There was an error in Table 1 as published. The GSE103465 dataset includes a total of 6 samples, consisting of 3 controls and 3 patients. We inadvertently wrote “6 patients,” which was a typographical error. We sincerely apologize for this oversight. Our subsequent analyses were performed using the correct data from GSE103465 (3controls and 3 patients). This correction does not affect any part of the analysis or the conclusions drawn from the data. The corrected Table 1 appears below.
Table 1
| Diseases | GEO Series | GPL Platform | Sample Size | Group | |
|---|---|---|---|---|---|
| Control | Case | ||||
| PCOS | GSE10946 | GPL570 | 11 | 12 | Discovery cohort |
| GSE34526 | GPL570 | 3 | 7 | Discovery cohort | |
| GSE80432 | GPL6244 | 4 | 4 | Validation cohort | |
| RIF | GSE103465 | GPL16043 | 3 | 3 | Discovery cohort |
| GSE111974 | GPL17077 | 24 | 24 | Discovery cohort | |
| GSE26787 | GPL570 | 5 | 5 | Validation cohort | |
Details of GEO datasets used in the study.
PCOS, Polycystic Ovarian Syndrome; RIF, Recurrent Implantation Failure; GEO, Gene Expression Omnibus. Regarding GSE10946, we used both lean and obese non-PCOS samples as controls to avoid bias and reflect real-world metabolic diversity.
Also, there was an error in Figure 4C as published. We apologize for the typographical error in Figure 4C — the gene symbol was mistakenly written as “LCXD3” instead of the correct “PLCXD3”. The corrected Figure 4C appear below.
Figure 4
Lastly, there was an error in the legend for Table 1 as published. The corrected legend appears below.
“TABLE 1 Details of GEO datasets used in the study. PCOS: Polycystic Ovarian Syndrome, RIF: Recurrent Implantation Failure, GEO: Gene Expression Omnibus. Regarding GSE10946, we used both lean and obese non-PCOS samples as controls to avoid bias and reflect real-world metabolic diversity.”
The original version of this article has been updated.
Statements
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.
Summary
Keywords
PCOS (polycystic ovarian syndrome), RIF (Recurrent Implantation Failure), integrated transcriptome analysis, machine learning, TCA cycle
Citation
Chen W, Yang Q, Hu L, Wang M, Yang Z, Zeng X and Sun Y (2025) Correction: Shared diagnostic genes and potential mechanism between PCOS and recurrent implantation failure revealed by integrated transcriptomic analysis and machine learning. Front. Immunol. 16:1682282. doi: 10.3389/fimmu.2025.1682282
Received
08 August 2025
Accepted
12 August 2025
Published
25 August 2025
Volume
16 - 2025
Edited and reviewed by
Luz Pamela Blanco, National Institutes of Health (NIH), United States
Updates
Copyright
© 2025 Chen, Yang, Hu, Wang, Yang, Zeng and Sun.
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: Qingling Yang, qingling531@163.com; Yingpu Sun, syp2008@vip.sina.com
†These authors have contributed equally to this work
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.