Transcriptomic characteristics according to tumor size and SUVmax in papillary thyroid cancer patients

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Title
Transcriptomic characteristics according to tumor size and SUVmax in papillary thyroid cancer patients
Author(s)
S H Ju; S E Lee; S Yi; N R Choi; K H Kim; S M Kim; J Y Koh; Seon-Kyu KimSeon-Young Kim; J Y Heo; J O Park; S Park; B S Koo; Y E Kang
Bibliographic Citation
Scientific Reports, vol. 14, pp. 11005-11005
Publication Year
2024
Abstract
The SUVmax is a measure of FDG uptake and is related with tumor aggressiveness in thyroid cancer, however, its association with molecular pathways is unclear. Here, we investigated the relationship between SUVmax and gene expression profiles in 80 papillary thyroid cancer (PTC) patients. We conducted an analysis of DEGs and enriched pathways in relation to SUVmax and tumor size. SUVmax showed a positive correlation with tumor size and correlated with glucose metabolic process. The genes that indicate thyroid differentiation, such as SLC5A5 and TPO, were negatively correlated with SUVmax. Unsupervised analysis revealed that SUVmax positively correlated with DNA replication(r = 0.29, p = 0.009), pyrimidine metabolism(r = 0.50, p < 0.0001) and purine metabolism (r = 0.42, p = 0.0001). Based on subgroups analysis, we identified that PSG5, TFF3, SOX2, SL5A5, SLC5A7, HOXD10, FER1L6, and IFNA1 genes were found to be significantly associated with tumor aggressiveness. Both high SUVmax PTMC and macro-PTC are enriched in pathways of DNA replication and cell cycle, however, gene sets for purine metabolic pathways are enriched only in high SUVmax macro-PTC but not in high SUVmax PTMC. Our findings demonstrate the molecular characteristics of high SUVmax tumor and metabolism involved in tumor growth in differentiated thyroid cancer.
Keyword
SUVmaxPET/CTTranscriptomicsPapillary thyroid carcinoma
ISSN
2045-2322
Publisher
Springer-Nature Pub Group
Full Text Link
http://dx.doi.org/10.1038/s41598-024-61839-0
Type
Article
Appears in Collections:
Aging Convergence Research Center > 1. Journal Articles
Division of A.I. & Biomedical Research > Genomic Medicine Research Center > 1. Journal Articles
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