Integrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks.

Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.

Integration of scRNA and bulk RNA-sequence to construct the 5-gene molecular prognostic model based on the heterogeneity of thyroid carcinoma endothelial cell.

Thyroid cancer (TC) is a kind of cancer with high heterogeneity, which leads to significant difference in prognosis. The prognostic molecular processes are not well understood. Cancer cells and tumor microenvironment (TME) cells jointly determine the heterogeneity. However, quite a little attention was paid to cells in the TME in the past years. In this study, we not only reveal that endothelial cells (ECs) are strongly associated with the progress of papillary thyroid cancer (PTC) using single-cell RNA-seq (scRNA-seq) data downloaded from Gene Expression Omnibus (GEO) and WGCNA, but also screen 5 crucial genes of ECs: CLDN5, ABCG2, NOTCH4, PLAT, and TMEM47. Furthermore, the 5-gene molecular prognostic model is constructed, which can predict how well a patient will do on PD-L1 blockade immunotherapy for TC and evaluate prognosis. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis demonstrates that PLAT is decreased in TC and the increase of PLAT can restrain the migratory capacity of TC cells. Meanwhile, in TC cells, PLAT suppresses VEGFa/VEGFR2-mediated human umbilical vascular endothelial cell (HUVEC) proliferation and tube formation. Totally, we construct the 5-gene molecular prognostic model from the perspective of EC and provide a new idea for immunotherapy of TC.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm.

PURPOSE: Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis. METHODS: Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWISD and ADCSD), DWI and ADC signal intensity ratio (DWISIR and ADCSIR), mean ADC and minimum ADC value (ADCmean and ADCmin) and ADC value standard deviation (ADCVSD). Univariate and multivariate logistic regression were conducted to identify independent predictors, and develop a prediction model. We performed receiver operating characteristic (ROC) analysis to determine the optimal threshold of risk factors, and constructed combined threshold models. Our study calculated diagnostic performance including area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and unnecessary biopsy rate of all models were calculated and compared them with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) result. RESULTS: Two independent predictors of malignant nodules were identified by multivariate analysis: DWISIR (P = 0.007) and ADCmin (P < 0.001). The AUCs for multivariate prediction model, combined DWISIR and ADCmin thresholds model, combined DWISIR and ADCSIR thresholds model and ACR-TIRADS were 0.946 (0.896-0.996), 0.875 (0.759-0.991), 0.777 (0.648-0.907) and 0.722 (0.588-0.857). The combined DWISIR and ADCmin threshold model had the lowest unnecessary biopsy rate of 0%, compared with 56.3% for ACR-TIRADS. CONCLUSION: Quantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.

Circular forms of dedicator of cytokinesis 1 promotes breast cancer progression by derepressing never in mitosis related kinase 2 via sponging miR-128-3p.

The conjecture of breast cancer is uncertain because of its explosive growth and the complicated molecular mechanisms. Circular RNAs (circRNAs) are regulatory RNA sequences present in the genome and their regulatory mechanism involves the sponging of microRNAs (miRNAs). In this study, we explored the regulation between circular forms of dedicator of cytokinesis 1 (circDOCK1) (hsa_circ_0007142) and miR-128-3p, and its implication on the pathogenesis of breast cancer modulated by never in mitosis (NIMA) related kinase 2 (NEK2). We revealed an increase in circDOCK1 and NEK2 expression, and a decrease in miR-128-3p expression in breast cancer tissues and cell lines. Bioinformatics analysis and experimental validation indicated a positive correlation between circDOCK1 and NEK2 expression but a negative correlation was recorded between miR-128-3p and circDOCK1 or NEK2, respectively. Furthermore, inhibition of circDOCK1 expression was followed by an increase in miR-128-3p and a decrease in NEK2 levels in vitro and in vivo. The luciferase assay concluded that miR-128-3p was a direct target of circDOCK1 while NEK2 was the direct target of miR-128-3p. Furthermore, circDOCK1 inhibition hindered breast cancer development by repressing NEK2 and thus promoting the increased expression of miR-128-3p both in vitro and in vivo. We therefore conclude that circDOCK1 promotes breast cancer progression by targeting miR-128-3p-mediated downregulation of NEK2 and that the circDOCK1/hsa-miR-128-3p/NEK2 axis may be a novel therapeutic target for breast cancer treatment.