Systematic Prediction of Minor Histocompatibility Antigens to Inform GvHD Outcomes after Allogeneic Stem Cell Transplantation

T cell alloreactivity against minor histocompatibility antigens (mHAgs), polymorphic peptides resulting from donor-recipient (D-R) disparity at sites of genetic polymorphisms (SNPs, indels, frameshifts), is at the core of the therapeutic effect of allogeneic hematopoietic stem cell transplantation (allo-HSCT). Despite the crucial role of mHAgs in graft-versus-leukemia and graft-versus-host (GvHD) reactions, it has not been possible thus far to consistently link patient-specific mHAg repertoires to clinical outcomes. As a result, only D-R HLA matching and the activity of GvHD prophylaxis strategies are currently available to help clinicians in this challenge.

We hypothesized that post-transplant outcomes could be impacted by genome-wide mHAg load, delineated in an organ- and malignancy-specific fashion. We have therefore devised an analytic framework to systematically identify autosomal and Y-encoded mHAgs, based on the integration of polymorphism detection by whole-exome sequencing (WES) of germline DNA from D-R pairs together with organ-specific transcriptional- and proteome-level expression together with HLA class I epitope prediction. A critical component of the pipeline was building a reliable expression atlas for acute or chronic GvHD-targeted tissues. To capture less frequent but biologically relevant cell types consistently underestimated in bulk RNA expression profiles, we evaluated multiple external single-cell datasets of healthy human skin, liver, lung, GI, oral mucosa, and lacrimal gland. For each tissue, we merged the corresponding single-cell data sets and then clustered and annotated tissue-resident cell types, for which specific expressed genes were then identified, totaling 13,512 genes expressed in ≥1 GvHD target tissue.

To determine how mHAg load related to GvHD risk, we applied our mHAg pipeline to paired WES (≥85% target base coverage at ≥20x depth) generated from 220 D-R pairs treated with a matched-related donor allo-HSCT for AML/MDS. We considered the impact of diagnosis, prognostic risk score, status at transplant, conditioning regimen, and graft source against median mHAg load on risk for acute and chronic GvHD. Across these patients, only total autosomal mHAg load > median was associated with increased risk of developing grade II-IV aGvHD (HR = 2.54, 95% confidence interval: 1.03 - 6.26, p = 0.043). While the total autosomal mHAg load was not associated with development of cGvHD, subgroup analysis of 55 FàM transplants revealed that a combined score of autosomal and Y-encoded mHAgs > median was associated with development of NIH moderate/severe cGvHD (p = 0.042).

We next asked whether organ-specific mHAg load could predict the risk for organ-restricted acute or chronic GvHD. By evaluating organ-specific GvHD occurrence across deciles of mHAg load, we identified 2 distinct patterns of association. In the case of lung cGvHD, all 14 positive cases occurred in patients with a lung-specific autosomal mHAg load > median. By logistic regression modelling, lung mHAg load > median was the sole factor associated with increased risk of lung cGvHD (OR = 17.22, 95% CI: 3.18 - 321.63, p = 0.008). In contrast, for aGvHD of the liver, we observed an opposite pattern, with 12 of 13 affected patients having a liver mHAg load < median. We hypothesized that a limited set of immunodominant liver mHAgs might drive the clinical manifestations in these patients. By analyzing the mHAg landscape of patients affected by liver aGvHD, we observed an enriched representation of 7 polymorphisms in genes with preferential expression in liver. Notably, these SNPs were less frequent in patients developing aGvHD without liver involvement (p = 0.002) and co-occurred at a lower frequency in patients experiencing liver cGvHD (p = 0.0002). For one patient experiencing liver aGvHD, we could trace ex vivo T cells specific for 1 (of the 3 predicted) driver liver mHAgs.

Overall, our findings indicate that molecular characterization of D-R pairs to define GvHD risk could facilitate the design of personalized post-HSCT treatments to minimize this highly morbid condition, including incorporation of additional immunosuppressive therapies, introduced early for high-risk patients, or reduced-intensity approaches in low-risk settings. This is particularly valuable for lung GvHD, which is associated with the highest morbidity and mortality.