Construction of a Tumor Immune Microenvironment-Related Prognostic Model in BRAF-Mutated Papillary Thyroid Cancer

Abstract

BRAF mutation is a representative oncogenic mutation, with a frequency of 60% in papillary thyroid carcinoma (PTC), but the reasons for the poor prognosis and more aggressive course of BRAF-mutated PTC are controversial. Tumor immune microenvironment (TIME) is an essential factor permitting the development and progression of malignancy, but whether TIME participates in the prognosis of BRAF-mutated PTC has not yet been reported. The primary goal of the present study was to provide a comprehensive TIME-related prognostic model to increase the predictive accuracy of progression-free survival (PFS) in patients with BRAF-mutated PTC. In this study, we analyzed the mRNA-seq data and corresponding clinical data of PTC patients obtained from the TCGA database. By calculating the TIME scores (immune score, stromal score and ESTIMATE score), the BRAF mutation group (n=237) was dichotomized into the high- and low-score groups. By functional analysis of differentially expressed genes (DEGs) in different high/low score groups, we identified 2 key TIME-related genes, HTR3A and NIPAL4, which affected PFS in BRAF-mutated PTC. A risk scoring system was developed by multivariate Cox analysis based on the abovementioned 2 TIME-related genes. Then, the BRAF-mutated cohort was divided into the high- and low-risk groups using the median risk score as a cutoff. A high risk score correlated positively with a higher HTR3A/NIPAL4 expression level but negatively with PFS in BRAF-mutated PTC. Ultimately, a nomogram was constructed by combining risk score with clinical parameter (Tumor stage), and the areas under the ROC curve (AUCs) of the nomogram for predicting 1-, 3- and 5-year PFS were then calculated and found to be 0.694, 0.707 and 0.738, respectively, indicating the improved accuracy and clinical utility of the nomogram versus the risk score model in the BRAF-mutated PTC cohort. Moreover, we determined the associations between prognostic genes or risk score and immune cell infiltration by two-way ANOVA. In the high-risk score, high HTR3A expression, and high NIPAL4 expression groups, higher infiltration of immune cells was found. Collectively, these findings confirm that the nomogram is effective in predicting the outcome of BRAF-mutated PTC and will add a spatial dimension to the developing risk stratification system.

Machine learning-based dynamic prediction of lateral lymph node metastasis in patients with papillary thyroid cancer

“…Apart from generating a new machine learning model, we also explored the correlation between several risk factors and LLNM. Despite the fact that the correlation between variables and outcomes is invisible in most machine learning-based models, the ranked importance of variables in the optimal model was obtained by using a classifier-specific explainer (Figures 4C, D 15) considered tumors >1.0 cm as a risk factor for LLNM (16,17), Wu et al suggested a tumor size threshold of >0.7 cm (30), while Kim et al (31) reported that PTC >2 cm was a strong independent risk factor for LLNM. Tumor size on ultrasound images is an important indicator of tumor growth.…”

“…The incidence of PTC is currently showing rapid growth worldwide. Although the prognosis of patients with PTC is excellent, with a 10-year survival rate of more than 90% ( 16 ), early LLNM is quite common. Between 20% and 69% of patients with stage N0 PTC have been reported to have subclinical LLNM ( 17 ).…”

“…( 29 ) and Zhou et al. ( 15 ) considered tumors >1.0 cm as a risk factor for LLNM ( 16 , 17 ), Wu et al. suggested a tumor size threshold of >0.7 cm ( 30 ), while Kim et al.…”

Combined BRAF and PIM1 inhibitory therapy for papillary thyroid carcinoma based on BRAFV600E regulation of PIM1: Synergistic effect and metabolic mechanisms

“…The BRAFV600E mutation, which occurs in approximately 60 % of PTC cases [7] , is a key driver of thyroid tumorigenesis through its involvement in the activation of the mitogen-activated protein kinase (MAPK)/extracellular signal–regulated kinase (ERK) pathway [ 8 , 9 ]. This mutation is strongly associated with invasive characteristics, including metastasis, recurrence, and resistance to radioactive iodine therapy, making it an important target for PTC treatment [10] , [11] , [12] .…”