Fig. 4: Patient-specific modelling and stratification by pro-proliferation and anti-apoptotic species predicts prognosis of DLBCL patients. | Blood Cancer Journal

Fig. 4: Patient-specific modelling and stratification by pro-proliferation and anti-apoptotic species predicts prognosis of DLBCL patients.

From: Patient-specific computational models predict prognosis in B cell lymphoma by quantifying pro-proliferative and anti-apoptotic signatures from genetic sequencing data

Fig. 4

Kaplan-Meier (KM) plots were generated using modelling of patient data derived from Chapuy et al. (A, B), and then validated using Lacy et al. (C, D), and the MSK IMPACT cohort (E-F). A KM plot comparing progression-free survival (PFS) for DLBCL patients classified as simultaneously anti-apoptotic (AA) and pro-proliferative (PP)(AAPP) or not (Other), using personalised simulations. B KM plot comparing PFS for DLBCL patients classified as simultaneously anti-apoptotic and pro-proliferative (AAPP, prange), only one of AA or PP (green), or neither (Other, blue), using personalised simulations. The proportion of patients in each group is shown on the right. KM plots generated the same way as (A, B) using patients from ref. [8], stratified using AAPP alone (C), AA and/or PP (D). KM plots generated the same way as (A–C) using patients from the MSK IMPACT Heme cohort (2024), stratified using AAPP alone (E), AA and/or PP (F). G KM plots, generated without modelling in the indicated cohorts, comparing PFS/OS for patients with at least one mutation mapping to each of the cell cycle and apoptotic networks (AAPP, orange), with at least one mutation mapping to either the AA or PP network but not both (AA or PP, green), and patients who don’t have a mutation that maps to either AA or PP signalling networks (Other, blue). Significance values from log rank test indicated as follows: * P ≤ 0.05, ** P ≤ 0.01, *** P ≤ 0.001.

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