Hürthle cell thyroid carcinoma (HTC) accounts for 3–5% of all thyroid malignancies. Widely invasive HTC is characterized by poor prognosis and limited responsiveness to standard therapy with radioiodine. The molecular landscape of HTC is significantly different from the genetic signature seen in other forms of thyroid cancer. We performed a comprehensive literature review on the association between the molecular features of HTC and cancer metabolism. We searched the Pubmed, Embase, and Medline databases for clinical and translational studies published between 1980 and 2020 in English, coupling “HTC” with the following keywords: “genomic analysis”, “mutations”, “exome sequencing”, “molecular”, “mitochondria”, “metabolism”, “oxidative phosphorylation”, “glycolysis”, “oxidative stress”, “reactive oxygen species”, and “oncogenes”. HTC is characterized by frequent complex I mitochondrial DNA mutations as early clonal events. This genetic signature is associated with the abundance of malfunctioning mitochondria in cancer cells. HTC relies predominantly on aerobic glycolysis as a source of energy production, as oxidative phosphorylation-related genes are downregulated. The enhanced glucose utilization by HTC is used for diagnostic purposes in the clinical setting for the detection of metastases by fluorodeoxyglucose positron emission tomography (FGD-PET/CT) imaging. A comprehensive metabolomic profiling of HTC in association with its molecular landscape might be necessary for the implementation of tumor-specific therapeutic approaches.

Background: Thyroid cancer (TC) remains a significant clinical challenge worldwide, with a subset of patients facing aggressive disease progression and therapeutic resistance. Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have emerged as promising therapeutic approaches for various malignancies, yet their efficacy in TC remains uncertain. The objective of this study was to investigate PD-L1 expression in aggressive TC and its association with histological subtypes, molecular mutation, and progression-free survival. Methods: This is a retrospective study of patients with advanced TC seen in two tertiary health care centers. Included in this study were patients with advanced TC with recurrence or progression on therapy for whom tumor molecular profiling and PD-L1 status were available. Kaplan–Meier estimators were utilized to analyze the progression-free survival (PFS) between patients with PD-L1 positive and negative status in Anaplastic TC (ATC) subgroup. Results: A total of 176 patients with advanced thyroid cancer were included (48.9% female). Of the patients, 13 had ATC, 11 Medullary TC (MTC), 81 Papillary TC Classic Variant (PTCCV), 20 Follicular TC (FTC), 8 Oncocytic TC (OTC), 10 Poorly Differentiated TC (PDTC), and 30 had the Papillary TC Follicular Variant (PTCFV). BRAF mutation was present in 41%, TERT in 30%, RAS in 19%, TP53 in 10%, and RET in 8.6% of patients. PD-L1 positivity was significantly different across different TC types and histological subtypes (p < 0.01): Patients with OTC had the highest frequency of PD-L1 positivity (71%), followed by ATC (69%), PTCCV (28.5%), and FTC (11%). Patients with MTC and PTCFV did not exhibit any PD-L1 positivity. TP53 mutation was positively associated with PD-L1 expression (21.6% vs. 7.5%, p = 0.03), and RAS mutation was negatively associated with PD-L1 expression (8.1% vs. 24.2% p = 0.04). Among patients with ATC, positive PD-L1 expression was associated with lower PFS (p = 0.002). Conclusions: PD-L1 expression varies across different TC types and histological subtypes and may be modulated by the mutational landscape. PD-L1 expression in ATC is associated with shorter PFS. Follow up studies are warranted to elucidate the molecular mechanism driving the observed differences in immune pathways, potentially paving the way for the development of more effective and personalized immune therapies for patients with aggressive TC.

Pancreatic cancer has the worst prognosis and lowest survival rate among all cancers. Pancreatic cancer cells are highly metabolically active and typically reprogrammed for aberrant glucose metabolism; thus they respond poorly to therapeutic modalities. It is highly imperative to understand mechanisms that are responsible for high glucose metabolism and identify natural/synthetic agents that can repress glucose metabolic machinery in pancreatic cancer cells, to improve the therapeutic outcomes/management of pancreatic cancer patients. We have identified a glycoside, steviol that effectively represses glucose consumption in pancreatic cancer cells via the inhibition of the translation initiation machinery of the molecular components. Herein, we report that steviol effectively inhibits the glucose uptake and lactate production in pancreatic cancer cells (AsPC1 and HPAF-II). The growth, colonization, and invasion characteristics of pancreatic cancer cells were also determined by in vitro functional assay. Steviol treatment also inhibited the tumorigenic and metastatic potential of human pancreatic cancer cells by inducing apoptosis and cell cycle arrest in the G1/M phase. The metabolic shift by steviol was mediated through the repression of the phosphorylation of mTOR and translation initiation proteins (4E-BP1, eIF4e, eIF4B, and eIF4G). Overall, the results of this study suggest that steviol can effectively suppress the glucose metabolism and translation initiation in pancreatic cancer cells to mitigate their aggressiveness. This study might help in the design of newer combination therapeutic strategies for pancreatic cancer treatment.

Thyroid cancer is a very common endocrine system malignancy. Nevertheless, a dearth of precise markers makes it challenging to apply precision medicine to thyroid cancer. The limitations of standard diagnosis techniques (fine-needle aspiration biopsy), such as indeterminate cases and inaccuracies in distinguishing between different types of cancers, lead to unnecessary surgeries and thus warrant the development of more discriminatory biomarkers to improve the accuracy of existing diagnostic and prognostic techniques. Moreover, individualized therapies for thyroid cancer are necessary to avoid overtreatment of indolent lesions and undertreatment of high-risk progressive disease. As thyroid cancer metabolic signatures are associated with disease aggressiveness and responsiveness to therapy, metabolomics has been recently used for diagnostic and prognostic biomarker discovery. This strategy has enabled the detection of several metabolites from tissue samples or biofluids to facilitate the classification of disease aggressiveness and to potentially assist in individualized therapies. In this review, we summarize the utilization and potential of metabolomics in thyroid cancer.

SAGE-Journals-Accessible-Video-Player 10.1089/ve.2024.0020.M1 sj-vid-1-vde-10.1089_ve.2024.0020

Thyroid cancer is a very common endocrine system malignancy. Nevertheless, a dearth of precise markers makes it challenging to apply precision medicine to thyroid cancer. The limitations to standard diagnosis technique (fine needle aspiration biopsy) such as indeterminate cases and inaccuracies in distinguishing between different types of cancers lead to unnecessary surgeries and thus warrant development of more discriminatory biomarkers to improve the accuracy of the existing diagnostic and prognostic techniques. Moreover, individualized therapies for thyroid cancer are necessary to avoid overtreatment of indolent lesions and undertreatment of high-risk progressive disease. Since thyroid cancer metabolic signatures are associated with disease ag-gressiveness and responsiveness to therapy, metabolomics has been recently used for diagnostic and prognostic biomarkers discovery. This strategy enabled detection of several metabolites from tissue samples or biofluids to facilitate the classification of disease aggressiveness and to potentially assist in individualized therapies. In this review, we have summarized the utilization and potential of metabolomics in thyroid cancer.