Comprehensive Analysis of the Prognosis and Drug Sensitivity of Differentiation-Related lncRNAs in Papillary Thyroid Cancer

A New Ferroptosis-Related Long Non-Coding RNA Risk Model Predicts the Prognosis of Patients With Papillary Thyroid Cancer

Background

Ferroptosis is a novel form of regulated cell death that involves in cancer progression. However, the role of ferroptosis-related long non-coding RNAs (lncRNAs) in papillary thyroid cancer (PTC) remains to be elucidated. The purpose of this paper was to clarify the prognostic value of ferroptosis-related lncRNAs in PTC.

Methods

The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. The correlation between ferroptosis-related genes (FRGs) and lncRNA was determined using Pearson correlation analysis. Multivariate Cox regression model (P < 0.01) was performed to establish a ferroptosis-related lncRNAs risk model. Kaplan-Meier survival analysis, receiver operating characteristic (ROC) curves, risk curve and nomograms were then performed to assess the accuracy and clinical applicability of prognostic models. The correlations between the prognosis model and clinicopathological variables, immune and m6A were analyzed. Finally, in vitro assays were performed to verify the role of LINC00900, LINC01614 and PARAL1 on the proliferation, migration and invasion in TPC-1 and BCPAP cells, as well as the relationship between three lncRNAs and ferroptosis.

Results

A five-ferroptosis-related lncRNAs (PARAL1, LINC00900, DPH6-DT, LINC01614, LPP-AS2) risk model was constructed. Based on the risk score, samples were divided into the high- and low-risk groups. Patients in the low-risk group had better prognosis than those in high-risk group. Compared to traditional clinicopathological features, risk score was more accurate in predicting prognosis in patients with PTC. Additionally, the difference of immune cell, function and checkpoints was observed between two groups. Moreover, experiments showed that LINC00900 promoted the proliferation, migration and invasion in TPC-1 and BCPAP cells, while LINC01614 and PARAL1 revealed opposite effects, all of which were related to ferroptosis.

Conclusions

In summary, we identified a five-ferroptosis-related lncRNAs risk model to predict the prognosis of PTC. Furthermore, our study also revealed that LINC00900 functioned as a tumor suppressor lncRNA, LINC01614 and PARAL1 as an oncogenic lncRNA in PTC.

Ubiquitin-modifying enzymes in thyroid cancer：Mechanisms and functions

Thyroid cancer is the most common malignant tumor of the endocrine system, and evidence suggests that post-translational modifications (PTMs) and epigenetic alterations play an important role in its development. Recently, there has been increasing evidence linking dysregulation of ubiquitinating enzymes and deubiquitinases with thyroid cancer. This review aims to summarize our current understanding of the role of ubiquitination-modifying enzymes in thyroid cancer, including their regulation of oncogenic pathways and oncogenic proteins. The role of ubiquitination-modifying enzymes in thyroid cancer development and progression requires further study, which will provide new insights into thyroid cancer prevention, treatment and the development of novel agents.

m6A reader IGF2BP2 promotes lymphatic metastasis by stabilizing DPP4 in papillary thyroid carcinoma

Lymph node metastasis (LNM) is a major cause of locoregional recurrence of papillary thyroid carcinoma (PTC). However, the mechanisms responsible for LNM are unclear. Aberrant N6-methyladenosine (m6A) RNA modification plays a vital role in cancer progression and metastasis, and whether m6A modification regulates LNM in PTC remains to be determined. This study showed that IGF2BP2 was upregulated in PTC and positively associated with LNM. Functionally, IGF2BP2 knockdown significantly inhibited PTC cell proliferation and invasion in vitro, and vice versa. Moreover, IGF2BP2 knockdown significantly inhibited lymphatic metastasis in vivo. Mechanistically, Human m6A epitranscriptomic microarray, MeRIP, and RIP assays demonstrated that IGF2BP2 activated the NF-KB pathway by enhancing DPP4 stability in an m6A-dependent manner. Furthermore, IGF2BP2 knockdown increased the sensitivity of PTC cells to cisplatin therapy to a certain extent, while its overexpression produced the opposite effects. Overall, this study uncovers that IGF2BP2 promotes lymphatic metastasis via stabilizing DPP4 in an m6A-dependent manner, and provides new insights for understanding the mechanism of lymphatic metastasis in PTC.

New insights into COL26A1 in thyroid carcinoma: prognostic prediction, functional characterization, immunological drug target and ceRNA network

Background

Thyroid carcinoma (THCA) is one of the most commonly diagnosed malignancies. Collagen is the main component in extracellular matrix. Rising studies have determined the oncogenic effect of collagen in cancer progression, which is intriguing to be further explored. Collagen type XXVI alpha 1 chain (COL26A1) is a newly discovered collagen subtype, functions of which still remain poorly demonstrated in THCA.

Methods

Based on the transcriptome data from The Cancer Genome Atlas (TCGA) and other public databases, we conducted investigations of COL26A1 in THCA with respects to diagnostic/prognostic prediction, functional characterization, immune infiltration, chemical drug target and non-coding RNA regulatory network. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) and western blot were used to verify the expression of COL26A1 in THCA.

Results

COL26A1 was significantly upregulated in THCA, and the high COL26A1 expression inferred poor prognosis [hazard ratio (HR) =4.76; 95% confidence interval (CI): 1.36-16.73; P=0.015]. The diagnostic area under the curve (AUC) of COL26A1 achieved 0.736 (95% CI: 0.669-0.802). COL26A1 was also identified as an independent prognostic predictor for THCA (HR =3.928; 95% CI: 3.716-4.151; P<0.001). Besides, logistic regression analysis indicated that age >45 years [odds ratio (OR) =1.532; 95% CI: 1.081-2.176; P=0.017], pathological stage III (OR =2.055; 95% CI: 1.314-3.184; P=0.001), tall cell subtype (OR =5.533; 95% CI: 2.420-14.957; P<0.001), residual tumor R1 (OR =1.844; 95% CI: 1.035-3.365; P=0.041) and extrathyroidal extension (OR =1.800; 95% CI: 1.225-1.660; P=0.003) were risk factors associated with high COL26A1 expression in THCA. Functional characterizations implied that COL26A1 was associated with immunological processes and oncogenic signaling pathways. High COL26A1 expression was accompanied by more abundant infiltration of immune cells and higher stromal/immune score. In addition, most immune checkpoints were significantly positively co-expressed with COL26A1, including PD-1, PD-L1 and CTLA4. Drugs including trichloroethylene, acetamide and thioacetamide etc. that can decrease the expression of COL26A1 were also identified. The predicted long noncoding RNA (lncRNA)-microRNA (miRNA)-COL26A1 regulatory axes were successfully deciphered. qRT-PCR and western blot verified the upregulation of COL26A1 in THCA.

Conclusions

Our work has primarily appraised COL26A1 as a promising biomarker for diagnosis/prognosis and immuno/therapeutic target in THCA.

The m5 C methyltransferase NSUN2 promotes codon-dependent oncogenic translation by stabilising tRNA in anaplastic thyroid cancer

BACKGROUND

Translation dysregulation plays a crucial role in tumourigenesis and cancer progression. Oncogenic translation relies on the stability and availability of tRNAs for protein synthesis, making them potential targets for cancer therapy.

METHODS

This study performed immunohistochemistry analysis to assess NSUN2 levels in thyroid cancer. Furthermore, to elucidate the impact of NSUN2 on anaplastic thyroid cancer (ATC) malignancy, phenotypic assays were conducted. Drug inhibition and time-dependent plots were employed to analyse drug resistance. Liquid chromatography-mass spectrometry and bisulphite sequencing were used to investigate the m5 C methylation of tRNA at both global and single-base levels. Puromycin intake and high-frequency codon reporter assays verified the protein translation level. By combining mRNA and ribosome profiling, a series of downstream proteins and codon usage bias were identified. The acquired data were further validated by tRNA sequencing.

RESULTS

This study observed that the tRNA m5 C methyltransferase NSUN2 was up-regulated in ATC and is associated with dedifferentiation. Furthermore, NSUN2 knockdown repressed ATC formation, proliferation, invasion and migration both in vivo and in vitro. Moreover, NSUN2 repression enhanced the sensitivity of ATC to genotoxic drugs. Mechanically, NSUN2 catalyses tRNA structure-related m5 C modification, stabilising tRNA that maintains homeostasis and rapidly transports amino acids, particularly leucine. This stable tRNA has a substantially increased efficiency necessary to support a pro-cancer translation program including c-Myc, BCL2, RAB31, JUNB and TRAF2. Additionally, the NSUN2-mediated variations in m5C levels and different tRNA Leu iso-decoder families, partially contribute to a codon-dependent translation bias. Surprisingly, targeting NSUN2 disrupted the c-Myc to NSUN2 cycle in ATC.

CONCLUSIONS

This research revealed that a pro-tumour m5C methyltransferase, dynamic tRNA stability regulation and downstream oncogenes, c-Myc, elicits a codon-dependent oncogenic translation network that enhances ATC growth and formation. Furthermore, it provides new opportunities for targeting translation reprogramming in cancer cells.

The Emerging Roles of circRNAs in Papillary Thyroid Carcinoma: Molecular Mechanisms and Biomarker Potential

Papillary thyroid carcinoma (PTC) is a common endocrine malignant tumor. The incidence of PTC has increased in the past decades and presents a younger trend. Accumulating evidence indicates that circular RNAs (circRNAs), featured with non-linear, closed-loop structures, play pivotal roles in tumorigenesis and regulate cell biological processes, such as proliferation, migration, and invasion, by acting as microRNA (miRNA) sponges. Additionally, due to their unique stability, circRNAs hold promising potential as diagnostic biomarkers and effective therapeutic targets for PTC treatment. In this review, we systematically arrange the expression level of circRNAs, related clinical characteristics, circRNA-miRNA-mRNA regulatory network, and molecular mechanisms. Furthermore, related signaling pathways and their potential ability of diagnostic biomarkers and therapeutic targets are discussed, which might provide a new strategy for PTC diagnosis, monitoring, and prognosis.

A cell cycle-related lncRNA signature predicts the progression-free interval in papillary thyroid carcinoma

The cell cycle plays a vital role in tumorigenesis and progression. Long non-coding RNAs (lncRNAs) are key regulators of cell cycle processes. Therefore, understanding cell cycle-related lncRNAs (CCR-lncRNAs) is crucial for determining the prognosis of papillary thyroid carcinoma (PTC). RNA-seq and clinical data of PTC were acquired from The Cancer Genome Atlas, and CCR-lncRNAs were selected based on Pearson's correlation coefficients. According to univariate Cox regression, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses, a five-CCR-lncRNA signature (FOXD2-AS1, LOC100507156, BSG-AS1, EGOT, and TMEM105) was established to predict the progression-free interval (PFI) in PTC. Kaplan-Meier survival, time-dependent receiver operating characteristic curve, and multivariate Cox regression analyses proved that the signature had a reliable prognostic capability. A nomogram consisting of the risk signature and clinical characteristics was constructed that effectively predicted the PFI in PTC. Functional enrichment analyses indicted that the signature was involved in cell cycle- and immune-related pathways. Furthermore, we also analyzed the correlation between the signature and immune cell infiltration. Finally, we verified the differential expression of CCR-lncRNAs in vitro using quantitative real-time polymerase chain reaction. Overall, the newly developed prognostic risk signature based on five CCR-lncRNAs may become a marker for predicting the PFI in PTC.

Comprehensive analysis of lncRNA-mediated ceRNA regulatory networks and key genes associated with papillary thyroid cancer coexistent with Hashimoto's thyroiditis

OBJECTIVE

The incidence of papillary thyroid cancer (PTC) concomitant with Hashimoto's thyroiditis (HT) is gradually increasing over the past decades. This study aims to identify differentially expressed lncRNAs between tumor tissues of PTC with or without HT and further to confer a better understanding of lncRNA-based competing endogenous RNA (ceRNA) network in PTC with HT.

METHODS

GSE138198 containing tissue mRNA data and GSE192560 containing lncRNA data were utilized to perform differentially expression analysis. The ceRNA network was constructed based on miRNA-mRNA interactions merging with lncRNA-microRNA interactions. Functional enrichment analysis and protein-protein interaction (PPI) analysis were performed. The mRNA levels of core genes in the PPI analysis in tumor tissues collected from 112 PTC patients including 35 cases coexistent with HT were determined by quantitative real-time polymerase chain reaction (qRT-PCR).

RESULTS

A total of 57 genes and 40 lncRNAs, with value of |log2 fold change (FC)|≥ 1 and the adjusted P-value < 0.05, were deemed as differentially expressed genes and lncRNAs between PTC with and without HT. The pathways most significantly enriched by differentially expressed genes between PTC with and without HT were viral protein interaction with cytokine and cytokine receptor and cytokine-cytokine receptor interaction. CXCL10, CXCL9, CCL5, FCGR3A, and CCR2 owned degree values not less than 10 were deemed as core genes differentially expressed between PTC with and without HT. A total of 76 pairs of lncRNA-miRNA-mRNA ceRNA were obtained. Results of qRT-PCR partially demonstrated the bioinformatics results that the mRNA levels of CXCL10, CXCL9, CCL5, and CCR2 were remarkably elevated in tumor tissues collected from PTC patients coexistent with HT than those without HT (P < 0.001).

CONCLUSION

Our study offers a better understanding of the lncRNA-related ceRNA network involved in PTC with HT, providing novel key genes associated with PTC coexistent with HT.

A Potential Four-Gene Signature and Nomogram for Predicting the Overall Survival of Papillary Thyroid Cancer

Background. Although the prognosis of papillary thyroid cancer (PTC) is relatively good, some patients experience recurrence or distant metastasis after thyroidectomy and progress to radioactive iodine refractory stage. Therefore, accurate prediction of clinical outlook can aid to screen out the minority of patients with poorer prognosis and avoid excessive treatment in low-risk patients. Methods. The RNA-seq and clinical data of PTC patients was downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. Multivariate and Lasso Cox regression analyses were used to construct a prognostic nomogram to predict overall survival (OS). Thereafter, quantitative RT-PCR and Human Protein Atlas (HPA) database were employed to verify the expression of key genes. Results. A four-gene risk score comprising ABI3BP, DPT, MRO, and TENM1 was exhibited strong prognostic value. Moreover, an integrated nomogram was established based on the risk score, age, AJCC (American Joint Commission on Cancer) stage, tumor size, extrathyroidal extension, and history of neoadjuvant treatment, which exhibited significantly better predictive performance than TNM stage system ( $P<0.05$ ). GSEA (Gene Set Enrichment Analysis) and GSVA (Gene Set Variation Analysis) revealed that the different tumor-associated hallmarks, biological processes, and pathways were substantially enriched in the poor-prognosis group. In addition, a ceRNA network was constructed by including the four genes (ABI3BP, DPT, MRO, and TENM1), 54 lncRNAs, and 10 miRNAs. Finally, both the relative mRNA and protein expression of ABI3BP, DPT, MRO, and TENM1 were validated. Conclusion. The present study identified a four-gene risk signature and developed a novel nomogram, which could be regarded as a reliable prognostic model for PTC patients. The findings also revealed preliminary potential mechanisms that may influence the prognosis outcome. These results can be conducive to design personalized treatment and prognosis management in affected patients.