TRaCS, computational algorithm to determine tissue specific alloreactive putative peptide minor histocompatibility antigens (pmHA).

<p>Whole exome sequencing of cryopreserved donor and recipient DNA was performed, with an average coverage of 90x. The variable <b><i>n</i></b> refers to the number of nsSNP_GVH and <b><i>m</i></b> to pmHA. The variable <b><i>m</i></b> along with protein tissue expression level was then analyzed in MATLAB to determine T cell responses.</p

Cox proportional hazards model for cumulative GVHD (N = 47 of 73 evaluable) association with simulated organ specific T cell counts.

<p>Cox proportional hazards model for cumulative GVHD (N = 47 of 73 evaluable) association with simulated organ specific T cell counts.</p

Effect of alloreactivity operator on T cell vector .

<p>Successive iterations (<i>t</i>, <i>t+1 etc</i>.) modify the vector to . In this simplified model, <i>mHA</i>_<i>x</i><i>-HLA</i> only binds <i>TC</i>_<i>x</i> and so on. Matrix below represents a single iteration <i>t</i>.</p

Exome sequencing and peptide results by donor type (n = 77).

<p>Exome sequencing and peptide results by donor type (n = 77).</p

Cox proportional hazards model for cumulative grade 2–4 acute and moderate to severe chronic GVHD (N = 39 of 73 evaluable) association with simulated organ specific T cell counts (expressed in 1000’s).

<p>Cox proportional hazards model for cumulative grade 2–4 acute and moderate to severe chronic GVHD (N = 39 of 73 evaluable) association with simulated organ specific T cell counts (expressed in 1000’s).</p

Matrix illustrating the relative effect of antigen binding affinity on the T cell clonal interaction between different clones.

<p>Successive cells in each row of the matrix calculate the effect of <i>TC</i>_<i>i</i> on T cell being studied, <i>TC</i>_<i>x</i>. This generates a weighting factor, α, which modulates the impact of population of <i>TC</i>_<i>i</i> on the growth of <i>TC</i>_<i>x</i>.</p

Modeling the effect of Treg on effector T cell growth.

<p>Modeling the effect of Treg on effector T cell growth, red curve, <i>r</i> reduced at 21st iteration from -1 to -0.25; T cell population drops but then recovers slowly. In the blue curve <i>r</i> reduced at 25th iteration from -1 to +0.25 with direction reversal (from–to +), signifying anti-inflammatory cytokine effect supersedes pro-inflammatory cytokine effect.</p

T cell clonal growth in SCT simulations.

<p>A. Individual T cell clone growth simulations accounting for peptide-HLA complex binding affinity and protein of origin tissue expression (IC50/RPKM). Increased T cell frequency (Y-axis) seen if the protein is expressed at a higher level. Different <i>pmHA</i> from a single patient/organ. B. Variable growth pattern of the number of clones in the simulations, number of clones rising over ‘time’ (iterations); T cell clonal growth in response to colonic alloreactive peptides depicted. C. Number of T cell clones after 500 iterations, reflecting the number of high affinity peptides expressed in the tissues studied (GTEX). A non-significant trend towards a larger number of clones in MUD recipients is observed in this graph.</p