Work

A Proliferation Score Defined by PCLI-Anchored Transcriptomics Predicts Outcomes in Multiple Myeloma

Year: 2026

Type: article

Abstract: 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 MM Mayo Clinic patients with paired plasma cell proliferation measurements, we performed a differential expression analysis to identify genes consistently associated with proliferative activity. These genes were subsequently incorporated into a prognostic model development using baseline RNA-seq profiles in purified CD138 + cells from 656 patients in the CoMMpass cohort, where an elastic net-based Cox model yielded an eight-gene Gene-based Proliferation Score (GPS). Differential expression analysis identified 108 proliferation-associated genes, and the resulting eight-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 hub-gene. In the CoMMpass dataset, on dividing the GPS score by median the high-GPS group (n=328) had a median overall survival of 63.6 months (95% CI: 56.5–76.7), whereas the low-GPS group (n=328) had a median overall survival of 106.1 months. (p < 0.001). In another Mayo Clinic RNA-seq cohort, high-GPS patients(n=12) similarly demonstrated worse survival (median OS: 39.2 vs. 157.1 months in the low group; p = 0.03). GPS emerged as an independent prognostic alongside high-risk markers and also predicted S-phase content in an independent dataset.

Source: Blood Neoplasia

DOI: 10.1016/j.bneo.2026.100288