UCLA researchers in the Department of Pulmonology have identified a novel non-invasive combinatorial biomarker for prediction, early detection, and monitoring of acute and chronic allograft injury.
BACKGROUND: Post-surgery treatment and rejection surveillance for solid organ transplantation remains challenging, primarily due to a limited ability to accurately assess and control patient immune responses. After the allograft transplantation, patients require a carefully monitored regiment of immunosuppression medications to avoid post-surgery complications which can lead to acute rejection (AR) and injury of the transplanted organ. Even with recent advances in the field of transplant medicine, finding a balanced treatment plan to avoid under-immunosuppression which can leading to AR, or over-immunosuppression which can result in infection or medication toxicity, poses a challenge. If improperly treated, AR and acute organ injuries can develop into more serious chronic conditions such as Chronic Lung Allograft Dysfunction (CLAD) or Cardiac Allograft Vasculopathy (CAV) that are notably harder to treat. The current standard of care to predict immune response and assess post-surgery immune status for most organ transplantation patients involves costly and highly invasive biopsies which are limited by low sensitivity and diagnostic accuracy.
One recently proposed biomarker for allograft injury is donor-derived cell-free DNA (dd-cfDNA). Natural cell turnover of human tissues results in continuously released fragmented, cell-free DNA (cf-DNA) into the bloodstream. Tracking the ratio of transplant recipient cf-DNA and dd-cfDNA released from the allograft in blood samples provides a potential tool for early AR detection. Current high-resolution sequencing and genotyping technologies to easily and affordably quantify dd-cfDNA from non-invasively obtained blood samples make dd-cfDNA an attractive biomarker. However, the wide-scale use of dd-cfDNA is largely hampered by low sensitivity, high false positive rates, and poor diagnostic capability. Thus, there is a pressing need for a reliable noninvasive biomarker for allograft injury that can accurately assess patient immune function after transplantation and detect early signs of allograft injury.
INNOVATION: Researchers at UCLA led by Dr. Michael Shino have developed a method for non-invasively monitoring overall immune function and status for organ transplant patients. This novel method utilizes both dd-cfDNA and specific cytokine levels within post-transplant individuals as a highly accurate combinatorial biomarker for allograft injury. Utilizing high-resolution genotyping and cytokine detection technologies like ELISAs, this method quantifies dd-cfDNA and cytokine levels from blood, bronchoalveolar lavage (BAL), and urine samples. Final analysis and comparison of these levels provides an accurate diagnostic threshold that can be used to predict if a patient is likely to develop an allograft injury and monitor post-transplant patients with chronic allograft injuries.
POTENTIAL APPLICATIONS:
- Accurate and reliable risk prediction of transplant recipients for acute rejection (AR)
- Early detection of ongoing allograft injury and chronic rejection
ADVANTAGES:
- Improved accuracy of post-transplant immune status monitoring
- Decreased patient costs for post-transplant surveillance
- Early detection of AR prior to development of chronic allograft dysfunction
- Minimally invasive method for obtaining samples needed for allograft surveillance
- Allows for customized immunosuppression medication regimens based on patient AR risk
DEVELOPMENT-TO-DATE: The researchers have confirmed the accuracy of their method by collecting samples from 125 lung transplant recipients and successfully stratifying them based on their risk in developing CLAD. They also demonstrated that individually, dd-cfDNA and cytokine levels were insufficient as reliable biomarkers.
Keywords: Allograft rejection, Organ transplantation, biopsy, screening, CLAD, immunosuppression, biomarker, acute cellular rejection, cell-free DNA, cytokine, diagnostics, autoimmune and inflammation, screening