Centrosome associated genes pattern for risk sub-stratification in multiple myeloma.

Area of Science:

• Genomics
• Cancer Biology
• Molecular Diagnostics

Background:

• Multiple myeloma (MM) exhibits extreme genomic instability with diverse molecular subgroups impacting clinical outcomes.
• Previous research identified 35 candidate genes linked to carcinogenesis and centrosome function, highlighting MM's molecular heterogeneity.
• The study aimed to develop a risk stratification model utilizing these candidate genes.

Purpose of the Study:

• To establish a novel risk stratification model for multiple myeloma (MM) using a panel of candidate genes.
• To evaluate the prognostic significance of the developed model in MM patient stratification.
• To assess the model's ability to refine prognoses within specific patient subgroups, including those without TP53 loss and high-risk patients.

Main Methods:

• Analysis of 151 multiple myeloma patients, with plasma cells (PCs) isolated via magnetic-activated cell sorting (MACS).
• Gene expression profiling (GEP) and Interphase FISH (fluorescence in situ hybridization) with cytoplasmic immunoglobulin light chain staining (cIg FISH) were performed on PCs.
• Statistical analyses were conducted using R freeware, with a training cohort of 73 patients and a validation cohort of 78 patients.

Main Results:

• A risk stratification model, the Centrosome Associated Gene Pattern (CAGP), comprising 12 selected genes was successfully established.
• The CAGP model demonstrated independent prognostic value for multiple myeloma stratification.
• The CAGP model effectively sub-stratified prognosis in patients lacking TP53 loss and within the IMWG high-risk patient group.

Conclusions:

• The newly developed CAGP risk stratification model complements existing prognostic tools in multiple myeloma.
• This model offers refined classification of patients based on disease risk.
• The CAGP approach can be utilized independently or in conjunction with other prognostic factors for improved patient management.