Apoptosis-related genes influence prognosis and immune characteristics of diffuse large B-cell lymphoma.
Dysregulation of apoptosis-related genes (ARGs) may contribute to tumorigenesis and impact patient prognosis, but their specific influence on prognosis and immune characteristics in diffuse large B-cell lymphoma (DLBCL) remains unclear.
Gene expression profiles were collected from GEO datasets GSE10846 (training set; n = 414) and GSE181063 (validation set; n = 1310), totaling 1724 DLBCL samples. Univariate Cox and LASSO Cox regression analyses were performed to identified key ARGs, which were used to construct a risk score model. Patients were stratified into high/low-risk groups using the risk score. Functional enrichment analyses were conducted to explore biological functions and pathways. Immune cell infiltration was assessed using the CIBERSORT algorithm.
39 ARGs were significantly associated with overall survival in DLBCL patients. The risk score model effectively stratified patients into high/low-risk groups with distinct survival outcomes. Consensus clustering revealed distinct molecular subtypes with varying prognoses and biological characteristics. Enrichment analyses indicated that the prognostic genes are involved in critical pathways related to apoptosis and immune responses. High-risk patients exhibited higher immune scores and a distinct tumor immune microenvironment.
Apoptosis-related genes are valuable prognostic biomarkers in DLBCL and are associated with distinct immune characteristics. The risk model may aid in personalized risk assessment and inform treatment strategies. These findings provide insights into potential therapeutic targets by modulating apoptosis and immune responses in DLBCL.
Gene expression profiles were collected from GEO datasets GSE10846 (training set; n = 414) and GSE181063 (validation set; n = 1310), totaling 1724 DLBCL samples. Univariate Cox and LASSO Cox regression analyses were performed to identified key ARGs, which were used to construct a risk score model. Patients were stratified into high/low-risk groups using the risk score. Functional enrichment analyses were conducted to explore biological functions and pathways. Immune cell infiltration was assessed using the CIBERSORT algorithm.
39 ARGs were significantly associated with overall survival in DLBCL patients. The risk score model effectively stratified patients into high/low-risk groups with distinct survival outcomes. Consensus clustering revealed distinct molecular subtypes with varying prognoses and biological characteristics. Enrichment analyses indicated that the prognostic genes are involved in critical pathways related to apoptosis and immune responses. High-risk patients exhibited higher immune scores and a distinct tumor immune microenvironment.
Apoptosis-related genes are valuable prognostic biomarkers in DLBCL and are associated with distinct immune characteristics. The risk model may aid in personalized risk assessment and inform treatment strategies. These findings provide insights into potential therapeutic targets by modulating apoptosis and immune responses in DLBCL.