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[The Prognostic Predictive Value of TP53 mutation Variant Allele Frequency in Diffuse Large B-Cell Lymphoma]
Ling-Long Zhang1, Li An1, Xiao-Long Qi1
1Department of Hematology, Xinjiang Uygur Autonomous Region People's Hospital, Urumqi 830001, Xinjiang Uygur Autonomous Region, China.
Objective:
To explore the effect of TP53 mutation variant allele frequency(VAF) on the prognosis of diffuse large B-cell lymphoma(DLBCL) patients.
Methods:
This study included 155 patients with DLBCL who were first diagnosed in the People's Hospital of Xinjiang Uygur Autonomous Region from March 2009 to March 2022. Complete clinical data and paraffin-embedded tumor tissue samples were obtained, and DNA was extracted from tumor tissues. The gene mutation profile of DLBCL patients was detected and analyzed by second-generation sequencing technology. Kaplan-Meier method was used to analyze the mutation status of TP53 gene and the relationship between mutation VAF and OS. Cox regression univariate and multivariate analysis was use to analyze the independent factors affecting OS. A nornogram model for predicting 1, 3, and 5 years OS in DLBCL patients were established to evaluated the performance of the model based on C-index and calibration curves.
Results:
The average value of TP53 mutation VAF in male DLBCL patients was significantly higher than that in female patients (P < 0.05). Patients with TP53 mutantion had shorter OS than those with wild-type patients (P =0.030). The optimal VAF threshold for TP53 mutation based on OS stratification was 33.61% (P < 0.001), and patients with TP53 mutation VAF ≥34% had shorter OS than those with TP53 mutation VAF < 34% and wild-type patients (P < 0.001). Multivariate Cox analysis showed that TP53 mutation VAF≥34% was an independent poor predictor of OS ( HR =4.05, P < 0.001), and IPI score ≥3 was an independent predictor of OS poor ( HR =2.27, P =0.008). In combination with factors with independent prognostic significance obtained from multi-factor analysis, we constructed a nomogram model for predicting 1-year, 3-year, 5-year OS in DLBCL patients. The results showed that the C index of TP53 mutation VAF combined with IPI model was 0.743, which predicted the value of 1-year, 3-year, and 5-year OS in DLBCL patients. Calibration curves show that the model has good agreement between predicted and actual survival of DLBCL patients at 1-year, 3-year, and 5-year.
Conclusion:
TP53 mutation VAF has prognostic value in DLBCL patients, and TP53 mutation VAF≥34% is an independent risk factor for OS in DLBCL patients. The prognosis model of TP53 mutation VAF combined with IPI nomogram constructed in this study has good predictive performance for DLBCL patients.
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