Identification of Immune-Related Genes for Risk Stratification in Multiple Myeloma Based on Whole Bone Marrow Gene...

Area of Science:

• Oncology
• Immunology
• Genetics

Background:

• Multiple myeloma (MM) is a plasma cell malignancy.
• Tumor immunotherapy offers new hope for MM patients.
• Understanding immune-related gene (IRG) expression is crucial for personalized immunotherapy.

Purpose of the Study:

• To explore the prognostic value of IRGs in MM.
• To identify key IRGs and transcription factors (TFs) associated with MM progression.
• To develop and validate an immune-related prognostic signature for MM.

Main Methods:

• Combined gene expression profiling (GEP) and clinical data from the GEO database.
• Utilized Weighted Gene Co-expression Network Analysis (WGCNA) to identify hub IRGs and TFs.
• Employed Cox and LASSO regression to build a prognostic signature.
• Validated the signature using statistical methods, ssGSEA, GSEA, and in vitro assays.

Main Results:

• Identified 14 TFs and 88 IRGs linked to the International Staging System (ISS).
• Developed a 10-IRG prognostic signature (BDNF, CETP, CD70, LMBR, LTBP1, NENF, NR1D1, NR1H2, PTK2B, SEMA4) for overall survival (OS).
• The signature accurately predicted survival and stratified MM patients by risk, reflecting tumor microenvironment status and pathway activation.

Conclusions:

• An immune-related gene signature serves as a valuable prognostic marker for MM patients.
• This signature can aid in guiding personalized immunotherapy strategies.
• The findings highlight the role of specific IRGs in MM progression and patient outcomes.