ORIGINAL RESEARCH article
Front. Oncol.
Sec. Cancer Genetics
Volume 15 - 2025 | doi: 10.3389/fonc.2025.1630707
TCR and BCR Repertoire Analysis Reveals Distinct Signatures Between Benign and Malignant Ovarian Tumors
Provisionally accepted- 1National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences (CAS), Beijing, China
- 2Changping Laboratory, Beijing, P. R. China., Beijing, China
- 3Department of Obstetrics and Gynecology, Seventh Medical Center of Chinese PLA General Hospital, Beijing 100700, China, Beijing, China
- 4Gynecological Mini-Invasive Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, China
- 5National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing 100101, China, Beijing, China
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Background: The immune system is of paramount importance in maintaining human health and defending against pathogens. Among them, the adaptive immune system is a crucial component of the immune system, as it is responsible for generating and modulating the immune repertoire, which is vital for immune responses.We conducted a comprehensive analysis of T cell receptor (TCR) and B cell receptor (BCR) clonotypes in the peripheral blood immune repertoire of 20 patients with benign and malignant ovarian tumors. The analysis elucidates the differences between the two immune repertoires in various aspects and constructs an early screening machine learning model for ovarian tumors based on the characteristics of the immune repertoire.The finding revealed that patients with malignant ovarian tumors exhibited a reduction in balance, richness, and diversity in their immune repertoires compared to those with benign tumors. Additionally, there was a negative correlation between patient age and immune repertoire diversity, and the immune repertoire of patients with malignant tumors displayed high heterogeneity. By employing machine learning techniques, we have developed an early screening model based on 16 TCR V-J genes and 11 BCR V-J genes, which achieved an average AUC of 0.93 (TCR) and 0.958 (BCR) on the ovarian tumor test dataset. Moreover, a comparison of the spatial distributions of TCR and BCR revealed, for the first time, that TCR was more significantly associated with the benign-to-malignant transformation of ovarian tumors.Our study highlights the critical role of the adaptive immune repertoire in distinguishing between benign and malignant ovarian tumors. TCR demonstrated more distinct spatial distribution patterns between benign and malignant states, suggesting its potential as a more sensitive biomarker for ovarian tumor detection.These findings provide new insights into the immunological landscape of ovarian tumors and offer a promising avenue for early diagnosis and prognosis assessment.
Keywords: Ovarian tumors, tcr, BCR, machine learning, Biomarks
Received: 22 May 2025; Accepted: 14 Jul 2025.
Copyright: © 2025 Wang, Zhang, Zhao, Du, Tang, Jin, Kang, Zhao and Meng. 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) or licensor 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: Yuanguang Meng, Department of Obstetrics and Gynecology, Seventh Medical Center of Chinese PLA General Hospital, Beijing 100700, China, Beijing, China
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