Identification of extracellular matrix-related prognostic biomarkers and their role associated with multiple myeloma

Background: The extracellular matrix (ECM) has progressively gained prominence in multiple myeloma (MM), however, poorly understood is the prognostic role of ECM-related genes in MM. This project aimed to construct a prognostic signature and brought a new theoretical support for MM patients (TRN: ChiCTR8529409910, Data: October 23). Methods: : Expression data from MM samples in GSE24080 and GSE57317 were downloaded and analyzed. Subsequently, prognostic signature was constructed. The underlying mechanism analysis was interpreted by gene ontology (GO) analysis, kyoto encyclopedia of genes genomes (KEGG), and gene set enrichment analysis (GSEA). In addition, the Genomics of Drug Sensitivity in Cancer (GDSC) and Tumor Immune Dysfunction and Exclusion (TIDE) algorithms were utilized to predict the sensitivity of MM patients to chemotherapy and immune-checkpoint blockade (ICB) treatment. Also, potential drugs were predicted for the treatment of MM. A classifier for predicting ICB response was constructed. Finally, we validated KCTD3 expression and function in MM cells. Results: : After a series of downscaling, FABP5, XK, KCTD3, CISH, CCSAP, BCAR3, LATS2, TRIM59, TRIM2 and FKBP1B were maintained and applied to construct a prognostic feature, and then a risk score was calculated. Patients in the high-risk group stratified by median risk score had a poorer prognosis. The risk score had a high accuracy [area under curve (AUC) > 0.7]. 138 small molecule compounds with potential targeting risk score were predicted for MM patients through the Connectivity Map (CMap) database. In addition, a classifier capable of accurately predicting immune-checkpoint blockade (ICB) responses was constructed. KCTD3 has high expression in MM, and KCTD3 silencing inhibited MM cell proliferation. Conclusion: This study provided a reliable prognostic signature for MM and suggested the potential compounds for prognostic treatment of MM. Also, our study offered a sizable reference for ICB treatment prediction in MM.