Molecular phenotyping of rejection-related changes in mucosal biopsies from lung transplants

Precision diagnostics in transplanted organs using microarray-assessed gene expression: concepts and technical methods of the Molecular Microscope® Diagnostic System (MMDx)

There is a major unmet need for improved accuracy and precision in the assessment of transplant rejection and tissue injury. Diagnoses relying on histologic and visual assessments demonstrate significant variation between expert observers (as represented by low kappa values) and have limited ability to assess many biological processes that produce little histologic changes, for example, acute injury. Consensus rules and guidelines for histologic diagnosis are useful but may have errors. Risks of over- or under-treatment can be serious: many therapies for transplant rejection or primary diseases are expensive and carry risk for significant adverse effects. Improved diagnostic methods could alleviate healthcare costs by reducing treatment errors, increase treatment efficacy, and serve as useful endpoints for clinical trials of new agents that can improve outcomes. Molecular diagnostic assessments using microarrays combined with machine learning algorithms for interpretation have shown promise for increasing diagnostic precision via probabilistic assessments, recalibrating standard of care diagnostic methods, clarifying ambiguous cases, and identifying potentially missed cases of rejection. This review describes the development and application of the Molecular Microscope® Diagnostic System (MMDx), and discusses the history and reasoning behind many common methods, statistical practices, and computational decisions employed to ensure that MMDx scores are as accurate and precise as possible. MMDx provides insights on disease processes and highly reproducible results from a comparatively small amount of tissue and constitutes a general approach that is useful in many areas of medicine, including kidney, heart, lung, and liver transplants, with the possibility of extrapolating lessons for understanding native organ disease states.

The 2022 Banff Meeting Lung Report

The Lung Session of the 2022 16th Banff Foundation for Allograft Pathology Conference-held in Banff, Alberta-focused on non-rejection lung allograft pathology and novel technologies for the detection of allograft injury. A multidisciplinary panel reviewed the state-of-the-art of current histopathologic entities, serologic studies, and molecular practices, as well as novel applications of digital pathology with artificial intelligence, gene expression analysis, and quantitative image analysis of chest computerized tomography. Current states of need as well as prospective integration of the aforementioned tools and technologies for complete assessment of allograft injury and its impact on lung transplant outcomes were discussed. Key conclusions from the discussion were: (1) recognition of limitations in current standard of care assessment of lung allograft dysfunction; (2) agreement on the need for a consensus regarding the standardized approach to the collection and assessment of pathologic data, inclusive of all lesions associated with graft outcome (eg, non-rejection pathology); and (3) optimism regarding promising novel diagnostic modalities, especially minimally invasive, which should be integrated into large, prospective multicenter studies to further evaluate their utility in clinical practice for directing personalized therapies to improve graft outcomes.

Defining a natural killer cell-enriched molecular rejection-like state in lung transplant transbronchial biopsies

In lung transplantation, antibody-mediated rejection (AMR) diagnosed using the International Society for Heart and Lung Transplantation criteria is uncommon compared with other organs, and previous studies failed to find molecular AMR (ABMR) in lung biopsies. However, understanding of ABMR has changed with the recognition that ABMR in kidney transplants is often donor-specific antibody (DSA)-negative and associated with natural killer (NK) cell transcripts. We therefore searched for a similar molecular ABMR-like state in transbronchial biopsies using gene expression microarray results from the INTERLUNG study (#NCT02812290). After optimizing rejection-selective transcript sets in a training set (N = 488), the resulting algorithms separated an NK cell-enriched molecular rejection-like state (NKRL) from T cell-mediated rejection (TCMR)/Mixed in a test set (N = 488). Applying this approach to all 896 transbronchial biopsies distinguished 3 groups: no rejection, TCMR/Mixed, and NKRL. Like TCMR/Mixed, NKRL had increased expression of all-rejection transcripts, but NKRL had increased expression of NK cell transcripts, whereas TCMR/Mixed had increased effector T cell and activated macrophage transcripts. NKRL was usually DSA-negative and not recognized as AMR clinically. TCMR/Mixed was associated with chronic lung allograft dysfunction, reduced one-second forced expiratory volume at the time of biopsy, and short-term graft failure, but NKRL was not. Thus, some lung transplants manifest a molecular state similar to DSA-negative ABMR in kidney and heart transplants, but its clinical significance must be established.

Application possibilities of artificial intelligence in facial vascularized composite allotransplantation-a narrative review

Facial vascularized composite allotransplantation (FVCA) is an emerging field of reconstructive surgery that represents a dogmatic shift in the surgical treatment of patients with severe facial disfigurements. While conventional reconstructive strategies were previously considered the goldstandard for patients with devastating facial trauma, FVCA has demonstrated promising short- and long-term outcomes. Yet, there remain several obstacles that complicate the integration of FVCA procedures into the standard workflow for facial trauma patients. Artificial intelligence (AI) has been shown to provide targeted and resource-effective solutions for persisting clinical challenges in various specialties. However, there is a paucity of studies elucidating the combination of FVCA and AI to overcome such hurdles. Here, we delineate the application possibilities of AI in the field of FVCA and discuss the use of AI technology for FVCA outcome simulation, diagnosis and prediction of rejection episodes, and malignancy screening. This line of research may serve as a fundament for future studies linking these two revolutionary biotechnologies.

Intra-subject variability in oscillometry correlates with acute rejection and CLAD post-lung transplant

Background

Chronic lung allograft dysfunction (CLAD) is the major cause of death post-lung transplantation, with acute cellular rejection (ACR) being the biggest contributing risk factor. Although patients are routinely monitored with spirometry, FEV₁ is stable or improving in most ACR episodes. In contrast, oscillometry is highly sensitive to respiratory mechanics and shown to track graft injury associated with ACR and its improvement following treatment. We hypothesize that intra-subject variability in oscillometry measurements correlates with ACR and risk of CLAD.

Methods

Of 289 bilateral lung recipients enrolled for oscillometry prior to laboratory-based spirometry between December 2017 and March 2020, 230 had ≥ 3 months and 175 had ≥ 6 months of follow-up. While 37 patients developed CLAD, only 29 had oscillometry at time of CLAD onset and were included for analysis. These 29 CLAD patients were time-matched with 129 CLAD-free recipients. We performed multivariable regression to investigate the associations between variance in spirometry/oscillometry and the A-score, a cumulative index of ACR, as our predictor of primary interest. Conditional logistic regression models were built to investigate associations with CLAD.

Results

Multivariable regression showed that the A-score was positively associated with the variance in oscillometry measurements. Conditional logistic regression models revealed that higher variance in the oscillometry metrics of ventilatory inhomogeneity, X5, AX, and R5-19, was independently associated with increased risk of CLAD (p < 0.05); no association was found for variance in %predicted FEV₁.

Conclusion

Oscillometry tracks graft injury and recovery post-transplant. Monitoring with oscillometry could facilitate earlier identification of graft injury, prompting investigation to identify treatable causes and decrease the risk of CLAD.

Multi-omic molecular profiling and network biology for precision anaesthesiology: a narrative review

Technological advancement, data democratisation, and decreasing costs have led to a revolution in molecular biology in which the entire set of DNA, RNA, proteins, and various other molecules - the 'multi-omic' profile - can be measured in humans. Sequencing 1 million bases of human DNA now costs US$0.01, and emerging technologies soon promise to reduce the cost of sequencing the whole genome to US$100. These trends have made it feasible to sample the multi-omic profile of millions of people, much of which is publicly available for medical research. Can anaesthesiologists use these data to improve patient care? This narrative review brings together a rapidly growing literature in multi-omic profiling across numerous fields that points to the future of precision anaesthesiology. Here, we discuss how DNA, RNA, proteins, and other molecules interact in molecular networks that can be used for preoperative risk stratification, intraoperative optimisation, and postoperative monitoring. This literature provides evidence for four fundamental insights: (1) Clinically similar patients have different molecular profiles and, as a consequence, different outcomes. (2) Vast, publicly available, and rapidly growing molecular datasets have been generated in chronic disease patients and can be repurposed to estimate perioperative risk. (3) Multi-omic networks are altered in the perioperative period and influence postoperative outcomes. (4) Multi-omic networks can serve as empirical, molecular measurements of a successful postoperative course. With this burgeoning universe of molecular data, the anaesthesiologist-of-the-future will tailor their clinical management to an individual's multi-omic profile to optimise postoperative outcomes and long-term health.

Interventional pulmonology techniques in lung transplantation

Lung transplantation is a key therapeutic option for several end-stage lung diseases. Interventional pulmonology techniques, mostly bronchoscopy, play a key role throughout the whole path of lung transplantation, from donor evaluation to diagnosis and management of post-transplant complications. We carried out a non-systematic, narrative literature review aimed at describing the main indications, contraindications, performance characteristics and safety profile of interventional pulmonology techniques in the context of lung transplantation. We highlighted the role of bronchoscopy during donor evaluation and described the debated role of surveillance bronchoscopy (with bronchoalveolar lavage and transbronchial biopsy) to detect early rejection, infections and airways complications. The conventional (transbronchial forceps biopsy) and the new techniques (i.e. cryobiopsy, biopsy molecular assessment, probe-based confocal laser endomicroscopy) can detect and grade rejection. Several endoscopic techniques (e.g. balloon dilations, stent placement, ablative techniques) are employed in the management of airways complications (ischemia and necrosis, dehiscence, stenosis and malacia). First line pleural interventions (i.e. thoracentesis, chest tube insertion, indwelling pleural catheters) may be useful in the context of early and late pleural complications occurring after lung transplantation. High quality studies are advocated to define endoscopic standard protocols and thus help improving long-term prognostic outcomes of lung transplant recipients.

The molecular features of chronic lung allograft dysfunction in lung transplant airway mucosa

BACKGROUND

Many lung transplants fail due to chronic lung allograft dysfunction (CLAD). We recently showed that transbronchial biopsies (TBBs) from CLAD patients manifest severe parenchymal injury and dedifferentiation, distinct from time-dependent changes. The present study explored time-selective and CLAD-selective transcripts in mucosal biopsies from the third bronchial bifurcation (3BMBs), compared to those in TBBs.

METHODS

We used genome-wide microarray measurements in 324 3BMBs to identify CLAD-selective changes as well as time-dependent changes and develop a CLAD classifier. CLAD-selective transcripts were identified with linear models for microarray data (limma) and were used to build an ensemble of 12 classifiers to predict CLAD. Hazard models and random forests were then used to predict the risk of graft loss using the CLAD classifier, transcript sets associated with rejection, injury, and time.

RESULTS

T cell-mediated rejection and donor-specific antibody were increased in CLAD 3BMBs but most had no rejection. Like TBBs, 3BMBs showed a time-dependent increase in transcripts expressed in inflammatory cells that was not associated with CLAD or survival. Also like TBBs, the CLAD-selective transcripts in 3BMBs reflected severe parenchymal injury and dedifferentiation, not inflammation or rejection. While 3BMBs and TBBs did not overlap in their top 20 CLAD-selective transcripts, many CLAD-selective transcripts were significantly increased in both for example LOXL1, an enzyme controlling matrix remodeling. In Cox models for one-year survival, the 3BMB CLAD-selective transcripts and CLAD classifier predicted graft loss and correlated with CLAD stage. Many 3BMB CLAD-selective transcripts were also increased by injury in kidney transplants and correlated with decreased kidney survival, including LOXL1.

CONCLUSIONS

Mucosal and transbronchial biopsies from CLAD patients reveal a diffuse molecular injury and dedifferentiation state that impacts prognosis and correlates with the physiologic disturbances. CLAD state in lung transplants shares features with failing kidney transplants, indicating elements shared by the injury responses of distressed organs.

The MMDx® diagnostic system: A critical re-appraisal of its knowledge gaps and a call for rigorous validation studies

Transcriptomics generates pathogenetic insights not obtainable by histology, but translation of these insights into diagnostic tests is not a trivial task. This opinion-piece critically appraises declarative MMDx statements, such as the infallibility of machine learning algorithms, measurements of gene expression with >99% precision, and "unambiguous reclassifications" of contentious biopsies such as those with borderline change, polyomavirus nephropathy, chronic active T-cell or mixed rejection, isolated intimal arteritis, and renal medullary pathology. It is shown that molecular diagnoses that do not agree with histology cannot be attributed primarily to pathology reading errors. Neither can all molecular calls derived from arbitrary binary thresholds be automatically accepted as the ground truth. Important other sources of discrepancies between clinico-pathologic and molecular calls include: (a) organ being studied, (b) disease definition, (c) clinical histologic, and gene expression heterogeneity within the same diagnostic label, (d) size and composition of comparator groups, (e) molecular noise, (f) variability in output of different machine learning algorithms, and (g) the nonavailability of a molecular classifier for chronic active TCMR. Carefully designed clinical trials are needed to determine which of the proposed indications of MMDx provide incremental value over existing standard of care protocols.

Solving the Conundrum of Eosinophils in Alloimmunity

Eosinophils are bone-marrow-derived granulocytes known for their ability to facilitate clearance of parasitic infections and their association with asthma and other inflammatory diseases. The purpose of this review is to discuss the currently available human observational and animal experimental data linking eosinophils to the immunologic response in solid organ transplantation. First, we present observational human studies that demonstrate a link between transplantation and eosinophils yet were unable to define the exact role of this cell population. Next, we describe published experimental models and demonstrate a defined mechanistic role of eosinophils in downregulating the alloimmune response to murine lung transplants. The overall summary of this data suggests that further studies are needed to define the role of eosinophils in multiple solid organ allografts and points to the possibility of manipulating this cell population to improve graft survival.

The promise of machine learning applications in solid organ transplantation

Solid-organ transplantation is a life-saving treatment for end-stage organ disease in highly selected patients. Alongside the tremendous progress in the last several decades, new challenges have emerged. The growing disparity between organ demand and supply requires optimal patient/donor selection and matching. Improvements in long-term graft and patient survival require data-driven diagnosis and management of post-transplant complications. The growing abundance of clinical, genetic, radiologic, and metabolic data in transplantation has led to increasing interest in applying machine-learning (ML) tools that can uncover hidden patterns in large datasets. ML algorithms have been applied in predictive modeling of waitlist mortality, donor–recipient matching, survival prediction, post-transplant complications diagnosis, and prediction, aiming to optimize immunosuppression and management. In this review, we provide insight into the various applications of ML in transplant medicine, why these were used to evaluate a specific clinical question, and the potential of ML to transform the care of transplant recipients. 36 articles were selected after a comprehensive search of the following databases: Ovid MEDLINE; Ovid MEDLINE Epub Ahead of Print and In-Process & Other Non-Indexed Citations; Ovid Embase; Cochrane Database of Systematic Reviews (Ovid); and Cochrane Central Register of Controlled Trials (Ovid). In summary, these studies showed that ML techniques hold great potential to improve the outcome of transplant recipients. Future work is required to improve the interpretability of these algorithms, ensure generalizability through larger-scale external validation, and establishment of infrastructure to permit clinical integration.

Screening gene signatures for clinical response subtypes of lung transplantation

Lung is the most important organ in the human respiratory system, whose normal functions are quite essential for human beings. Under certain pathological conditions, the normal lung functions could no longer be maintained in patients, and lung transplantation is generally applied to ease patients' breathing and prolong their lives. However, several risk factors exist during and after lung transplantation, including bleeding, infection, and transplant rejections. In particular, transplant rejections are difficult to predict or prevent, leading to the most dangerous complications and severe status in patients undergoing lung transplantation. Given that most common monitoring and validation methods for lung transplantation rejections may take quite a long time and have low reproducibility, new technologies and methods are required to improve the efficacy and accuracy of rejection monitoring after lung transplantation. Recently, one previous study set up the gene expression profiles of patients who underwent lung transplantation. However, it did not provide a tool to predict lung transplantation responses. Here, a further deep investigation was conducted on such profiling data. A computational framework, incorporating several machine learning algorithms, such as feature selection methods and classification algorithms, was built to establish an effective prediction model distinguishing patient into different clinical subgroups, corresponding to different rejection responses after lung transplantation. Furthermore, the framework also screened essential genes with functional enrichments and create quantitative rules for the distinction of patients with different rejection responses to lung transplantation. The outcome of this contribution could provide guidelines for clinical treatment of each rejection subtype and contribute to the revealing of complicated rejection mechanisms of lung transplantation.

T Cells With Activated STAT4 Drive the High-Risk Rejection State to Renal Allograft Failure After Kidney Transplantation

In kidney transplantation, deteriorated progression of rejection is considered to be a leading course of postoperative mortality. However, the conventional histologic diagnosis is limited in reading the rejection status at the molecular level, thereby triggering mismatched pathogenesis with clinical phenotypes. Here, by applying uniform manifold approximation and projection and Leiden algorithms to 2,611 publicly available microarray datasets of renal transplantation, we uncovered six rejection states with corresponding signature genes and revealed a high-risk (HR) state that was essential in promoting allograft loss. By identifying cell populations from single-cell RNA sequencing data that were associated with the six rejection states, we identified a T-cell population to be the pathogenesis-triggering cells associated with the HR rejection state. Additionally, by constructing gene regulatory networks, we identified that activated STAT4, as a core transcription factor that was regulated by PTPN6 in T cells, was closely linked to poor allograft function and prognosis. Taken together, our study provides a novel strategy to help with the precise diagnosis of kidney allograft rejection progression, which is powerful in investigating the underlying molecular pathogenesis, and therefore, for further clinical intervention.

Transcripts associated with chronic lung allograft dysfunction in transbronchial biopsies of lung transplants

Transplanted lungs suffer worse outcomes than other organ transplants with many developing chronic lung allograft dysfunction (CLAD), diagnosed by physiologic changes. Histology of transbronchial biopsies (TBB) yields little insight, and the molecular basis of CLAD is not defined. We hypothesized that gene expression in TBBs would reveal the nature of CLAD and distinguish CLAD from changes due simply to time posttransplant. Whole-genome mRNA profiling was performed with microarrays in 498 prospectively collected TBBs from the INTERLUNG study, 90 diagnosed as CLAD. Time was associated with increased expression of inflammation genes, for example, CD1E and immunoglobulins. After correcting for time, CLAD manifested not as inflammation but as parenchymal response-to-wounding, with increased expression of genes such as HIF1A, SERPINE2, and IGF1 that are increased in many injury and disease states and cancers, associated with development, angiogenesis, and epithelial response-to-wounding in pathway analysis. Fibrillar collagen genes were increased in CLAD, indicating matrix changes, and normal transcripts were decreased-dedifferentiation. Gene-based classifiers predicted CLAD with AUC 0.70 (no time-correction) and 0.87 (time-corrected). CLAD related gene sets and classifiers were strongly prognostic for graft failure and correlated with CLAD stage. Thus, in TBBs, molecular changes indicate that CLAD primarily reflects severe parenchymal injury-induced changes and dedifferentiation.

Review: immunosuppression for the lung transplant patient

Lung transplantation (LTx) has evolved significantly since its inception and the improvement in LTx outcomes over the last three decades has predominantly been driven by advances in immunosuppression management. Despite the lack of new classes of immunosuppression medications, immunosuppressive strategies have evolved significantly from a universal method to a more targeted approach, reflecting a greater understanding of the need for individualized therapy and careful consideration of all factors that are influenced by immunosuppression choice. This has become increasingly important as the demographics of lung transplant recipients have changed over time, with older and more medically complex candidates being accepted and undergoing LTx. Furthermore, improved survival post lung transplant has translated into more immunosuppression related comorbidities long-term, predominantly chronic kidney disease (CKD) and malignancy, which has required further nuanced management approaches. This review provides an update on current traditional lung transplant immunosuppression strategies, with modifications based on pre-existing recipient factors and comorbidities, peri-operative challenges and long term complications, balanced against the perpetual challenge of chronic lung allograft dysfunction (CLAD). As we continue to explore and understand the complexity of LTx immunology and the interplay of different factors, immunosuppression strategies will require ongoing critical evaluation and personalization in order to continue to improve lung transplant outcomes.

The Biology and Molecular Basis of Organ Transplant Rejection

Allograft rejection is defined as tissue injury in a transplanted allogeneic organ produced by the effector mechanisms of the adaptive alloimmune response. Effector T lymphocytes and IgG alloantibodies cause two different types of rejection that can occur either individually or simultaneously: T cell-mediated rejection (TCMR) and antibody-mediated rejection (ABMR). In TCMR, cognate effector T cells infiltrate the graft and orchestrate an interstitial inflammatory response in the kidney interstitium in which effector T cells engage antigen-presenting myeloid cells, activating the T cells, antigen-presenting cells, and macrophages. The result is intense expression of IFNG and IFNG-induced molecules, expression of effector T cell molecules and macrophage molecules and checkpoints, and deterioration of parenchymal function. The diagnostic lesions of TCMR follow, i.e. interstitial inflammation, parenchymal deterioration, and intimal arteritis. In ABMR, HLA IgG alloantibodies produced by plasma cells bind to the donor antigens on graft microcirculation, leading to complement activation, margination, and activation of NK cells and neutrophils and monocytes, and endothelial injury, sometimes with intimal arteritis. TCMR becomes infrequent after 5-10 years post-transplant, probably reflecting adaptive mechanisms such as checkpoints, but ABMR can present even decades post-transplant. Some rejection is triggered by inadequate immunosuppression and non-adherence, challenging the clinician to target effective immunosuppression even decades post-transplant.

The Impact of Inflammation on the Immune Responses to Transplantation: Tolerance or Rejection?

Transplantation (Tx) remains the optimal therapy for end-stage disease (ESD) of various solid organs. Although alloimmune events remain the leading cause of long-term allograft loss, many patients develop innate and adaptive immune responses leading to graft tolerance. The focus of this review is to provide an overview of selected aspects of the effects of inflammation on this delicate balance following solid organ transplantation. Initially, we discuss the inflammatory mediators detectable in an ESD patient. Then, the specific inflammatory mediators found post-Tx are elucidated. We examine the reciprocal relationship between donor-derived passenger leukocytes (PLs) and those of the recipient, with additional emphasis on extracellular vesicles, specifically exosomes, and we examine their role in determining the balance between tolerance and rejection. The concept of recipient antigen-presenting cell "cross-dressing" by donor exosomes is detailed. Immunological consequences of the changes undergone by cell surface antigens, including HLA molecules in donor and host immune cells activated by proinflammatory cytokines, are examined. Inflammation-mediated donor endothelial cell (EC) activation is discussed along with the effect of donor-recipient EC chimerism. Finally, as an example of a specific inflammatory mediator, a detailed analysis is provided on the dynamic role of Interleukin-6 (IL-6) and its receptor post-Tx, especially given the potential for therapeutic interdiction of this axis with monoclonal antibodies. We aim to provide a holistic as well as a reductionist perspective of the inflammation-impacted immune events that precede and follow Tx. The objective is to differentiate tolerogenic inflammation from that enhancing rejection, for potential therapeutic modifications. (Words 247).

Set Up for Failure: Pre-Existing Autoantibodies in Lung Transplant

Lung transplant patients have the lowest long-term survival rates compared to other solid organ transplants. The complications after lung transplantation such as primary graft dysfunction (PGD) and ultimately chronic lung allograft dysfunction (CLAD) are the main reasons for this limited survival. In recent years, lung-specific autoantibodies that recognize non-HLA antigens have been hypothesized to contribute to graft injury and have been correlated with PGD, CLAD, and survival. Mounting evidence suggests that autoantibodies can develop during pulmonary disease progression before lung transplant, termed pre-existing autoantibodies, and may participate in allograft injury after transplantation. In this review, we summarize what is known about pulmonary disease autoantibodies, the relationship between pre-existing autoantibodies and lung transplantation, and potential mechanisms through which pre-existing autoantibodies contribute to graft injury and rejection.

Many heart transplant biopsies currently diagnosed as no rejection have mild molecular antibody-mediated rejection-related changes

BACKGROUND

The Molecular Microscope (MMDx) system classifies heart transplant endomyocardial biopsies as No-rejection (NR), Early-injury, T cell-mediated (TCMR), antibody-mediated (ABMR), mixed, and possible rejection (possible TCMR, possible ABMR). Rejection-like gene expression patterns in NR biopsies have not been described. We extended the MMDx methodology, using a larger data set, to define a new "Minor" category characterized by low-level inflammation in non-rejecting biopsies.

METHODS

Using MMDx criteria from a previous study, molecular rejection was assessed in 1,320 biopsies (645 patients) using microarray expression of rejection-associated transcripts (RATs). Of these biopsies, 819 were NR. A new archetypal analysis model in the 1,320 data set split the NRs into NR-Normal (N = 462) and NR-Minor (N = 359).

RESULTS

Compared to NR-Normal, NR-Minor were more often histologic TCMR1R, with a higher prevalence of donor-specific antibody (DSA). DSA positivity increased in a gradient: NR-Normal 24%; NR-Minor 34%; possible ABMR 42%; ABMR 66%. The top 20 transcripts distinguishing NR-Minor from NR-Normal were all ABMR-related and/or IFNG-inducible, and also exhibited a gradient of increasing expression from NR-Normal through ABMR. In random forest analysis, TCMR and Early-injury were associated with reduced LVEF and increased graft loss, but NR-Minor and ABMR scores were not. Surprisingly, hearts with MMDx ABMR showed comparatively little graft loss.

CONCLUSIONS

Many heart transplants currently diagnosed as NR by histologic or molecular assessment have minor increases in ABMR-related and IFNG-inducible transcripts, associated with DSA positivity and mild histologic inflammation. These results suggest that low-level ABMR-related molecular stress may be operating in many more hearts than previously estimated. (ClinicalTrials.gov #NCT02670408).

Do we need to treat chronic active T cell-mediated rejection?

Chronic active T cell-mediated rejection, demonstrated by the presence of inflammation in areas of fibrosis, is associated with long-term allograft loss. Kung et al., in this issue of Kidney International, describe a series of cases of CA TCMR and analyze their clinical, molecular, and pathologic features as well as their response to therapy. Their translational study aids in understanding this diverse phenotype and provides future direction for managing these patients.

The Molecular Microscope (MMDXR ) interpretation of thoracic and abdominal allograft biopsies: Putting things in perspective for the clinician

The Molecular Microscope System (MMDX^R ) has significant potential to enhance biopsy interpretation. However, discussions of MMDx do not acknowledge the basic accuracy of histology readings, and the ability of pathology as a stand-alone tool to guide patient management. MMDx overstates its ability to automatically correct for problems in biopsy readings. Assertions of accuracy approaching 99% are not supported by "real world" data. The high rate of discrepancies between MMDx® and standard biopsy readings can be attributed to the summation of many factors other than histology interpretation, including molecular noise, assay thresholding, limited sensitivity of microarray technology for low expression genes, errors in classifier development, narrow data interpretation, and lack of spatial context. It is not widely recognized that molecular signatures are not disease-specific and are affected by the stage of disease as well as the extent of tissue injury. The effect of sampling error on MMDx performance is significantly under-estimated, particularly in heart and lung biopsies. Therefore, MMDx reports should always be interpreted in the context of conventional biopsy readings. The clinical picture and conventional biopsy reading should be allowed to over-ride the molecular interpretation when there is concern that confounding factors are at play.

IL-6 receptor blockade for allograft dysfunction after lung transplantation in a patient with COPA syndrome

Objective

COPA syndrome is a genetic disorder of retrograde cis‐Golgi vesicle transport that leads to upregulation of pro‐inflammatory cytokines (mainly IL‐1β and IL‐6) and the development of interstitial lung disease (ILD). The impact of COPA syndrome on post‐lung transplant (LTx) outcome is unknown but potentially detrimental. In this case report, we describe progressive allograft dysfunction following LTx for COPA‐ILD. Following the failure of standard immunosuppressive approaches, detailed cytokine analysis was performed with the intention of personalising therapy.

Methods

Multiplexed cytokine analysis was performed on serum and bronchoalveolar lavage (BAL) fluid obtained pre‐ and post‐LTx. Peripheral blood mononuclear cells (PMBCs) obtained pre‐ and post‐LTx were stimulated with PMA, LPS and anti‐CD3/CD28 antibodies. Post‐LTx endobronchial biopsies underwent microarray‐based gene expression analysis. Results were compared to non‐COPA LTx recipients and non‐LTx healthy controls.

Results

Multiplexed cytokine analysis showed rising type I/II IFNs, and IL‐6 in BAL post‐LTx that decreased following treatment of acute rejection but rebounded with further clinical deterioration. In vitro stimulation of PMBCs suggested that myeloid cells were driving deterioration, through IL‐6 signalling pathways. Tocilizumab (IL‐6 receptor antibody) administration for 3 months (4 mg kg⁻¹, monthly) effectively suppressed IL‐6 levels in BAL. Mucosal gene expression profile following tocilizumab suggested greater similarity to normal.

Conclusion

Clinical effectiveness of IL‐6 receptor blockade was not observed. However, we identified IL‐6 upregulation associated with graft injury, effective IL‐6 suppression with tocilizumab and evidence of beneficial effect on molecular transcripts. This mechanistic analysis suggests a role for IL‐6 blockade in post‐LTx care that should be investigated further.

When tissue is the issue: A histological review of chronic lung allograft dysfunction

Although chronic lung allograft dysfunction (CLAD) remains the major life-limiting factor following lung transplantation, much of its pathophysiology remains unknown. The discovery that CLAD can manifest both clinically and morphologically in vastly different ways led to the definition of distinct subtypes of CLAD. In this review, recent advances in our understanding of the pathophysiological mechanisms of the different phenotypes of CLAD will be discussed with a particular focus on tissue-based and molecular studies. An overview of the current knowledge on the mechanisms of the airway-centered bronchiolitis obliterans syndrome, as well as the airway and alveolar injuries in the restrictive allograft syndrome and also the vascular compartment in chronic antibody-mediated rejection is provided. Specific attention is also given to morphological and molecular markers for early CLAD diagnosis or histological changes associated with subsequent CLAD development. Evidence for a possible overlap between different forms of CLAD is presented and discussed. In the end, "tissue remains the (main) issue," as we are still limited in our knowledge about the actual triggers and specific mechanisms of all late forms of posttransplant graft failure, a shortcoming that needs to be addressed in order to further improve the outcome of lung transplant recipients.

Screening and identification of key regulatory connections and immune cell infiltration characteristics for lung transplant rejection using mucosal biopsies

This study aimed to explore key regulatory connections underlying lung transplant rejection. The differentially expressed genes (DEGs) between rejection and stable lung transplantation (LTx) samples were screened using R package limma, followed by functional enrichment analysis and protein-protein interaction network construction. Subsequently, a global triple network, including miRNAs, mRNAs, and transcription factors (TFs), was constructed. Furthermore, immune cell infiltration characteristics were analyzed to investigate the molecular immunology of lung transplant rejection. Finally, potential drug-target interactions were generated. In brief, 739 DEGs were found between rejection and stable LTx samples. PTPRC, IL-6, ITGAM, CD86, TLR8, TYROBP, CXCL10, ITGB2, and CCR5 were defined as hub genes. Eight TFs, including STAT1, SPIB, NFKB1, SPI1, STAT5A, RUNX1, VENTX, and BATF, and five miRNAs, including miR-335-5p, miR-26b-5p, miR-124-3p, miR-1-3p, and miR-155-5p, were involved in regulating hub genes. The immune cell infiltration analysis revealed higher proportions of activated memory CD4 T cells, follicular helper T cells, γδ T cells, monocytes, M1 and M2 macrophages, and eosinophils in rejection samples, besides lower proportions of resting memory CD4 T cells, regulatory T cells, activated NK cells, M0 macrophages, and resting mast cells. This study provided a comprehensive perspective of the molecular co-regulatory network underlying lung transplant rejection.

Banff 2019 Meeting Report: Molecular diagnostics in solid organ transplantation-Consensus for the Banff Human Organ Transplant (B-HOT) gene panel and open source multicenter validation

This meeting report from the XV Banff conference describes the creation of a multiorgan transplant gene panel by the Banff Molecular Diagnostics Working Group (MDWG). This Banff Human Organ Transplant (B-HOT) panel is the culmination of previous work by the MDWG to identify a broadly useful gene panel based on whole transcriptome technology. A data-driven process distilled a gene list from peer-reviewed comprehensive microarray studies that discovered and validated their use in kidney, liver, heart, and lung transplant biopsies. These were supplemented by genes that define relevant cellular pathways and cell types plus 12 reference genes used for normalization. The 770 gene B-HOT panel includes the most pertinent genes related to rejection, tolerance, viral infections, and innate and adaptive immune responses. This commercially available panel uses the NanoString platform, which can quantitate transcripts from formalin-fixed paraffin-embedded samples. The B-HOT panel will facilitate multicenter collaborative clinical research using archival samples and permit the development of an open source large database of standardized analyses, thereby expediting clinical validation studies. The MDWG believes that a pathogenesis and pathway based molecular approach will be valuable for investigators and promote therapeutic decision-making and clinical trials.

Molecular T-cell‒mediated rejection in transbronchial and mucosal lung transplant biopsies is associated with future risk of graft loss

BACKGROUND

We previously developed molecular assessment systems for lung transplant transbronchial biopsies (TBBs) with high surfactant and bronchial mucosal biopsies, identifying T-cell‒mediated rejection (TCMR) on the basis of the expression of rejection-associated transcripts, but the relationship of rejection to graft loss is unknown. This study aimed to develop molecular assessments for TBBs and mucosal biopsies and to establish the impact of molecular TCMR on graft survival.

METHODS

We used microarrays and machine learning to assign TCMR scores to an expanded cohort of 457 TBBs (367 high surfactant plus 90 low surfactant) and 314 mucosal biopsies. We tested the score agreement between TBB-TBB, mucosal-mucosal, and TBB-mucosal biopsy pairs in the same patient. We also assessed the association of molecular TCMR scores with graft loss (death or retransplantation) and compared it with the prognostic associations for histology and donor-specific antibodies.

RESULTS

The molecular TCMR scores assigned in all the TBBs performed similarly to those in high-surfactant TBBs, indicating that variation in alveolation in TBBs does not prevent the detection of TCMR. Mucosal biopsy pieces showed less piece-to-piece variation than TBBs. TCMR scores in TBBs agreed with those in mucosal biopsies. In both TBBs and mucosal biopsies, molecular TCMR was associated with graft loss, whereas histologic rejection and donor-specific antibodies were not.

CONCLUSIONS

Molecular TCMR can be detected in TBBs regardless of surfactant and in mucosal biopsies, which show less variability in the sampled tissue than TBBs. On the basis of these findings, molecular TCMR appears to be an important predictor of the risk of future graft failure.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02812290.