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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.

SUBMITTER: Xia Y

PROVIDER: S-EPMC9215106 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCuproptosis, a new form of programmed cell death, has been recently reported to be closely related to tumor progression. However, the significance of cuproptosis-related genes (CRGs) in papillary thyroid carcinoma (PTC) is still unclear. Therefore, this study aimed to investigate the role of the CRG signature in prognosis prediction and immunotherapeutic effect estimation in patients with PTC.MethodsRNA-seq data and the corresponding clinical information of patients with PTC were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Comprehensive analyses, namely, consensus clustering, immune analyses, functional enrichment, least absolute shrinkage and selection operator-multivariate Cox regression, and nomogram analysis, were performed to identify new molecular subgroups, determine the tumor immune microenvironment (TIME) status of the identified subgroups, and construct a clinical model. Independent verification cohort data and quantitative real-time polymerase chain reaction (qPCR) was performed to validate the expression of specific prognosis-related and differentially expressed CRGs (P-DECRGs).ResultsIn the TCGA database, 476 patients with PTC who had complete clinical and follow-up information were included. Among 135 CRGs, 21 were identified as P-DECRGs. Two molecular subgroups with significantly different disease-free survival and TIME statuses were identified based on these 21 P-DECRGs. The differentially expressed genes between the two subgroups were mainly associated with immune regulation. The risk model and nomogram were constructed based on four specific P-DECRGs and validated as accurate prognostic predictions and TIME status estimation for PTC by TCGA and GEO verification cohorts. Finally, the qPCR results of 20 PTC and paracancerous thyroid tissues validated those in the TCGA database.ConclusionsFour specific P-DECRGs in PTC were identified, and a clinical model based on them was established, which may be helpful for individualized immunotherapeutic strategies and prognostic prediction in patients with PTC.

Project description:BackgroundPapillary thyroid cancer has been associated with chronic inflammation. A systematic understanding of immune cell infiltration in PTC is essential for subsequent immune research and new diagnostic and therapeutic strategies.MethodsThree different algorithms, single-sample gene set enrichment analysis (ssGSEA), immune cell marker and CIBERSORT, were used to evaluate immune cell infiltration levels (abundance and proportion) in 10 data sets (The Cancer Genome Atlas [TCGA], GSE3467, GSE3678, GSE5364, GSE27155, GSE33630, GSE50901, GSE53157, GSE58545, and GSE60542; a total of 799 PTC and 194 normal thyroid samples). Consensus unsupervised clustering divided PTC patients into low-immunity and high-immunity groups. Weighted gene coexpression network analysis (WGCNA) and gene set enrichment analysis (GSEA) were used to analyze the potential mechanisms causing differences in the immune response.ResultsCompared with normal tissues, PTC tissues had a higher overall immune level and higher abundance levels and proportions of M2 macrophages, Tregs, monocytes, neutrophils, dendritic cells (DCs), mast cells (MCs), and M0 macrophages. Compared with early PTC, advanced PTC showed higher immune infiltration and higher abundance levels and proportions of M2 macrophages, Tregs, monocytes, neutrophils, DCs, MCs, and M0 macrophages. Compared to the low-immunity group, the high-immunity group exhibited more advanced stages, larger tumor sizes, greater lymph node metastases, higher tall-cell PTCs, lower follicular PTC proportions, more BRAF mutations, and fewer RAS mutations. Epstein-Barr virus (EBV) infection was the most significantly enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway for key module genes.ConclusionsIn human PTC, M2 macrophages, Tregs, monocytes, neutrophils, DCs, MCs, and M0 macrophages appear to play a tumor-promoting role, while M1 macrophages, CD8+ T cells, B cells, NK cells, and T follicular helper (TFH) cells (including eosinophils, γδ T cells, and Th17 cells with weak supporting evidence) appear to play an antitumor role. During the occurrence and development of PTC, the overall immune level was increased, and the abundance and proportion of tumor-promoting immune cells were significantly increased, indicating that immune escape had been aggravated. Finally, we speculate that EBV may play an important role in changing the immune microenvironment of PTC tumors.

Project description:BackgroundPapillary thyroid cancer (PTC) is the most common type of thyroid cancer. However, due to the lack of reliable prognostic biomarkers for PTC, overtreatment has been on the rise. Therefore, our research aims to identify new and promising prognostic biomarkers and provide fresh perspectives for clinical decision making.MethodsThe RNA-seq data and clinical data of PTC samples were obtained from The Cancer Genome Atlas data portal. GSE64912 and GSE83520 datasets were downloaded through the GEOquery R package. The difference in the expression of oxoglutarate dehydrogenase like (OGDHL) between PTC and normal tissues was explored by the Wilcoxon test. Kaplan-Meier (KM) and Cox regression analyses were used to further explore the prognostic value of OGDHL. The tumor microenvironments of PTC patients were explored based on ssGSEA and Tumor Immune Estimation Resource online database. Gene Set Enrichment Analysis (GSEA) was performed to explore the biological processes associated with OGDHL.ResultsThe expression level of OGDHL in PTC was significantly altered compared to that in normal tissues (p < 0.05). Various biological processes associated with OGDHL were also explored through GSEA. KM analysis suggested that the low-OGDHL group had a better overall survival [OS, p = 3.49e-03, hazard ratio (HR) = 4.567]. The receiver operating characteristic curve also indicated the favorable prognostic potential of OGDHL. Moreover, OGDHL was proved to be an independent prognostic indicator in Cox analysis (p = 1.33e-02, HR = 0.152). In the analysis of the tumor microenvironment, the low-OGDHL group showed a lower immune score and stromal score, while tumor purity was higher. The expression of OGDHL was also closely correlated with the infiltration of immune cells.ConclusionOur study elucidated the influence of OGDHL on the prognosis of PTC and demonstrated its potential as a novel biomarker, which would provide new insights into the prognosis monitoring and clinical decision making in PTC patients.

Project description:Radioactive iodine-refractory metastatic differentiated thyroid cancer (RAIR) is associated with a poor prognosis. Multikinase inhibitors have demonstrated improvement in progression-free but not overall survival in such patients, but usage is limited by significant adverse effects and the development of resistance. Clinical research has demonstrated improvement in progression-free survival with the combined use of the BRAF/MEK inhibitor in patients with metastatic melanoma and anaplastic thyroid cancer with the BRAFV600E mutation and has shown promise in redifferentiation of BRAF-positive RAIR differentiated thyroid cancer. A 58-year-old woman went to her primary care physician for a growing mass on the left side of her neck. CT imaging noted a 6 x 8 x 6 cm mixed cystic and solid mass and lymphadenopathy. Core biopsy subsequently showed metastatic papillary thyroid cancer (Stage III, PT4a/PN1b), and she underwent a total thyroidectomy with left neck dissection. She then received 204mCi 131I post-total thyroidectomy. Unfortunately, her thyroglobulin continued to increase post-radioactive iodine (RAI) treatment, indicating persistent and/or recurrent thyroid cancer. An RAI-131 whole-body scan on the thyrogen protocol showed no significant RAI uptake. A fluorodeoxyglucose (FDG)-positron emission tomography (PET) CT scan was then performed, which showed recurrent metastatic disease with hypermetabolism noted in the left thyroid bed and FDG-avid bilateral cervical lymph nodes and pulmonary nodules. Given these findings, her cancer was classified as radioactive iodine refractory (RAIR). Molecular testing indicated the BRAFV600E mutation. After a discussion with the patient, it was decided to initiate therapy with a BRAF inhibitor (dabrafenib 150 mg twice a day) and MEK inhibitor (trametinib 2 mg once a day) in an attempt to redifferentiate RAIR. Repeat RAI-131 thyrogen whole body scan one month after initiation of therapy demonstrated left level 2 cervical lymphadenopathy radioiodine uptake. The patient subsequently received 216 mCi 131I treatment given evidence of redifferentiation. Her post-treatment scan indicated additional uptake in a left lower lobe pulmonary nodule as well as a left paratracheal mass indicating successful RAI-131 uptake by metastases. Her thyroglobulin level, six months post-RAI, decreased to 4.0 indicating an encouraging response. Further surveillance, including imaging studies, is planned. This case illustrates the re-differential potential for dabrafenib and trametinib treatment in patients with BRAFV600E-mutated RAIR differentiated thyroid cancer. This therapy has been shown to be successful in small series of patients and could potentially be offered to RAIR patients with the BRAFV600E mutation as an alternative to multikinase treatment given its favorable side-effect profile.

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

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