The value of high-resolution HLA in the perioperative period of non-sensitized lung transplant recipients

Using a combination of biomarkers to monitor allograft dysfunction in lung transplant recipients

Allograft dysfunction is a major limitation of survival in organ transplant recipients including those who have received lung transplantation. Early detection of allograft dysfunction is thus crucial to improve outcomes in these patients. However, there are several causes of allograft dysfunction with allograft infection and rejection being the two important causes. It is often difficult to distinguish between those causes as the presentation can be similar. Allograft rejection, especially antibody-mediated rejection (AMR) and chronic lung allograft dysfunction (CLAD) are often identified too late where progression has already occurred. Biomarkers like anti-HLA antibodies including donor-specific antibodies (DSA), donor-derived cell-free DNA (dd-cfDNA), immune cell function (ICF) assays and next-generation sequencing for microorganisms allow for early identification of allograft dysfunction as well as differentiate rejection from other processes such as infection. This in turn allows for early intervention and, ideally, improved long-term allograft outcomes. Greater evidence exists for these biomarkers in other solid organ transplantations including kidney and heart transplantation, but application to lung transplant recipients is increasing and seems equally promising. In this review, we evaluate existing evidence for using these biomarkers and share our center practice in utilizing a combination of these biomarkers post-transplantation to assess for allograft dysfunction.

Development and validation of primary graft dysfunction predictive algorithm for lung transplant candidates

BACKGROUND

Primary graft dysfunction (PGD) is the leading cause of early morbidity and mortality after lung transplantation. Accurate prediction of PGD risk could inform donor approaches and perioperative care planning. We sought to develop a clinically useful, generalizable PGD prediction model to aid in transplant decision-making.

METHODS

We derived a predictive model in a prospective cohort study of subjects from 2012 to 2018, followed by a single-center external validation. We used regularized (lasso) logistic regression to evaluate the predictive ability of clinically available PGD predictors and developed a user interface for clinical application. Using decision curve analysis, we quantified the net benefit of the model across a range of PGD risk thresholds and assessed model calibration and discrimination.

RESULTS

The PGD predictive model included distance from donor hospital to recipient transplant center, recipient age, predicted total lung capacity, lung allocation score (LAS), body mass index, pulmonary artery mean pressure, sex, and indication for transplant; donor age, sex, mechanism of death, and donor smoking status; and interaction terms for LAS and donor distance. The interface allows for real-time assessment of PGD risk for any donor/recipient combination. The model offers decision-making net benefit in the PGD risk range of 10% to 75% in the derivation centers and 2% to 10% in the validation cohort, a range incorporating the incidence in that cohort.

CONCLUSION

We developed a clinically useful PGD predictive algorithm across a range of PGD risk thresholds to support transplant decision-making, posttransplant care, and enrich samples for PGD treatment trials.

A Single-Center Analysis of How HLA Mismatch and Donor-Specific Antibodies Affect Short-Term Outcome After Lung Transplantation: A Pilot Study Before a Country-Wide Histocompatibility Study in Japan

BACKGROUND

Analyzing HLA polymorphism in lung transplantation (LTx) is important, given its impact on LTx recipient survival and graft function. Accordingly, we conducted a retrospective study to examine the influence of HLA mismatch and donor-specific antibodies (DSA) on short-term outcomes and early-phase post-LTx complications.

METHOD

HLA antigen or eplet mismatch in LTx patients at Tohoku University Hospital from 2018 to 2023 was determined, and DSA was measured on admission for surgery to identify preformed DSA and at weeks 4 to 12 post-LTx for de novo DSA, respectively.

RESULTS

The participants were 45 LTx recipients, HLA-A/B/DR antigen mismatch (5-6 of 6) being identified in 57%, HLA-A/B/Cw/DR/DQ mismatch (8-10 of 10) in 57%, and HLA eplet mismatch (>61) in 46%. The prevalence of preformed DSA was 24%, and persistence (uncleared) was 16%. The incidence of de novo DSA was 16% after LTx. During the study,16 recipients experienced grade 3 primary graft dysfunction (PGD), 8 developed acute rejection, and 5 died. No HLA-related variables were significantly associated with post-LTx mortality and were not risk factors for high-grade PGD or acute rejection.

CONCLUSION

Despite limitations in sample size, resulting in tentative findings, the study serves as a crucial pilot study for an ongoing multicenter prospective trial in Japan.

Donor and recipient risk factors for the development of primary graft dysfunction following lung transplantation

Primary Graft Dysfunction (PGD) is a major cause of both short-term and long-term morbidity and mortality following lung transplantation. Various donor, recipient, and technical risk factors have been previously identified as being associated with the development of PGD. Here, we present a comprehensive review of the current literature as it pertains to PGD following lung transplantation, as well as discussing current strategies to mitigate PGD and future directions. We will pay special attention to recent advances in lung transplantation such as ex-vivo lung perfusion, thoracoabdominal normothermic regional perfusion, and up-to-date literature published in the interim since the 2016 ISHLT consensus statement on PGD and the COVID-19 pandemic.

A Nomogram for Predicting Brain Metastasis in IIIA-N2 Non-Small Cell Lung Cancer After Complete Resection: A Competing Risk Analysis

Background

Brain metastasis (BM) is one of the most common failure patterns of pIIIA-N2 non-small cell lung cancer (NSCLC) after complete resection. Prophylactic cranial irradiation (PCI) can improve intracranial control but not overall survival. Thus, it is particularly important to identify the risk factors that are associated with BM and subsequently provide instructions for selecting patients who will optimally benefit from PCI.

Methods and Materials

Between 2011 and 2014, patients with pIIIA-N2 NSCLC who underwent complete resection in our institution were reviewed and enrolled in the study. Clinical characteristics, pathological parameters, treatment mode, BM time, and overall survival were analyzed. A nomogram was built based on the corresponding parameters by Fine and Gray’s competing risk analysis to predict the 1-, 3-, and 5-year probabilities of BM. Receiver operating characteristic curves and calibration curves were chosen for validation. A statistically significant difference was set as P <0.05.

Results

A total of 517 patients were enrolled in our retrospective study. The median follow-up time for surviving patients was 53.2 months (range, 0.50–123.17 months). The median age was 57 (range, 25–80) years. Of the 517 patients, 122 (23.6%) had squamous cell carcinoma, 391 (75.6%) received adjuvant chemotherapy, and 144 (27.3%) received post-operative radiotherapy. The 1-, 3-, and 5-year survival rates were 94.0, 72.9, and 66.0%, respectively. The 1-, 3-, and 5-year BM rates were 5.4, 15.7, and 22.2%, respectively. According to the univariate analysis, female, non-smokers, patients with non-squamous cell carcinoma, bronchial invasion, perineural invasion, and patients who received adjuvant chemotherapy were more likely to develop BM. In a multivariate analysis, non-squamous cell carcinoma (subdistribution hazard ratios, SHR: 3.968; 95% confidence interval, CI: 1.743–9.040; P = 0.0010), bronchial invasion (SHR: 2.039, 95% CI: 1.325–3.139; P = 0.0012), perineural invasion (SHR: 2.514, 95% CI: 1.058–5.976; P = 0.0370), and adjuvant chemotherapy (SHR: 2.821, 95% CI: 1.424–5.589; P = 0.0030) were independent risk factors for BM. A nomogram model was established based on the final multivariable analysis result. The area under the curve was 0.767 (95% CI, 0.758–0.777).

Conclusions

For patients with IIIA-N2 NSCLC after complete resection, a nomogram was established based on clinicopathological factors and treatment patterns for predicting the BM. Based on this nomogram, patients with a high risk of BM who may benefit from PCI can be screened.

Next-generation sequencing and clinical histocompatibility testing

Histocompatibility testing is essential for donor identification and risk assessment in solid organ and hematopoietic stem cell transplant. Additionally, it is useful for identifying donor specific alleles for monitoring donor specific antibodies in post-transplant patients. Next-generation sequence (NGS) based human leukocyte antigen (HLA) typing has improved many aspects of histocompatibility testing in hematopoietic stem cell and solid organ transplant. HLA disease association testing and research has also benefited from the advent of NGS technologies. In this review we discuss the current impact and future applications of NGS typing on clinical histocompatibility testing for transplant and non-transplant purposes.