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Tumor mutation burden-assisted risk stratification for papillary thyroid cancer

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Abstract

Purpose

Although papillary thyroid cancer (PTC) has a low mortality rate, the rate of recurrence remains relatively high. This study aims to develop a molecular signature to predict the recurrence of PTC.

Methods

A total of 333 PTC patients’ data from The Cancer Genome Atlas (TCGA) were included. We calculated tumor mutation burden (TMB) and analyzed the mutation status of BRAF and TERT promoter.

Results

Tumor recurrence occurred in 17 of 263 cases in TMB-L patients versus 14 of 70 cases in TMB-H patients (hazard ratio [HR], 3.55; 95% confidence interval [CI], 1.75–7.21; P < 0.001). The HR for recurrence in TMB-H patients remained significant after adjustment for classical clinicopathologic factors (patient age, gender, extrathyroidal extension and lymph node metastasis). These clinical factors had no effect on recurrence rate in TMB-L patients, but had a strong adverse effect on the prognosis of TMB-H patients. Compared with TMB-L patients lacking mutation, the HR (95% CI) of recurrence for TMB-H patients with coexisting BRAF V600E and/or TERT C228/250 T mutations was 6.68 (2.41–18.57), which remained significant after adjustment for clinicopathological factors. The mutation status of BRAF V600E and TERT C228/250 T had little effect on PTC recurrence in TMB-L patients. Either of the mutation was associated with high recurrence rate in TMB-H patients.

Conclusions

The presence of BRAF V600E and/or TERT promoter mutations denotes a high risk of recurrence in TMB-H patients. This represents a powerful molecular prognostic genotype that can help predict patients with the highest risk of recurrence.

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Fig. 1: The effects of TMB on PTC recurrence.
Fig. 2: Kaplan-Meier survival curves of interaction of TMB-H with clinicopathologic risk factors in affecting recurrence-free probability.
Fig. 3: Kaplan-Meier analyses of impacts of TMB-H or BRAF/TERT mutations or their coexistence on recurrence-free survival.

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Data availability

The datasets analyzed during the current study are available in the TCGA Data Portal, [https://tcga-data.nci.nih.gov/tcga/].

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Acknowledgements

The results published here are based upon data generated by the TCGA Research Network: http://cancergenome.nih.gov/.

Author contributions

Conceived idea: H.L.Z. and T.H.M.; Acquisition and analysis of data: Z.J.C. and W.R.W.; Data verification: J.J.X. and Y.T.S.; Interpretation of data: Z.J.C., W.R.W., J.J.X,. and Y.T.S. Investigation: Z.J.C., W.R.W., J.J.X., Y.T.S., H.L.Z., T.H.M., M.H.G., and H.X.G.; Writing-Review and Editing: Z.J.C., W.R.W., J.J.X., Y.T.S., T.H.M., M.H.G., and H.X.G.; Supervision: T.H.M., M.H.G., H.X.G.; All authors approved the final version of the manuscript.

Funding

This research did not receive any specific grant from any funding agency in the public, commercial or not-for-profit sector.

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Author notes

  1. These authors contributed equally: Zhijiang Chen, Weiran Wang, Jiajie Xu, Yuntao Song

Authors and Affiliations

  1. Department of Endocrinology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong Province, China

    Zhijiang Chen & Haixia Guan

  2. Department of Translational Medicine, Genetron Health (Beijing) Technology, Co. Ltd., Beijing, China

    Weiran Wang, Honglin Zhu & Tonghui Ma

  3. Key Laboratory of Endocrine Gland Diseases of Zhejiang Province, Otolaryngology & Head and Neck Center, Cancer Center, Department of Head and Neck Surgery, Zhejiang Provincial People’s Hospital (Afliated People’s Hospital, Hangzhou Medical College), Hangzhou, Zhejiang Province, China

    Jiajie Xu & Minghua Ge

  4. Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Head and Neck Surgery, Peking University Cancer Hospital and Institute, Beijing, China

    Yuntao Song

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Chen, Z., Wang, W., Xu, J. et al. Tumor mutation burden-assisted risk stratification for papillary thyroid cancer. Endocrine 78, 296–305 (2022). https://doi.org/10.1007/s12020-022-03154-0

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  • DOI: https://doi.org/10.1007/s12020-022-03154-0

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