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Data Sheet 1_TCR and BCR repertoire analysis reveals distinct signatures between benign and malignant ovarian tumors.pdf

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Data_Sheet_1_TCR_and_BCR_repertoire_analysis_reveals_distinct_signatures_between_benign_and_malignant_ovarian_tumors_pdf/29878592
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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.
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2025-08-11
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