Identification of Hub Genes in Anaplastic Thyroid Carcinoma: Evidence From Bioinformatics Analysis

Knockdown of KAT5/KIF11 induces autophagy and promotes apoptosis in anaplastic thyroid cancer cells

K (lysine) acetyltransferase (KAT) 5, which is a member of the KAT family of enzymes, has been found to act as a regulatory factor in various types of cancer. However, the role of KAT5 in anaplastic thyroid carcinoma (ATC) and its underlying mechanism is still elusive. The expression levels of KAT5 and kinesin family member 11 (KIF11) in ATC cells were assessed utilizing reverse transcription-quantitative PCR and western blot analyses. The cell proliferative ability was assessed via Cell Counting Kit-8 assay and using 5-ethynyl-2'-deoxyuridine staining. Flow cytometry and western blot analyses were applied for the assessment of cell apoptosis. Cell autophagy was investigated by employing western blot analysis and immunofluorescence staining. In addition, the enrichment of histone H3 lysine 27 acetylation (H3K27ac) and RNA polymerase II (RNA pol II) was analyzed by chromatin immunoprecipitation assay. It was shown that KAT5 expression was markedly increased in ATC cells. KAT5 depletion suppressed the cell proliferative capability but promoted the induction of apoptosis and autophagy. In addition, the autophagy inhibitor 3-methyladenine reversed the effects of KAT5 deficiency on the proliferative and apoptotic activities of 8505C cells. With regard to the mechanism, it was found that KAT5 inhibited the expression of KIF11 by repressing the enrichment of H3K27ac and RNA pol II. Upregulation of KIF11 expression reversed the effects of KAT5 silencing on the proliferative activity, apoptosis and autophagy of 8505C cells. In conclusion, the results indicated that KAT5 induced autophagy and promoted apoptosis of ATC cells by targeting KIF11, which may provide a promising target for the treatment of ATC.

Weighted gene co-expression network reveals driver genes contributing to phenotypes of anaplastic thyroid carcinoma and immune checkpoint identification for therapeutic targets

Background

Anaplastic thyroid carcinoma (ATC) is a rare but extremely malignant tumor, with a rapid growth rate and early metastasis thus leading to poor survival of patients. The molecular mechanisms underlying these aggressive traits of ATC remain unknown, which impedes the substantial progress in treatment to prolong ATC patient survival.

Methods

We applied weighted gene co-expression network analysis (WGCNA) to identify ATC-specific modules. The Metascape web and R package clusterProfiler were employed to perform enrichment analysis. Combined with differentially expressed gene analysis, we screened out the most potential driver genes and validated them using receiver operator characteristic (ROC) analysis, quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blotting, immunohistochemistry (IHC), and triple immunofluorescence staining.

Results

A gene expression matrix covering 75 normal samples, 83 papillary thyroid carcinoma (PTC), 26 follicular thyroid carcinoma (FTC), 19 poor-differentiated thyroid carcinoma (PDTC), and 41 ATC tissue samples were integrated, based on which we detected three most potential ATC-specific modules and found that hub genes of these modules were enriched in distinct biological signals. Hub genes in the turquoise module were mainly enriched in mitotic cell cycle, tube morphogenesis, and cell differentiation, hub genes in the magenta module were mainly clustered in the extracellular matrix organization, positive regulation of cell motility, and regulation of Wnt signaling pathway, while hub genes in the blue module primarily participated in the inflammatory response, innate immune response, and adaptive immune response. We showed that 9 top genes, 8 transcription factors (TFs), and 4 immune checkpoint genes (ICGs) were differentially expressed in ATC compared to other thyroid samples and had high diagnostic values for ATC, among which, 9 novel ATC-specific genes (ADAM12, RNASE2, CASP5, KIAA1524, E2F7, MYBL1, SRPX2, HAVCR2, and TDO2) were validated with our clinical samples. Furthermore, we illustrated that ADAM12, RNASE2, and HAVCR2 were predominantly present in the cytoplasm.

Conclusion

Our study identified a set of novel ATC-specific genes that were mainly related to cell proliferation, invasion, metastasis, and immunosuppression, which might throw light on molecular mechanisms underlying aggressive phenotypes of ATC and provide promisingly diagnostic biomarkers and therapeutic targets.

Evaluate the diagnostic and prognostic value of NUSAP1 in papillary thyroid carcinoma and identify the relationship with genes, proteins, and immune factors

Background

Nucleolar spindle-associated protein 1 (NUSAP1) is reported to be a useful diagnostic and prognostic marker for a variety of cancers, but relevant studies are lacking in papillary thyroid carcinoma (PTC).

Methods

The relationship between NUSAP1 expression and the overall survival (OS) of pan-cancer was examined by GEPIA and KMplot. We explored the relationship between NUSAP1 and clinical PTC data based on the THCA dataset of TCGA and the GEO dataset of NCBI; GO, KEGG analysis, and ceRNA networks were performed on co-expressed genes through LinkedOmics and Starbase. We assessed the relevance between NUSAP1 and the tumor microenvironment using ESTIMATE, correlations between NUSAP1 and immune cells with TIMER, the relationship between NUSAP1 and immunotherapy by TCIA, and small-molecule drugs targeting NUSAP1 that can be discovered using the CMap database.

Results

Higher expression of NUSAP1 in pan-cancer tissues was correlated with shorter OS. NUSAP1 was also significantly expressed in PTC tissues and was an independent prognostic risk factor. Compared to the NUSAP1 low expression group, the NUSAP1 high expression group was more likely to also have lymph node metastasis, pathological PTC type, shorter progression-free survival (PFS), and higher scores for immune checkpoint inhibitor treatment. The genes associated with NUSAP1 were mostly involved in the cell cycle, immune-related pathways, and AITD. Ten lncRNAs (GAS5, SNHG7, UCA1, SNHG1, HCP5, DLEU2, HOTAIR, TP53TG1, SNHG12, C9orf106), eleven miRNAs (hsa-miR-10a-5p, hsa-miR-10b-5p, hsa-miR-18a-5p, hsa-miR-18b-5p, hsa-miR-128-3p, hsa-miR-214-3p, hsa-miR-219a-2-3p, hsa-miR-339-5p, hsa-miR-494-3p, hsa-miR-545-3p, hsa-miR-769-5p), and one mRNA (NUSAP1) were constructed. NUSAP1 participated in the formation of the tumor microenvironment. CMap predicted the 10 most important small molecules about NUSAP1.

Conclusions

In PTC, NUSAP1 shows good diagnostic value and prognostic value; NUSAP1 impacts the cell cycle, immune-related pathways, and AITD and has a complex effect on the tumor microenvironment in PTC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02652-9.

The Predictive Competing Endogenous RNA Regulatory Networks and Potential Prognostic and Immunological Roles of Cyclin A2 in Pan-Cancer Analysis

Although accumulating evidence has verified the relationship between CCNA2 and cancers, no pan-cancer analysis about the function and the upstream molecular mechanism of CCNA2 is available. For the first time, we analyzed potential oncogenic roles of CCNA2 in 33 cancer types via The Cancer Genome Atlas (TCGA) database. Overexpression of CCNA2 is widespread in almost all cancer types, and it is related to poor prognosis and advanced pathological stages in most cases. Moreover, we conducted upstream miRNAs and lncRNAs of CCNA2 to establish upstream regulatory networks in kidney renal clear cell carcinoma (LINC00997/miR-27b-3p/CCNA2), liver hepatocellular carcinoma (SNHG16, GUSBP11, FGD5-AS1, LINC00630, CD27-AS1, LINC00997/miR-22-3p/CCNA2, miR-29b-3p/CCNA2, miR-29c-3p/CCNA2, and miR-204-5p/CCNA2), and lung adenocarcinoma (miRNA-218-5p/CCNA2 and miR-204-5p/CCNA2) by expression analysis, survival analysis, and correlation analysis. The CCNA2 expression is positively correlated with Th2 cell infiltration and negatively correlated with CD4+ central memory and effector memory T-cell infiltration in different cancer types. Furthermore, CCNA2 is positively associated with expressions of immune checkpoints (CD274, CTLA4, HAVCR2, LAG3, PDCD1, and TIGIT) in most cancer types. Our first CCNA2 pan-cancer study contributes to understanding the prognostic and immunological roles and potential upstream molecular mechanisms of CCNA2 in different cancers.

Activation of the TGF-β1/Smad signaling by KIF2C contributes to the malignant phenotype of thyroid carcinoma cells

Kinesin family member 2C (KIF2C) has been identified as a potential oncogene in various types of human cancers; however, the role of KIF2C in thyroid cancer has not yet been elucidated. Quantitative real-time polymerase chain reaction and western blotting were employed for gene expression analysis. Cell Counting Kit-8 and ethynyl-2'-deoxyuridine assays were performed to examine cell proliferation. Cell migration and invasion were assessed by wound-healing and transwell invasion assays. Results showed that KIF2C expression was upregulated in thyroid carcinoma cell lines. In addition, upregulation of KIF2C promoted the proliferation, migration, and invasion of thyroid carcinoma cells, while downregulation of KIF2C exerted the opposite effects. Overexpression of KIF2C induced the activation of transforming growth factor-β1 (TGF-β1)/Smad signaling in thyroid carcinoma cells. However, inhibition of TGF-β1/Smad signaling through silencing TGF-β1 attenuated the promoting effects of KIF2C overexpression on the malignant phenotype of thyroid carcinoma cells. Besides, overexpression of TGF-β1 suppressed the inhibitory effect of KIF2C knockdown on the proliferation and metastasis of thyroid carcinoma cells. In conclusion, our findings demonstrated that KIF2C contributed to the malignant phenotype of thyroid carcinoma cells by inducing the activation of TGF-β1/Smad signaling, thus uncovering a novel mechanism for thyroid carcinoma progression.