TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors
BackgroundThe 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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-08-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2025.1630707/full |
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| author | Zhonghuang Wang Zhonghuang Wang Zhe Zhang Dongli Zhao Dongli Zhao Zhenglin Du Bixia Tang Enhui Jin Hailong Kang Wenming Zhao Yuanguang Meng |
| author_facet | Zhonghuang Wang Zhonghuang Wang Zhe Zhang Dongli Zhao Dongli Zhao Zhenglin Du Bixia Tang Enhui Jin Hailong Kang Wenming Zhao Yuanguang Meng |
| author_sort | Zhonghuang Wang |
| collection | DOAJ |
| description | BackgroundThe 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.MethodsWe 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.ResultThe 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.ConclusionsOur 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. |
| format | Article |
| id | doaj-art-798a3b8d84c24c8fb18ee98da6393c80 |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj-art-798a3b8d84c24c8fb18ee98da6393c802025-08-20T03:39:26ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2025-08-011510.3389/fonc.2025.16307071630707TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumorsZhonghuang Wang0Zhonghuang Wang1Zhe Zhang2Dongli Zhao3Dongli Zhao4Zhenglin Du5Bixia Tang6Enhui Jin7Hailong Kang8Wenming Zhao9Yuanguang Meng10National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, ChinaChangping Laboratory, Beijing, ChinaDepartment of Obstetrics and Gynecology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, ChinaDepartment of Obstetrics and Gynecology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, ChinaGynecological Mini-Invasive Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing, ChinaNational Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, ChinaNational Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, ChinaNational Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, ChinaNational Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, ChinaNational Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences/China National Center for Bioinformation, Beijing, ChinaDepartment of Obstetrics and Gynecology, Seventh Medical Center of Chinese PLA General Hospital, Beijing, ChinaBackgroundThe 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.MethodsWe 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.ResultThe 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.ConclusionsOur 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.https://www.frontiersin.org/articles/10.3389/fonc.2025.1630707/fullovarian tumorsTCRBCRmachine learningbiomarks |
| spellingShingle | Zhonghuang Wang Zhonghuang Wang Zhe Zhang Dongli Zhao Dongli Zhao Zhenglin Du Bixia Tang Enhui Jin Hailong Kang Wenming Zhao Yuanguang Meng TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors Frontiers in Oncology ovarian tumors TCR BCR machine learning biomarks |
| title | TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors |
| title_full | TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors |
| title_fullStr | TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors |
| title_full_unstemmed | TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors |
| title_short | TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors |
| title_sort | tcr and bcr repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors |
| topic | ovarian tumors TCR BCR machine learning biomarks |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2025.1630707/full |
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