Identification and validation of an immune-related prognostic signature and key gene in papillary thyroid carcinoma

Characterization and validation of fatty acid metabolism-related genes predicting prognosis, immune infiltration, and drug sensitivity in endometrial cancer

Endometrial cancer is considered to be the second most common tumor of the female reproductive system, and patients diagnosed with advanced endometrial cancer have a poor prognosis. The influence of fatty acid metabolism in the prognosis of patients with endometrial cancer remains unclear. We constructed a prognostic risk model using transcriptome sequencing data of endometrial cancer and clinical information of patients from The Cancer Genome Atlas (TCGA) database via least absolute shrinkage and selection operator regression analysis. The tumor immune microenvironment was analyzed using the CIBERSORT algorithm, followed by functional analysis and immunotherapy efficacy prediction by gene set variation analysis. The role of model genes in regulating endometrial cancer in vitro was verified by CCK-8, colony formation, wound healing, and transabdominal invasion assays, and verified in vivo by subcutaneous tumor transplantation in nude mice. A prognostic model containing 14 genes was constructed and validated in 3 cohorts and clinical samples. The results showed differences in the infiltration of immune cells between the high-risk and low-risk groups, and that the high-risk group may respond better to immunotherapy. Experiments in vitro confirmed that knockdown of epoxide hydrolase 2 (EPHX2) and acyl-CoA oxidase like (ACOXL) had an inhibitory effect on EC cells, as did overexpression of hematopoietic prostaglandin D synthase (HPGDS). The same results were obtained in experiments in vivo. Prognostic models related to fatty acid metabolism can be used for the risk assessment of endometrial cancer patients. Experiments in vitro and in vivo confirmed that the key genes HPGDS, EPHX2, and ACOXL in the prognostic model may affect the development of endometrial cancer.

Integrated transcriptome sequencing and weighted gene co-expression network analysis reveals key genes of papillary thyroid carcinomas

Objective

Papillary thyroid carcinoma (PTC) accounts for the majority of thyroid cancers and has a high recurrence rate. We aimed to screen key genes involved in PTC to provide novel insights into the mechanisms of PTC.

Methods

Seven microarray datasets of PTC were downloaded from gene expression omnibus database. Differentially expressed genes (DEGs) between PTC and normal samples were screened in the merged dataset. Then, protein-protein interaction (PPIs) functional modules analysis and weighted gene co-expression network analysis (WGCNA) were utilized to identify PTC-associated key genes. The identified key genes were then characterized from various aspects, including gene set enrichment analysis (GSEA) and the associations with immune infiltration, methylation levels and prognosis.

Results

A large numbers of DEGs were identified, and these DEGs are involved in several cancer pathways. Nine key genes (including down-regulated genes GNA14, AVPR1A, and WFS1, and up-regulated genes LAMB3, PLAU, MET, MFGE8, PRSS23, and SERPINA1) were identified. Patients in the AVPR1A and GNA14 high expression groups had better disease-free survival (DFS) than those in the low expression group. Key genes were mainly involved in P53 pathway, estrogen response, apoptosis, glycolysis, NOTCH signaling, epithelial mesenchymal transition, WNT_beta catenin signaling, and inflammatory response. The expression of key genes was associated with immune cell infiltration and corresponding methylation levels. The verification results of key gene proteins and mRNA expression levels using external validation datasets were consistent with our expectations, implying the involvements of key genes in PTC.

Conclusion

The key genes may serve as potential therapeutic targets for PTC. This study provides novel insights into the mechanisms underlying PTC development.

TIPARP as a prognostic biomarker and potential immunotherapeutic target in male papillary thyroid carcinoma

BACKGROUND

Male patients with papillary thyroid carcinoma (PTC) tend to have poorer prognosis compared to females, partially attributable to a higher rate of lymph node metastasis (LNM). Developing a precise predictive model for LNM occurrence in male PTC patients is imperative. While preliminary predictive models exist, there is room to improve accuracy. Further research is needed to create optimized prognostic models specific to LNM prediction in male PTC cases.

METHODS

We conducted a comprehensive search of publicly available microarray datasets to identify candidate genes continuously upregulated or downregulated during PTC progression in male patients only. Univariate Cox analysis and lasso regression were utilized to construct an 11-gene signature predictive of LNM. TIPARP emerged as a key candidate gene, which we validated at the protein level using immunohistochemical staining. A prognostic nomogram incorporating the signature and clinical factors was developed based on the TCGA cohort.

RESULTS

The 11-gene signature demonstrated good discriminative performance for LNM prediction in training and validation datasets. High TIPARP expression associated with advanced stage, high T stage, and presence of LNM. A prognostic nomogram integrating the signature and clinical variables reliably stratified male PTC patients into high and low recurrence risk groups.

CONCLUSIONS

We identified a robust 11-gene signature and prognostic nomogram for predicting LNM occurrence in male PTC patients. We propose TIPARP as a potential contributor to inferior outcomes in males, warranting further exploration as a prognostic biomarker and immunotherapeutic target. Our study provides insights into the molecular basis for gender disparities in PTC.

Diagnosis and Prognosis of Thyroid Cancer by Immune-related Genes

BACKGROUND

Thyroid carcinoma (THCA) is the most common malignant endocrine tumor with low mortality and a relatively good prognosis. Immune genes have attracted much attention as molecular markers of THCA prognosis and potential targets of immunotherapy.

METHODS

Our study analyzed the transcriptome and clinical data of immune-related genes (IRGs) of THCA in gene expression omnibus, the cancer genome atlas-THCA, and ImmPort databases. By univariate Cox regression analysis, 15 genes were significantly correlated with the survival of patients with THCA. Five IRGs ( NMU, UBE2C, CDKN2A, COL19A1, and GPM6A ) were selected by LASSO regression analysis as independent prognostic factors to construct a disease-free survival-related prognostic risk model.

RESULTS

Kaplan-Meier survival analysis showed that there was a significant difference in disease-free survival between high and low-risk groups. The higher the risk score, the worse the survival of patients. Clinical correlation analysis showed that age and Stage stage of patients were correlated with risk score ( P < 0.05). Quantitative real-time polymerase chain reaction confirmed that there were differences in the expression of 5 IRGs between tumor tissues and normal thyroid tissues. Spearman correlation analysis indicated that the relative expression levels of NMU, CDKN2A, UBE2C, COL19A1 , and GPM6A were positively correlated with programmed death-ligand 1 and recombinant a disintegrin and metalloproteinase with thrombospondin 1.

CONCLUSION

Based on the bioinformatics method, we constructed a prognosis evaluation model and risk score system of IRGs in THCA, which provided a reference for predicting the prognosis of patients with THCA.

Construction of novel 7 integrin-related gene signatures in thyroid cancer construction of model based on integrin genes

Advanced and metastatic THCA patients usually have a poor prognosis. Thus, this study aimed to establish a risk model to discriminate the high risk population. The expression and clinical data were obtained from TCGA database. The cluster analysis, lasso, univariate and multivariate cox analyses were used to construct risk model. K-M, ROC and DCA were applied to validate the efficiency and stability of the model. GO, KEGG, and ssGSEA analysis were performed to identify the potential mechanism of signatures. The 7-gene prognosis model was constructed, including FAM27E3, FIGN, GSTM4, BEX5, RBPMS2, PHF13, and DCSTAMP. ROC and DCA results showed our model had a better prognosis prediction performance than other risk models. The high risk score was associated with the poor prognosis of THCA patients with different clinical characteristics. The risk score was closely related to cell cycle. Further, we found that the expressions of signatures were significantly dysregulated in THCA and associated with prognosis. These gene expressions were affected by some clinical characteristics, methylation and CNV. Some signatures played a role in drug sensitivity and pathway activation. We constructed a 7-gene signature model based on the integrin-related genes, which showed a great prognostic value in THCA.

The expression of two immunosuppressive SIGLEC family molecules in papillary thyroid cancer and their effect on prognosis

BACKGROUND

The thyroid cancer (THCA) subtype that occurs more frequently is papillary thyroid cancer (PTC). Despite a favorable postoperative outcome, traditional antitumor therapy does not offer ideal results for patients with metastasis, relapse, and radioiodine resistance. Recent studies demonstrated the remarkable effects of immune checkpoint inhibitors on solid tumors, of which the immunoglobulin superfamily member SIGLEC10 and SIGLEC15 act as novel immunotherapy targets for tumors. Nevertheless, their role in PTC prognosis is still indefinite.

METHODS

Immunohistochemistry was utilized to examine the expression of SIGLEC10 and SIGLEC15 in 244 PTC tissue specimens. Then the expression correlation between the two was analyzed in normal tissues (NT), tumor cells (TC), and tumor stroma (TS), respectively. Subsequently, the retrospective data on patients with PTC were collected to examine whether the two immunosuppressive SIGLEC family members could affect their prognosis.

RESULTS

We confirmed that TC expressed higher levels of SIGLEC10 than NT. However, SIGLEC10 was down-regulated in TS and predicted poor outcomes. Meanwhile, down-regulation of SIGLEC15 expression was observed in both TC and TS, indicating a favorable prognosis. PTC patients with both SIGLEC10-SIGLEC15+ expression in TC and TS had a significantly higher recurrence risk. The expression of SIGLEC10 in TS and SIGLEC15 in TC or TS was an independent predictor of PFS, and a positive correlation was shown between SIGLEC10 and SIGLEC15 expression in TS.

CONCLUSIONS

Therefore, our results indicate that SIGLEC10 and SIGLEC15 may be applied as significant prognostic markers for PTC and attractive targets for THCA immunotherapy.

Altered profile of glycosylated proteins in serum samples obtained from patients with Hashimoto's thyroiditis following depletion of highly abundant proteins

Objectives

Hashimoto's thyroiditis (HT) is one of the most common autoimmune disorders; however, its underlying pathological mechanisms remain unclear. Although aberrant glycosylation has been implicated in the N-glycome of immunoglobulin G (IgG), changes in serum proteins have not been comprehensively characterized. This study aimed to investigate glycosylation profiles in serum samples depleted of highly abundant proteins from patients with HT and propose the potential functions of glycoproteins for further studies on the pathological mechanisms of HT.

Methods

A lectin microarray containing 70 lectins was used to detect and analyze glycosylation of serum proteins using serum samples (N=27 HT; N=26 healthy control [HC]) depleted of abundant proteins. Significant differences in glycosylation status between HT patients and the HC group were verified using lectin blot analysis. A lectin-based pull-down assay combined with mass spectrometry was used to investigate potential glycoproteins combined with differentially present lectins, and an enzyme-linked immunosorbent assay (ELISA) was used to identify the expression of targeted glycoproteins in 131 patients with papillary thyroid carcinoma (PTC), 131 patients with benign thyroid nodules (BTN) patients, 130 patients with HT, and 128 HCs.

Results

Compared with the HC group, the majority of the lectin binding signals in HT group were weakened, while the Vicia villosa agglutinin (VVA) binding signal was increased. The difference in VVA binding signals verified by lectin blotting was consistent with the results of the lectin microarray. A total of 113 potential VVA-binding glycoproteins were identified by mass spectrometry and classified by gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses. Using ELISA, we confirmed that lactoferrin (LTF) and mannan-binding lectin-associated serine protease 1 (MASP-1) levels were elevated in the serum of patients with HT and PTC.

Conclusion

Following depletion of abundant proteins, remaining serum proteins in HT patients exhibited lower glycosylation levels than those observed in HCs. An increased level of potential VVA-binding glycoproteins may play an important role in HT development. LTF and MASP-1 expression was significantly higher in the serum of HT and PTC patients, providing novel insight into HT and PTC.

Identification of iron metabolism-related genes as prognostic indicators for papillary thyroid carcinoma: a retrospective study

Background

The thyroid cancer subtype that occurs more frequently is papillary thyroid carcinoma (PTC). Despite a good surgical outcome, treatment with traditional antitumor therapy does not offer ideal results for patients with radioiodine resistance, recurrence, and metastasis. The evidence for the connection between iron metabolism imbalance and cancer development and oncogenesis is growing. Nevertheless, the iron metabolism impact on PTC prognosis is still indefinite.

Methods

Herein, we acquired the medical data and gene expression of individuals with PTC from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Typically, three predictive iron metabolism-related genes (IMRGs) were examined and employed to build a risk score (RS) model via the least absolute shrinkage and selection operator (LASSO) regression, univariate Cox, and differential gene expression analyses. Then we analyzed somatic mutation and immune cell infiltration among RS groups. We also validated the prognostic value of two IMRGs (SFXN3 and TFR2) by verifying their biological function through in vitro experiments.

Results

Based on RS, all patients with PTC were stratified into low- and high-risk groups, where Kaplan-Meier analysis indicated that disease-free survival (DFS) in the high-risk group was much lower than in the low-risk group (P < 0.0001). According to ROC analysis, the RS model successfully predicted the 1-, 3-, and 5-year DFS of individuals with PTC. Additionally, in the TCGA cohort, a nomogram model with RS was developed and exhibited a strong capability to anticipate PTC patients' DFS. In the high-risk group, the enriched pathological processes and signaling mechanisms were detected utilizing the gene set enrichment analysis (GSEA). Moreover, the high-risk group had a significantly higher level of BRAF mutation frequency, tumor mutation burden, and immune cell infiltration than the low-risk group. In vitro experiments found that silencing SFXN3 or TFR2 significantly reduced cell viability.

Conclusion

Collectively, our predictive model depended on IMRGs in PTC, which could be potentially utilized to predict the PTC patients' prognosis, schedule follow-up plans, and provide potential targets against PTC.

Bone Marrow Mesenchymal Stem Cells with Long Non-Coding RNA-Growth Arrest Specific 5 (LncRNA-GAS5) Modification Impede the Migration and Invasion Activities of Papillary Thyroid Carcinoma Cells

The impact of bone marrow mesenchymal stem cells (BMSCs) on the behaviors of papillary thyroid carcinoma (PTC) cells and LncRNAs remains poorly understood. This study mainly explores the mechanism of LncRNA-GAS5-modified BMSCs on the behaviors of PTC cells, aiming to further elucidate PTC carcinogenesis and provide evidence for drug development. PTC cell lines were assigned into blank group, BMSCs group (co-culture with BMSCs), GAS5 group (co-culture with LncRNA-GAS5-modified BMSCs) and positive control group (cultured in the presence of 60 μg/mL β-elemene) followed by analysis of LncRNA-GAS5 expression, the number of migrating and invading PTC cells, the quantity of EMT-related markers, MMP-9 and MMP-2. LncRNA-GAS5 level was lowest in the blank group, while highest in the GAS5 group (P <0.05), followed by positive control group and BMSCs group. Moreover, the number of migrated and invaded cells was highest in the blank group, while lowest in GAS5 group (P < 0.05), followed by positive control group and BMSCs group. PTC cells exhibited the highest expression of EMT-related markers (N-cadherin and Vimentin) and MMPs but lowest E-cadherin level in blank group and positive control group. These proteins showed an opposite trend in GAS5 group and BMSCs group. Additionally, a more remarkable difference was recorded in the GAS5 group (P <0.05). LncRNA-GAS5-modified BMSCs can down-regulate Vimentin and N-cadherin while up-regulate E-cadherin, thereby restraining the expression of MMP-9 and MMP-2. In this way, the EMT process can be manipulated, leading to inhibition of PTC cells behaviors by LncRNA-GAS5-modified BMSCs, indicating that LncRNA-GAS5 might be applied as a therapeutic target for PTC.

Expression of transcription, growth factors, steroid hormone receptors, LC3B in papillary thyroid cancer tissue, association with prognosis and risk of recurrence

Introduction. Biological characteristics of the tumor play a major role in it’s development and progression. Currently, using the molecular markers aimed at resolving the problems in clinical oncology is becoming more important, including thyroid carcinomas. Heterogeneous contradictory data had been accumulated to date showing the ability of tumors genetic and biological parameters to predict the diseases outcome.Aim. To investigate prognostic value of transcription, growth factors, components of AKT / mTOR signaling pathway and autophagy protein LC3B in patients with papillary thyroid cancer in relation to recurrences and overall survival.Materials and methods. The study included 65 patients with T1–4N0–1M0 papillary thyroid cancer. According to the criteria of the American Thyroid Association (ATA) (2015), patients were divided into groups of patients with high, low and intermediate risk. 30 patients were classified as low risk, 23 as intermediate risk, and 12 as high risk. The BRAFV600 mutation was identified in 18 samples. The expression of transcription factors (p65 and p50 subunits of nuclear factor kappa B (NF-κB p65, NF-κB p50), hypoxia-inducible factor 1 (HIF-1), hypoxia-inducible factor 2 (HIF-2), growth factors (vascular endothelial growth factor (VEGF), receptor VEGF (VEGF-2), carbonic anhydrases of type 9 (CAIX)), AKT, c-RAF, GSK- 3β, p70S6, mammalian target of rapamycin (m-TOR), PDK, PTEN, 4E-BP1 in the tumor was assessed by real-time polymerase chain reaction (PCR). The BRAFV600 mutation was investigated using real-time allele-specific PCR. The content of the LC3B protein was examined using the Western Blot method.Results. As a result of the study, there is an increase in c-RAF expression with an increase in risk from low to high, which was accompanied by a decrease in 4E-BP1 expression. c-RAF mRNA levels were increased 3.0- and 2.8‑fold in the intermediate and high-risk groups, respectively, compared to low risk patients. There is a change in the expression of Brn-3α depending on the relapse risk. The maximum mRNA levels were found in patients with intermediate risk, where the figure was 4.3 and 6.2 times higher than in patients with low and high risk, respectively. An increase in LC3B expression by 56.0 and 28.0 times was shown in the tumor tissue of patients with intermediate risk compared with patients with low and high risk. This fact corresponds with an increasing content of the protein itself, which was higher in patients with intermediate risk. Patients with a negative BRAF gene status had an intermediate and high risk of tumor recurrence. The prognostic significance of the estrogen receptor β (ER-β) and NF-κB p50 expression level had been revealed in relation with relapse-free and overall survival of patients with papillary thyroid cancer.Conclusion. As a result of the study, additional molecular markers were found in order to for predict the tumors recurrence risk. The study showed the significance of ERβ and NF-κB p50 expression levels for predicting disease outcomes.

Analysis of the regulatory mechanisms of prognostic immune factors in thyroid cancer

Objective

To explore the regulatory mechanism of immune prognostic factors in thyroid cancer.

Methods

Based on the TCGA database and GEO database, this study used bioinformatics methods to study the potential regulatory mechanism of thyroid cancer prognosis, analyzed the differentially expressed genes and differential miRNAs between thyroid cancer and normal paracancerous tissues by R software, and constructed lasso risk factors. The immune prognostic factors of thyroid cancer were obtained from the model, and the miRDB website was used to predict the possibility of differential miRNA target binding of the immune prognostic factors and correlation analysis was performed, and finally verified by cell experiments.

Results

There were 1413 differentially expressed genes between thyroid cancer and normal paracancerous tissues, among which 21 immune-related genes were prognostic factors with significant differences in expression; lasso risk model obtained AKAP12, APOC1, TIMP3, ADAMTS9, ANK2, HTRA3, SYNDIG1 , ADAMTS5 and DACT1 were nine prognostic factors. A total of 58 differential miRNAs were found in thyroid cancer tissues and non-cancerous tissues. The possibility of differential miRNA targeting and binding of immune prognostic factors on the miRDB website and cell experiments was analyzed.

Conclusions

The potential miRNA regulatory mechanism of immune prognostic factors in thyroid cancer has been explored.

Analysis of immune related gene expression profiles and immune cell components in patients with Barrett esophagus

Barrett's esophagus (BE) is a well-known precancerous condition of esophageal adenocarcinoma. However, the immune cells and immune related genes involved in BE development and progression are not fully understood. Therefore, our study attempted to investigate the roles of immune cells and immune related genes in BE patients. The raw gene expression data were downloaded from the GEO database. The limma package in R was used to screen differentially expressed genes (DEGs). Then we performed the least absolute shrinkage and selection operator (LASSO) and random forest (RF) analyses to screen key genes. The proportion of infiltrated immune cells was evaluated using the CIBERSORT algorithm between BE and normal esophagus (NE) samples. The spearman index was used to show the correlations of immune genes and immune cells. Receiver operating characteristic (ROC) curves were used to assess the diagnostic value of key genes in BE. A total of 103 differentially expressed immune-related genes were identified between BE samples and normal samples. Then, 7 genes (CD1A, LTF, FABP4, PGC, TCF7L2, INSR,SEMA3C) were obtained after Lasso analysis and RF modeling. CIBERSORT analysis revealed that resting CD4 T memory cells and gamma delta T cells were present at significantly lower levels in BE samples. Moreover, plasma cell and regulatory T cells were present at significantly higher levels in BE samples than in NE samples. INSR had the highest AUC values in ROC analysis. We identified 7 immune related genes and 4 different immune cells in our study, that may play vital roles in the occurrence and development of BE. Our findings improve the understanding of the molecular mechanisms of BE.

Construction of a Signature Model to Predict the Radioactive Iodine Response of Papillary Thyroid Cancer

Papillary thyroid cancer (PTC) accounts for about 90% of thyroid cancer. There are approximately 20%-30% of PTC patients showing disease persistence/recurrence and resistance to radioactive iodine (RAI) treatment. For these PTC patients with RAI refractoriness, the prognosis is poor. In this study, we aimed to establish a comprehensive prognostic model covering multiple signatures to increase the predictive accuracy for progression-free survival (PFS) of PTC patients with RAI treatment. The expression profiles of mRNAs and miRNAs as well as the clinical information of PTC patients were extracted from TCGA and GEO databases. A series of bioinformatics methods were successfully applied to filtrate a two-RNA model (IPCEF1 and hsa-mir-486-5p) associated with the prognosis of RAI-therapy. Finally, the RNA-based risk score was calculated based on the Cox coefficient of the individual RNA, which achieved good performances by the time-dependent receiver operating characteristic (tROC) curve and PFS analyses. Furthermore, the predictive power of the nomogram, integrated with the risk score and clinical parameters (age at diagnosis and tumor stage), was assessed by tROC curves. Collectively, our study demonstrated high precision in predicting the RAI response of PTC patients.

Single-Cell Transcriptome Analysis Reveals Inter-Tumor Heterogeneity in Bilateral Papillary Thyroid Carcinoma

Background

The tumor microenvironment (TME) plays a pivotal role in cancer progression in papillary thyroid carcinoma (PTC), yet the composition and the phenotype of cells within the TME in bilateral PTC are poorly understood.

Methods

We performed unbiased transcriptome-wide single-cell RNA sequencing (scRNA-seq) analysis on 29,561 cells from 3 pairs of bilateral PTC and 1 non-tumor thyroid sample. The results of the analysis were validated by a large-scale bulk transcriptomic dataset deposited in The Cancer Genome Atlas (TCGA) database.

Results

Our integrative analysis of thyroid follicular cells revealed 42 signaling pathways enriched in malignant follicular cells, including cytokine-cytokine receptor interaction, PI3K/Akt signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, and tumor necrosis factor (TNF) signaling pathway. A 6-gene signature (CXCL3, CXCL1, IL1A, CCL5, TNFRSF12A, and IL18) in the cytokine-cytokine receptor interaction pathway was constructed to predict the prognosis of patients with PTC, with high risk scores being associated with decreased overall survival [hazard ratio (HR) = 3.863, 95% CI = 2.233-6.682, p < 0.001]. Gene set variation analysis (GSVA) indicated that the pathways enriched in bilateral PTC were significantly different, indicating great heterogeneity in bilateral PTC, even with the same BRAF V600E mutation. Comprehensive analysis of T cells revealed that the proportion of CD8+ tissue-resident memory T cells expressing IFNG decreased in tumor samples with advanced N stage. Within the myeloid compartment, the ratio of suppressive M2-like to pro-inflammatory M1-like macrophages increased with advanced disease stage, which was confirmed in the bulk dataset using transcriptomic profiles. In addition, we also identified numerous biologically critical interactions among myeloid cells, T cells, and follicular cells, which were related to T-cell recruitment, M2-like macrophage polarization, malignant follicular cell progression, and T-cell inhibitory signaling.

Conclusion

Our integrative analyses revealed great inter-tumor heterogeneity within the TME in bilateral PTC, which will offer assistance for precise diagnosis and treatment.

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

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.