Major barriers to chronic graft-versus-host disease (cGVHD) research are the inability to predict the likelihood
of response to cGVHD therapy and subsequent patient survival. This absence of predictive biomarkers is partly
due to the complex pathology of cGVHD, which involves both soluble and cellular factors but mostly due to the
paucity, so far, of samples collected when specific cGVHD treatments are initiated, particularly as novel and
more targeted treatments for cGVHD are now available. Thus, major questions remaining in the field are: Can
we target more than one cGVHD pathway with a single drug? Can we detect biomarkers to predict future
resistance to treatment using already validated cGVHD biomarkers? Can we discover more specific markers
through a high throughput proteomics pipeline? Can we validate and utilize these predictive biomarkers to
provide strong support for FDA approval of these biomarkers? For this project, we will use samples (plasma
and PBMCs) collected during Dr. Pavletic trial testing Pacritanib, a multi-kinase inhibitor with specificity for
JAK2 and IRAK1, in patients with steroid-refractory/steroid-dependent (SR/D) cGVHD to analyze proteomic
signatures associated with prediction of cGVHD therapy nonresponse, and with prognosis of nonrelapse
mortality (NRM). Proposed markers are based on previous studies and will include other novel or hypothesized
factors. We will test the hypothesis that plasma proteomic panels measured prior to the start of cGVHD
treatment with pacritinib (PAC) will stratify HCT patients for prediction of resistance, and NRM at 1 year. We
will determine the thresholds of different biomarkers and panels that provide best sensitivity and specificity.
Our overarching hypothesis addresses gaps remaining by addressing two specific aims (SA): SA1: Are five
previously identified plasma cGVHD biomarkers [chemokine (C-X-C motif) ligand 9 (CXCL9), CXCL10, matrix
metalloproteinase 3 (MMP3), Dickkopf-related protein 3 (DKK3), and Stimulation 2 (ST2; the interleukin (IL)-33
receptor)] predictive of resistance to PAC therapy? We will measure them using ELISA from fresh blood
samples collected during this award: ~35 samples pre-treatment and 3- and 6-months post-treatment. SA2:
Can additional plasma biomarkers that are key biologic drivers of cGVHD resistance be discovered through our
proteomics pipeline comparing responders vs. non responders? We will address this question using our well-
established proteomic workflow that can identify and quantify more than 2000 proteins. Upon completion, these
studies will result in biomarker panels that may facilitate prediction of response and resistance to therapy and
identify candidates for new therapeutic approaches.