Exploratory study of <i>TP53</i> mutations in circulating tumor DNA as prognostic and longitudinal monitoring biomarkers for relapsed ovarian carcinoma patients.

Z Zheng Feng Y Yi Fu X Xingzhu Ju (Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China) Z Zhong Zheng (Department of Chemistry, The University of Chicago, Chicago, IL, USA.) J Jing Zhang Y Yanping Zhong (Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China) R Ruimin Li Z Zhilong Li J Jiaxi Peng W Weijia Jiang (BGI Genomics, Shenzhen, China) Y Yuying Wang (State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University) X Xiaohua Wu (Fudan University Shanghai Cancer Center Shanghai China) H Hao Wen

Abstract

e17568 Background: This study aims to investigate the prognostic and recurrence monitoring applications of TP53 mutated circulating tumor DNA in platinum-resistant ovarian cancer (PROC) with pegylated liposomal doxorubicin (PLD) therapy. Methods: This is a prospective observational study (NCT05976932), and twenty-seven PROC patients with TP53 mutations were recruited with PLD treatment. CA125 levels were measured prior to each cycle of chemotherapy. While TP53 mutations in circulating tumor DNA were detected in the first three cycles of chemotherapy, and subsequent each two cycles together with radiological assessments. Three TP53 algorithms were established for prognostic evaluation and recurrence monitoring: [1] Algorithm 1, TP53 mutation burden algorithm ( TP53 mutation be detected after clearance or TP53 MAC ≥ 1000); [2] Algorithm 2, dynamic TP53MAC change algorithm ( TP53 mutation be detected after clearance or TP53MAC reach twofold of the nadir); and [3] Algorithm 3, combined algorithm (positive if either Algorithm 1 or Algorithm 2 is met). Results: The median PFS of the enrolled cohort was 114 days (95% CI: 66.51-161.50 days), and the median baseline TP53 MAC value was 72.43 (range from 0.00 to 6583.60). Results meeting the aforementioned criteria were assigned to the ‘TP53+’ group, while the others were assigned to the 'TP53-' group. Prognostic evaluation based on the first three cycles exhibit significant differences between the TP53+ and TP53- groups across all three TP53 algorithms (log-rank p =0.00327, 0.00017 and 0.00001, respectively). Algorithm 3 shows the best performance while the TP53+ group had a median progression-free survival (PFS) of 79 days (95% CI: 50.14-107.86 days), versus 159 days (95% CI: 78.21-239.79 days) in the TP53- group. Conversely, CA125 levels showed no prognostic significance ( p =0.87010). What’s more, monitoring TP53MAC during longitudinal follow-up of PROC patients may indicate the risk of recurrence earlier than radiological evidence. Specifically, Algorithm 3 achieved a sensitivity of 74.07% (95% CI: 53.72%-88.89%) and median lead time of 26 days ( one treatment cycle in advance), much better than CA125, whose sensitivity was 48.15% (95% CI: 28.67%-68.05%). Conclusions: Multiple TP53 mutation algorithms were developed in this study based on the sensitive, rapid and cost-effective digital PCR platform, demonstrating the potential of TP53 in prognostic evaluation and recurrence monitoring for PROC patients. Clinical trial information: NCT05976932 .

Article Details

Volume / Issue Vol. 44, Issue 16_suppl
Published June 01, 2026
ISSN 0732-183X
Publisher Lippincott Williams & Wilkins

Journal Info

Journal of Clinical Oncology

Lippincott Williams & Wilkins

ISSN: 0732-183X Health Sciences

Authors (13)

Z

Zheng Feng

Y

Yi Fu

X

Xingzhu Ju

Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China

Z

Zhong Zheng

Department of Chemistry, The University of Chicago, Chicago, IL, USA.

J

Jing Zhang

Y

Yanping Zhong

Department of Gynecologic Oncology, Fudan University Shanghai Cancer Center, Shanghai, China

R

Ruimin Li

Z

Zhilong Li

J

Jiaxi Peng

W

Weijia Jiang

BGI Genomics, Shenzhen, China

Y

Yuying Wang

State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University

X

Xiaohua Wu

Fudan University Shanghai Cancer Center Shanghai China

H

Hao Wen