell subset interactions with monocytes may be studied as vectors in an immune phase space. • The magnitude and angles of these vectors plotted in the immune phase space at day 60 and 90 post transplant are associated with cumulative acute and chronic GVHD as well as relapse incidence. • This simple methodology of measuring immune reconstitution may serve as a guide to optimize immunosuppression intensity in allograft recipients. • Future studies in uniform groups of patients with similar disease and donor characteristics are needed to determine the general utility of immune phase space mapping of immune effector cell populations.
