CircRNA circTIAM1 promotes papillary thyroid cancer progression through the miR-646/HNRNPA1 signaling pathway

Papillary thyroid cancer (PTC) is a common endocrine tumor with a rapidly increasing incidence in recent years. Although the majority of PTCs are relatively indolent and have a good prognosis, a certain proportion is highly aggressive with lymphatic metastasis, iodine resistance, and easy recurrence. Circular RNAs (circRNAs) are a class of noncoding RNAs that are linked to a variety of tumor processes in several cancers, including PTC. In the current study, circRNA high-throughput sequencing was performed to identify alterations in circRNA expression levels in PTC tissues. circTIAM1 was then selected because of its increased expression in PTC and association with apoptosis, proliferation, and migration of PTC cells in vitro and in vivo. Mechanistically, circTIAM1 acted as a sponge of microRNA-646 and functioned in PTC by targeting miR-646 and heterogeneous ribonucleoprotein A1. Fluorescence in situ hybridization and dual-luciferase reporter assays further confirmed these connections. Overall, our results reveal an important oncogenic role of circTIAM1 in PTC and may represent a potentially therapeutic target against PTC progression.

Ultrasonic Intelligent Diagnosis of Papillary Thyroid Carcinoma Based on Machine Learning

Thyroid diseases are divided into papillary carcinoma and nodular diseases, which are very harmful to the human body. Ultrasound is a common diagnostic method for thyroid diseases. In the process of diagnosis, doctors need to observe the characteristics of ultrasound images, combined with professional knowledge and clinical experience, to give the disease situation of patients. However, different doctors have different clinical experience and professional backgrounds, and the diagnosis results lack objectivity and consistency, so an intelligent diagnosis technology for thyroid diseases based on the ultrasound image is needed in clinic, which can give objective and reliable diagnosis opinions on thyroid diseases by extracting the texture, shape, and other information of the image and assist doctors in clinical diagnosis. This paper mainly studies the intelligent ultrasonic diagnosis of papillary thyroid cancer based on machine learning, compares the ultrasonic characteristics of PTMC diagnosed by using the new ultrasound technology (CEUS and UE), and summarizes the differential diagnosis effect and clinical application value of the two technology methods for PTMC. In this paper, machine learning, diffuse thyroid image features, and RBM learning methods are used to study the ultrasonic intelligent diagnosis of papillary thyroid cancer based on machine learning. At the same time, the new contrast-enhanced ultrasound (CEUS) technology and ultrasound elastography (UE) technology are used to obtain the experimental phenomena in the experiment of ultrasonic intelligent diagnosis of papillary thyroid cancer. The results showed that 90% of the cases were diagnosed by contrast-enhanced ultrasound and confirmed by postoperative pathology. CEUS and UE have reliable practical value in the diagnosis of PTMC, and the combined application of CEUS and UE can improve the sensitivity and accuracy of PTMC diagnosis.

Effects of Anti-Cancer Drug Sensitivity-Related Genetic Differences on Therapeutic Approaches in Refractory Papillary Thyroid Cancer

Thyroid cancer (TC) includes tumors of follicular cells; it ranges from well differentiated TC (WDTC) with generally favorable prognosis to clinically aggressive poorly differentiated TC (PDTC) and undifferentiated TC (UTC). Papillary thyroid cancer (PTC) is a WDTC and the most common type of thyroid cancer that comprises almost 70–80% of all TC. PTC can present as a solid, cystic, or uneven mass that originates from normal thyroid tissue. Prognosis of PTC is excellent, with an overall 10-year survival rate >90%. However, more than 30% of patients with PTC advance to recurrence or metastasis despite anti-cancer therapy; consequently, systemic therapy is limited, which necessitates expansion of improved clinical approaches. We strived to elucidate genetic distinctions due to patient-derived anti-cancer drug-sensitive or -resistant PTC, which can support in progress novel therapies. Patients with histologically proven PTC were evaluated. PTC cells were gained from drug-sensitive and -resistant patients and were compared using mRNA-Seq. We aimed to assess the in vitro and in vivo synergistic anti-cancer effects of a novel combination therapy in patient-derived refractory PTC. This combination therapy acts synergistically to promote tumor suppression compared with either agent alone. Therefore, genetically altered combination therapy might be a novel therapeutic approach for refractory PTC.