Potential Impact of Microarray Diagnosis of T Cell–Mediated Rejection in Kidney Transplants: The INTERCOM Study

Abstract

We previously developed a microarray-based test for T cell-mediated rejection (TCMR) in a reference set of 403 biopsies. To determine the potential impact of this test in clinical practice, we undertook INTERCOM, a prospective international study of 300 indication biopsies from 264 patients (ClinicalTrials.gov NCT01299168). Biopsies from six centers-Baltimore, Barcelona, Edmonton, Hannover, Manchester and Minneapolis-were analyzed by microarrays, assigning TCMR scores by an algorithm developed in the reference set and comparing TCMR scores to local histology assessment. The TCMR score correlated with histologic TCMR lesions-tubulitis and interstitial infiltration. The accuracy for primary histologic diagnoses (0.87) was similar to the reference set (0.89). The TCMR scores reclassified 77/300 biopsies (26%): 16 histologic TCMR were molecularly non-TCMR; 15 histologic non-TCMR were molecularly TCMR, including 6 with polyoma virus nephropathy; and all 46 ''borderline'' biopsies were reclassified as TCMR (8) or non-TCMR (38). Like the reference set, discrepancies were primarily in situations where histology has known limitations, for example, in biopsies with scarring and inflammation/tubulitis potentially from other diseases. Neither the TCMR score nor histologic TCMR was associated with graft loss. Thus the molecular TCMR score has potential to add new insight, particularly in situations where histology is ambiguous or potentially misleading.

Assessing rejection-related disease in kidney transplant biopsies based on archetypal analysis of molecular phenotypes

“…The previously developed and independently validated molecular classifiers for ABMR (12, 13) and TCMR (10,11), plus the lesion classifiers described in this paper, can now be merged into the AA diagnostic system to assess rejection-related states in new biopsies. When new samples become available, their gene expression data can be fed directly into the fixed classifiers from this study to generate AA-based molecular assessments.…”

“…Molecular tests are usually derived by supervised analyses, in which conventional phenotypes (e.g., histologic diagnoses) are used to guide the development of molecular classifiers: machine learning-based algorithms that detect patterns of gene expression associated with the phenotypes. Our previous studies have been based on such classifiers comparing rejection vs. nonrejection phenotypes (10)(11)(12)(13)(14). However, we have subsequently found that methods that combine multiple classifiers provide better estimates than single classifiers (15), implying that a new method is needed to assemble the input from multiple classifiers into a single probabilistic assessment.…”

The Banff 2015 Kidney Meeting Report: Current Challenges in Rejection Classification and Prospects for Adopting Molecular Pathology

“…Over the last decade, transplant biopsies, blood, and urine have been studied comprehensively, primarily using transcriptomics, and have led to novel insights into the molecular phenotypes of organ transplants 47, 48, 49, 50, 51, 52, 53. Current ongoing studies—for example, the INTERCOM studies 47, 48—are assessing a molecular microscope approach in real time for examining kidney allograft biopsies and comparing the gene expression classifiers and diagnosis to the current gold standard histopathology. This represents a step forward and will generate important results to help guide integration of molecular analysis with morphology.…”

Relationships among injury, fibrosis, and time in human kidney transplants

“…We studied 681 kidney transplant biopsies with histology scores for fibrosis (ci score: 0-3) and atrophy (ct score: 0-3) (Table 1), from a previously described set of 703 indication biopsies from 564 kidneys, including a discovery set of 403 biopsies (31) and a validation set of 300 biopsies (32). These biopsies were collected prospectively as a sample of troubled kidneys from the prevalent renal transplant population, representing a continuous scale of the TxBx from 3 days to 35 years (33).…”