Studies by the founding scientists of Transplant Genomics Inc. (TGI) to be presented this week at the World Transplant Congress (WTC) are helping lay the groundwork for the company's development of genomic biomarkers for transplant graft status. The studies are reflective of the pipeline of clinical tests TGI will be commercializing as part of a surveillance program to detect and respond to early signs of graft injury to improve management of organ transplant recipients, with the potential to extend lives and reduce costs of associated healthcare. TGI's first test will be a blood test used to routinely monitor kidney transplant recipients, indicating when treatment or biopsy is required.
"These studies have demonstrated the feasibility of our approach to provide rich and objective diagnostic information," commented Stan Rose, PhD, President & CEO of Transplant Genomics and a kidney transplant recipient himself. "In the studies, peripheral blood gene expression profiling demonstrated excellent potential as a noninvasive monitoring tool that could enable differential diagnosis of graft status in kidney and liver transplant recipients. The studies also indicate that molecular profiling of tissue offers the potential to help clarify ambiguous histological results."
Early Detection Can Make a Difference
An ongoing challenge in transplant treatment is subclinical acute kidney rejection (SCAR), defined as histologic rejection even though the patient's serum creatinine readings -a measure of kidney function- are normal. SCAR is associated with worse long-term graft survival.
In Molecular Signature in the Peripheral Blood for Sub-clinical Acute Kidney Rejection,1 to be presented by John Friedewald and colleagues on Wednesday, July 30, 2014, the researchers showed that peripheral blood gene expression profiling can correctly classify kidney transplant patients with subclinical acute rejection, acute rejection and transplant excellence.
"Peripheral blood gene expression profiling potentially provides a viable method for detecting SCAR as part of a regular surveillance program and for monitoring effectiveness of treatment," commented study author John Friedewald, MD, Associate Professor of Medicine and Surgery at Northwestern University's Feinberg School of Medicine and a transplant nephrologist at Northwestern Memorial Hospital and the Kovler Organ Transplant Center.
Gene Expression Profiling Can Be Powerful Molecular Classifier
Molecular Phenotyping of Kidney Biopsies by Global Gene Expression Tightly Correlates with Histology Phenotypes and Long-term Outcomes,2 presented by Sunil Kurian and colleagues on Sunday, July 27, 2014, compared gene expression profiling data from biopsy tissue against biopsy results in 292 patients. The authors showed that gene expression profiling has a predictive accuracy of 90 - 94% for acute rejection, acute dysfunction no rejection, chronic allograft nephropathy and transplant excellence samples, when compared to histology-documented phenotypes.
Discovery of Peripheral Blood and Biopsy-Based Molecular Classifiers in Brazilian Kidney Transplant Patients,3 presented by Carlucci Ventura, Sunil Kurian and colleagues on Sunday, July 27, 2014, validated biopsy molecular phenotypes created with a US population in an independent cohort of significantly different racial/ethnic backgrounds. Predictive accuracies ranged from 87% to 94%. The researchers concluded that there are strong unifying immune mechanisms driving transplant disease and thus "international molecular diagnostics are feasible."
Gene Expression Profiling Can Distinguish Cause of Liver Rejection
Blood and Biopsy mRNA Expression Signatures Can Distinguish Major Causes of Graft Injury in Liver Transplant Recipients,4 to be presented by Josh Levitsky and colleagues on Thursday, July 31, 2014, demonstrated that genomic signatures of specific types of liver graft injuries can be identified from both blood and biopsy tissue. The signatures are able to distinguish acute rejection in liver transplant recipients from other major causes of graft injury, such as hepatitis C virus recurrence (HCV-R) and alternative causes (acute dysfunction no rejection/recurrence) with high predictive accuracy. These signatures have the potential to enhance the specificity of diagnosis, particularly in managing patients with contrasting etiologies (e.g., acute rejection vs. HCV-R), determining pathophysiological mechanisms and informing decisions to perform liver biopsies as well as immunosuppression minimization and withdrawal.