Table 4.
Plasma Biomarkers for Acute GVHD
| Name | Study | (n) | Associations/Timepoints in aGVHD (D0 = HCT date) | Framework steps completed | Potential clinical implementation | Ref |
|---|---|---|---|---|---|---|
| Diagnostic Biomarkers: Systemic | ||||||
| Biomarker panel: IL-2-R-α, HGF, IL-8, TNFR-1 | Paczesny 2009 | 424 | Identified GVHD at onset of symptoms | Step 1: Discovery Step 2: 2 cohorts |
• Improve diagnostic accuracy • Differentiate GVHD vs other complications |
9 |
| Diagnostic Biomarkers: Organ specific | ||||||
| REG3α | Ferrara 2011 | 1014 | Increased levels at onset of symptoms in GI-GVHD | Step 1: Discovery Step 2: 2 cohorts |
• Improve diagnostic accuracy in specific organs (ie colitis/dermatitis vs GI/skin GVHD) | 11 |
| TIM3 | Hansen 2013 | 149 | Increased levels associated with GI-GVHD | Step 1: Discovery Step 2: 2 cohorts |
13 | |
| Elafin | Paczesny 2010 | 492 | Increased levels at onset of skin GVHD | Step 1: Discovery | 15 | |
| Solán 2021 | 149 | Increased levels in skin GVHD | Step 1: Previous discovery | 16 | ||
| Predictive Biomarkers | ||||||
| ST2 | Vander Lugt 2013 | 673 | Increased levels at onset of treatment with corticosteroids associated with SR-aGVHD | Step 1: Discovery Step 2: 3 cohorts |
• Intensify for high risk group • Reduce immunosuppression for low/standard risk group |
19 |
| Response Biomarkers | ||||||
| ST2, TIM3 | McDonald 2017 | 165 | Increased levels after 14d of steroids predicts treatment failure | Step 1: Hypothesis | • Monitoring treatment response • Guide GVHD management • Future: Clinical efficacy endpoint |
23 |
| Prognostic Biomarkers | ||||||
| REG3α | Ferrara 2011 | 1014 | Increased levels at diagnosis associated with NRM | Step 1: Discovery Step 2: 2 cohorts |
• Anticipate course of disease • Adjust immunosuppression |
11 |
| Rowan 2020 | 415 | Increased levels D+7, D+14 and D+21 associated with NRM | Step 1: Previous discovery Step 2: Multi-center cohorts |
25 | ||
| ST2 | Vander Lugt 2013 | 673 | Increased levels D+14 associated with NRM | Step 1: Discovery Step 2: 3 cohorts |
19 | |
| Ponce 2015 | 113 | Increased levels D+28 associated with TRM in CBT | Step 1: Previous discovery | 27 | ||
| Abu Zaid 2017 | 211 | Increased levels D+28 associated with NRM | Step 1: Previous discovery Step 2: Clinical trial cohorts |
26 | ||
| Kanakry 2017 | 58 | Increased levels D+30 associated with NRM in haplo PTCy | Step 1: Previous discovery | 28 | ||
| Rowan 2020 | 415 | Increased levels D+7, D+14 and D+21 associated with NRM | Step 1: Previous discovery Step 2: Multi-center cohorts |
25 | ||
| Biomarker Algorithm | Levine 2015 | 792 | Score based on ST2 + Reg3a (+TNFR1) at GVHD categorizes into groups for NRM | Step 1: Previous discovery Step 2: 3 cohorts |
21 | |
| Hartwell 2017 | 1287 | Score based on ST2 + Reg3a D+7 categorizes into groups for NRM | Step 1: Previous discovery Step 2: multi-center cohorts |
30 | ||
| Hotta 2021 | 112 | Score based on ST2 + Reg3a D+7 categorizes into groups for NRM | Step 1: Previous discovery Step 2: Multi-center cohorts |
31 | ||
| Major-Monfried 2018 | 507 | Score based on ST2 + Reg3a after 7d of steroids categorizes into groups for NRM in SR-aGVHD | Step 1: Previous discovery Step 2: 2 cohorts |
32 | ||
| Srinagesh 2019 | 615 | Score based on ST2 + Reg3a after 28d of steroids categorizes into groups for NRM | Step 1: Previous discovery | 33 | ||
| TIM3 | Abu Zaid 2017 | 211 | Increased levels D+28 associated with NRM | Step 1: Previous discovery Step 2: Clinical trial cohorts |
26 | |
| Risk Biomarkers | ||||||
| No validated aGVHD risk biomarker exists | • Implement preemptive strategies | |||||
NRM, nonrelapse mortality, aGVHD, acute graft versus host disease, TRM, transplant related mortality, CBT, cord blood transplant, SR, steroid refractory, Haplo, haploidentical, PT Cy, post-transplant cyclophosphamide