Thyroid cancer and the immune system: a model for effective immune surveillance

Tumor microenvironment in thyroid cancer: Immune cells, patterns, and novel treatments

The tumor immune microenvironment of thyroid cancer is the heterogeneous histological space in which tumor cells coexist with host cells. Published data from this review were identified by search and selection database of Pubmed, Elsevier, and Science Direct. Searching was made in two steps using different keywords. In thyroid pathology, the inflammatory response is very important, and might have a key role finding new diagnostic and therapeutic methods, particularly in thyroid cancer. Different immune cells may be more or less present in different types of thyroid cancer and may even have different functions, hence the importance of knowing their presence in different thyroid tumor pathologies. Cancer-related inflammation could be a useful target for new diagnostic and therapeutic strategies by analyzing peritumoral and intratumoral immune cells in different types of thyroid tumors. Moreover, novel strategies for thyroid cancer treatments, such as monoclonal antibodies targeting checkpoint inhibitors, are emerging as promising alternatives.

HS3ST3A1 and CAPN8 Serve as Immune-Related Biomarkers for Predicting the Prognosis in Thyroid Cancer

Background

Thyroid cancer (TC) tends to be a common malignancy worldwide and results in various outcomes due to its different subtypes. The tumor microenvironment (TME) was demonstrated to play crucial roles in various malignancies, including thyroid cancer. This study combined the ESTIMATE and CIBERSORT algorithms, identified four TME-related genes, and evaluated their correlation with clinical characteristics. These findings revealed the malignant performance of TME in TC, and the TME-related DEGs might serve as prognostic biomarkers, which can be utilized for the prediction of immunotherapy effects in patients with TC.

Methods

The clinical and gene expression profiles of TC patients were collected from the TCGA dataset. The ESTIMATE algorithm was utilized to estimate stromal and immune scores and predict the level of stromal and immune cell infiltration. The differential expressed genes related to TME were filtered by the "limma" package in R, and the PPI network was constructed by a string website. KEGG pathway and GO analyses were performed to investigate the biological progression and molecular functions of TME-related DEGs. Then, univariate Cox regression analysis was employed to screen four genes correlated with clinical characteristics. GSEA was conducted to assess their roles in the TME of TC. To further investigate the association between TME-related genes and tumor-infiltrating immune cells (TIICs), the CIBERSORT algorithm was performed. Finally, the malignancy behaviors of the two genes were verified by RT-qPCR, IHC, MTT, colony formation, and transwell assays.

Results

Four TME-related DEGs, LRRN4CL, HS3ST3A1, PCOLCE2, and CAPN8, were identified and were significantly predictive of poor overall survival. KEGG and GO pathway analysis established that the TME-related DEGs were involved in immune responses and pathways in cancer. Furthermore, the malignancy behaviors of HS3ST3A1 and CAPN8 were verified by cellular functional experiments. These results revealed that the TME-related genes HS3ST3A1 and CAPN8 were able to serve as predictors of prognosis in patients with TC.

Conclusion

HS3ST3A1 and CAPN8 may serve as valuable prognostic biomarkers and TME indicators, which can be utilized for the prediction of immunotherapy effects and provide novel treatment strategies for patients with TC.

Identification and Validation of Prognostic Related Hallmark ATP-Binding Cassette Transporters Associated With Immune Cell Infiltration Patterns in Thyroid Carcinoma

ATP-binding cassette (ABC) transporters are a large superfamily of membrane proteins that facilitate the translocation of heterogeneous substrates. Studies indicate that ABC transporters may play important roles in various carcinomas. However, the correlation between ABC transporters and immunomodulation in thyroid carcinoma (TC), as well as the prognoses for this disease, is poorly understood.TC data from The Cancer Genome Atlas (TCGA) database were used to identify prognostic hallmark ABC transporters associated with immune cell infiltration patterns via multiple bioinformatic analyses. Thereafter, quantitative real-time polymerase chain reaction (qRT-PCR) was performed to validate the expression of these selected hallmark ABC transporters in both TC and para-cancerous thyroid tissues. Of a total of 49 ABC transporters, five (ABCA8, ABCA12, ABCB6, ABCB8, and ABCC10) were identified as hallmark ABC transporters. All five were differentially expressed in TC and associated with the relapse-free survival rates of patients with TC. Immunoregulation by these five hallmark ABC transporters involved the modulation of various aspects of immune cell infiltration, such as hot or cold tumor subsets and the abundances of infiltrating immune cells, as well as specific immunomodulators and chemokines. Besides the diverse significantly correlated factors, the five hallmark ABC transporters and correlated genes were most highly enriched in plasma membrane, transporter activity, and transmembrane transport of small molecules. In addition, many chemicals, namely bisphenol A and vincristine, affected the expression of these five transporters. The qRT-PCR results of collected TC and para-cancerous thyroid tissues were consistent with those of TCGA. The findings in this study may reveal the role played by these five hallmark ABC transporters in regulating immune cell infiltration patterns in TC as well as the molecular mechanisms underlying their functions, leading to a better understanding of their potential prognostic and immunotherapeutic values.

Role of Suprabasin in the Dedifferentiation of Follicular Epithelial Cell-Derived Thyroid Cancer and Identification of Related Immune Markers

Background: Aberrant regulation of suprabasin (SBSN) is associated with the development of cancer and immune disorders. SBSN influences tumor cell migration, proliferation, angiogenesis, and immune resistance. In this study, we investigated the potential correlation between SBSN expression and immune infiltration in thyroid cancer.

Methods: The expression of SBSN in 80 papillary thyroid carcinoma (PTC) specimens was determined using quantitative reverse-transcription polymerase chain reaction, western blotting, and immunohistochemical staining. The expression of SBSN in 9 cases of poorly differentiated thyroid carcinoma (PDTC) and 18 cases of anaplastic thyroid carcinoma (ATC) was evaluated by immunohistochemical staining. Comprehensive bioinformatics analysis of SBSN expression was performed using The Cancer Genome Atlas and Gene Expression Omnibus datasets, and the relationship of SBSN expression with M2 macrophages and T regulatory cells (Tregs) in ATC and PTC was verified by immunohistochemical staining.

Results: Compared with those in adjacent normal tissues, the expression levels of SBSN mRNA and protein were significantly higher in PTC tissues. SBSN expression level was correlated with that of cervical lymph node metastasis in PTC patients. Immunohistochemical staining results showed statistically significant differences among high-positive expression rates of SBSN in PTC, PDTC, and ATC. Functional enrichment analysis showed that SBSN expression was associated with pathways related to cancer, cell signaling, and immune response. Furthermore, analysis of the tumor microenvironment (using CIBERSORT-ABS and xCell algorithms) showed that SBSN expression affected immune cell infiltration and the cancer immunity cycle, and immunohistochemistry confirmed a significant increase in M2 macrophage and Treg infiltration in tumor tissues with high-positive SBSN expression.

Conclusion: These findings reveal that SBSN may be involved in thyroid carcinogenesis, tumor dedifferentiation progression, and immunosuppression as an important regulator of tumor immune cell infiltration.

Development and validation of a ferroptosis-related prognostic model for the prediction of progression-free survival and immune microenvironment in patients with papillary thyroid carcinoma

BACKGROUND

Ferroptosis is an iron-dependent and regulated cell death that has been widely reported in a variety of malignancies. The overall survival of papillary thyroid cancer (PTC) is excellent, but the identification of patients with poor prognosis still faces challenges. Nevertheless, whether ferroptosis-related genes (FRGs) can be used to screen high-risk patients is not clear.

METHODS

We obtained the clinical data of patients with PTC and FRGs from the UCSC Xena platform and the FerrDb respectively. Differentially expressed genes (DEGs) of FRGs were obtained from the entire The Cancer Genome Atlas (TCGA). Subsequently, the entire TCGA dataset was randomly split into two subsets: training and test datasets. Based on DEGs, we constructed a predictive model which was tested in the test dataset and the entire TCGA dataset to predict progression-free survival (PFS). Patients were categorized into high- or low-risk groups based on their median risk score. We analyzed differences in some aspects, including pathway enrichment analysis, single-sample Gene Set Enrichment Analysis (ssGSEA), tumor microenvironment (TME), human leukocyte antigen (HLA) genes, and tumor mutation burden (TMB) analyses, between high-risk and low-risk groups.

RESULTS

A predictive model with three FRGs (HSPA5, AURKA, and TSC22D3) was constructed. Patients in the high-risk group had worse PFS compared with patients in the low-risk group. Functional analysis results revealed that ssGSEA, immune cell infiltration, TME, HLA, and TMB were closely associated with ferroptosis.

CONCLUSION

The prognostic model constructed in this study can effectively predict PFS for patients with PTC.

The landscape of tumors-infiltrate immune cells in papillary thyroid carcinoma and its prognostic value

Introduction

Thyroid cancer is a very common malignant tumor in the endocrine system, while the incidence of papillary thyroid carcinoma (PTC) throughout the world also shows a trend of increase year by year. In this study, we constructed two models: ICIscore and Riskscore. Combined with these two models, we can make more accurate and reasonable inferences about the prognosis of PTC patients.

Methods

We selected 481 PTC samples from TCGA and 147 PTC samples from GEO (49 samples in GSE33630, 65 samples in GSE35570 and 33 samples in GSE60542). We performed consistent clustering for them and divided them into three subgroups and screened differentially expressed genes from these three subgroups. Then we divided the differential genes into three subtypes. We also distinguished the up-regulated and down-regulated genes and calculated ICIscore for each PTC sample. ICIscore consists of two parts: (1) the PCAu was calculated from up-regulated genes. (2) the PCAd was calculated from down-regulated genes. The PCAu and PCAd of each sample were the first principal component of the relevant gene. What’s more, we divided the patients into two groups and constructed mRNA prognostic signatures. Additionally we also verified the independent prognostic value of the signature.

Results

Though ICIscore, we were able to observe the relationship between immune infiltration and prognosis. The result suggests that the activation of the immune system may have both positive and negative consequences. Though Riskscore, we could make more accurate predictions about the prognosis of patients with PTC. Meanwhile, we also generated and validated the ICIscore group and Riskscore group respectively.

Conclusion

All the research results show that by combining the two models constructed, ICIscore and Riskscore, we can make a more accurate and reasonable inference about the prognosis of patients with clinical PTC patients. This suggests that we can provide more effective and reasonable treatment plan for clinical PTC patients.

Immune Cell Confrontation in the Papillary Thyroid Carcinoma Microenvironment

Background

Papillary 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.

Methods

Three 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.

Results

Compared 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.

Conclusions

In 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.

Cancer Stem Cells in Thyroid Tumors: From the Origin to Metastasis

Thyroid tumors are extremely heterogeneous varying from almost benign tumors with good prognosis as papillary or follicular tumors, to the undifferentiated ones with severe prognosis. Recently, several models of thyroid carcinogenesis have been described, mostly hypothesizing a major role of the thyroid cancer stem cell (TCSC) population in both cancer initiation and metastasis formation. However, the cellular origin of TCSC is still incompletely understood. Here, we review the principal epigenetic mechanisms relevant to TCSC origin and maintenance in both well-differentiated and anaplastic thyroid tumors. Specifically, we describe the alterations in DNA methylation, histone modifiers, and microRNAs (miRNAs) involved in TCSC survival, focusing on the potential of targeting aberrant epigenetic modifications for developing novel therapeutic approaches. Moreover, we discuss the bidirectional relationship between TCSCs and immune cells. The cells of innate and adaptive response can promote the TCSC-driven tumorigenesis, and conversely, TCSCs may favor the expansion of immune cells with protumorigenic functions. Finally, we evaluate the role of the tumor microenvironment and the complex cross-talk of chemokines, hormones, and cytokines in regulating thyroid tumor initiation, progression, and therapy refractoriness. The re-education of the stromal cells can be an effective strategy to fight thyroid cancer. Dissecting the genetic and epigenetic landscape of TCSCs and their interactions with tumor microenvironment cells is urgently needed to select more appropriate treatment and improve the outcome of patients affected by advanced differentiated and undifferentiated thyroid cancers.

Immune and Inflammatory Cells in Thyroid Cancer Microenvironment

A hallmark of cancer is the ability of tumor cells to avoid immune destruction. Activated immune cells in tumor microenvironment (TME) secrete proinflammatory cytokines and chemokines which foster the proliferation of tumor cells. Specific antigens expressed by cancer cells are recognized by the main actors of immune response that are involved in their elimination (immunosurveillance). By the recruitment of immunosuppressive cells, decreasing the tumor immunogenicity, or through other immunosuppressive mechanisms, tumors can impair the host immune cells within the TME and escape their surveillance. Within the TME, cells of the innate (e.g., macrophages, mast cells, neutrophils) and the adaptive (e.g., lymphocytes) immune responses are interconnected with epithelial cancer cells, fibroblasts, and endothelial cells via cytokines, chemokines, and adipocytokines. The molecular pattern of cytokines and chemokines has a key role and could explain the involvement of the immune system in tumor initiation and progression. Thyroid cancer-related inflammation is an important target for diagnostic procedures and novel therapeutic strategies. Anticancer immunotherapy, especially immune checkpoint inhibitors, unleashes the immune system and activates cytotoxic lymphocytes to kill cancer cells. A better knowledge of the molecular and immunological characteristics of TME will allow novel and more effective immunotherapeutic strategies in advanced thyroid cancer.