Related Experiment Video
Updated: Jul 29, 2026
In Vivo Inhibition of MicroRNA to Decrease Tumor Growth in Mice
Published on: August 23, 2019
Comprehensive Long-Read Sequencing Analysis Discloses the Transcriptome Features of Papillary Thyroid Microcarcinoma
Yanqiang Wang1, Binbin Zou1, Yanyan Zhang2
1Key Laboratory of Cellular Physiology of the Ministry of Education (Shanxi Medical University), Translational Medicine Research Center, Department of Pathology, Shanxi Medical University, Taiyuan, Shanxi 030001, China.
Context:
Papillary thyroid microcarcinoma (PTMC) is the most common type of thyroid cancer. It has been shown that lymph node metastasis is associated with poor prognosis in patients with PTMC.
Objective:
We aim to characterize the PTMC transcriptome landscape and identify the candidate transcripts that are associated with lateral neck lymph node metastasis of PTMC.
Methods:
We performed full-length transcriptome sequencing in 64 PTMC samples. Standard bioinformatic pipelines were applied to characterize and annotate the full-length expression profiles of 2 PTMC subtypes. Functional open reading frame (ORF) annotation of the known and novel transcripts were predicted by HMMER, DeepLoc, and DeepTMHMM tools. Candidate transcripts associated with the pN1b subtype were identified after transcript quantification and differential gene expression analyses.
Results:
We found that skipping exons accounted for the more than 27.82% of the alternative splicing events. At least 42.56% of the discovered transcripts were novel isoforms of annotated genes. A total of 39 193 ORFs in novel transcripts and 18 596 ORFs in known transcripts were identified. Distribution patterns of the characterized transcripts in functional domain, subcellular localization, and transmembrane structure were predicted. In total, 1033 and 1204 differentially expressed genes were identified in the pN0 and pN1b groups, respectively. Moreover, novel isoforms of FRMD3, NOD1, and SHROOM4 were highlighted for their association with pN1b subtype.
Conclusion:
Our data provided the global transcriptome landscape of PTMC and also revealed the novel isoforms that associated with PTMC aggressiveness.
