MEG3 Expression Indicates Lymph Node Metastasis and Presence of Cancer-Associated Fibroblasts in Papillary Thyroid Cancer
Rodríguez, Tomás C
Carnazza, Michelle A
Tiwari, Raj K
UMass Chan AffiliationsMorningside Graduate School of Biomedical Sciences
RNA Therapeutics Institute
Document TypeJournal Article
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AbstractPapillary thyroid cancer is the most common endocrine malignancy, occurring at an incidence rate of 12.9 per 100,000 in the US adult population. While the overall 10-year survival of PTC nears 95%, the presence of lymph node metastasis (LNM) or capsular invasion indicates the need for extensive neck dissection with possible adjuvant radioactive iodine therapy. While imaging modalities such as ultrasound and CT are currently in use for the detection of suspicious cervical lymph nodes, their sensitivities for tumor-positive nodes are low. Therefore, advancements in preoperative detection of LNM may optimize the surgical and medical management of patients with thyroid cancer. To this end, we analyzed bulk RNA-sequencing datasets to identify candidate markers highly predictive of LNM. We identified MEG3, a long-noncoding RNA previously described as a tumor suppressor when expressed in malignant cells, as highly associated with LNM tissue. Furthermore, the expression of MEG3 was highly predictive of tumor infiltration with cancer-associated fibroblasts, and single-cell RNA-sequencing data revealed the expression of MEG3 was isolated to cancer-associated fibroblasts (CAFs) in the most aggressive form of thyroid cancers. Our findings suggest that MEG3 expression, specifically in CAFs, is highly associated with LNM and may be a driver of aggressive disease.
SourceDadafarin S, Rodríguez TC, Carnazza MA, Tiwari RK, Moscatello A, Geliebter J. MEG3 Expression Indicates Lymph Node Metastasis and Presence of Cancer-Associated Fibroblasts in Papillary Thyroid Cancer. Cells. 2022 Oct 10;11(19):3181. doi: 10.3390/cells11193181. PMID: 36231143; PMCID: PMC9562881.
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/51603
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Except where otherwise noted, this item's license is described as Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).