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Gene Expression as a Predictor of Treatment Response in Thyroid Cancer

Gene Expression as a Predictor of Treatment Response in Thyroid Cancer

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Gene expression profiling shows promise in predicting thyroid cancer response to radioactive iodine, enabling more personalized treatments and improved patient outcomes.

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Recent research conducted by scientists at the Karolinska Institutet highlights the potential of gene expression profiling to predict how patients with papillary thyroid carcinoma (PTC) will respond to radioactive iodine (RAI) therapy. RAI is a common post-surgical treatment aimed at destroying residual cancer cells, but it is only effective when tumor cells can absorb iodine. Unfortunately, approximately 15% of PTC patients and up to half of those with metastatic disease exhibit low or absent iodine uptake, rendering RAI ineffective and necessitating alternative approaches.

In the study, published in Endocrine Pathology and led by Vincenzo Condello and Christofer Juhlin, researchers analyzed 36 tumor samples where iodine uptake was directly measured post-surgery. Using RNA sequencing, they identified 63 genes that differed significantly in expression between tumors with high and low iodine avidity. Notably, the gene ANO1, which encodes an iodine transporter located in thyroid cell membranes, showed a strong correlation with iodine absorption, making it a promising biomarker for treatment response.

Further analysis revealed that genes involved in thyroid hormone synthesis and critical signaling pathways such as PI3K-AKT and MAPK were deregulated in tumors with reduced iodine uptake. Based on these findings, the team developed a predictive model combining ANO1 expression, tumor subtype, and tissue type, demonstrating good accuracy in early identification of patients unlikely to benefit from RAI therapy.

This advancement paves the way for more personalized treatment strategies in thyroid cancer. By employing molecular profiling, clinicians could better determine which patients should receive RAI or be directed toward other treatments, ultimately improving outcomes and reducing unnecessary exposure to ineffective therapies.

This innovative approach exemplifies progress in the field of thyroid cancer management, emphasizing tailored therapies based on genetic and molecular characteristics. The findings underscore the importance of gene expression analysis in developing predictive tools for cancer treatment response.

Source: https://medicalxpress.com/news/2025-09-gene-treatment-response-thyroid-cancer.html

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