Metabolic syndrome and thyroid Cancer: risk, prognosis, and mechanism

Automatic prediction of non-iodine-avid status in lung metastases for radioactive I131 treatment in differentiated thyroid cancer patients

Objectives

The growing incidence of differentiated thyroid cancer (DTC) have been linked to insulin resistance and metabolic syndrome. The imperative need for developing effective diagnostic imaging tools to predict the non-iodine-avid status of lung metastasis (LMs) in differentiated thyroid cancer (DTC) patients is underscored to prevent unnecessary radioactive iodine treatment (RAI).

Methods

Primary cohort consisted 1962 pretreated LMs of 496 consecutive DTC patients with pretreated initially diagnosed LMs who underwent chest CT and subsequent post-treatment radioiodine SPECT. After automatic lesion segmentation by SE V-Net, SE Net deep learning was trained to predict non-iodine-avid status of LMs. External validation cohort contained 123 pretreated LMs of 24 consecutive patients from other two hospitals. Stepwise validation was further performed according to the nodule's largest diameter.

Results

The SE-Net deep learning network yielded area under the receiver operating characteristic curve (AUC) values of 0.879 (95% confidence interval: 0.852-0.906) and 0.713 (95% confidence interval: 0.613-0.813) for internal and external validation. With the LM diameter decreasing from ≥10mm to ≤4mm, the AUCs remained relatively stable, for smallest nodules (≤4mm), the model yielded an AUC of 0.783. Decision curve analysis showed that most patients benefited using deep learning to decide radioactive I131 treatment.

Conclusion

This study presents a noninvasive, less radioactive and fully automatic approach that can facilitate suitable DTC patient selection for RAI therapy of LMs. Further prospective multicenter studies with larger study cohorts and related metabolic factors should address the possibility of comprehensive clinical transformation.

Relationship between METS-IR and thyroid cancer incidence in Korea: a nationwide population-based study

Background

Several previous studies found a positive relationship between metabolic syndrome (MetS) and thyroid cancer (TC) risk. However, there is no research that has studied the relationship between the metabolic score for insulin resistance (METS-IR), a novel surrogate marker for IR, and TC incidence. Thus, we designed this retrospective cohort study to evaluate the relationship between the incidence of TC and METS-IR.

Method

We analyzed a cohort of 314,321 Korean adults aged over 40 years who participated in the National Health Screening Program from 2009 to 2010. The individuals were divided into four groups based on METS-IR quartiles. Follow-up was until the diagnosis of TC or death, or until December 31, 2019, if neither. The relationship between METS-IR and TC incidence was analyzed using the Cox proportional-hazards model with multi-variable adjustments.

Results

A total of 4,137 participants (1.3%) were diagnosed with TC during a mean follow-up of 9.5 ± 1.5 years. The population with Q1 METS-IR scores showed higher disease-free probabilities than those with Q4 METS-IR scores (p <0.001). The hazard ratio (95% confidential interval) for TC incidence in Q2, Q3, and Q4 METS-IR value were 1.14 (1.05 to 1.25), 1.21 (1.11 to 1.33), and 1.30 (1.18 to 1.42) compared with Q1 of METS-IR, respectively. The incidence of TC tended to increase with increasing METS-IR values in the total population, especially the male population in the restricted cubic spline. In subgroup analysis, the TC risk was more pronounced in the subgroups under 65 and with a BMI < 25 kg/m2.

Conclusion

METS-IR was positively correlated with TC incidence in Korea.

Exploring the Link between BMI and Aggressive Histopathological Subtypes in Differentiated Thyroid Carcinoma-Insights from a Multicentre Retrospective Study

Obesity's role in thyroid cancer development is still debated, as well as its association with aggressive histopathological subtypes (AHSs). To clarify the link between Body Mass Index (BMI) and AHS of differentiated thyroid carcinoma (DTC), we evaluated patients who underwent thyroidectomy for DTC from 2020 to 2022 at four European referral centres for endocrine surgery. Based on BMI, patients were classified as normal-underweight, overweight, or obese. AHSs were defined according to 2022 WHO guidelines. Among 3868 patients included, 34.5% were overweight and 19.6% obese. Histological diagnoses were: 93.6% papillary (PTC), 4.8% follicular (FTC), and 1.6% Hürthle cell (HCC) thyroid carcinoma. Obese and overweight patients with PTC had a higher rate of AHSs (p = 0.03), bilateral, multifocal tumours (p = 0.014, 0.049), and larger nodal metastases (p = 0.017). In a multivariate analysis, BMI was an independent predictor of AHS of PTC, irrespective of gender (p = 0.028). In younger patients (<55 years old) with PTC > 1 cm, BMI predicted a higher ATA risk class (p = 0.036). Overweight and obese patients with FTC had larger tumours (p = 0.036). No difference was found in terms of AHS of FTC and HCC based on BMI category. Overweight and obese patients with PTC appear to be at an increased risk for AHS and aggressive clinico-pathological characteristics.

Advances in targeted therapy and biomarker research in thyroid cancer

Driven by the intricacy of the illness and the need for individualized treatments, targeted therapy and biomarker research in thyroid cancer represent an important frontier in oncology. The variety of genetic changes associated with thyroid cancer demand more investigation to elucidate molecular details. This research is clinically significant since it can be used to develop customized treatment plans. A more focused approach is provided by targeted therapies, which target certain molecular targets such as mutant BRAF or RET proteins. This strategy minimizes collateral harm to healthy tissues and may also reduce adverse effects. Simultaneously, patient categorization based on molecular profiles is made possible by biomarker exploration, which allows for customized therapy regimens and maximizes therapeutic results. The benefits of targeted therapy and biomarker research go beyond their immediate clinical impact to encompass the whole cancer landscape. Comprehending the genetic underpinnings of thyroid cancer facilitates the creation of novel treatments that specifically target aberrant molecules. This advances the treatment of thyroid cancer and advances precision medicine, paving the way for the treatment of other cancers. Taken simply, more study on thyroid cancer is promising for better patient care. The concepts discovered during this investigation have the potential to completely transform the way that care is provided, bringing in a new era of personalized, precision medicine. This paradigm shift could improve the prognosis and quality of life for individuals with thyroid cancer and act as an inspiration for advances in other cancer types.

Thyroid cancer and insulin resistance

Thyroid cancer has shown a parallel increase with diabetes in the last few years. This narrative review aims to explain the association between these two entities, focusing on insulin resistance as the mediator and exploring the effects of antidiabetic agents on thyroid cancer incidence and progression.We searched Pubmed for English-written articles on insulin resistance, diabetes, antidiabetic treatments, and thyroid cancer reported from January 2019 to April 2023. Exclusion criteria were preclinical and clinical studies involving a population with thyroid dysfunction, benign nodular goiter, or those that only analyzed thyroid cancer's association with obesity.The results of the narrative literature review revealed 96 articles. Additionally, four studies from a manual search were retrieved. After the exclusion criteria were applied, we included 20 studies. Out of 8 studies on insulin-resistant or Metabolic Syndrome patients, all suggest a positive association with thyroid cancer. At the same time, for diabetes, four out of five publications support a link with thyroid cancer. The seven remaining studies on antidiabetics suggest that metformin might benefit thyroid cancer. In contrast, the evidence for an association between Glucagon-like peptide-1 receptor agonists (GLP-1 RA) and increased thyroid cancer findings is limited.In conclusion, the association between thyroid cancer and diabetes may be explained by insulin resistance, as shown in observational studies. However, the causal role is yet to be defined. Although the wide use of different antidiabetic agents has been related to thyroid cancer prevalence and progression, future research with drugs such as metformin or GLP-1 RA is still needed.

Assessment of causal association between differentiated thyroid cancer and disordered serum lipid profile: a Mendelian randomization study

Background

Research has shown that the disordered serum lipid profile may be associated with the risk of differentiated thyroid cancer (DTC). Whether this association reflect causal effect is still unclear. The aim of this study was to evaluate the causality of circulating lipoprotein lipids on DTC.

Methods

Mendelian randomization (MR) analysis was conducted to evaluate the relationship between the circulating lipoprotein lipids and DTC risk using single-nucleotide polymorphisms (SNPs) from a genome-wide association (GWA) study containing a high-incidence Italian population of 690 cases samples with DTC and 497 controls.

Results

Univariate and multivariate mendelian randomization analysis demonstrated that 'total cholesterol', 'HDL cholesterol', 'apolipoprotein B' and 'ratio of apolipoprotein B to apolipoprotein A1' were correlated with DTC. According to sensitivity analysis, our results were reliable. Furthermore, multivariate analysis revealed that there is no causative association between DTC and any of the many cause factors when they interact with one another, suggesting that there was a deep interaction between the four factors, which could affect each other. Finally, the mechanism of the related effects each other as well as the target genes with significant SNP regulatory effects in DTC was explored by conducting functional enrichment analysis and constructing the regulatory networks.

Conclusions

We obtained four exposure factors (total cholesterol, HDL cholesterol, apolipoprotein B and ratio of apolipoprotein B to apolipoprotein A1) closely related to DTC, which laid a theoretical foundation for the treatment of DTC.

Glucagon-like peptide 1 receptor agonists and thyroid cancer: is it the time to be concerned?

Glucagon-like peptide 1 receptor agonists (GLP-1RAs) have changed considerably the management of type 2 diabetes (T2D). However, recently published data from retrospective cohort studies suggest that chronic exposure to GLP-1RAs in T2D may increase the risk of papillary and medullary thyroid cancer. In this perspective, the role of the incretin system in thyroid carcinogenesis has been reviewed and critically commented on, aiming to understand if the time has arrived to be concerned about the risk. Although evidence suggested, speculative hypotheses should be verified, and further studies are urgently needed to clarify the issue.

Obesity and thyroid cancer risk

PURPOSE OF REVIEW

This review explores recent evidence assessing the relationship between obesity and thyroid cancer.

RECENT FINDINGS

Consistent evidence from observational studies suggests that obesity increases the risk of thyroid cancer. The relationship persists when alternative measures of adiposity are used, but the strength of association may vary according to the timing and duration of obesity and how obesity or other metabolic parameters are defined as exposures. Recent studies have reported an association between obesity and thyroid cancers that are larger or have adverse clinicopathologic features, including those with BRAF mutations, thus providing evidence that the association is relevant for clinically significant thyroid cancers. The underlying mechanism for the association remains uncertain but may be driven by disruption in adipokines and growth-signaling pathways.

SUMMARY

Obesity is associated with an increased risk of thyroid cancer, although further research is required to understand the biological mechanisms underpinning this relationship. Reducing the prevalence of obesity is predicted to lessen the future burden of thyroid cancer. However, the presence of obesity does not impact current recommendations for screening or management of thyroid cancer.

The Tumor Microenvironment and the Estrogen Loop in Thyroid Cancer

Thyroid cancer (TC) cells employ multiple signaling pathways, such as PI3K/AKT/mTOR and RAS/Raf/MAPK, fostering cell proliferation, survival and metastasis. Through a complex interplay with immune cells, inflammatory mediators and stroma, TC cells support an immunosuppressive, inflamed, pro-carcinogenic TME. Moreover, the participation of estrogens in TC pathogenesis has previously been hypothesized, in view of the higher TC incidence observed among females. In this respect, the interactions between estrogens and the TME in TC could represent a relevant, unexplored area of research. We thereby collectively reviewed the available evidence concerning the potential carcinogenic role of estrogens in TC, specifically focusing on their crosstalk with the TME.