Impact of TP53 Mutations on EGFR-Tyrosine Kinase Inhibitor Efficacy and Potential Treatment Strategy

Jing Fu; Yuyang Tong; Ziguang Xu; Yaonan Li; Ya Zhao; Tao Wang; Cuidan Li; Shundong Cang

doi:10.1016/j.cllc.2022.08.007

Impact of TP53 Mutations on EGFR-Tyrosine Kinase Inhibitor Efficacy and Potential Treatment Strategy

Clin Lung Cancer. 2023 Jan;24(1):29-39. doi: 10.1016/j.cllc.2022.08.007. Epub 2022 Aug 15.

Authors

Jing Fu¹, Yuyang Tong¹, Ziguang Xu², Yaonan Li³, Ya Zhao¹, Tao Wang¹, Cuidan Li⁴, Shundong Cang⁵

Affiliations

¹ Department of Oncology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, Henan Province, China.
² Department of Pathology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, Henan Province, China.
³ Department of Emergency, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, Henan Province, China.
⁴ CAS Key Laboratory of Genome Sciences & Information, Beijing Institute of Genomics, Chinese Academy of Sciences, China National Center for Bioinformation, Beijing, China.
⁵ Department of Oncology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, People's Hospital of Henan University, Zhengzhou, Henan Province, China. Electronic address: cangshundong@163.com.

PMID: 36117108
DOI: 10.1016/j.cllc.2022.08.007

Abstract

Background: We investigated the impact of factors that influence TP53 mutations on the efficacy of EGFR-tyrosine kinase inhibitors and potential treatment strategies.

Materials and methods: Tumor samples were collected to screen gene mutations by next-generation sequencing, as well as the patients' baseline characteristics. The overall response to treatment with TKIs was evaluated based on interval computed tomography scans at each follow-up time point. A Fisher's exact test and log-rank test were used to determine the statistical differences in this study.

Results: A total of 1134 clinical samples were collected from NSCLC patients, and TP53^mut was identified in 644 cases and EGFR^mut in 622 cases. A low frequency of TP53^mut or more than 50% EGFR co-mutation rate were related to the prognosis of TKI-treated patients. In addition, TP53^mut in the region outside of the DB domain had the strongest correlation with TKI resistance, whereas various types of mutations in the DB domain only had an impact on PFS. A grouping study of EGFR-TKI-based treatment revealed that EGFR-TKIs with chemotherapy were associated with more significant survival benefits for patients with prognostic TP53^mut, whereas EGFR-TKI therapy was favorable for TP53^wt patients. Furthermore, TP53^mut could shorten the time to the relapse of postoperative patients, who will also likely respond well to EGFR-TKIs with chemotherapy.

Conclusion: Various characteristics of TP53^mut affect the prognosis of TKI-treated patients to varying degrees. EGFR-TKIs with chemotherapy were benefit for patients' survival with prognostic TP53^mut, which provides an important reference for treatment management of EGFR^mut patients.

Keywords: EGFR-TKIs based combination therapy; EGFR-TKIs resistance; Prognosis; TP53 co-mutations.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

ErbB Receptors
Humans
Lung Neoplasms* / drug therapy
Lung Neoplasms* / genetics
Lung Neoplasms* / pathology
Mutation / genetics
Neoplasm Recurrence, Local / drug therapy
Protein Kinase Inhibitors / pharmacology
Tumor Suppressor Protein p53 / genetics
Tyrosine Kinase Inhibitors

Substances

Tyrosine Kinase Inhibitors
Protein Kinase Inhibitors
ErbB Receptors
TP53 protein, human
Tumor Suppressor Protein p53
EGFR protein, human