Collection of autologous CD34+ hematopoietic progenitor cells (HPC) in multiple myeloma: CD34 + cell collection yield in relation to molecular subtype, karyotype, and FISH results

BACKGROUND: Autologous stem cell transplantation remains a cornerstone of treatment for patients with transplant-eligible multiple myeloma (MM). Previous studies using gene expression profiling (GEP) have classified MM into seven molecular subgroups: HY, CD-1, CD-2, LB, PR, MS, and MF. Together with GEP signature, it can help identify patients with better or worse outcomes. In this study, we wanted to study how these molecular subtypes, along with cytogenetics, FISH results, and different treatment regimens, relate to the count of CD34 + hematopoietic progenitor cells (HPC) collected during stem cell mobilization. METHODS: We conducted a retrospective study of 505 MM patients who underwent hematopoietic progenitor cell (HPC) collection between January 2017 and December 2020. Demographic, molecular (FISH, cytogenetics, GEP), clinical, treatment, and mobilization regimen data were collected and analyzed to determine factors influencing CD34 + HPC yield. RESULTS: Factors associated with reduced CD34 + HPC collection included PR and MF GEP subtypes, deletion 13 (-13), and high-risk genetic classification. In contrast, normal versus abnormal karyotype, hyperdiploid versus hypodiploid karyotype, and the use of either proteasome inhibitors in combination with heterogeneous chemotherapy regimens did not significantly impact CD34 + HPC yield.

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Journal
PLoS ONE
Published
2026-05-12
DOI
https://doi.org/10.1371/journal.pone.0349212
Primary Topic
Multiple Myeloma Research and Treatments
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article
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article

Collection of autologous CD34+ hematopoietic progenitor cells (HPC) in multiple myeloma: CD34 + cell collection yield in relation to molecular subtype, karyotype, and FISH results

Anwar Rjoop, Ivette Perez, Gina Drobena, Majd M. AlBarakat et al.
PLoS ONE
Multiple Myeloma Research and Treatments
article

Collection of autologous CD34+ hematopoietic progenitor cells (HPC) in multiple myeloma: CD34 + cell collection yield in relation to molecular subtype, karyotype, and FISH results

Anwar Rjoop, Ivette Perez, Gina Drobena, Majd M. AlBarakat, Daoud O. Al Aruri, Frits van Rhee
article en

Abstract

BACKGROUND: Autologous stem cell transplantation remains a cornerstone of treatment for patients with transplant-eligible multiple myeloma (MM). Previous studies using gene expression profiling (GEP) have classified MM into seven molecular subgroups: HY, CD-1, CD-2, LB, PR, MS, and MF. Together with GEP signature, it can help identify patients with better or worse outcomes. In this study, we wanted to study how these molecular subtypes, along with cytogenetics, FISH results, and different treatment regimens, relate to the count of CD34 + hematopoietic progenitor cells (HPC) collected during stem cell mobilization. METHODS: We conducted a retrospective study of 505 MM patients who underwent hematopoietic progenitor cell (HPC) collection between January 2017 and December 2020. Demographic, molecular (FISH, cytogenetics, GEP), clinical, treatment, and mobilization regimen data were collected and analyzed to determine factors influencing CD34 + HPC yield. RESULTS: Factors associated with reduced CD34 + HPC collection included PR and MF GEP subtypes, deletion 13 (-13), and high-risk genetic classification. In contrast, normal versus abnormal karyotype, hyperdiploid versus hypodiploid karyotype, and the use of either proteasome inhibitors in combination with heterogeneous chemotherapy regimens did not significantly impact CD34 + HPC yield.

PLoS ONEVol. 21(5)
University of Jordan (JO), Jordan University of Science and Technology (JO), University of Arkansas for Medical Sciences (US)
Openalex Percentile: Top 5%
Multiple Myeloma Research and Treatments
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Collection of autologous CD34+ hematopoietic progenitor cells (HPC) in multiple myeloma: CD34 + cell collection yield in relation to molecular subtype, karyotype, and FISH results — Anwar Rjoop, Ivette Perez, et al. · PLoS ONE (2026) | TGRS Research Map | TGRS