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. 2025 Jun 16:16:1553850.
doi: 10.3389/fimmu.2025.1553850. eCollection 2025.

Characteristics and predictive model for diffuse large B-cell lymphoma with early chemoimmunotherapy failure

Affiliations

Characteristics and predictive model for diffuse large B-cell lymphoma with early chemoimmunotherapy failure

Ying-Yu Dong et al. Front Immunol. .

Abstract

Introduction: The outcomes of refractory or relapsed diffuse large B-cell lymphoma are generally poor, especially those relapsed or progressed within 12 months from diagnosis named as early chemoimmunotherapy failure (ECF), with a 2-year OS of 24.7%. Due to the dismal outcome, early recognition of ECF and developing targeted innovative treatments to improve patient prognosis are urgent.

Methods: This study recruited 2038 newly diagnosed DLBCL patients treated with R-CHOP/RminiCHOP or R-CHOP-based immunochemotherapy in Ruijin hospital and 411 hospital from December 1997 to December 2020.

Results: Compared to the control group, ECF patients were significantly associated with elderly age, advanced Ann Arbor stage, elevated serum LDH, poor performance status, multiple extranodal involvements, double expressor lymphoma (DEL), and non-GCB subtype, as well as high frequencies of TP53, FOXO1 and FBXW7 mutations. Through multivariate analysis, elderly age, advanced stage, elevated serum LDH, DEL, and mutations of TP53 or FOXO1 were independent predictors of ECF.

Discussion: Based on these predictors, a nomogram of ECF was established, and the straining cohort of our Chinese patients as well as the external cohort from Western countries showed a good predictive power of the ECF model, indicating the efficiency of our ECF predicting model, regardless of patients' race. Our ECF model allows clinicians to early recognize ECF patients, to optimize the therapeutic strategies and to improve the outcome of those chemo-resistant patients.

Keywords: CAR- T cells; DLBCL - diffuse large B cell lymphoma; RCHOP-like regimen; chemo-resistant; early chemoimmunotherapy failure; nomogram.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Patient flowchart. DLBCL, diffuse large B-cell lymphoma; ECF, early chemoimmunotherapy failure; LCF, late chemoimmunotherapy failure.
Figure 2
Figure 2
Survival and mutation analysis of DLBCL patients. (A, B) Progression-free survival (PFS) (A) and overall survival (OS) (B) of DLBCL patients in the control (n=1338), ECF (n=376) and LCF (n=324) groups. (C-E) Mutation profiles (C), gene mutation burden (D), and molecular subtypes (E) of patients in the control (n=616) and ECF (n=148) groups. The symbol * means that the comparison between the two groups is statistically different, P<0.05.
Figure 3
Figure 3
Differential gene expression and immune cell infiltration in the control and ECF groups. (A) The volcano plots show the differential expression of genes in the control (n=274) and ECF (n=97) groups. (B) Up-regulated pathways in ECF patients compared to the control group. (C, D) Violin plot of cell cycle-related genes and tumor microenvironment, cell cycle signaling-related genes (C) Tumor microenvironment in the control (n=274) and ECF (n=97) groups (D). The symbols *, **, and *** indicate the levels of statistical significance for each variable. Specifically, * denotes a p-value less than 0.05, suggesting the result is statistically significant at the 5% level. ** indicates a p-value less than 0.01, showing stronger significance, while *** represents a p-value less than 0.001, implying a highly significant result.
Figure 4
Figure 4
ECF nomogram. (A) Construction of ECF nomogram. (B, C) ROC curves of the training (n=2038) (B) and validation sets (BCC cohort n=320) (C). (D, E) Calibration curves of the training (D) and validation sets (E).

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