Pre-Transplant Chromosome Genomic Array Testing Improves Prognosis for Myelofibrosis Patients Undergoing Transplantation

Xiaoyu Qu; Emily Stevens; Matthew P Fitzgibbon; Lan Beppu; Tim M Monahan; Cecilia Yeung; Derek L Stirewalt; David Wu; Jerald P Radich; H Joachim Deeg; Min Fang

doi:10.1016/j.jtct.2024.12.018

Pre-Transplant Chromosome Genomic Array Testing Improves Prognosis for Myelofibrosis Patients Undergoing Transplantation

Transplant Cell Ther. 2024 Dec 23:S2666-6367(24)00837-6. doi: 10.1016/j.jtct.2024.12.018. Online ahead of print.

Authors

Affiliations

¹ Fred Hutchinson Cancer Center, Seattle, WA.
² Virginia Mason Franciscan Health, Seattle, WA.
³ Fred Hutchinson Cancer Center, Seattle, WA; University of Washington, Seattle, WA.
⁴ University of Washington, Seattle, WA.
⁵ Fred Hutchinson Cancer Center, Seattle, WA; University of Washington, Seattle, WA. Electronic address: mfang@fredhutch.org.

PMID: 39722322
DOI: 10.1016/j.jtct.2024.12.018

Abstract

Background: Despite its known superior diagnostic yield for chromosomal anomalies compared to karyotype and FISH studies, Chromosome Genomic Array Testing (CGAT) is not used as a routine clinical test for myelofibrosis. Meanwhile, although many prognostic systems exist that risk stratify patients at diagnosis, limited tools are available to prognosticate transplant outcome.

Objective: The current study aimed at testing if CGAT results obtained before transplantation improves prognosis of post-transplant outcome in myelofibrosis patients compared with current risk categorization systems namely DIPSS plus.

Study design: We studied myelofibrosis patients who underwent hematopoietic cell transplantation between 2000 and 2017 at our center (n=44). We assessed the prognostic significance of CGAT, DIPSS plus, and the total count of gene mutations, for post-transplant clinical outcomes including relapse-free survival (RFS), overall survival (OS), and graft-versus-host-disease (GVHD).

Results: Abnormal CGAT results were seen in 24 patients (55%), including 18 with copy-neutral loss of heterozygosity (cnLOH, 41%). With a median follow-up of 91 (range 2-258) months starting from the CGAT sample date, RFS was 59%, and OS was 68%. The outcome analysis showed significant prognostic implication from CGAT (normal vs abnormal), specifically for patients with intermediate-risk by DIPSS-plus scores and those with 0∼2 mutations. CGAT alone significantly stratified the patients' RFS outcome (P=0.03). The addition of CGAT to DIPSS-plus improved the significance from a P value of 0.08 to 0.003, while the addition of CGAT to mutation count improved the P value from 0.02 to 0.01. The best stratification system for RFS was achieved when CGAT, DIPSS-plus, and mutation count were all considered (P = 1e-08). The current study also confirmed individual anomalies that are prognostically significant, including U2AF1 mutation (n=5, P=0.03) and 1q gain (n=3, P=0.01), which were associated with worse RFS. ASXL1 mutations (n=14) appeared to associate with a later onset of chronic GVHD (P=0.03).

Conclusion: Pre-transplant CGAT analysis augments the existing risk stratification tools and may be considered as routine clinical testing for myelofibrosis.

Keywords: Chromosome Genomic Array Testing; Myelofibrosis; Post-Transplant Prognosis.