Yan Gui^1,#, Wen Pan^1,#, Ziyi Dong^1,#, Dongzhi Hu^1,#, Yaoyang Guo¹, Xinyi Wen¹, Haiyang Zhang², Zhansheng Jiang^1,*, Xiangqian Zheng^1,*, Ming Gao^2,*, Junyi Wang^1,*

Oncology Research, Vol.33, No.12, pp. 3991-4011, 2025, DOI:10.32604/or.2025.067182 - 27 November 2025

Abstract Objectives: Metastatic spread to the lung is one of the leading causes of fatal outcomes in thyroid cancer, but the underlying molecular mechanisms remain unclear. To investigate how exosomal microRNA-17-5p (miR-17-5p) promotes lung metastasis in thyroid cancer within the framework of the “seed and soil” hypothesis. Methods: Serum exosomes from thyroid cancer lung metastasis patients and controls were analyzed for miR-17, which was elevated in metastatic cases. miR-17 was transfected into embryonic lung fibroblasts (MRC-5), and their supernatants were co-cultured with thyroid cancer cells (Cal62). Cell proliferation and migration were evaluated using colony formation, Ki67… More >

JONG-HYUK AHN¹, JIN WOOK YI^2,3,*

Oncology Research, Vol.33, No.8, pp. 1909-1931, 2025, DOI:10.32604/or.2025.065847 - 18 July 2025

Abstract Background: With growing interest in space exploration, understanding microgravity’s impact on human health is essential. This study aims to investigate gene expression changes and migration and invasion potential in five thyroid-related cell lines cultured under simulated microgravity. Methods: Five thyroid-related cell lines—normal thyrocytes (Nthy-ori 3-1), papillary thyroid cancer (PTC) cells (SNU-790, TPC-1), poorly differentiated thyroid cancer cell (BCPAP), and anaplastic thyroid cancer cell (SNU-80)—were cultured under simulated microgravity (10⁻³ g) using a clinostat. Differentially expressed genes (DEGs) were analyzed using cDNA microarray, followed by functional annotation and assessment of aggressiveness via Transwell migration and invasion assays.… More >

FANG CHEN¹, DONGQIANG YANG², YUHUA RU³, SHAN CAO¹, AISHE GAO¹

Oncology Research, Vol.33, No.7, pp. 1799-1800, 2025, DOI:10.32604/or.2025.064363 - 26 June 2025

Abstract This article has no abstract. More >

María Belén Rocco, Clara Requena D’Alessio, Valeria Giselle Sánchez, Horacio Eduardo Romeo, María Laura Barreiro Arcos^*

BIOCELL, Vol.49, No.4, pp. 629-646, 2025, DOI:10.32604/biocell.2025.062525 - 30 April 2025

Abstract Introduction: Hyperthyroidism is known to affect various physiological systems, including the immune system. Thyroid hormones (THs) play a crucial role in regulating immune function, and alterations in THs levels can lead to immune dysregulation. Objective: Currently, we aimed to elucidate the effects of hyperthyroidism on immune function in BALB/c mice, with a focus on anatomical and histological changes in lymphoid organs, the immune response to mitogenic stimulation, mitochondrial dynamics, and reactive oxygen species (ROS) production. Methods: Hyperthyroidism was induced in BALB/c mice by administering thyroxine (T4; 14 mg/L) in their drinking water for 30 days. Thyroid… More >

Kaku Haribabu^1,*, Prasath R¹, Praveen Joe IR²

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 413-448, 2025, DOI:10.32604/cmes.2025.059406 - 11 April 2025

Abstract Thyroid nodules, a common disorder in the endocrine system, require accurate segmentation in ultrasound images for effective diagnosis and treatment. However, achieving precise segmentation remains a challenge due to various factors, including scattering noise, low contrast, and limited resolution in ultrasound images. Although existing segmentation models have made progress, they still suffer from several limitations, such as high error rates, low generalizability, overfitting, limited feature learning capability, etc. To address these challenges, this paper proposes a Multi-level Relation Transformer-based U-Net (MLRT-UNet) to improve thyroid nodule segmentation. The MLRT-UNet leverages a novel Relation Transformer, which processes… More >

YE ZHANG¹, YANAN LIANG², YAN WU², LIWEN SONG², ZUWANG ZHANG^2,*

Oncology Research, Vol.32, No.11, pp. 1747-1763, 2024, DOI:10.32604/or.2024.030945 - 16 October 2024

Abstract Background: Papillary thyroid cancer (PTC) is the most prevalent histological type of differentiated thyroid malignancy. Circular RNAs (circRNAs) have been implicated in the pathogenesis and progression of various cancers. circTIAM1 (hsa_circ_0061406) is a novel circRNA with aberrant expression in PTC. However, its functional roles in PTC progression remain to be investigated. Methods: The expression levels of circTIAM1 in the PTC and the matched para-cancerous tissues were detected by quantitative real-time reverse-transcription PCR (qRT-PCR). The subcellular localization of circTIAM1 was examined by fluorescence in-situ hybridization (FISH). Kaplan-Meier plot was used to analyze the association of clinicopathological features… More >

LIANG HE^1,2, WEI HAN^1,3, KAI YUE¹, XUDONG WANG^1,*

Oncology Research, Vol.32, No.9, pp. 1467-1478, 2024, DOI:10.32604/or.2024.047382 - 23 August 2024

Abstract Objectives: Thyroid cancer (THCA) is the most common malignant tumor in endocrine system and the incidence has been increasing worldwide. And the number of patients dying from THCA has also gradually risen because the incidence continues to increase, so the mechanisms related to effective targets is necessary to improve the survival. This study was to preliminarily investigate the effects of the COL4A2 gene on the regulation of thyroid cancer (THCA) cell proliferation and the associated pathways. Methods: Bioinformatics analysis revealed that COL4A2 was closely associated with cancer development. COL4A2 expression in THCA tissues was analyzed… More >

ELHAM SHAKIBA¹, SETI BOROOMAND², SIMA KHERADMAND KIA³, MEHDI HEDAYATI^4,*

Oncology Research, Vol.32, No.6, pp. 1011-1019, 2024, DOI:10.32604/or.2024.049235 - 23 May 2024

Abstract This review aimed to describe the inculpation of microRNAs (miRNAs) in thyroid cancer (TC) and its subtypes, mainly medullary thyroid carcinoma (MTC), and to outline web-based tools and databases for bioinformatics analysis of miRNAs in TC. Additionally, the capacity of miRNAs to serve as therapeutic targets and biomarkers in TC management will be discussed. This review is based on a literature search of relevant articles on the role of miRNAs in TC and its subtypes, mainly MTC. Additionally, web-based tools and databases for bioinformatics analysis of miRNAs in TC were identified and described. MiRNAs can… More > Graphic Abstract

Sujithra Sankar^1,*, S. Sathyalakshmi²

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 3111-3138, 2024, DOI:10.32604/cmc.2024.048408 - 15 May 2024

Abstract In the era of advanced machine learning techniques, the development of accurate predictive models for complex medical conditions, such as thyroid cancer, has shown remarkable progress. Accurate predictive models for thyroid cancer enhance early detection, improve resource allocation, and reduce overtreatment. However, the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency. This paper proposes a novel association-rule based feature-integrated machine learning model which shows better classification and prediction accuracy than present state-of-the-art models. Our study also focuses on the application of SHapley Additive exPlanations (SHAP) values as… More >

Muhammad Armghan Latif¹, Zohaib Mushtaq², Saad Arif³, Sara Rehman⁴, Muhammad Farrukh Qureshi⁵, Nagwan Abdel Samee⁶, Maali Alabdulhafith^6,*, Yeong Hyeon Gu⁷, Mohammed A. Al-masni⁷

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4225-4241, 2024, DOI:10.32604/cmc.2024.047621 - 26 March 2024

Abstract Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid gland. Accurate and timely diagnosis of these disorders is crucial for effective treatment and patient care. This research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection techniques. Sequential forward feature selection, sequential backward feature elimination, and bidirectional feature elimination are investigated in this study. In ensemble learning, random forest, adaptive boosting, and bagging classifiers are employed. The effectiveness of… More >