Related Experiment Video
Updated: Apr 3, 2026
Measurement of T Cell Alloreactivity Using Imaging Flow Cytometry
Published on: April 19, 2017
A Computational Gene Expression Score for Predicting Immune Injury in Renal Allografts
Tara K Sigdel1, Oriol Bestard2, Tim Q Tran1
1Division of Transplant Surgery, Department of Surgery, University of California San Francisco, San Francisco, CA 94017, United States of America.
Background:
Whole genome microarray meta-analyses of 1030 kidney, heart, lung and liver allograft biopsies identified a common immune response module (CRM) of 11 genes that define acute rejection (AR) across different engrafted tissues. We evaluated if the CRM genes can provide a molecular microscope to quantify graft injury in acute rejection (AR) and predict risk of progressive interstitial fibrosis and tubular atrophy (IFTA) in histologically normal kidney biopsies.
Methods:
Computational modeling was done on tissue qPCR based gene expression measurements for the 11 CRM genes in 146 independent renal allografts from 122 unique patients with AR (n = 54) and no-AR (n = 92). 24 demographically matched patients with no-AR had 6 and 24 month paired protocol biopsies; all had histologically normal 6 month biopsies, and 12 had evidence of progressive IFTA (pIFTA) on their 24 month biopsies. Results were correlated with demographic, clinical and pathology variables.
Results:
The 11 gene qPCR based tissue CRM score (tCRM) was significantly increased in AR (5.68 ± 0.91) when compared to STA (1.29 ± 0.28; p < 0.001) and pIFTA (7.94 ± 2.278 versus 2.28 ± 0.66; p = 0.04), with greatest significance for CXCL9 and CXCL10 in AR (p <0.001) and CD6 (p<0.01), CXCL9 (p<0.05), and LCK (p<0.01) in pIFTA. tCRM was a significant independent correlate of biopsy confirmed AR (p < 0.001; AUC of 0.900; 95% CI = 0.705-903). Gene expression modeling of 6 month biopsies across 7/11 genes (CD6, INPP5D, ISG20, NKG7, PSMB9, RUNX3, and TAP1) significantly (p = 0.037) predicted the development of pIFTA at 24 months.
Conclusions:
Genome-wide tissue gene expression data mining has supported the development of a tCRM-qPCR based assay for evaluating graft immune inflammation. The tCRM score quantifies injury in AR and stratifies patients at increased risk of future pIFTA prior to any perturbation of graft function or histology.
Insights
A novel 11-gene immune response assay quantifies acute rejection (AR) and predicts future graft damage. This molecular tool assesses kidney transplant health early, identifying risks before clinical signs appear.
Area of Science:
- Transplant immunology
- Molecular diagnostics
- Genomics
Background:
- A common immune response module (CRM) of 11 genes was identified across various transplanted organs.
- This CRM is a potential biomarker for acute rejection (AR) in allografts.
Purpose of the Study:
- To evaluate the utility of CRM genes in quantifying graft injury during AR.
- To determine if CRM genes can predict progressive interstitial fibrosis and tubular atrophy (pIFTA) in kidney allografts with normal histology.
Main Methods:
- Gene expression of 11 CRM genes was measured using quantitative PCR (qPCR) in 146 renal allografts.
- Computational modeling analyzed gene expression data from patients with and without AR, and those who developed pIFTA.
- Results were correlated with clinical and pathological data.
Main Results:
- The 11-gene tissue CRM score (tCRM) was significantly elevated in AR compared to stable grafts and those with pIFTA.
- tCRM independently correlated with biopsy-confirmed AR (AUC 0.900).
- A 7-gene signature at 6 months predicted pIFTA development by 24 months (p=0.037).
Conclusions:
- A tCRM-qPCR assay effectively quantifies immune inflammation in kidney allografts.
- The tCRM score aids in evaluating graft injury and stratifying AR risk.
- This assay can identify patients at risk for future graft damage before functional or histological changes are apparent.
