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Pediatric papillary thyroid carcinoma

ABSTRACT: Pediatric patients with papillary thyroid carcinoma currently lack widely adopted risk stratification criteria, which leads to a lack of individualized treatment and prognosis assessments. In this retrospective study, 83 pediatric benign (PB), 85 pediatric malignant (PM) and 66 adult malignant (AM) thyroid nodules were evaluated, and 10,426 proteins were quantified by mass spectrometry. We found 243 significantly dysregulated proteins from the PM vs. PB and 122 from PM vs. AM. Function and pathway analyses showed the enhanced activation of the inflammatory and immune system in pediatric malignant patients compared with the others. Nineteen proteins were selected to predict recurrence using a machine learning model with an accuracy of 88.24%. Our study generated a protein-based personalized prognostic prediction model that can stratify pediatric patients with papillary thyroid carcinoma into high or low recurrence risk groups, providing a reference for clinical decision-making and individualized treatment.

ORGANISM(S): Homo Sapiens

SUBMITTER: Tiannan Guo

PROVIDER: PXD050347 | iProX | Tue Mar 05 00:00:00 GMT 2024

REPOSITORIES: iProX

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Project description:Background: With the incidence of papillary thyroid carcinoma rising worldwide, the decision about lobectomy versus total thyroidectomy will become relevant for an increasing number of patients. There exists no reliable biomarker for metastatic potential or tendency of recurrence that could assist in the risk stratification of patients. Objective: To develop a gene expression classifier for metastatic potential by measuring RNA expression in the primary tumor at the time of cancer surgery. Further, to investigate the ability of the gene expression classifier to identify metastatic and recurrent cases. Method: Genome-wide expression analyses. The development cohort consisted of freshly frozen tissues from 38 patients collected between the years 1986 and 2009. Validation was performed on a consecutive cohort of formalin fixated paraffin embedded surgical tissue specimens from 183 patients treated at Odense and Aarhus University Hospitals. Results: A 17 gene classifier (ADAMTS1, ANTXR1, C7, CXCL12, EBF1, FBLN2, FOSL2, GGT5, GPR124, JAM3, LRIG1, NDRG1, PRRX1, ROBO1, SORL1, TCF4, and ZEB1) was identified based on the expression values of these genes in the groups with and without metastasis in the development cohort. The 17 gene classifier for regional and/or distant metastasis identified was tested against the clinical status in the validation cohort. Sensitivity was 51.6% (95% CI 41.2%-61.8) and specificity 61.6 % (95% CI 50.5%-71.9%). Further, the Kaplan-Meyer method was used to estimate whether the classifier was useful as a prognostic marker for recurrences. Log-rank testing failed to identify any significance (p=0.32). Conclusion: A 17 gene classifier for metastatic potential was developed, and the results showed a clear biological difference between groups. However, through validation, the prognostic significance of this classifier could not be shown in identifying metastatic cases or in the ability of dichotomizing patients according to risk of recurrence after primary treatment. 38 patients with papillary thyroid carcinoma from a consecutive cohort of patients, no replicates

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Pediatric papillary thyroid carcinoma

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