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Novel alternative tools for metastatic pheochromocytomas/paragangliomas prediction

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Abstract

Objective

The existing prediction models for metastasis in pheochromocytomas/paragangliomas (PPGLs) showed high heterogeneity in different centers. Therefore, this study aimed to establish new prediction models integrating multiple variables based on different algorithms.

Design and methods

Data of patients with PPGLs undergoing surgical resection at the Peking Union Medical College Hospital from 2007 to 2022 were collected retrospectively. Patients were randomly divided into the training and testing sets in a ratio of 7:3. Subsequently, decision trees, random forest, and logistic models were constructed for metastasis prediction with the training set and Cox models for metastasis-free survival (MFS) prediction with the total population. Additionally, Ki-67 index and tumor size were transformed into categorical variables for adjusting models. The testing set was used to assess the discrimination and calibration of models and the optimal models were visualized as nomograms. Clinical characteristics and MFS were compared between patients with and without risk factors.

Results

A total of 198 patients with 59 cases of metastasis were included and classified into the training set (n = 138) and testing set (n = 60). Among all models, the logistic regression model showed the best discrimination for metastasis prediction with an AUC of 0.891 (95% CI, 0.793–0.990), integrating SDHB germline mutations [OR: 96.72 (95% CI, 16.61–940.79)], S-100 (-) [OR: 11.22 (95% CI, 3.04–58.51)], ATRX (-) [OR: 8.42 (95% CI, 2.73–29.24)] and Ki-67 ≥ 3% [OR: 7.98 (95% CI, 2.27–32.24)] evaluated through immunohistochemistry (IHC), and tumor size ≥ 5 cm [OR: 4.59 (95% CI, 1.34–19.13)]. The multivariate Cox model including the above risk factors also showed a high C-index of 0.860 (95% CI, 0.810–0.911) in predicting MFS after surgery. Furthermore, patients with the above risk factors showed a significantly poorer MFS (P ≤ 0.001).

Conclusions

Models established in this study provided alternative and reliable tools for clinicians to predict PPGLs patients’ metastasis and MFS. More importantly, this study revealed for the first time that IHC of ATRX could act as an independent predictor of metastasis in PPGLs.

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Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

References

  1. Beard CM, Sheps SG, Kurland LT, Carney JA, Lie JT (1983) Occurrence of pheochromocytoma in Rochester, Minnesota, 1950 through 1979. Mayo Clin Proc 58(12):802–804

    CAS  PubMed  Google Scholar 

  2. Lenders JW, Duh QY, Eisenhofer G et al (2014) Pheochromocytoma and paraganglioma: an endocrine society clinical practice guideline. J Clin Endocrinol Metab 99(6):1915–1942. https://doi.org/10.1210/jc.2014-1498

    Article  CAS  PubMed  Google Scholar 

  3. Lam AK (2017) Update on adrenal tumours in 2017 world health organization (WHO) of endocrine tumours. Endocr Pathol 28(3):213–227. https://doi.org/10.1007/s12022-017-9484-5

    Article  PubMed  Google Scholar 

  4. Eisenhofer G, Bornstein SR, Brouwers FM et al (2004) Malignant pheochromocytoma: current status and initiatives for future progress. Endocr Relat Cancer 11(3):423–436. https://doi.org/10.1677/erc.1.00829

    Article  CAS  PubMed  Google Scholar 

  5. Hescot S, Leboulleux S, Amar L et al (2013) One-year progression-free survival of therapy-naive patients with malignant pheochromocytoma and paraganglioma. J Clin Endocrinol Metab 98(10):4006–4012. https://doi.org/10.1210/jc.2013-1907

    Article  CAS  PubMed  Google Scholar 

  6. Turkova H, Prodanov T, Maly M et al (2016) Characteristics and outcomes of metastatic sdhb and sporadic pheochromocytoma/paraganglioma: an national institutes of health study. Endocr Pract 22(3):302–314. https://doi.org/10.4158/ep15725.Or

    Article  PubMed  Google Scholar 

  7. Gimenez-Roqueplo AP, Favier J, Rustin P et al (2003) Mutations in the SDHB gene are associated with extra-adrenal and/or malignant phaeochromocytomas. Cancer Res 63(17):5615–5621

    CAS  PubMed  Google Scholar 

  8. King KS, Prodanov T, Kantorovich V et al (2011) Metastatic pheochromocytoma/paraganglioma related to primary tumor development in childhood or adolescence: significant link to SDHB mutations. J Clin Oncol 29(31):4137–4142. https://doi.org/10.1200/jco.2011.34.6353

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Schovanek J, Martucci V, Wesley R et al (2014) The size of the primary tumor and age at initial diagnosis are independent predictors of the metastatic behavior and survival of patients with SDHB-related pheochromocytoma and paraganglioma: a retrospective cohort study. BMC Cancer 14:523. https://doi.org/10.1186/1471-2407-14-523

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hamidi O, Young WF Jr, Iñiguez-Ariza NM et al (2017) Malignant pheochromocytoma and paraganglioma: 272 patients over 55 years. J Clin Endocrinol Metab 102(9):3296–3305. https://doi.org/10.1210/jc.2017-00992

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ayala-Ramirez M, Feng L, Johnson MM et al (2011) Clinical risk factors for malignancy and overall survival in patients with pheochromocytomas and sympathetic paragangliomas: primary tumor size and primary tumor location as prognostic indicators. J Clin Endocrinol Metab 96(3):717–725. https://doi.org/10.1210/jc.2010-1946

    Article  CAS  PubMed  Google Scholar 

  12. Zelinka T, Musil Z, Dušková J et al (2011) Metastatic pheochromocytoma: does the size and age matter? Eur J Clin Invest 41(10):1121–1128. https://doi.org/10.1111/j.1365-2362.2011.02518.x

    Article  PubMed  PubMed Central  Google Scholar 

  13. Cho YY, Kwak MK, Lee SE et al (2018) A clinical prediction model to estimate the metastatic potential of pheochromocytoma/paraganglioma: ASES score. Surgery 164(3):511–517. https://doi.org/10.1016/j.surg.2018.05.001

    Article  PubMed  Google Scholar 

  14. Strong VE, Kennedy T, Al-Ahmadie H et al (2008) Prognostic indicators of malignancy in adrenal pheochromocytomas: clinical, histopathologic, and cell cycle/apoptosis gene expression analysis. Surgery 143(6):759–768. https://doi.org/10.1016/j.surg.2008.02.007

    Article  PubMed  Google Scholar 

  15. Salmenkivi K, Heikkilä P, Haglund C, Louhimo J, Arola J (2003) Lack of histologically suspicious features, proliferative activity, and p53 expression suggests benign diagnosis in phaeochromocytomas. Histopathology 43(1):62–71. https://doi.org/10.1046/j.1365-2559.2003.01645.x

    Article  CAS  PubMed  Google Scholar 

  16. Feng F, Zhu Y, Wang X et al (2011) Predictive factors for malignant pheochromocytoma: analysis of 136 patients. J Urol 185(5):1583–1590. https://doi.org/10.1016/j.juro.2010.12.050

    Article  PubMed  Google Scholar 

  17. Eisenhofer G, Lenders JW, Siegert G et al (2012) Plasma methoxytyramine: a novel biomarker of metastatic pheochromocytoma and paraganglioma in relation to established risk factors of tumour size, location and SDHB mutation status. Eur J Cancer 48(11):1739–1749. https://doi.org/10.1016/j.ejca.2011.07.016

    Article  CAS  PubMed  Google Scholar 

  18. Crona J, Lamarca A, Ghosal S, Welin S, Skogseid B, Pacak K (2019) Genotype-phenotype correlations in pheochromocytoma and paraganglioma: a systematic review and individual patient meta-analysis. Endocr Relat Cancer 26(5):539–550. https://doi.org/10.1530/erc-19-0024

    Article  CAS  PubMed  Google Scholar 

  19. Thompson LD (2002) Pheochromocytoma of the adrenal gland scaled score (PASS) to separate benign from malignant neoplasms: a clinicopathologic and immunophenotypic study of 100 cases. Am J Surg Pathol 26(5):551–566. https://doi.org/10.1097/00000478-200205000-00002

    Article  PubMed  Google Scholar 

  20. Kimura N, Takayanagi R, Takizawa N et al (2014) Pathological grading for predicting metastasis in phaeochromocytoma and paraganglioma. Endocr Relat Cancer 21(3):405–414. https://doi.org/10.1530/erc-13-0494

    Article  PubMed  Google Scholar 

  21. Koh JM, Ahn SH, Kim H et al (2017) Validation of pathological grading systems for predicting metastatic potential in pheochromocytoma and paraganglioma. PLoS ONE 12(11):e0187398. https://doi.org/10.1371/journal.pone.0187398

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Pierre C, Agopiantz M, Brunaud L et al (2019) COPPS, a composite score integrating pathological features, PS100 and SDHB losses, predicts the risk of metastasis and progression-free survival in pheochromocytomas/paragangliomas. Virchows Arch 474(6):721–734. https://doi.org/10.1007/s00428-019-02553-5

    Article  CAS  PubMed  Google Scholar 

  23. van Nederveen FH, Gaal J, Favier J et al (2009) An immunohistochemical procedure to detect patients with paraganglioma and phaeochromocytoma with germline SDHB, SDHC, or SDHD gene mutations: a retrospective and prospective analysis. Lancet Oncol 10(8):764–771. https://doi.org/10.1016/s1470-2045(09)70164-0

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lee H, Jeong S, Yu Y et al (2020) Risk of metastatic pheochromocytoma and paraganglioma in SDHx mutation carriers: a systematic review and updated meta-analysis. J Med Genet 57(4):217–225. https://doi.org/10.1136/jmedgenet-2019-106324

    Article  CAS  PubMed  Google Scholar 

  25. Zhang X, Lian P, Su M et al (2021) Single-cell transcriptome analysis identifies a unique tumor cell type producing multiple hormones in ectopic ACTH and CRH secreting pheochromocytoma. Elife. https://doi.org/10.7554/eLife.68436

    Article  PubMed  PubMed Central  Google Scholar 

  26. Unger P, Hoffman K, Pertsemlidis D, Thung S, Wolfe D, Kaneko M (1991) S100 protein-positive sustentacular cells in malignant and locally aggressive adrenal pheochromocytomas. Arch Pathol Lab Med 115(5):484–487

    CAS  PubMed  Google Scholar 

  27. Kumaki N, Kajiwara H, Kameyama K et al (2002) Prediction of malignant behavior of pheochromocytomas and paragangliomas using immunohistochemical techniques. Endocr Pathol Summer 13(2):149–156. https://doi.org/10.1385/ep:13:2:149

    Article  Google Scholar 

  28. Job S, Draskovic I, Burnichon N et al (2019) Telomerase activation and ATRX mutations are independent risk factors for metastatic pheochromocytoma and paraganglioma. Clin Cancer Res 25(2):760–770. https://doi.org/10.1158/1078-0432.Ccr-18-0139

    Article  CAS  PubMed  Google Scholar 

  29. Singhi AD, Liu TC, Roncaioli JL et al (2017) Alternative lengthening of telomeres and loss of DAXX/ATRX expression predicts metastatic disease and poor survival in patients with pancreatic neuroendocrine tumors. Clin Cancer Res 23(2):600–609. https://doi.org/10.1158/1078-0432.Ccr-16-1113

    Article  CAS  PubMed  Google Scholar 

  30. Hsu YR, Torres-Mora J, Kipp BR et al (2019) Clinicopathological, immunophenotypic and genetic studies of mediastinal paragangliomas†. Eur J Cardiothorac Surg 56(5):867–875. https://doi.org/10.1093/ejcts/ezz115

    Article  PubMed  Google Scholar 

  31. Liau JY, Tsai JH, Jeng YM, Lee JC, Hsu HH, Yang CY (2015) Leiomyosarcoma with alternative lengthening of telomeres is associated with aggressive histologic features, loss of ATRX expression, and poor clinical outcome. Am J Surg Pathol 39(2):236–244. https://doi.org/10.1097/pas.0000000000000324

    Article  PubMed  Google Scholar 

  32. Liau JY, Tsai JH, Yang CY et al (2015) Alternative lengthening of telomeres phenotype in malignant vascular tumors is highly associated with loss of ATRX expression and is frequently observed in hepatic angiosarcomas. Hum Pathol 46(9):1360–1366. https://doi.org/10.1016/j.humpath.2015.05.019

    Article  CAS  PubMed  Google Scholar 

  33. Zhou Y 2023 Data from: Novel alternative tools for metastatic pheochromocytomas/paragangliomas prediction. https://doi.org/10.7910/DVN/HWBD74

  34. Richards S, Aziz N, Bale S et al (2015) Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American college of medical genetics and genomics and the association for molecular pathology. Genet Med 17(5):405–424. https://doi.org/10.1038/gim.2015.30

    Article  PubMed  PubMed Central  Google Scholar 

  35. Nölting S, Bechmann N, Taieb D et al (2022) Personalized management of pheochromocytoma and paraganglioma. Endocr Rev 43(2):199–239. https://doi.org/10.1210/endrev/bnab019

    Article  PubMed  Google Scholar 

  36. Cui Y, Ma X, Gao Y et al (2021) Local-regional recurrence of pheochromocytoma/paraganglioma: characteristics, risk factors and outcomes. Front Endocrinol (Lausanne) 12:762548. https://doi.org/10.3389/fendo.2021.762548

    Article  PubMed  Google Scholar 

  37. Dyer MA, Qadeer ZA, Valle-Garcia D, Bernstein E (2017) ATRX and DAXX: Mechanisms and mutations. Cold Spring Harb Perspect Med. https://doi.org/10.1101/cshperspect.a026567

    Article  PubMed  PubMed Central  Google Scholar 

  38. Yang CY, Liau JY, Huang WJ et al (2015) Targeted next-generation sequencing of cancer genes identified frequent TP53 and ATRX mutations in leiomyosarcoma. Am J Transl Res 7(10):2072–2081

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Fishbein L, Khare S, Wubbenhorst B et al (2015) Whole-exome sequencing identifies somatic ATRX mutations in pheochromocytomas and paragangliomas. Nat Commun 6:6140. https://doi.org/10.1038/ncomms7140

    Article  CAS  PubMed  Google Scholar 

  40. Heaphy CM, de Wilde RF, Jiao Y et al (2011) Altered telomeres in tumors with ATRX and DAXX mutations. Science 333(6041):425. https://doi.org/10.1126/science.1207313

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Pacurari M, Addison JB, Bondalapati N et al (2013) The microRNA-200 family targets multiple non-small cell lung cancer prognostic markers in H1299 cells and BEAS-2B cells. Int J Oncol 43(2):548–560. https://doi.org/10.3892/ijo.2013.1963

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This research was supported by the CAMS Innovation Fund for Medical Sciences (CIFMS) (grant number 2021-I2M-C&T-B-002), and the National High Level Hospital Clinical Research Funding (grant number 2022-PUMCH-C-028).

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Author notes

  1. Y. Cui and Y. Zhou contributed equally to this work.

Authors and Affiliations

  1. Department of Endocrinology, Key Laboratory of Endocrinology, National Health Commission of the People’s Republic of China, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, People’s Republic of China

    Cui Y., Y. Zhou, Y. Gao, X. Ma, Y. Wang, T. Zhou, S. Chen, L. Lu, A. Tong & Y. Li

  2. Department of Urology Surgery, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, People’s Republic of China

    X. Zhang

  3. Medical Research Center, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, People’s Republic of China

    Y. Zhang

  4. Department of Pathology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, People’s Republic of China

    X. Chang

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Correspondence to X. Chang or A. Tong.

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This study was approved by the ethics committees of Peking Union Medical College Hospital (JS-3535).

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Cui, Y., Zhou, Y., Gao, Y. et al. Novel alternative tools for metastatic pheochromocytomas/paragangliomas prediction. J Endocrinol Invest 47, 1191–1203 (2024). https://doi.org/10.1007/s40618-023-02239-5

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