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Clinical Studies

Circulating small extracellular vesicle-based miRNA classifier for follicular thyroid carcinoma: a diagnostic study

British Journal of Cancer volume 130, pages 925–933 (2024)Cite this article

Subjects

Abstract

Background

The diagnosis of follicular thyroid carcinoma (FTC) prior to surgery remains a major challenge in the clinic.

Methods

This multicentre diagnostic study involved 41 and 150 age- and sex-matched patients in the training cohort and validation cohort, respectively. The diagnostic properties of circulating small extracellular vesicle (sEV)-associated and cell-free RNAs were compared by RNA sequencing in the training cohort. Subsequently, using a quantitative real-time polymerase chain reaction (qRT‒PCR) assay, high-quality candidates were identified to construct an RNA classifier for FTC and verified in the validation cohort. The parallel expression, stability and influence of the RNA classifier on surgical strategy were also investigated.

Results

The diagnostic properties of sEV long RNAs, cell-free long RNAs and sEV microRNAs (miRNAs) were comparable and superior to those of cell-free miRNAs in RNA sequencing. Given the clinical application, the circulating sEV miRNA (CirsEV-miR) classifier was developed from five miRNAs based on qRT‒PCR data, which could well identify FTC patients (area under curve [AUC] of 0.924 in the training cohort and 0.844 in the multicentre validation cohort). Further tests revealed that the CirsEV-miR score was significantly correlated with the tumour burden, and the levels of sEV miRNAs were also higher in sEVs from the FTC cell line, organoid and tissue. Additionally, circulating sEV miRNAs remained constant after different treatments, and the addition of the CirsEV-miR classifier as a biomarker improves the current surgical strategy.

Conclusions

The CirsEV-miR classifier could serve as a noninvasive, convenient, specific and stable auxiliary test to help diagnose FTC following ultrasonography.

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Fig. 1: Flow diagrams showing the overall study design and patients in the training and validation cohorts.
Fig. 2: Identification of circulating candidates for FTC in the training set.
Fig. 3: Classifier development and validation process for FTC.
Fig. 4: Parallel expression and stability of circulating sEV miRNAs.

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Data availability

The sequencing data have been deposited in GEO under accession code GSE221088. The other data used during the current study are available from the corresponding author on reasonable request.

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Funding

This study was supported by grants from the National Natural Science Foundation of China (82173245, 82300881); the Sichuan Science and Technology Program (2023YFS0148 and 2023YFS0149); 1·3·5 Project for Disciplines of Excellence-Clinical Research Incubation Project and Science and Technology Achievement Transformation Project, West China Hospital, Sichuan University (21HXFH005, CGZH21004); the Fundamental Research Funds for the Central Universities (2022SCU12061) and the postdoctoral project, West China Hospital, Sichuan University (2023HXBH051).

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Author notes

  1. These authors contributed equally: Genpeng Li, Hongke Wang.

Authors and Affiliations

  1. Division of Thyroid Surgery, Department of General Surgery, West China Hospital, Sichuan University, Chengdu, China

    Genpeng Li, Wenjie Chen, Jing Huang, Yuting Shao, Jiaye Liu, Tao Wei, Rixiang Gong, Jingqiang Zhu, Zhihui Li & Jianyong Lei

  2. The Laboratory of Thyroid and Parathyroid Disease, Frontiers Science Center for Disease-related Molecular Network, West China Hospital of Sichuan University, Chengdu, China

    Genpeng Li, Wenjie Chen, Jing Huang, Yuting Shao, Jiaye Liu, Tao Wei, Rixiang Gong, Jingqiang Zhu, Zhihui Li & Jianyong Lei

  3. MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Life Sciences, Tsinghua University, Beijing, China

    Hongke Wang, Yilan Bai & Zhi Lu

  4. Department of Pathology, West China Hospital of Sichuan University, Chengdu, China

    Jinjing Zhong

  5. Head and Neck Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China

    Ke Jiang

  6. Thyroid Surgery, West China Tianfu Hospital, Chengdu, China

    Yanping Gong

  7. Thyroid and Breast Surgery, West China Fourth Hospital, Chengdu, China

    Junhui Zhang

  8. Department of Head and Neck Surgery, Sichuan Provincial Cancer Hospital, Chengdu, China

    Ronghao Sun

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  1. Genpeng Li
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Contributions

Z Li and J Lei were responsible for study conception, design and supervision. Y Gong, J Zhang, R Sun, T Wei, R Gong, J Zhu and Z Li provided the clinical specimens. H Wang, Y Bai and Z Lu performed the RNA sequencing and bioinformatic analysis. J Liu provided the organoids. G Li, J Zhong, W Chen and J Huang performed the qRT‒PCR validation, questionnaire collection and data analysis. G Li, H Wang, J Zhong and J Lei wrote and revised the manuscript. All the authors read and approved the final manuscript. G Li and H Wang contributed equally to this work and could be co-first authors.

Corresponding author

Correspondence to Jianyong Lei.

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The authors declare no competing interests.

Ethics approval and consent to participate

This study was approved by the institutional ethics review board of West China Hospital of Sichuan University (number: 2019 (507)), and informed consent was obtained from each patient.

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Li, G., Wang, H., Zhong, J. et al. Circulating small extracellular vesicle-based miRNA classifier for follicular thyroid carcinoma: a diagnostic study. Br J Cancer 130, 925–933 (2024). https://doi.org/10.1038/s41416-024-02575-0

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