In tumor cells, thyroid hormone analogues non-immunologically regulate PD-L1 and PD-1 accumulation that is anti-apoptotic

Relationship between programmed cell death and targeted therapy for thyroid cancer in patients with a poor prognosis: an update

In recent years, the incidence of thyroid cancer has steadily increased. However, the detailed mechanisms of pathogenesis are still unclear. Therefore, a comprehensive understanding of the underlying carcinogenesis mechanisms of thyroid cancer is required. Programmed cell death (PCD) is a cell death process mediated by specific molecular program, regulated by specific genes within the cell. Accumulating evidence suggests that PCD plays an indispensable role in thyroid cancer, maintaining intracellular stability by regulating genes and eliminating damaged or aged cells. In this review, we summarize six identified forms of PCD, analyze biomarkers for different PCD pathways in thyroid cancer, and briefly elucidate the roles of various PCD pathways in targeted therapies for thyroid cancers with a poor prognosis. We also provide an outlook on future treatments for drug-resistant thyroid cancer, poorly differentiated thyroid cancer, and iodine-refractory thyroid cancer, aiming to accurately identify targets and offer effective targeted therapeutic strategies.

(Thyroid) Hormonal regulation of breast cancer cells

Thyroid hormone as L-thyroxine (T4) acts nongenomically at physiological concentrations at its cancer cell surface receptor on integrin αvβ3 ('thyrointegrin') to cause cancer cell proliferation. In the case of estrogen receptor (ERα)-positive breast cancer cells, T4 via the integrin promotes ERα-dependent cancer growth in the absence of estrogen. Thus, tumor growth in the post-menopausal patient with ERα-positive cancer may again be ER-dependent because of T4. Additional mechanisms by which T4 may contribute uniquely to aggressive breast cancer behavior-independently of ER-are stimulation of immune checkpoint inhibitor gene expression and of several anti-apoptosis mechanisms. These observations may call for consideration of elimination of host T4 production in breast cancer patients whose response is suboptimal to standard chemotherapy regimens. Euthyroidism in such a setting may be maintained with exogenous 3,3',5-triiodo-L-thyronine (T3).

Identification of Transcriptional Pattern Related to Immune Cell Infiltration With Gene Co-Expression Network in Papillary Thyroid Cancer

BACKGROUND

A growing body of evidence suggests that immune cell infiltration in cancer is closely related to clinical outcomes. However, there is still a lack of research on papillary thyroid cancer (PTC).

METHODS

Based on single-sample gene set enrichment analysis (SSGSEA) algorithm and weighted gene co-expression network analysis (WGCNA) tool, the infiltration level of immune cell and key modules and genes associated with the level of immune cell infiltration were identified using PTC gene expression data from The Cancer Genome Atlas (TCGA) database. In addition, the co-expression network and protein-protein interactions network analysis were used to identify the hub genes. Moreover, the immunological and clinical characteristics of these hub genes were verified in TCGA and GSE35570 datasets and quantitative real-time polymerase chain reaction (PCR). Finally, receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value of hub genes.

RESULTS

Activated B cell, activated dendritic cell, CD56bright natural killer cell, CD56dim natural killer cell, Eosinophil, Gamma delta T cell, Immature dendritic cell, Macrophage, Mast cell, Monocyte, Natural killer cell, Neutrophil and Type 17 T helper cell were significantly changed between PTC and adjacent normal groups. WGCNA results showed that the black model had the highest correlation with the infiltration level of activated dendritic cells. We found 14 hub genes whose expression correlated to the infiltration level of activated dendritic cells in both TCGA and GSE35570 datasets. After validation in the TCGA dataset, the expression level of only 5 genes (C1QA, HCK, HLA-DRA, ITGB2 and TYROBP) in 14 hub genes were differentially expressed between PTC and adjacent normal groups. Meanwhile, the expression levels of these 5 hub genes were successfully validated in GSE35570 dataset. Quantitative real-time PCR results showed the expression of these 4 hub genes (except C1QA) was consistent with the results in TCGA and GSE35570 dataset. Finally, these 4 hub genes had diagnostic value to distinguish PTC and adjacent normal controls.

CONCLUSIONS

HCK, HLA-DRA, ITGB2 and TYROBP may be key diagnostic biomarkers and immunotherapy targets in PTC.

Nano-Strategies Targeting the Integrin αvβ3 Network for Cancer Therapy

Integrin αvβ3, a cell surface receptor, participates in signaling transduction pathways in cancer cell proliferation and metastasis. Several ligands bind to integrin αvβ3 to regulate proliferation and metastasis in cancer cells. Crosstalk between the integrin and other signal transduction pathways also plays an important role in modulating cancer proliferation. Carcinoembryonic antigen cell adhesion molecule 6 (CEACAM6) activates the downstream integrin FAK to stimulate biological activities including cancer proliferation and metastasis. Blockage of signals related to integrin αvβ3 was shown to be a promising target for cancer therapies. 3,3′,5,5′-tetraiodothyroacetic acid (tetrac) completely binds to the integrin with the thyroid hormone to suppress cancer proliferation. The (E)-stilbene analog, resveratrol, also binds to integrin αvβ3 to inhibit cancer growth. Recently, nanotechnologies have been used in the biomedical field for detection and therapeutic purposes. In the current review, we show and evaluate the potentiation of the nanomaterial carrier RGD peptide, derivatives of PLGA-tetrac (NDAT), and nanoresveratrol targeting integrin αvβ3 in cancer therapies.

Thyroid dysfunction and breast cancer risk among women in the UK Biobank cohort

This study aimed to evaluate the association between thyroid dysfunction and breast cancer risk. We included 239,436 females of the UK Biobank cohort. Information on thyroid dysfunction, personal and family medical history, medications, reproductive factors, lifestyle, and socioeconomic characteristics was retrieved from baseline self-reported data and hospital inpatient databases. Breast cancer diagnoses were identified through population-based registries. We computed Cox models to estimate hazard ratios (HRs) of breast cancer incidence for thyroid dysfunction diagnosis and treatments, and examined potential confounding and effect modification by comorbidities and breast cancer risk factors. In our study, 3,227 (1.3%) and 20,762 (8.7%) women had hyper- and hypothyroidism prior to the baseline. During a median follow-up of 7.1 years, 5,326 (2.2%) women developed breast cancer. Compared to no thyroid dysfunction, there was no association between hypothyroidism and breast cancer risk overall (HR = 0.93, 95% confidence interval (CI): 0.84-1.02, 442 cases), but we found a decreased risk more than 10 years after hypothyroidism diagnosis (HR=0.85, 95%CI 0.74-0.97, 226 cases). There was no association with hyperthyroidism overall (HR=1.08, 95%CI 0.86-1.35, 79 cases) but breast cancer risk was elevated among women with treated hyperthyroidism (HR=1.38, 95%CI: 1.03-1.86, 44 cases) or aged 60 years or more at hyperthyroidism diagnosis (HR=1.74, 95%CI: 1.01-3.00, 113 cases), and 5-10 years after hyperthyroidism diagnosis (HR=1.58, 95%CI: 1.06-2.33, 25 cases). In conclusion, breast cancer risk was reduced long after hypothyroidism diagnosis, but increased among women with treated hyperthyroidism. Future studies are needed to determine whether the higher breast cancer risk observed among treated hyperthyroidism could be explained by hyperthyroidism severity, type of treatment or aetiology.

Association between programmed cell death ligand 1 expression and thyroid cancer: A meta-analysis

BACKGROUND

Programmed cell death ligand 1 (PD-L1), which is highly expressed in a variety of malignant tumors, is closely related to clinicopathological features and prognosis. However, there are few studies on the potential effects of PD-L1 on thyroid carcinoma, the incidence of which has shown an upward trend worldwide. This study aimed to explore the association between PD-L1 expression and clinicopathological features and prognosis of thyroid cancer.

METHODS

An elaborate retrieval was performed using Medline, PubMed, Cochrane Library, EMBASE, Web of Science, WanFang databases, and China National Knowledge Infrastructure to determine the association between PD-L1 expression and disease-free survival (DFS), overall survival (OS), and clinicopathological features in patients with thyroid cancer. Study selection, data extraction, risk assessment, and data synthesis were performed independently by 2 reviewers. In this meta-analysis, RevMan 5.3 and Stata 15.1 were used for bias risk assessment and data synthesis.

RESULTS

After a detailed search, 2546 cases reported in 13 articles were included in this meta-analysis. The outcomes revealed that high expression of PD-L1 in patients with thyroid cancer was associated with poor DFS (hazard ratio [HR] = 3.37, 95% confidence interval [CI] 2.54-4.48, P < .00001) and OS (HR = 2.52, 95% CI: 1.20-5.32, P = .01). High PD-L1 expression was associated with tumor size ≥2 cm, tumor recurrence, extrathyroidal extension, concurrent thyroiditis, unifocal tumor, and absence of psammoma body (P < .05). Subgroup analysis showed that positive expression of PD-L1 was related to poor prognosis for DFS of non-medullary thyroid carcinoma, and the overexpression of PD-L1 in differentiated thyroid carcinoma (DTC) was related to tumor recurrence, concurrent thyroiditis, extrathyroidal extension, unifocal DTC, late stage DTC, and BRAFV600E mutation in DTC.

CONCLUSION

PD-L1 is a significant predictor of prognosis and malignancy of thyroid cancer (especially DTC), and PD-L1 inhibitors may be a promising therapeutic option for refractory thyroid cancer in the future.

Role of thyroid hormone-integrin αvβ3-signal and therapeutic strategies in colorectal cancers

Thyroid hormone analogues-particularly, L-thyroxine (T₄) has been shown to be relevant to the functions of a variety of cancers. Integrin αvβ3 is a plasma membrane structural protein linked to signal transduction pathways that are critical to cancer cell proliferation and metastasis. Thyroid hormones, T₄ and to a less extend T₃ bind cell surface integrin αvβ3, to stimulate the extracellular signal-regulated kinase 1/2 (ERK1/2) pathway to stimulate cancer cell growth. Thyroid hormone analogues also engage in crosstalk with the epidermal growth factor receptor (EGFR)-Ras pathway. EGFR signal generation and, downstream, transduction of Ras/Raf pathway signals contribute importantly to tumor cell progression. Mutated Ras oncogenes contribute to chemoresistance in colorectal carcinoma (CRC); chemoresistance may depend in part on the activity of ERK1/2 pathway. In this review, we evaluate the contribution of thyroxine interacting with integrin αvβ3 and crosstalking with EGFR/Ras signaling pathway non-genomically in CRC proliferation. Tetraiodothyroacetic acid (tetrac), the deaminated analogue of T₄, and its nano-derivative, NDAT, have anticancer functions, with effectiveness against CRC and other tumors. In Ras-mutant CRC cells, tetrac derivatives may overcome chemoresistance to other drugs via actions initiated at integrin αvβ3 and involving, downstream, the EGFR-Ras signaling pathways.

Actions of Thyroid Hormones on Thyroid Cancers

L-Thyroxine (T4) is the principal ligand of the thyroid hormone analogue receptor on the extracellular domain of integrin αvβ3. The integrin is overexpressed and activated in cancer cells, rapidly dividing endothelial cells, and platelets. The biologic result is that T4 at physiological concentration and without conversion to 3,3',5-triiodo-L-thyronine (T3) may stimulate cancer cell proliferation and cancer-relevant angiogenesis and platelet coagulation. Pro-thrombotic activity of T4 on platelets is postulated to support cancer-linked blood clotting and to contribute to tumor cell metastasis. We examine some of these findings as they may relate to cancers of the thyroid. Differentiated thyroid cancer cells respond to physiological levels of T4 with increased proliferation. Thus, the possibility exists that in patients with differentiated thyroid carcinomas in whom T4 administration and consequent endogenous thyrotropin suppression have failed to arrest the disease, T4 treatment may be stimulating tumor cell proliferation. In vitro studies have shown that tetraiodothyroacetic acid (tetrac), a derivative of T4, acts via the integrin to block T4 support of thyroid cancer and other solid tumor cells. Actions of T4 and tetrac or chemically modified tetrac modulate gene expression in thyroid cancer cells. T4 induces radioresistance via induction of a conformational change in the integrin in various cancer cells, although not yet established in thyroid cancer cells. The thyroid hormone receptor on integrin αvβ3 mediates a number of actions of T4 on differentiated thyroid cancer cells that support the biology of the cancer. Additional studies are required to determine whether T4 acts on thyroid cancer cells.

Nongenomic Actions of Thyroid Hormone: The Integrin Component

The extracellular domain of plasma membrane integrin αvβ3 contains a cell surface receptor for thyroid hormone analogues. The receptor is largely expressed and activated in tumor cells and rapidly dividing endothelial cells. The principal ligand for this receptor is l-thyroxine (T₄), usually regarded only as a prohormone for 3,5,3'-triiodo-l-thyronine (T₃), the hormone analogue that expresses thyroid hormone in the cell nucleus via nuclear receptors that are unrelated structurally to integrin αvβ3. At the integrin receptor for thyroid hormone, T₄ regulates cancer and endothelial cell division, tumor cell defense pathways (such as anti-apoptosis), and angiogenesis and supports metastasis, radioresistance, and chemoresistance. The molecular mechanisms involve signal transduction via mitogen-activated protein kinase and phosphatidylinositol 3-kinase, differential expression of multiple genes related to the listed cell processes, and regulation of activities of other cell surface proteins, such as vascular growth factor receptors. Tetraiodothyroacetic acid (tetrac) is derived from T₄ and competes with binding of T₄ to the integrin. In the absence of T₄, tetrac and chemically modified tetrac also have anticancer effects that culminate in altered gene transcription. Tumor xenografts are arrested by unmodified and chemically modified tetrac. The receptor requires further characterization in terms of contributions to nonmalignant cells, such as platelets and phagocytes. The integrin αvβ3 receptor for thyroid hormone offers a large panel of cellular actions that are relevant to cancer biology and that may be regulated by tetrac derivatives.

Immune gene signature delineates a subclass of thyroid cancer with unfavorable clinical outcomes

Thyroid cancer (THCA) is a heterogeneous disease with multiple clinical outcomes Immune cells regulate its progression. Three immunomolecular subtypes (C1, C2, C3) were identified in gene expression data sets from TCGA and GEO databases. Among them, subtype C3 had highest frequency of BRAF mutations, lowest frequency of RAS mutations, highest mutation load and shorter progression-free survival. Functional enrichment analysis for the genes revealed that C1 was up-regulated in the ERK cascade pathway, C2 was up-regulated in cell migration and proliferation pathways, while C3 was enriched in body fluid, protein regulation and response to steroid hormones functions. Notably, the three molecular subtypes exhibit differences in immune microenvironments as shown by timer database and analysis of immune expression signatures. The abundance of B_cell, CD4_Tcell, Neutrophil, Macrophage and Dendritic cells in C2 subtype were lower than in C1 and C3 subtypes Leukocyte fraction, proliferation macrophage regulation, lymphocyte infiltration, IFN gamma response and TGF beta response scores were significantly higher in C3 compared with C1 and C2 subtypes. Unlike C3 subtype, it was observed that C1 and C2 subtypes were significantly negatively correlated with most immune checkpoint genes in two different cohorts. The characteristic genes were differentially expressed between cancer cells, adjacent tissues, and metastatic tissues in different cohorts. In summary, THCA can be subclassified into three molecular subtypes with distinct histological types, genetic and transcriptional phenotypes, all of which have potential clinical implications.

Thyroid hormone-induced expression of inflammatory cytokines interfere with resveratrol-induced anti-proliferation of oral cancer cells

Thyroid hormone, L-thyroxine (T₄), induces inflammatory genes expressions and promotes cancer growth. It also induces expression of the checkpoint programmed death-ligand 1 (PD-L1), which plays a vital role in cancer progression. On the other hand, resveratrol inhibits inflammatory genes expressions. Moreover, resveratrol increases nuclear inducible cyclooxygenase (COX)-2 accumulation, complexes with p53, and induces p53-dependent anti-proliferation. In this study, we investigated the effect of T₄ on resveratrol-induced anti-proliferation in oral cancer. T₄ increased the expression and cytoplasmic accumulation of PD-L1. Increased expressions of pro-inflammatory genes, interleukin (IL)-1β and transforming growth factor (TGF)-β1, were shown to stimulate PD-L1 expression. T₄ stimulated pro-inflammatory and proliferative genes expressions, and oral cancer cells proliferation. In contrast, resveratrol inhibited those genes and activated anti-proliferative genes. T₄ retained resveratrol-induced COX-2 in cytoplasm and prevented COX-2 nuclear accumulation when resveratrol treated cancer cells. A specific signal transducer and activator of transcription 3 (STAT3) inhibitor, S31-201, blocked T₄-induced inhibition and restored resveratrol-induced nuclear COX-2 accumulation. By inhibiting the T₄-activated STAT3 signal transduction axis with S31-201, resveratrol was able to sequentially reestablish COX-2/p53-dependent gene expressions and anti-proliferation. These findings provide a novel understanding of the inhibitory effects of T₄ on resveratrol-induced anticancer properties via the sequential expression of PD-L1 and inflammatory genes.

Development of a prognostic index based on an immunogenomic landscape analysis of papillary thyroid cancer

BACKGROUND

Papillary thyroid cancer (PTC) is the most common subtype of thyroid cancer, and inflammation relates significantly to its initiation and prognosis. Systematic exploration of the immunogenomic landscape therein to assist in PTC prognosis is therefore urgent. The Cancer Genome Atlas (TCGA) project provides a large number of genetic PTC samples that enable a comprehensive and reliable immunogenomic study.

METHODS

We integrated the expression profiles of immune-related genes (IRGs) and progression-free intervals (PFIs) in survival in 493 PTC patients based on the TCGA dataset. Differentially-expressed and survival-associated IRGs in PTC patients were estimated a computational difference algorithm and COX regression analysis. The potential molecular mechanisms and properties of these PTC-specific IRGs were also explored with the help of computational biology. A new prognostic index based on immune-related genes was developed by using multivariable COX analysis.

RESULTS

A total of 46 differentially expressed immune-related genes were significantly correlated with clinical outcome of PTC patients. Functional enrichment analysis revealed that these genes were actively involved in a cytokine-cytokine receptor interaction KEGG pathway. A prognostic signature based on RGs (AGTR1, CTGF, FAM3B, IL11, IL17C, PTH2R and SPAG11A) performed moderately in prognostic predictions and correlated with age, tumor stage, metastasis, number of lesions, and tumor burden. Intriguingly, the prognostic index based on IRGs reflected infiltration by several types of immune cells.

CONCLUSIONS

Together, our results screened several IRGs of clinical significance, revealed drivers of the immune repertoire, and demonstrated the importance of a personalized, IRG-based immune signature in the recognition, surveillance, and prognosis of PTC.

The Role of Thyroid Hormones in Hepatocyte Proliferation and Liver Cancer

Thyroid hormones T3 and T4 (thyroxine) control a wide variety of effects related to development, differentiation, growth and metabolism, through their interaction with nuclear receptors. But thyroid hormones also produce non-genomic effects that typically start at the plasma membrane and are mediated mainly by integrin αvβ3, although other receptors such as TRα and TRβ are also able to elicit non-genomic responses. In the liver, the effects of thyroid hormones appear to be particularly important. The liver is able to regenerate, but it is subject to pathologies that may lead to cancer, such as fibrosis, cirrhosis, and non-alcoholic fatty liver disease. In addition, cancer cells undergo a reprogramming of their metabolism, resulting in drastic changes such as aerobic glycolysis instead of oxidative phosphorylation. As a consequence, the pyruvate kinase isoform M2, the rate-limiting enzyme of glycolysis, is dysregulated, and this is considered an important factor in tumorigenesis. Redox equilibrium is also important, in fact cancer cells give rise to the production of more reactive oxygen species (ROS) than normal cells. This increase may favor the survival and propagation of cancer cells. We evaluate the possible mechanisms involving the plasma membrane receptor integrin αvβ3 that may lead to cancer progression. Studying diseases that affect the liver and their experimental models may help to unravel the cellular pathways mediated by integrin αvβ3 that can lead to liver cancer. Inhibitors of integrin αvβ3 might represent a future therapeutic tool against liver cancer. We also include information on the possible role of exosomes in liver cancer, as well as on recent strategies such as organoids and spheroids, which may provide a new tool for research, drug discovery, and personalized medicine.