A sorafenib-sparing effect in the treatment of thyroid carcinoma cells attained by co-treatment with a novel isoflavone derivative and 1,25 dihydroxyvitamin D3

Antineoplastic properties of polyphenols in TPC-1 human papillary thyroid carcinoma cell line: a systematic review

Thyroid cancer usually responds to surgical and ablative therapy, but when it's refractory the alternative lies in tyrosine kinase inhibitors that, in addition to harmful side effects, acts only in a palliative way. The concern for other therapeutic possibilities brought evidence on flavonoids, hypothesizing a possible strategy. This review aimed to organize a compilation of in vitro studies using polyphenol substances in TPC-1 (human papillary thyroid carcinoma cell line) summarizing it's results and describing the metabolic pathways involved. Articles were selected on PubMed, Google Scholar, LILACS, BVS and SciELO, using keywords "thyroid cancer", "flavonoids" and "TPC-1", until June 2022. 185 studies were selected. After identification and exclusion of duplicates and exclusion criteria applied, 11 original articles were evaluated. Of these, the findings of flavonoids added to TPC-1 were: inhibition of cell growth and viability, promotion of cell cycle arrest and induction of apoptosis. Polyphenolic compounds have antineoplastic properties by different mechanisms as shown in vitro, but the concentrations needed are above usual dietary consumption and the findings are limited to experimental cellular studies. Despite that, these results should be useful to guide further analysis aiming to reveal the real safety and efficacy of polyphenols in this scenario.

Vitamin D-Related Genes and Thyroid Cancer-A Systematic Review

Vitamin D, formerly known for its role in calcium-phosphorus homeostasis, was shown to exert a broad influence on immunity and on differentiation and proliferation processes in the last few years. In the field of endocrinology, there is proof of the potential role of vitamin D and vitamin D-related genes in the pathogenesis of thyroid cancer-the most prevalent endocrine malignancy. Therefore, the study aimed to systematically review the publications on the association between vitamin D-related gene variants (polymorphisms, mutations, etc.) and thyroid cancer. PubMed, EMBASE, Scopus, and Web of Science electronic databases were searched for relevant studies. A total of ten studies were found that met the inclusion criteria. Six vitamin D-related genes were analyzed (VDR-vitamin D receptor, CYP2R1-cytochrome P450 family 2 subfamily R member 1, CYP24A1-cytochrome P450 family 24 subfamily A member 1, CYP27B1-cytochrome P450 family 27 subfamily B member 1, DHCR7-7-dehydrocholesterol reductase and CUBN-cubilin). Moreover, a meta-analysis was conducted to summarize the data from the studies on VDR polymorphisms (rs2228570/FokI, rs1544410/BsmI, rs7975232/ApaI and rs731236/TaqI). Some associations between thyroid cancer risk (VDR, CYP24A1, DHCR7) or the clinical course of the disease (VDR) and vitamin D-related gene polymorphisms were described in the literature. However, these results seem inconclusive and need validation. A meta-analysis of the five studies of common VDR polymorphisms did not confirm their association with increased susceptibility to differentiated thyroid cancer. Further efforts are necessary to improve our understanding of thyroid cancer pathogenesis and implement targeted therapies for refractory cases.

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi‐gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology‐based approach. This began with expression of genes previously implicated in specific drug responses, then expanded to evaluate genes whose products were related through biochemical pathways and interactions. Optimal pathway‐extended SVMs predicted responses in patients at accuracies of 70% (imatinib), 71% (lapatinib), 83% (sunitinib), 83% (erlotinib), 88% (sorafenib) and 91% (gefitinib). These best performing pathway‐extended models demonstrated improved balance predicting both sensitive and resistant patient categories, with many of these genes having a known role in cancer aetiology. Ensemble machine learning‐based averaging of multiple pathway‐extended models derived for an individual drug increased accuracy to >70% for erlotinib, gefitinib, lapatinib and sorafenib. Through incorporation of novel cancer biomarkers, machine learning‐based pathway‐extended signatures display strong efficacy predicting both sensitive and resistant patient responses to chemotherapy.

Plant natural products with anti-thyroid cancer activity

Thyroid cancer is the most frequent endocrine malignancy, with more than 500,000 cases per year worldwide. Differentiated thyroid cancers are the most common forms with best prognosis, while poorly/undifferentiated ones are rare (2% of all thyroid cancer), aggressive, frequently metastasize and have a worse prognosis. For aggressive, metastatic and advanced thyroid cancer novel antitumor molecules are urgently needed and phytochemical products can be a rational and extensive source, since secondary plant metabolites can guarantee the necessary biochemical variability for therapeutic purpose. Among bioactive molecules that present biological activity on thyroid cancer, resveratrol, curcumin, isoflavones, glucosinolates are the most common and used in experimental model. Most of them have been studied both in vitro and in vivo on this cancer, but rarely in clinical trial. This review summarizes phytochemicals, phytotherapeutics and plant derived compounds used in thyroid cancer.