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CORRECTION article

Front. Endocrinol., 10 December 2025

Sec. Cancer Endocrinology

Volume 16 - 2025 | https://doi.org/10.3389/fendo.2025.1738698

This article is part of the Research TopicNew potential biomarkers and cellular strategies for the study of prostate cancer and testicular cancer cellsView all 11 articles

Correction: TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models

Yutong Wang,,,,&#x;Yutong Wang1,2,3,4,5†Ailing Yu,,,,&#x;Ailing Yu1,2,3,4,6†Ziping Gao,,,&#x;Ziping Gao1,2,3,4†Xiaoying YuanXiaoying Yuan7Xiaochen DuXiaochen Du8Peng ShiPeng Shi9Haoyun GuanHaoyun Guan9Shuang WenShuang Wen10Honglong WangHonglong Wang10Liang Wang,,,*Liang Wang1,2,3,4*Bo Fan,,,*&#x;Bo Fan1,2,3,4*‡Zhiyu Liu,,,*Zhiyu Liu1,2,3,4*
  • 1Department of Urology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
  • 2Liaoning Provincial Key Laboratory of Urological Digital Precision Diagnosis and Treatment, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
  • 3Department of Urology, Liaoning Engineering Research Center of Integrated Precision Diagnosis and Treatment Technology for Urological Cancer, Dalian, Liaoning, China
  • 4Dalian Key Laboratory of Prostate Cancer Research, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China
  • 5Department of Colorectal Surgery, Dalian Municipal Central Hospital, Dalian, Liaoning, China
  • 6First Clinical College, Dalian Medical University, Dalian, Liaoning, China
  • 7Department of Anatomy, College of Basic Medicine, Dalian Medical University, Dalian, Liaoning, China
  • 8College of Humanities and Social Sciences, Dalian Medical University, Dalian, Liaoning, China
  • 9Second Clinical College, Dalian Medical University, Dalian, Liaoning, China
  • 10Department of Pathology, Dalian Friendship Hospital, Dalian, China

A Correction on
TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models

By Wang Y, Yu A, Gao Z, Yuan X, Du X, Shi P, Guan H, Wen S, Wang H, Wang L, Fan B and Liu Z (2025) Front. Endocrinol. 16:1568665. doi: 10.3389/fendo.2025.1568665

There was a mistake in Figure 4A as published. The image in Figure 4A was inadvertently duplicated in Figure 7A due to a technical oversight during the figure assembly process. The corrected Figure 4A appears below.

Figure 4
A composite image with four panels:  A: A nomogram assessing survival probability based on Gleason score, pathological stage, TET2 mutation, and perineural invasion, showing total points and survival rates over three to five years.  B: Kaplan-Meier survival curve comparing overall survival for pathological T1c versus T2 or more, with T1c having higher survival probability. P-value is less than 0.001.  C: Kaplan-Meier survival curve comparing overall survival based on Gleason scores. Lower scores show higher survival probability. P-value is 0.005.  D: Kaplan-Meier survival curve comparing TET2 mutant versus non-mutant, with non-mutant showing better survival. P-value is less than 0.001.

Figure 4. Prognostic modeling and survival analysis in transition zone prostate cancer. (A) Nomogram integrating clinicopathological variables for predicting 3-, 4-, and 5-year overall survival probabilities. (B) Kaplan-Meier curves stratified by pathological T stage. (C) Survival differentiation across Gleason grade groups. (D) Comparative survival analysis by TET2 mutation status.

The original version of this article has been updated.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: transition zone, prostate cancer, whole-exome sequencing, driver genes, medication prediction, TET2 mutation, machine learning models

Citation: Wang Y, Yu A, Gao Z, Yuan X, Du X, Shi P, Guan H, Wen S, Wang H, Wang L, Fan B and Liu Z (2025) Correction: TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models. Front. Endocrinol. 16:1738698. doi: 10.3389/fendo.2025.1738698

Received: 03 November 2025; Accepted: 28 November 2025;
Published: 10 December 2025.

Edited and reviewed by:

Jorge Adrián Ramírez De Arellano Sánchez, University of Guadalajara, Mexico

Copyright © 2025 Wang, Yu, Gao, Yuan, Du, Shi, Guan, Wen, Wang, Wang, Fan and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Liang Wang, d2FuZ2xkb2N0QHNpbmEuY29t; Bo Fan, ZmFuYm9AZG11LmVkdS5jbg==; Zhiyu Liu, bHp5ZG9jdEAxNjMuY29t

These authors have contributed equally to this work

ORCID: Bo Fan, orcid.org/0000-0001-6598-3237

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.