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

Abstract

Diagnosing lung transplant rejection currently depends on histologic assessment of transbronchial biopsies (TBB) with limited reproducibility and considerable risk of complications. Mucosal biopsies are safer but not histologically interpretable. Microarray‐based diagnostic systems for TBBs and other transplants suggest such systems could assess mucosal biopsies as well. We studied 243 mucosal biopsies from the third bronchial bifurcation (3BMBs) collected from seven centers and classified them using unsupervised machine learning algorithms. Using the expression of a set of rejection‐associated transcripts annotated in kidneys and validated in hearts and lung transplant TBBs, the algorithms identified and scored major rejection and injury‐related phenotypes in 3BMBs without need for labeled training data. No rejection or injury, rejection, late inflammation, and recent injury phenotypes were thus scored in new 3BMBs. The rejection phenotype correlated with IFNG‐inducible transcripts, the hallmarks of rejection. Progressive atrophy‐related changes reflected by the late inflammation phenotype in 3BMBs suggest widespread time‐dependent airway deterioration, which was especially pronounced after two years posttransplant. Thus molecular assessment of 3BMBs can detect rejection in a previously unusable biopsy format with potential utility in patients with severe lung dysfunction where TBB is not possible and provide unique insights into airway deterioration. ClinicalTrials.gov NCT02812290.

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

“…After redundant and duplicate genes were removed, the list contained 1749 genes. Then the MDWG members identified overlap between these genes and genes described in the peer‐reviewed literature 2,8,12,29,32,33,38‐50,9,51,52,10,53‐56,11,57‐64,65 as being strongly associated with relevant clinical phenotypes and identified 1050 genes to be considered for inclusion. In the next step, a list including all genes with consensus expert opinion were selected and for which all Hugo duplicates were then combined, leaving 670 unique genes.…”

The molecular diagnosis of rejection in liver transplant biopsies: First results of the INTERLIVER study

“…Rejection-associated transcripts (RATs) were derived in kidney transplants and validated in heart 34,58,59 and lung transbronchial and mucosal biopsies. 36,37 The RATs are the union of the top 200…”

“…Molecular measurement of gene expression using microarrays coupled with machine learning has the potential to improve the assessment of transplant biopsies by overcoming the limitations of conventional diagnostics 28 . We previously developed the Molecular Microscope ® Diagnostic System (MMDx) for kidney, 29‐32 heart, 33,34 and lung transplants 35‐37 . A number of factors argue that MMDx testing is more accurate than histology 29 : for example, use of continuous quantitative measurements, 29 low sampling error, 30 high reproducibility, 30 and lack of requirements for specific tissue elements such as glomeruli, cortex, or portal triads.…”

Operationalizing mucosal biopsies using machine learning to determine lung allograft dysfunction

“…The diagnosis of allograft injury and differentiation from rejection requires transbronchial biopsy, which is associated with severe complications, such as pneumothorax and bleeding, and is frequently inaccurate due to the heterogeneity observed in histopathology. The study by Halloran et al attempts to operationalize machine learning–based microarray analysis of prevalidated rejection‐associated transcripts within mucosal biopsies, in lieu of transbronchial biopsies, to improve diagnostic accuracy and safety.…”