Targeting DEP domain containing 1 in anaplastic thyroid carcinoma: Implications for stemness regulation and malignant phenotype suppression

Abstract

Background

Anaplastic thyroid carcinoma (ATC), a rare but highly aggressive endocrine malignancy, is characterized by a significant presence of cancer stem-like cells (CSCs). These CSCs, known for their self-renewal and differentiation capacities, contribute to various aggressive tumor properties, including recurrence, metastasis, heterogeneity, multidrug resistance, and radiation resistance. Despite their critical role, the regulatory mechanisms of CSCs in ATC remain poorly elucidated, posing challenges in effectively targeting these cells for treatment.

Methods

To delve into this, we employed the single sample gene set enrichment analysis (ssGSEA) algorithm to evaluate the stemness of samples in combined datasets. Samples were then classified into high and low stemness subgroups based on their average stemness scores. Differential gene expression between these subgroups was analyzed. We further explored the association of candidate genes with patient prognosis. Additionally, we conducted gene set enrichment analysis (GSEA) and a series of cell biology experiments to validate the role of DEP domain-containing protein 1 (DEPDC1) in fostering CSC-like traits and regulating the malignant phenotypes of ATC.

Results

Our investigation demonstrated that DEPDC1 was significantly upregulated in CSCs and is abundantly expressed in ATC tissues. In vitro assays revealed that knockdown of DEPDC1 markedly inhibited tumor sphere formation and attenuated the proliferation, invasion, and migration of ATC cells. This silencing also resulted in reduced expression of stemness markers associated with CSCs. Furthermore, our GSEA findings linked high DEPDC1 expression to cell cycle progression and the maintenance of tumor cell stemness, with DEPDC1 knockdown disrupting these signaling pathways. Collectively, our results position DEPDC1 as a pivotal regulator of CSC-like characteristics in ATC, where aberrant DEPDC1 expression amplifies stemness properties and fuels the cancer's aggressive behavior. Consequently, DEPDC1 emerges as a promising therapeutic target for ATC management. In summary, this study underscores the pivotal role of DEPDC1 in modulating CSC-like features in ATC, offering new avenues for targeted therapy in this challenging malignancy.

1. Introduction

The mortality rate associated with thyroid cancer (THCA), the most prevalent endocrine malignancy, is on an upward trend. The current therapeutic landscape for thyroid cancer predominantly includes surgical resection, radiotherapy, chemotherapy, and siRNA therapy delivery [1,2]. RNA interference (RNAi) is increasingly recognized by researchers as a potent gene-silencing mechanism with significant potential in cancer treatment [3,4]. Papillary thyroid carcinoma (PTC), constituting approximately 80% of all thyroid malignancies [5], contrasts starkly with anaplastic thyroid carcinoma (ATC), which, although accounting for less than 2% of thyroid cancers, contributes to 14–39.9% of thyroid cancer-related fatalities [6]. ATC is notorious for its rapid progression, resistance to conventional therapies, and dismal treatment outcomes, leading to its classification as one of the most lethal cancers. The one-year survival rate for ATC patients is alarmingly low, ranging from 5 to 19.9%, typically accompanied by a poor prognosis [[7], [8], [9]]. The American Joint Committee on Cancer (AJCC) categorizes ATC patients in the stage IV bracket of the Tumor-Lymph Node-Metastasis (TNM) classification, with the average survival duration post-diagnosis being a mere 3–7 months [10]. Presently, the therapeutic options available for ATC are limited and fail to substantially enhance overall patient survival [11,12]. Therefore, deciphering the key drivers behind ATC's malignant progression is imperative for advancing treatment strategies and improving patient outcomes.

Cancer stem cells (CSCs), a critical subpopulation within tumors, are characterized by their self-renewing capability, heterogeneity, and high tumorigenic potential. These cells play a pivotal role in driving malignant proliferation and enabling immune evasion within tumors. It has been demonstrated in prior research that anaplastic thyroid carcinoma (ATC) cells likely originate from oncogenic mutations in thyroid stem cells, underscoring the significance of CSCs in ATC's malignant progression. Contemporary evidence substantiates the hypothesis that the relentless capabilities of CSCs for self-renewal, tumor re-initiation, and ongoing evolution are fundamental to the observed aggressiveness and treatment resistance in ATC [13]. Furthermore, CSCs are intimately associated with tumor metastasis, immune system evasion, recurrence, and resistance to both radiotherapy and chemotherapy. These factors collectively contribute to the high incidence of treatment failure in clinical scenarios. Thus, strategically targeting and modulating CSCs holds substantial promise as an innovative and effective approach in cancer therapeutics.

DEP Domain Containing 1 (DEPDC1) is an emerging oncogene that has been identified as upregulated in a range of malignancies. This gene is located in the 1p31.3 region of human chromosome 1. Notably, DEPDC1's involvement has been recognized in the development of diverse cancers, including lung, gastric, hepatocellular, bladder, breast, prostate, and colorectal cancers (CRC) [[14], [15], [16], [17], [18], [19], [20], [21], [22], [23]]. Functionally, DEPDC1 can interact with zinc finger protein (ZNF224), resulting in the inhibition of A20's transcriptional activity and the restriction of NF-κB translocation from the cytoplasm to the nucleus [19]. A peptide corresponding to amino acids 611–628 of DEPDC1 has shown potential in disrupting the DEPDC1/ZNF224 complex, offering a promising avenue for inhibiting cell proliferation in bladder cancer [19]. Furthermore, DEPDC1 is implicated in regulating cell cycle progression in nasopharyngeal carcinoma [24], and in prostate cancer cells, it interacts with E2F1 to enhance its transcriptional activity, thereby activating genes that promote cell proliferation [22]. In breast cancer, DEPDC1 activates the PI3K/AKT/mTOR signaling pathway [21], and it has been shown to upregulate Forkhead Box M1 (FoxM1), facilitating cell proliferation [25]. MicroRNA-130a and microRNA-26b have been identified as negative regulators of DEPDC1 expression [25,26]. Despite these insights, the exploration of DEPDC1 in ATC remains nascent. The role of DEPDC1 in modulating the malignant phenotype of ATC is not well understood, prompting the need for further research.

The objective of this study was to identify and characterize six genes associated with cancer stem cell-like traits, aiming to elucidate the underlying factors driving the malignant progression of ATC. Our research revealed that diminishing the expression of DEPDC1 significantly inhibited characteristics associated with stemness and proliferation in cancer cells, thereby impacting the advancement of ATC. These findings highlight the pivotal role of DEPDC1 as a key facilitator of ATC's malignant features. Importantly, this suggests that DEPDC1 could serve as a potential therapeutic target in the treatment of ATC, offering new avenues for intervention in this aggressive cancer type.

2. Materials and methods

2.1. Microarray information

The microarray datasets from the GEO database were downloaded for analysis. These datasets include samples of different types of thyroid carcinomas (ATCs, PTCs, and PDTCs) as well as normal tissues [23]. The GPL570 platform was used for these datasets. To ensure the accuracy of the analysis, the datasets were corrected and their dimensionality was reduced using the Remove Batch effect function of the limma package and principal component analysis in the R4.1.3 environment.

2.2. Bioinformatics analysis

The stemness of ATC samples in the dataset was evaluated using the ssGSEA algorithm, which compares gene expression data with a specific gene set to estimate relative enrichment. The mean stemness score was calculated for all ATC samples, and the samples were then divided into high and low stemness groups. The differentially expressed genes between these groups were analyzed using the limma package. Protein-protein interaction (PPI) network analysis was conducted using the STRING database and Cytoscape software, with hub genes identified through the MCC method in cytoHubba. The prognostic significance of these hub genes was evaluated using Kaplan Meier survival analysis. The expression analysis of DEPDC1 in ATC vs. normal groups was performed using the limma package, and its correlation with stemness score in ATC samples was investigated. DEPDC1 expression-based grouping was used to identify differential genes, and gene set enrichment analysis was performed to explore pathways enriched in these genes. The differential genes were also clustered using MEGENA analysis. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted on the genes located in the submodule associated with DEPDC1.

2.3. Cell culture and transfection

Fenghui Biotechnology provided the KHM-5M and 8505C cell lines. Both cell lines were cultured in either DMEM or RPMI-1640 medium with 10% FBS obtained from Gbico in the USA. To achieve a confluence of 30–40%, the 8505C cells were seeded in 6-well plates. For transfection of siRNAs targeting DEPDC1, jetPRIME from Polyplus in the USA was utilized according to the accompanying instructions. Self-designing of the target sequence for DEPDC1 siRNAs was performed on the website of the National Center for Biotechnology Information (NCBI). The target sequence for DEPDC1 siRNA#1 was CGAGATGTATTCAGAACAA, while for DEPDC1 siRNA#2 it was CCAACTTACTCATACTGTA.

2.4. Western blot and qRT-PCR

The procedures for Western blot and qRT-PCR were conducted according to the methods outlined in a previous publication by our team [27]. The primary antibodies used for protein detection and immunohistochemistry were DEPDC1 (GeneTex, 1:1000, China) and β-actin (Proteintech, 1:3000, China). The study protocol received approval from the Ethics Committee of Zhejiang Provincial People's Hospital. The qRT-PCR primers used were as follows: DEPDC1 forward primer: 5′-GGTTCTGATTATGCCTACTGGTTGA-3′, DEPDC1 reverse primer: 5′-TGGAATCTATCCATGTTCCAGCTTA-3′, β-actin forward primer: 5′-ACCTTCTACAATGAGCTGCG-3′, β-actin reverse primer: 5′-CCTGGATAGCAACGTACATGG-3’.

2.5. Migration

In order to conduct the migration experiment, the ATC cells were subjected to treatment and subsequently placed in the upper chamber, which had been pre-coated. The upper chamber was filled with medium containing 0% FBS, while the lower chamber contained medium with 10% FBS, and both were incubated for a duration of 48 h. Following incubation, the migratory cells were fixed using methanol and stained using a 0.1% crystal violet solution obtained from Applygen, a company based in China. The cells that had invaded the lower chamber were then captured through photography after gently wiping off the cells present in the upper chamber. For the cell invasion experiment, the ATC cells that had been transfected were seeded in the upper chamber which had been pre-coated with a 5% Matrigel solution from Corning, a company based in the USA. Similar to the migration assay, the upper chamber was filled with medium containing 0% serum, while the lower chamber contained medium with 10% serum. The chambers were incubated for 48 h [5].

2.6. Invasion

After treating the invasive cells with methanol, they were subjected to staining using 0.1% crystal violet solution (Dawen biotech, China). Subsequently, the infiltrating cells were captured through photography following a gentle wipe-off of the cells present in the upper chamber [5].

2.7. Clone formation

In the clone formation assay, the ATC cells were treated and then placed in a 12-well plate with 500 cells per well. They were incubated for a period of one week. After this incubation period, the cells were fixed using methanol and stained using a 0.1% crystal violet solution from Dawen biotech, China. Finally, photographs of the stained cells were taken.

2.8. Data analysis

The mean ± SD of three independent tests was used to represent the data. Statistical differences between the two groups were analyzed using the unpaired Student's t-tests with GraphPad Prism 7. Statistical significance was indicated as * (P < 0.05), ** (P < 0.01), and *** (P < 0.001). In this study, the data were presented as the mean ± SD of three independent tests. This method allowed for the representation of the central tendency and variability of the data. To determine if there were statistical differences between the two groups, the unpaired Student's t-tests were conducted using GraphPad Prism 7. This statistical test is commonly used to compare the means of two groups. To indicate statistical significance, the commonly accepted criteria of * (P < 0.05), ** (P < 0.01), and *** (P < 0.001) were utilized. These symbols helped to easily identify the level of significance in the results.

3. Results

3.1. Processing and analysis of datasets related to thyroid cancer

The thyroid cancer datasets (GSE29265, GSE33630, and GSE76039) were retrieved from the GEO database and merged. Subsequently, batch effects were corrected while ensuring the preservation of differences between groups. Heatmaps, illustrating the stemness scores of samples within the merged dataset, were generated and are displayed in Fig. 1A. The samples were categorized into groups based on high and low stemness scores (Fig. 1B). Utilizing the limma package, differential analysis of stemness-related genes between these groups was conducted, with results presented in Fig. 1C. This analysis revealed significant alterations in several genes, including PBK, DEPDC1, NUF2, DLGAP5, TTK, TRIP13, and ANLN. To gain a deeper understanding of the roles these differential genes play in driving the malignant progression of ATC, we constructed a protein-protein interaction network. Within this network, DEPDC1 was identified as a key influencer (Fig. 1D).

Fig. 1.

Expression and identification of differential stemness genes in anaplastic thyroid carcinoma (ATC). (A) The heatmap displays the CSC-like characteristic scores of ATC samples. (B) The boxplot illustrates the different subgroups based on CSC-like characteristic scores. (C) The heatmap presents the expression profiles of differential stemness genes in thyroid cancer samples. (D) The protein-protein interactions network of differential stemness genes is shown.

3.2. Prognostic analysis

To assess the clinical significance of these differential stemness genes in ATC, we conducted a Kaplan-Meier survival analysis using the Kaplan-Meier plotter. Among the 7 genes, notable findings included PBK (hazard ratio [HR] = 2.31, log-rank P = 0.11), DEPDC1 (HR = 2.75, log-rank P = 0.037), NUF2 (HR = 0.52, log-rank P = 0.2), DLGAP5 (HR = 2.24, log-rank P = 0.12), TTK (HR = 2.01, log-rank P = 0.16), and TRIP13 (HR = 1.67, log-rank P = 0.34), all of which showed significant correlations with overall survival (Fig. 2A). High expression of these genes in ATC samples was generally indicative of poorer survival outcomes, with DEPDC1 showing the most substantial impact. Further investigation into DEPDC1 expression in ATC was conducted through analysis of the TCGA database. This analysis highlighted a significant elevation in DEPDC1 expression in ATC tissue samples (Fig. 2B). Furthermore, when examining thyroid cancer samples more broadly, DEPDC1 was found to be significantly upregulated across various stages of thyroid cancer (THCA). A positive correlation was also observed between DEPDC1 expression and lymph node metastasis in THCA patients (Fig. 2C and D). Collectively, these insights underscore a strong link between DEPDC1 expression and the aggressive progression of ATC, suggesting its role as a key factor in the malignancy and potential target for therapeutic intervention.

Fig. 2.

Identification of key genes of CLC-like in anaplastic thyroid carcinoma. (A) Kaplan-Meier plotter shows the overall survival (OS) of the 8 genes of CLC-like in thyroid carcinoma. (B) Expression of DEPDC1 in THCA and normal tissue. (C) Expression of DEPDC1 in different stages of THCA. (D) Expression of DEPDC1 in relation to nodal metastasis status.

3.3. DEPDC1 was highly expressed in CSCs

The up-regulation of DEPDC1 expression in the combined dataset was confirmed (Fig. 3A). Further correlation analysis indicated a robust association between DEPDC1 expression and stemness in the samples (Fig. 3B). In addition, our analysis revealed a strong correlation between DEPDC1 and genes linked to cancer stem cell-like traits in ATC samples (Fig. 3C and D). To delve deeper into this relationship, we categorized ATC samples into two groups based on the median expression of DEPDC1 (Fig. 3E). Subsequently, GSEA was employed to examine the genes differentially expressed between these groups. The GSEA findings suggested that the influence of DEPDC1 on cancer stem cell-like characteristics in ATC might be connected to pivotal biological pathways, notably those involved in cell cycle regulation and cell division processes (Fig. 3F). These insights contribute to a more comprehensive understanding of the role of DEPDC1 in the malignant progression of ATC and its potential as a target for therapeutic strategies.

Fig. 3.

DEPDC1 exhibits a strong correlat on with stemness. (A) The expression of DEPDC1 in ATC and NT. (B) Pearson correlation analysis reveals the relationship between DEPDC1 and stemness. (C–D) Pearson correlation analysis demonstrates the association of DEPDC1 with CD44 or MYC. (E) Boxplot depicting the differential expression of DEPDC1 in ATC samples. (F) GSEA analysis identifies significant differences in the enrichment of biological processes based on DEPDC1 expression.

3.4. MEGENA analysis

To elucidate the influence of DEPDC1 on the malignancy of anaplastic thyroid carcinoma (ATC), we analyzed a set of ATC samples exhibiting both high and low DEPDC1 expression using Multiscale Embedded Gene Co-expression Network Analysis (MEGENA). Post-elimination of batch variances, the analysis identified eight distinct gene clusters, including a DEPDC1-specific submodule (Fig. 4A and B). GO analysis of genes in the submodule c1-2 highlighted DEPDC1's association with key biological processes. These processes include mitotic spindle organization, microtubule cytoskeleton organization in mitosis, mitotic sister chromatid segregation, spindle assembly, and sister chromatid segregation (Fig. 4C). Additionally, KEGG analysis revealed a link between DEPDC1 and several critical pathways, such as cell cycle regulation, oocyte meiosis, and ubiquitin-mediated proteolysis (Fig. 4D). Moreover, DEPDC1 knockdown substantially impeded the cycle of ATC cells (Fig. 4E).

Fig. 4.

Identification of key genes of CLC-like and their associated signaling pathways. (A) Analytical clustering using MEGEAA. (B) DEPDC1 submodule. (C) Gene Ontology (GO) analysis and (D) Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis of the Differentially Expressed Genes (DEGs). (E) Silencing the effect of DEPDC1 on the cycle of ATC cells.

3.5. Aberrant expression of DEPDC1 was concerned with immunoinfiltration

In our investigation into the role of DEPDC1 in fostering cancer stem cell-like traits in ATC, we conducted prognosis and correlation analyses. Our findings revealed a significant link between higher DEPDC1 expression, enhanced immune-related signals, and poorer prognosis in ATC patients (Fig. 5A and B). Additionally, a pronounced correlation was identified between DEPDC1 expression levels and the activity of immune signaling pathways (Fig. 5C and D).

Fig. 5.

High expression of DEPDC1 in thyroid cancer cells promotes immune infiltration. (A–B) The study investigates the association between elevated DEPDC1 expression, immune-related signals, and poor prognosis in patients. (C–D) The correlation between DEPDC1 expression and immune signal activity.

3.6. DEPDC1 was vital for regulating cancer stem cell-like characteristics

To delve into DEPDC1's role in sustaining cancer stem cell-like properties in ATC, we conducted a series of experiments. Initially, DEPDC1 was effectively silenced, a fact confirmed by Western blot analysis (Fig. 6A). Following this, we assessed DEPDC1 levels in ATC stem cell spheres, revealing a significant elevation of DEPDC1 in these cells (Fig. 6B). The silencing of DEPDC1 resulted in marked suppression of stemness markers, including CD133, SOX2, and NANOG (Fig. 6C), and notably diminished the formation of ATC spheres (Fig. 6D). Furthermore, the knockdown of DEPDC1 led to a substantial reduction in the invasion and migration capabilities of ATC cells (Fig. 6E and F). Additionally, the absence of DEPDC1 had a significant effect on the clonal formation and proliferation of ATC cells (Fig. 6G).

Fig. 6.

The inhibition of DEPDC1 resulted in the suppression of CSCs characteristics and regulation of the malignant phenotypes of ATC. (A) The siRNA-DEPDC1 demonstrated an effective silencing effect. (B) Western blot to analyze DEPDC1 expression in control or sphere groups. (C) The knockdown efficiency of CD133, SOX2, and NANOG in KHM-5M and 8505C cells was analyzed using Western blot. (D) The sphere formation, (E) invasive ability, (F) migration ability, and (G) clone formation of KHM-5M and 8505C cells were assessed after DEPDC1 silencing.

4. Discussion

ATC is known for its high metastatic rate, significant local invasiveness, and generally poor prognosis. Compared to normal thyroid cells, ATC cells exhibit enhanced cancer stem cell-like traits, which are pivotal in driving its aggressive malignant behavior. Prior research has focused on unraveling the mechanisms that contribute to the heightened aggressiveness of ATC, employing comprehensive analyses of key regulatory pathways and networks [9,28]. Within the broader context of oncology, CSCs—a small yet potent subset of tumor cells with formidable tumorigenic capabilities—have been recognized as major contributors to cancer progression, recurrence, metastasis, and resistance to therapy in a variety of cancers [29]. To understand DEPDC1's biological function in ATC, we analyzed 40 ATC patient samples across three separate ATC datasets. We evaluated the stemness scores of relevant genes within these datasets and investigated the relationship between DEPDC1 expression and stemness characteristics. Our analysis indicated that DEPDC1 likely played a significant role in modulating tumor stem cell-like properties in ATC.

Previous research has consistently identified an upsurge in DEPDC1 expression across various cancer types, underscoring its role in cancer development [[15], [16], [17],30]. Additionally, DEPDC1's function in apoptosis induction and proliferation inhibition in HepG2 cells via miR-130A has been documented [31]. Recent studies have also pinpointed DEPDC1's involvement in cell division regulation [32] and its association with cell cycle signaling, cancer stem cell-like traits, and DNA damage repair processes. However, establishing DEPDC1's prognostic significance in ATC necessitates further validation in a broader cohort of clinical ATC samples. Our study specifically examined DEPDC1 expression in ATC samples, finding a significant increase compared to normal thyroid tissues. We then stratified these ATC samples into groups based on their stemness levels. The results revealed a pronounced elevation of DEPDC1 in the high-stemness group and among ATC patients. Furthermore, our analysis indicated a strong link between elevated DEPDC1 expression and reduced survival rates in patients. These observations position DEPDC1 as a promising candidate for both a prognostic biomarker and a therapeutic target in ATC. Importantly, our findings are in line with similar research conducted in other cancer populations, adding to the growing body of evidence supporting DEPDC1's critical role in cancer biology.

To decipher the molecular mechanisms by which DEPDC1 influences the progression of ATC, we performed a GSEA analysis. ATC samples were stratified based on DEPDC1 expression, and differential genes were analyzed. The results pointed to a significant enrichment of these genes in key biological processes, such as cell cycle regulation, DNA damage repair, and cancer stem cell-like traits. Prominent among these genes were DEPDC1, Clorf116, DLGAP5, NUF2, PBK, S100A14, TRIP13, and TTK. Furthermore, we utilized MEGENA, an advanced method for constructing gene co-expression networks via graph embedding. The MEGENA algorithm enabled us to cluster the differentially expressed genes induced by DEPDC1 into specific submodules, namely c1_2, c1_3, c1_4, c1_8, and c1_6. GO and KEGG pathway analyses, particularly focusing on the submodule c1_2 where DEPDC1 resides, revealed significant associations with processes including cell meiosis, cell cycle regulation, progesterone-mediated cell cycle progression, cell maturation, cell senescence, HIV-1 infection, and viral carcinogenesis [33,34]. Previous studies have highlighted DEPDC1's role in the cell cycle regulation of HeLa cells and its critical impact on poor patient prognosis [32,34]. Moreover, research has demonstrated that increased DEPDC1 expression contributes to the proliferation, invasion, migration, and other malignant characteristics of colorectal cancer [[35], [36], [37]].

Previous research has established DEPDC1 as a gene with aberrant expression patterns, known to be negatively regulated by miR-26b and implicated in driving the proliferation of triple-negative breast cancer cells [25,38]. In our study, we observed that deactivating DEPDC1 significantly suppressed the malignant traits of ATC cells. This included a notable reduction in cell proliferation, invasion, migration, colony formation, and spheroid formation capabilities. Additionally, DEPDC1 silencing led to decreased expression of key stemness markers, such as CD133, SOX2, and NANOG, in ATC cells. These results contribute to a further understanding of the pivotal role of DEPDC1 in governing stem-like properties in ATC. Nonetheless, more comprehensive studies are essential to thoroughly elucidate the mechanisms by which DEPDC1 modulates pathways related to the stem-like characteristics in ATC, enhancing our understanding of its potential as a therapeutic target.

This study reveals a novel association between DEPDC1 and the cancer stem cell-like attributes of ATC, bolstered by corroborative findings from our in vitro cellular assays. Our research positions DEPDC1 as a significant biomarker for exploring the mechanisms driving ATC progression. This discovery offers crucial insights into identifying potential therapeutic targets, paving the way for advanced treatment strategies for this aggressive cancer. The findings underscore the importance of DEPDC1 in the molecular landscape of ATC and open new avenues for targeted therapeutic research in this field.

Data availability

All data for this study are available from the corresponding author upon reasonable request. The GSE29265, GSE33630 and GSE76039 datasets were acquired from Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/) [39].

CRediT authorship contribution statement

Chaozhuang Zhu: Writing – original draft, Validation, Investigation, Formal analysis, Data curation, Conceptualization. Shuwei Ke: Writing – review & editing. Ying Li: Data curation. Wanli Zhang: Validation. Yulu Che: Visualization. Ruidan Zhang: Data curation. Ping Huang: Project administration, Funding acquisition. Tong Xu: Supervision, Software, Funding acquisition, Formal analysis, Data curation, Conceptualization.

Declaration of competing interest

The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Tong Xu reports financial support was provided by National Natural Science Foundation of China. Tong Xu reports financial support was provided by Medical and Health Science and Technology Project of Zhejiang. Tong Xu reports financial support was provided by Basic Scientific Research Project of Basic Scientific Research Funds of Hangzhou Medical College. Tong Xu reports a relationship with National Natural Science Foundation of China that includes: funding grants. Tong Xu reports a relationship with Medical and Health Science and Technology Project of Zhejiang that includes: funding grants. Tong Xu reports a relationship with Basic Scientific Research Project of Basic Scientific Research Funds of Hangzhou Medical College that includes: funding grants. All authors contributed to the research and approved the submitted version, and declared no known competing interests or personal relationships in this paper that could have appeared to influence the work reported. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Abbreviations

THCA

Thyroid cancer

PTC

Papillary thyroid carcinoma

ATC

Anaplastic thyroid carcinoma

TC

Thyroid cancers

TNM

Tumor-Lymph Node-Metastasis

AJCC

American Joint Commission on Cancer

CSCs

Cancer stem cells

DEPDC1

DEP domain containing 1

CRC

Colorectal cancer

ZNF224

Zinc finger protein

FoxM1

Forkhead Box M1

PDTCs

Poorly-differentiated thyroid carcinomas

ssGSEA

Single sample gene set enrichment analysis

PPI

Protein-protein interaction

MCC

Maximal Clique Centrality

GSEA

Gene set enrichment analysis

GO

Gene ontology

KEGG

Kyoto Encyclopedia of Genes and Genomes

MEGENA

Multiscale Embedded Gene Co-expression Network Analysis

Appendix A. Supplementary data

The following is the Supplementary data to this article: