Special Issue: Genetic Perspectives in Thyroid Cancer

Stem cell index-based RiskScore model for predicting prognosis in thyroid cancer and experimental verification

Objective

An mRNA expression-based stemness index (mRNAsi) has been developed to characterize cancer stemness. However, the predictive value of mRNAsi-based signature in therapeutic resistance and immunotherapy in thyroid cancer (THCA) remains unclarified. This study evaluated and validated the role of mRNAsi in drug sensitivity, its relationship between mRNAsi and THCA clinical features and immunity based on bioinformatics.

Methods

Based on transcriptome data of THCA patients from the Tumor Genome Atlas Project (TCGA) database, and expression data of multifunctional stem cell samples from the Progenitor Cell Biology Consortium (PCBC) databases, mRNAsi was calculated by the " one class logistic regression (OCLR)" method, Molecular subtypes of TCGA-THCA samples were identified with mRNAsi-related genes using ConsensusClusterPlus method. The gene mutation, clinical characteristics, immune characteristics, TIDE and drug sensitivity were compared among molecular subtypes. A prognostic model was designed with Lasso cox method. Modulation of malignant phenotype of THCA cell lines by model characterization genes is validated by CCK-8, flow cytometry. DNA methylation disorder in promoter region was analyzed between risk groups. The model was validated for survival in the internal Test dataset, while TCGA pan-cancer and immunotherapy datasets were further employed to validate the performance of this model.

Results

We obtained a total of 78 stem cell samples, each containing the expression profile of 8087 mRNA genes. Based on mRNAsi, THCA was divided into 3 subtypes. Subtype C2 had the poorest prognosis and highest immune score, while subtype C3 had the best prognosis, lowest mRANsi and highest TIDE score. Patients in subtype C2 showed higher sensitivity to Cisplatin, Erlotinib, Paclitaxel, and Lapatinib. The prognostic signature was generated using 5 mRNAsi-related genes, which could predict prognosis for THCA. qRT-PCR results showed that the expression of 5 genes were various in Hth7 and KTC-1 cells, and inhibition CELSR3 expression increased percentage of apoptosis in Hth7 and KTC-1 cells. mRNAsi related DNA methylation sites were mainly enriched in tumor related pathways. Good performance of this model was validated in Test dataset, pan-cancer and immunotherapy datasets.

Conclusion

This study identified three subtypes for classification and developed a prognostic model with mRNAsi-related genes, which provided great potential for prognosis and immunotherapy prediction.

AEBP1 promotes papillary thyroid cancer progression by activating BMP4 signaling

Papillary thyroid cancer (PTC) is the most prevalent endocrine cancer worldwide. Approximately 30 % of PTC patients will progress into the advanced or metastatic stage and have a relatively poor prognosis. It is well known that epithelial-mesenchymal transition (EMT) plays a pivotal role in thyroid cancer metastasis, resistance to therapy, and recurrence. Clarifying the molecular mechanisms of EMT in PTC progression will help develop the targeted therapy of PTC. The aberrant expression of some transcription factors (TFs) participated in many pathological processes of cancers including EMT. In this study, by performing bioinformatics analysis, adipocyte enhancer-binding protein 1 (AEBP1) was screened as a pivotal TF that promoted EMT and tumor progression in PTC. In vitro experiments indicated that knockout of AEBP1 can inhibit the growth and invasion of PTC cells and reduce the expression of EMT markers including N-cadherin, TWIST1, and ZEB2. In the xenograft model, knockout of AEBP1 inhibited the growth and lung metastasis of PTC cells. By performing RNA-sequencing, dual-luciferase reporter assay, and chromatin immunoprecipitation assay, Bone morphogenetic protein 4 (BMP4) was identified as a downstream target of AEBP1. Over-expression of BMP4 can rescue the inhibitory effects of AEBP1 knockout on the growth, invasion, and EMT phenotype of PTC cells. In conclusion, these findings demonstrated that AEBP1 plays a critical role in PTC progression by regulating BMP4 expression and the AEBP1-BMP4 axis may present novel therapeutic targets for PTC treatment.

Exploration of aminopeptidase N as new biomarker for early diagnosis of thyroid cancer

False-positive diagnosis and overdiagnosis are ongoing issues in clinical diagnosis of thyroid cancer. Identifying new disease markers is crucial for early diagnosis and improved treatment. Aminopeptidase N (APN) is a promising biomarker for cancer diagnosis due to its critical roles in tumor invasion, metastasis, angiogenesis, and other processes. However, its potential as biomarker for thyroid cancer diagnosis needs further investigation. This study developed an ultra-sensitive near-infrared fluorescence probe, LAN-apn, to investigate the expression level of APN in thyroid cancer and evaluate its potential as biomarker of thyroid cancer. LAN-apn could accurately and sensitively determine APN through fluorescence method (DL = 0.069 ng/mL) and colorimetric method (DL = 4.5 ng/mL). In addition, LAN-apn allowed for successful fluorescence imaging of APN in thyroid cancer cells and thyroid cancer tumors both in vivo and in vitro, and confirmed that APN was significantly upregulated in thyroid cancer. Therefore, APN may become a new biomarker for thyroid cancer diagnosis, and LAN-apn could be used as a new imaging tool for the study of APN-thyroid cancer relationship and the early diagnosis of thyroid cancer.

Overexpressed ZC3H13 suppresses papillary thyroid carcinoma growth through m6A modification-mediated IQGAP1 degradation

PURPOSE

The purpose of this study was to clarify the effect of ZC3H13 on the growth of papillary thyroid carcinoma (PTC).

METHODS

Firstly, we used qRT-PCR and Western blot to compare the difference in the expression of ZC3H13 between normal thyroid epithelial cells and PTC cell lines. Then, ZC3H13 overexpression/knockout thyroid cancer cells were constructed by lentivirus transfection, and the effects of overexpression of ZC3H13 on the proliferation, migration and invasion of PTC cells were detected by CCK8 and transwell experiments. Lastly, MeRIP-qPCR, RIP and o Actinomycin D were used to verify that ZC3H13 regulated the expression of downstream target gene IQGAP1 through m6A modification.

RESULTS

ZC3H13 expression was decreased in PTC cell lines BCPAP, KTC-1, k1, HTH83, and TPC-1. Proliferation, invasion, and migration of PTC cells were inhibited by overexpressed ZC3H13 but increased by knockdown of ZC3H13. IQGAP1 expression was suppressed by ZC3H13 overexpression but enhanced by ZC3H13 knockdown. In ZC3H13-overexpressed PTC cells, the m6A level of IQGAP1 mRNA was increased, and the IQGAP1 mRNA expression was decreased with the increasing time of Actinomycin D treatment. YTHDF2 enriched more IQGAP1 mRNA than IgG and knockdown of YTHDF2 reversed the effect of ZC3H13 overexpression on IQGAP1 mRNA stability. The xenograft tumor experiment in nude mice confirmed that the overexpression of ZC3H13 inhibited tumor growth, while overexpression of IQGAP1 could reverse the inhibitory effect of ZC3H13 overexpression on tumor growth.

CONCLUSION

ZC3H13 mediates IQGAP1 mRNA degradation by promoting m6A modification of IQGAP1 mRNA, this provides a prospective therapeutic target for PTC.

A radiomics nomogram for the ultrasound-based evaluation of central cervical lymph node metastasis in papillary thyroid carcinoma

PURPOSE

To develop and validate a radiomics nomogram based on ultrasound (US) to predict central cervical lymph node (LN) metastasis in patients with papillary thyroid carcinoma (PTC).

METHODS

PTC patients with pathologically confirmed presence or absence of central cervical LN metastasis in our hospital between March 2021 and November 2021 were enrolled as the training cohort. Radiomics features were extracted from the preoperative US images, and a radiomics signature was constructed. Univariate and multivariate logistic regression analyses were used to screen out the independent risk factors, and a radiomics nomogram was established. The performance of the model was verified in the independent test cohort of PTC patients who underwent thyroidectomy and cervical LN dissection in our hospital from December 2021 to March 2022.

RESULTS

In the independent test cohort, the radiomics model based on long-axis cross-section and short-axis cross-section images outperformed the radiomics models based on either one of these sections (the area under the curve (AUC), 0.69 vs. 0.62 and 0.66). The radiomics signature consisted of 4 selected features. The US radiomics nomogram included the radiomics signature, age, gender, BRAF V600E mutation status, and extrathyroidal extension (ETE) status. In the independent test cohort, the AUC of the receiver operating curve(ROC) of this nomogram was 0.76, outperformingthe clinical model and the radiomics model (0.63 and 0.69, respectively), and also much better than preoperative US examination (AUC, 0.60). Decision curve analysis indicated that the radiomics nomogram was clinically useful.

CONCLUSIONS

This study presents an efficient and useful US radiomics nomogram that can provide comprehensive information to assist clinicians in the individualized preoperative prediction of central cervical LN metastasis in PTC patients.