A proliferation score defined by PCLI-anchored transcriptomics predicts outcomes in multiple myeloma
4 affiliations
- 1Division of Hematology, Mayo Clinic, Rochester, MN
- 2Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN
- 3Division of Hematology and Medical Oncology, Mayo Clinic, Phoenix, AZ
- 4Division of Hematopathology, Mayo Clinic, Rochester, MN
Abstract
Cell proliferation is a fundamental driver of disease aggressiveness in multiple myeloma (MM); however, transcriptional programs underpinning proliferative capacity remain incompletely defined. Using Affymetrix microarray data from 136 Mayo Clinic patients with MM with paired plasma cell labeling index (PCLI), we performed a differential expression analysis to identify genes consistently associated with proliferative activity. These genes were subsequently incorporated into the development of a prognostic model using baseline RNA sequencing (RNA-seq) profiles in purified CD138⁺ cells from 656 patients in the CoMMpass cohort, in which an elastic net-based Cox model yielded an 8-gene-based proliferation score (GPS). Differential expression analysis identified 108 proliferation-associated genes, and the resulting 8-gene GPS (CHEK1, EXO1, MCM4, TK1, KIF14, SEPTIN11, PHF19, and HMGB3) formed a highly connected biological network enriched for DNA damage response and cell cycle regulation. CHEK1, TK1, EXO1, and MCM4 were mapped in a large network with CHEK1 as the hub gene. In the CoMMpass data set, on dividing the GPS score by the median, the high-GPS group (n = 328) had a median overall survival (OS) of 63.6 months (95% confidence interval, 56.5-76.7), whereas the low-GPS group (n = 328) had a median OS of 106.1 months (P < .001). Similarly, in another Mayo Clinic RNA-seq cohort, high-GPS group (n = 12) demonstrated worse survival (median OS, 39.2 vs 157.1 months for the low-GPS group; P = .03). GPS emerged as an independent prognostic factor alongside high-risk markers and also predicted S-phase content in an independent data set.
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BibTeX
@article{bohra2026proliferation,
title = {{A proliferation score defined by PCLI-anchored transcriptomics predicts outcomes in multiple myeloma}},
author = {Arwa Bohra and Surendra Dasari and Wilson I. Gonsalves and Richard K. Kandasamy and Prashant Kapoor and Saurabh Zanwar and Moritz Binder and Esteban Braggio and Erik Jessen and Angela Dispenzieri and Michael M. Timm and Dragan Jevremovic and S. Vincent Rajkumar and Shaji Kumar},
journal = {Blood neoplasia},
year = {2026},
month = aug,
doi = {10.1016/j.bneo.2026.100288},
url = {https://europepmc.org/article/PMC/PMC13717733},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - A proliferation score defined by PCLI-anchored transcriptomics predicts outcomes in multiple myeloma
AU - Arwa Bohra
AU - Surendra Dasari
AU - Wilson I. Gonsalves
AU - Richard K. Kandasamy
AU - Prashant Kapoor
AU - Saurabh Zanwar
AU - Moritz Binder
AU - Esteban Braggio
AU - Erik Jessen
AU - Angela Dispenzieri
AU - Michael M. Timm
AU - Dragan Jevremovic
AU - S. Vincent Rajkumar
AU - Shaji Kumar
PY - 2026
DA - 2026/08/24
JO - Blood neoplasia
DO - 10.1016/j.bneo.2026.100288
UR - https://europepmc.org/article/PMC/PMC13717733
AB - Cell proliferation is a fundamental driver of disease aggressiveness in multiple myeloma (MM); however, transcriptional programs underpinning proliferative capacity remain incompletely defined. Using Affymetrix microarray data from 136 Mayo Clinic patients with MM with paired plasma cell labeling index (PCLI), we performed a differential expression analysis to identify genes consistently associated with proliferative activity. These genes were subsequently incorporated into the development of a prognostic model using baseline RNA sequencing (RNA-seq) profiles in purified CD138⁺ cells from 656 patients in the CoMMpass cohort, in which an elastic net-based Cox model yielded an 8-gene-based proliferation score (GPS). Differential expression analysis identified 108 proliferation-associated genes, and the resulting 8-gene GPS (CHEK1, EXO1, MCM4, TK1, KIF14, SEPTIN11, PHF19, and HMGB3) formed a highly connected biological network enriched for DNA damage response and cell cycle regulation. CHEK1, TK1, EXO1, and MCM4 were mapped in a large network with CHEK1 as the hub gene. In the CoMMpass data set, on dividing the GPS score by the median, the high-GPS group (n = 328) had a median overall survival (OS) of 63.6 months (95% confidence interval, 56.5-76.7), whereas the low-GPS group (n = 328) had a median OS of 106.1 months (P < .001). Similarly, in another Mayo Clinic RNA-seq cohort, high-GPS group (n = 12) demonstrated worse survival (median OS, 39.2 vs 157.1 months for the low-GPS group; P = .03). GPS emerged as an independent prognostic factor alongside high-risk markers and also predicted S-phase content in an independent data set.
SN - 2950-3280
ER -