Identification of key functional gene signatures indicative of dedifferentiation in Papillary Thyroid cancer
Papillary thyroid cancer (PTC) is the most common type of thyroid cancer, and the majority of PTCs exhibit a relatively good prognosis. However, it has been observed recently that some PTCs may dedifferentiate in some situations. When PTC appears to be dedifferentiated, its prognosis becomes very poor, and conventional surgical treatment cannot achieve good therapeutic effects. Such patients often experience relapse or metastasis in a short period of time. At present, the treatment methods for poorly differentiated thyroid cancer (PDTC) and anaplastic thyroid cancer (ATC) are limited, and their progression mechanism is still unclear.
It has been shown that many ATC and PDTC result from dedifferentiation of DTC. In addition, some genetic abnormalities such as TERT and TP53 mutation may play an important role. A considerable number of studies have shown that occurrence and development of PDTC and ATC are closely related to immune microenvironment and epigenetic changes. Our previous study also revealed that some genes may have a significant impact on the initiation and progression of dedifferentiation thyroid cancer (DDTC) through metabolism related pathways. However, considering that dedifferentiation of DTC is accompanied by a great increase in the degree of malignancy, it is likely that dedifferentiation must involve more than one mechanism. It is not clear which malignant phenotypes are affected by genes closely related to DTC dedifferentiation and this needs to be investigated further.
This study was oriented toward mining out differentially expressed genes among PDTC, PTC and normal thyroid (NT) at the level of transcriptome, and then classifying them into different groups based on their biological functions, to explore possible dedifferentiation related processes. We expect that our findings could provide a plausible basis for further study of PDTC, thereby helping to predict prognosis and development of PTC, and exploring the possibility of reversing dedifferentiation or re-differentiation.
Sample collection
Six NT, five PTC and five PDTC specimens were obtained from eight patients who underwent surgical management in FUSCC . The information of the eight patients and 16 samples was described in our previous study. These 16 samples were included in a discovery cohort, and used for high-throughput RNA sequencing (RNA-seq) to identify differentially expressed genes. Written informed consent was obtained from each patient before his/her specimens were used in this study, and the study was approved by the Medical Ethics Committee of the FUSCC. All procedures performed in this study were in accordance with the Declaration of Helsinki.
RNA-seq analysis
Total RNA was extracted from all samples using TRIzol reagent (Life Technologies, Carlsbad, CA). We used RiboMinus eukaryote kit (Qiagen, Valencia, CA) to remove ribosomal RNA of total RNA (~3 mg) before RNA-seq libraries construction. Strand-specific RNA-Seq libraries were prepared using the Illumina workflow (New England BioLabs, Beverly, MA).Next, the samples were fragmented, reverse-transcribed, and ligated to Illumina adaptors. We purified the ligated cDNA products to remove second-strand cDNA. After 13-15 cycles of amplification, libraries were controlled for quality and quantified using with an Agilent 2100 bioanalyzer (Agilent Technologies, Santa Clara, CA) and sequenced by a HiSeq 2000 sequencing system (Illumina, SanDiego, CA) on a 100-bp paired-end run. Clustal Omega was used for sequence alignment. Human genome version GRCh38.100 were used throughout. Significant differences were determined by Limma package (version 3.11; https://bioconductor.org/packages/limma/).
