Urinary cell mRNA profiles predictive of human kidney allograft status

John R. Lee, Thangamani Muthukumar, Darshana Dadhania, Ruchuang Ding, Vijay K. Sharma, Joseph E. Schwartz, Manikkam Suthanthiran

Research output: Contribution to journalReview article

24 Citations (Scopus)


Kidney allograft status is currently characterized using the invasive percutaneous needle core biopsy procedure. The procedure has become safer over the years, but challenges and complications still exist including sampling error, interobserver variability, bleeding, arteriovenous fistula, graft loss, and even death. Because the most common type of acute rejection is distinguished by inflammatory cells exiting the intravascular compartment and gaining access to the renal tubular space, we reasoned that a kidney allograft may function as an in vivo flow cytometer and sort cells involved in rejection into urine. To test this idea, we developed quantitative polymerase chain reaction (PCR) assays for absolute quantification of mRNA and pre-amplification protocols to overcome the low RNA yield from urine. Here, we review our single center urinary cell mRNA profiling studies that led to the multicenter Clinical Trials in Organ Transplantation (CTOT-04) study and the discovery and validation of a 3-gene signature of 18S rRNA-normalized measures of CD3ε mRNA and IP-10 mRNA and 18S rRNA that is diagnostic and predictive of acute cellular rejection in the kidney allograft. We also review our development of a 4-gene signature of mRNAs for vimentin, NKCC2, E-cadherin, and 18S rRNA diagnostic of interstitial fibrosis/tubular atrophy (IF/TA).

Original languageEnglish
Pages (from-to)218-240
Number of pages23
JournalImmunological Reviews
Issue number1
Publication statusPublished - 1 Jan 2014
Externally publishedYes



  • Acute cellular rejection
  • Interstitial fibrosis
  • Kidney transplantation
  • PCR
  • Urinary cell mRNA profiling

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

Cite this

Lee, J. R., Muthukumar, T., Dadhania, D., Ding, R., Sharma, V. K., Schwartz, J. E., & Suthanthiran, M. (2014). Urinary cell mRNA profiles predictive of human kidney allograft status. Immunological Reviews, 258(1), 218-240. https://doi.org/10.1111/imr.12159