Beyond the Match: Where Transplant Immunology Has Been and Where We Must Go

The following article is an opinion piece written by Dr. David Lowe. The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position of Technology Networks.

For decades, human leukocyte antigen (HLA) typing has been a reliable tool for assessing compatibility between donors and recipients and remains the immunological foundation of transplant care. However, as the transplant field moves towards more personalized patient care, precision becomes a focal point. Transplant teams may benefit from tools that enable them to see the patient’s immunological profile beyond classical HLA type.

For clinicians and their labs, personalized care means finding the right donor or organ for the right patient. For the patients who are hardest to transplant, this may require HLA typing of the highest resolution and may necessitate the acquisition of this clinical information with shorter clinical timescales.

Classical HLA matching is the foundation, but what more should we consider?

Compatibility at the classical HLA loci (HLA-A,B,C,DR,DQ,DP) has been the central pillar of transplantation. These genes sit within the major histocompatibility complex (MHC) and enable patients’ immune systems to distinguish self from potentially dangerous foreign invaders. That’s why HLA typing has become the gold standard of transplant care—the closer the match, the lower the possibility that the graft is identified as harmful. However, full HLA matching does not guarantee a positive long-term transplant outcome.

This can often be seen in the stem cell transplant setting. A patient may be completely classically HLA matched to an unrelated donor, but there still remains a significant possibility of relapse or of developing graft-versus-host disease (GVHD) through different immune mechanisms. Emerging evidence in GVHD research points to other genes within the MHC impacting graft outcomes. These genes, which also display high degrees of polymorphism, have not previously been provided in routine testing algorithms. These findings highlight some of the missing pieces of the data story, pointing to the need for more expansive typing, not less.

From faster answers to continuous insight

One of the most important developments in solid organ transplant testing in recent years has been the development of virtual crossmatching. For years, confirming that a recipient could safely accept an organ relied on a physical crossmatch at the bench, with donor cells mixed with recipient serum, then incubated and read for a reaction.

Crossmatching is sensitive work and can take hours, but it is a crucial step in determining donor and recipient compatibility. With virtual crossmatching, where donor and recipient immunological data is analyzed in silico rather than at the bench, care teams can provide compatibility information more rapidly, supporting timely clinical decision-making alongside established clinical assessment. The key gain here is in reducing the time the organ is on ice awaiting implantation. This period, referred to as the cold ischemic time (CIT), is critical, and prolonged CIT is associated with poorer graft outcomes.

Beyond the patient experience, the adoption of virtual crossmatching can also confer logistical benefits. For centers that also provide trauma support, operating theatre space can often be required at short notice. Accelerating the compatibility assessment process via virtual crossmatching can provide opportunity to access the theatre earlier and reduce the risk of extended CIT if an acute trauma case needs to have priority theatre access.

Faster answers about transplant compatibility are only one part of the equation. The more valuable shift is the continuous insights that can be compiled after the transplant by using molecular tools and biomarkers to catch the early signs of graft dysfunction or rejection. Non-invasive testing is a promising shift here, where a urine sample can carry information about inflammation in a graft that once required a blood draw or a biopsy.

Low-burden monitoring also makes post-transplant care more accessible by enabling more regular testing despite a patient's distance from transplant centers. Patients often travel to a specialized center for transplants, then must travel back and forth for follow-up testing. This can make post-transplant care more difficult as gaps in follow-up monitoring can make early warning signs of graft failure go unnoticed, potentially leading to organ rejection or other serious complications. Non-invasive home testing, such as urinary assays, have the potential to give clinicians more real-time data to inform decisions throughout the transplant journey. 

Vitality of immunology for the hardest-to-treat patients

The clearest test of whether the transplant industry is delivering personalization is what happens to the patients who are hardest to treat. Women who are sensitized to HLA through pregnancy are increasingly difficult to transplant because their immune systems have potentially produced antibodies against a broad range of potential donors, often meaning they must wait longer for a transplant. Due to the increasing difficulty of matching these patients with donors, laboratory directors devote much of their effort to this population. 

If laboratory directors have a fuller, higher-resolution antibody picture of these patients’ immunological profiles, they may provide additional immunological information that clinicians can incorporate when evaluating complex transplant candidates.

Ongoing journey of immunology and transplant care

Personalization does not end at the match. For example, tailoring immunosuppression drug protocols to the individual, rather than starting everyone at a standard dose, rests on the ability to make data-driven decisions that are specific to each patient. With the right tools, laboratories can help care teams make more informed decisions throughout the transplant journey.

The transplant industry arguably tends to move more slowly than other fields when it comes to adopting new technologies or changing workflows. In fact, many of today’s protocols in practice aren’t far removed from those of two decades ago, even as underlying technology has become faster, cheaper, and more precise.

Though the change will take time, I am confident that we are moving in the right direction. Precise, personalized care will likely become possible from reading each patient's full immunological data story, both before the transplant and long after it. Acting on the full dataset, rather than the fraction we’ve historically had, will help to change transplant substantially. As technologies continue to develop, the transplant industry will learn a great deal more about what data points truly matter when determining the optimum transplant donor.

We are closer today to achieving personalized transplant care than we have ever been, but the work is far from over.