Exploring the Potential of Enhanced Prognostic Performance of NCCN‐IPI in Diffuse Large B‐Cell Lymphoma by Integrating Tumor Microenvironment Markers: Stromal FOXC1 and Tumor pERK1/2 Expression

Abstract

ABSTRACT Background FOXC1 and ERK1‐2 are proteins implicated in aggressive biological behavior of various malignancies including lymphomas. Material and Methods We investigate the additive prognostic value of stromal FOXC1 expression and tumor phosphorylated ERK1‐2 (pERK1‐2) expression to the established National Comprehensive Cancer Network International Prognostic Index (NCCN‐IPI), in 92 diffuse large B‐cell lymphoma (DLBCL) cases. Multidimensional analysis using statistics and machine learning (ML) models assessed prognostic value of established clinicopathologic variables with stromal FOXC1 and tumor pERK1‐2 expressions. Results Both high FOXC1 stroma group and high pERK1‐2 tumor group were significantly associated with shorter progression‐free survival (PFS) and overall survival (OS) compared with low group (p = 0.015, 0.034 and p = 0.025, 0.025 each respectively). In multivariable analysis, high FOXC1 stromal expression was an independent prognostic factor of OS (p = 0.037). The addition of stromal FOXC1 and tumor pERK1‐2 to the NCCN‐IPI score significantly improved prediction of time to death compared with NCCN‐IPI score alone (Harrell's C‐index = 0.801 vs. 0.764; p = 0.030). ML models reconfirmed the addition of stromal FOXC1 expression and tumor pERK1‐2 to NCCN‐IPI score had the highest C‐index (0.952) among combinations. Stromal FOXC1 and tumor pERK1‐2 were determinants of DLBCL prognosis, whose addition significantly improved prognostic performance of the NCCN‐IPI.

Keywords

• Diffuse Large B‐cell Lymphoma
• FOXC1
• Machine Learning Models
• pERK1‐2
• Prognostic Markers
• Tumor Microenvironment