Recurrence of Papillary Thyroid Cancer: A Systematic Appraisal of Risk Factors

Abstract

Background Thyroid cancer recurrence is associated with increased mortality and adverse outcomes. Recurrence risk is currently predicted using clinical tools, often restaging patients after treatment. Detailed understanding of recurrence risk at disease-onset could lead to personalised and improved patient care. Objective To perform a comprehensive bioinformatic and experimental analysis of 3 levels of genetic change (mRNA, microRNA, and somatic mutation) apparent in recurrent tumours and construct a new combinatorial prognostic risk model. Methods We analysed The Cancer Genome Atlas data (TCGA) to identify differentially expressed genes (mRNA/microRNA) in 46 recurrent versus 455 non-recurrent thyroid tumours. Two exonic mutational pipelines were used to identify somatic mutations. Functional gene analysis was performed in cell-based assays in multiple thyroid cell lines. The prognostic value of genes was evaluated with TCGA datasets. Results We identified a total of 128 new potential biomarkers associated with recurrence, including 40 mRNAs, 39 miRNAs and 59 genetic variants. Among differentially expressed genes, modulation of FN1, ITGα3 and MET had a significant impact on thyroid cancer cell migration. Similarly, ablation of miR-486 and miR-1179 significantly increased migration of TPC-1 and SW1736 cells. We further utilised genes with a validated functional role and identified a 5 gene risk score classifier as an independent predictor of thyroid cancer recurrence. Conclusions Our newly proposed risk model based on combinatorial mRNA and microRNA expression has potential clinical utility as a prognostic indicator of recurrence. These findings should facilitate earlier prediction of recurrence with implications for improving patient outcome by tailoring treatment to disease risk and increasing post-treatment surveillance.

LINC02454 related key pathways and genes in papillary thyroid cancer by weighted gene co-expression network analysis (WGCNA)

“…Moreover, Sponziello et al observed that FN1 was increased in aggressive thyroid cancer and governed thyroid cancer cells proliferation, adhesion, migration, and invasion(Sponziello et al 2016). Additionally, according to Nieto et al's research, FN1 was signi cantly upregulated in recurrent thyroid cancer and impacted cellular migration, highlighting it as a potential prognostic biomarker(Nieto et al 2022).In agreement with above study, we revealed that FN1 was signi cantly upregulated in PTC. Moreover, we found FN1 was the LINC02454 co-expressed gene involved in ECM − receptor interaction pathway.…”

Combined Vorinostat and Chloroquine Inhibit Sodium–Iodide Symporter Endocytosis and Enhance Radionuclide Uptake In Vivo

“…We propose that extensive dysregulation of endocytic genes in PTC results in NIS mislocalisation away from the PM and reduced radioiodide uptake, leading to a greater number of treatment-resistant tumour cells and increased risk of recurrence. Early detection of PTC recurrence has been shown to improve patient outcomes, but there is still a need for new biomarkers ( 53 ). In this study construction of a 30-endocytic gene risk score classifier for recurrence had higher specificity and sensitivity than single gene biomarkers, as well as being an independent predictor of recurrence.…”

Identification of key biomarkers related to epithelial‐mesenchymal transition and immune infiltration in ameloblastoma using integrated bioinformatics analysis

“…Xavier et al found that FN1 was closely associated with macrophage M2, and that its increased expression played a pivotal role in tumor resistance (Xavier et al, 2021). Moreover, upregulation FN1 expression was also strongly implicated in recurrence in hepatocellular carcinoma, endometrial cancer, and thyroid cancer (de Andrade et al, 2021; Kim et al, 2020; Nieto et al, 2021). Combined with our analysis, FN1 may promote invasion and recurrence of AMs by regulating EMT process and macrophages polarization, and it can be used as a promising biomarker for the diagnosis and therapeutic options of AMs.…”