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Papillary thyroid carcinoma behavior: clues in the tumor microenvironment.

ABSTRACT: The prevalence of thyroid carcinoma is increasing and represents the most common endocrine malignancy, with papillary thyroid carcinoma (PTC) being the most frequent subtype. The genetic alterations identified in PTCs fail to distinguish tumors with different clinical behaviors, such as extra-thyroidal extension and lymph node metastasis. We hypothesize that the immune microenvironment may play a critical role in tumor invasion and metastasis. Computational immunogenomic analysis was performed on 568 PTC samples in The Cancer Genome Atlas using CIBERSORT, TIMER and TIDE deconvolution analytic tools for characterizing immune cell composition. Immune cell infiltrates were correlated with histologic type, mutational type, tumor pathologic T stage and lymph node N stage. Dendritic cells (DCs) are highly associated with more locally advanced tumor T stage (T3/T4, odds ratio (OR) = 2.6, CI = 1.4-4.5, P = 5.4 × 10-4). Increased dendritic cells (OR = 3.4, CI = 1.9-6.3, P = 5.5 × 10-5) and neutrophils (OR = 10.5, CI = 2.7-44, P = 8.7 × 10-4) significantly correlate with lymph node metastasis. In addition, dendritic cells positively correlate with tall cell morphology (OR = 4.5, CI = 1.6-13, P = 4.9 × 10-3) and neutrophils negatively correlate with follicular morphology (OR = 1.3 × 10-3, CI = 5.3 × 10-5-0.031, P = 4.1 × 10-5). TIDE analysis indicates an immune-exclusive phenotype that may be mediated by increased galectin-3 found in PTCs. Thus, characterization of the PTC immune microenvironment using three computational platforms shows that specific immune cells correlate with mutational type, histologic type, local tumor extent and lymph node metastasis. Immunologic evaluation of PTCs may provide a better indication of biologic behavior, resulting in the improved diagnosis and treatment of thyroid cancer.

SUBMITTER: Bergdorf K

PROVIDER: S-EPMC8279427 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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 carcinoma (PTC) is the most common malignant endocrine tumour, and its incidence and prevalence are increasing considerably. Cellular heterogeneity in the tumour microenvironment is important for PTC prognosis. Spatial transcriptomics is a powerful technique for cellular heterogeneity study.MethodsIn conjunction with a clinical pathologist identification method, spatial transcriptomics was employed to characterise the spatial location and RNA profiles of PTC-associated cells within the tissue sections. The spatial RNA-clinical signature genes for each cell type were extracted and applied to outlining the distribution regions of specific cells on the entire section. The cellular heterogeneity of each cell type was further revealed by ContourPlot analysis, monocle analysis, trajectory analysis, ligand-receptor analysis and Gene Ontology enrichment analysis.ResultsThe spatial distribution region of tumour cells, typical and atypical follicular cells (FCs and AFCs) and immune cells were accurately and comprehensively identified in all five PTC tissue sections. AFCs were identified as a transitional state between FCs and tumour cells, exhibiting a higher resemblance to the latter. Three tumour foci were shared among all patients out of the 13 observed. Notably, tumour foci No. 2 displayed elevated expression levels of genes associated with lower relapse-free survival in PTC patients. We discovered key ligand-receptor interactions, including LAMB3-ITGA2, FN1-ITGA3 and FN1-SDC4, involved in the transition of PTC cells from FCs to AFCs and eventually to tumour cells. High expression of these patterns correlated with reduced relapse-free survival. In the tumour immune microenvironment, reduced interaction between myeloid-derived TGFB1 and TGFBR1 in tumour focus No. 2 contributed to tumourigenesis and increased heterogeneity. The spatial RNA-clinical analysis method developed here revealed prognosis-associated cellular heterogeneity in the PTC microenvironment.ConclusionsThe occurrence of tumour foci No. 2 and three enhanced ligand-receptor interactions in the AFC area/tumour foci reduced the relapse-free survival of PTC patients, potentially leading to improved prognostic strategies and targeted therapies for PTC patients.

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.

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Papillary thyroid carcinoma behavior: clues in the tumor microenvironment.

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